Masoud Alilou | Engineering | Best Researcher Award

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Assist. Prof. Dr. Masoud Alilou | Engineering | Best Researcher Award

Electrical Engineering from Urmia University of Technology, Iran

Dr. Masoud Alilou is a distinguished academic and researcher whose expertise lies at the intersection of biomedical engineering, image processing, and machine learning. Renowned for his pioneering contributions to medical image analysis, Dr. Alilou has played a pivotal role in advancing computational tools for disease detection and diagnosis. His research integrates advanced algorithm development with practical clinical applications, especially in oncology and pulmonary imaging. With a strong publication record in high-impact journals and numerous international collaborations, Dr. Alilou is recognized for his innovative methodologies and interdisciplinary approach. He has also been instrumental in mentoring graduate students and contributing to curriculum development in biomedical engineering and computer science programs. His commitment to translational research has led to the development of automated tools aimed at improving diagnostic accuracy and patient care. Over the years, Dr. Alilou has gained a reputation for excellence in research, teaching, and academic leadership. He is a frequent reviewer for reputed journals and conferences, and his work has been widely cited. Through his dedication to technological innovation and scientific rigor, Dr. Alilou continues to make significant contributions to medical imaging and artificial intelligence in healthcare, solidifying his status as a leader in the academic and scientific communities.

Professional Profile

Education

Dr. Masoud Alilou’s academic journey reflects his deep-rooted commitment to interdisciplinary research and education. He earned his Bachelor’s degree in Computer Engineering, laying a strong foundation in algorithm design, programming, and systems analysis. Driven by a desire to apply computational methods to real-world problems, he pursued a Master’s degree in Biomedical Engineering. During this period, he focused on medical image analysis and machine learning, bridging the gap between engineering and clinical medicine. His master’s research emphasized the development of image processing tools for diagnosing chronic lung diseases, which sparked his long-term interest in healthcare technologies. He later completed his Ph.D. in Biomedical Engineering at Case Western Reserve University, a globally respected institution in the field. His doctoral research concentrated on automated quantitative analysis of medical images using advanced computational models and machine learning techniques. During his Ph.D., Dr. Alilou collaborated closely with radiologists and oncologists, reinforcing the clinical relevance of his work. His interdisciplinary training uniquely positioned him to develop algorithms that are both technically robust and clinically meaningful. Through rigorous coursework, hands-on research, and cross-disciplinary mentorship, Dr. Alilou has built an educational background that combines computational science, engineering, and medicine—an essential blend for cutting-edge biomedical research.

Professional Experience

Dr. Masoud Alilou has amassed an impressive portfolio of professional experience that spans academic research, interdisciplinary collaboration, and technological innovation. Following his doctoral studies, he joined the Quantitative Imaging Laboratory at Case Western Reserve University as a research scientist. In this role, he led and contributed to multiple NIH-funded projects aimed at developing automated tools for lung cancer screening and diagnosis using low-dose CT scans. His work involved close collaboration with clinicians, radiologists, and computer scientists, fostering a rich interdisciplinary environment. Dr. Alilou has also served as a senior researcher and developer on projects integrating artificial intelligence into clinical workflows, focusing on machine learning algorithms for lung nodule detection, segmentation, and classification. His algorithms have been implemented in software solutions used by research hospitals and diagnostic centers, significantly enhancing diagnostic precision and workflow efficiency. In addition to research, Dr. Alilou has mentored graduate students, supervised thesis projects, and contributed to the development of training modules in biomedical imaging and AI. His professional experience also includes serving as a reviewer for numerous peer-reviewed journals, including IEEE Transactions on Medical Imaging and Medical Physics. Through these roles, Dr. Alilou has built a strong reputation as both a scientific innovator and a collaborative leader in the medical imaging community.

Research Interests

Dr. Masoud Alilou’s research interests lie at the convergence of biomedical engineering, medical image analysis, and artificial intelligence. Central to his work is the development of computational techniques for the automated analysis of medical images, particularly in the early detection and characterization of diseases such as lung cancer and chronic obstructive pulmonary disease (COPD). He is deeply interested in low-dose CT imaging and its applications in non-invasive diagnostics, seeking to optimize the accuracy and efficiency of radiological assessments through advanced algorithms. A significant focus of Dr. Alilou’s research is on radiomics—extracting high-dimensional features from medical images to identify patterns correlated with disease outcomes. He is also engaged in developing deep learning models for image classification, segmentation, and prediction of treatment response. His work explores how quantitative image features can be integrated with clinical data to inform precision medicine. Moreover, Dr. Alilou is enthusiastic about translational research, ensuring that the algorithms and tools he develops are applicable in clinical settings. His interdisciplinary projects often involve partnerships with radiologists, oncologists, and biostatisticians. Through his commitment to impactful research, Dr. Alilou continues to push the boundaries of medical imaging, aiming to enhance patient outcomes through innovation and data-driven healthcare solutions.

Research Skills

Dr. Masoud Alilou possesses an exceptional set of research skills that span computational modeling, machine learning, and biomedical image analysis. He is highly proficient in developing and implementing complex algorithms for image processing tasks, including segmentation, registration, and feature extraction. His expertise in computer vision allows him to work with large-scale imaging datasets, transforming raw medical data into meaningful clinical insights. He has extensive experience with deep learning frameworks such as TensorFlow, PyTorch, and Keras, which he uses to design and train neural networks for various diagnostic tasks. Additionally, Dr. Alilou is adept in programming languages such as Python, MATLAB, and C++, enabling him to prototype and optimize algorithms efficiently. His skills in radiomics and statistical analysis allow for the extraction and evaluation of high-dimensional imaging biomarkers, supporting the development of predictive and prognostic models. Dr. Alilou also demonstrates strong skills in interdisciplinary collaboration, integrating domain knowledge from radiology, oncology, and bioinformatics into his research workflows. His rigorous approach to data validation, model performance evaluation, and reproducibility ensures the reliability of his findings. Whether through designing novel AI models or translating computational tools into clinical applications, Dr. Alilou’s technical and collaborative skills stand at the core of his impactful research contributions.

Awards and Honors

Dr. Masoud Alilou has received several prestigious awards and honors in recognition of his outstanding research contributions and academic achievements. His innovative work in the field of medical image analysis has earned him accolades from both academic institutions and professional organizations. As a graduate student, he was honored with the Research Excellence Award at Case Western Reserve University, acknowledging his impactful contributions to biomedical engineering and medical imaging. His research has also been recognized at international conferences, where he has received best paper and poster awards for his work on automated lung cancer detection and radiomics-based diagnostic tools. Dr. Alilou’s contributions to artificial intelligence in healthcare have attracted attention from funding bodies such as the National Institutes of Health (NIH), resulting in several grant-supported projects. In addition, he has been invited to present his work at renowned symposiums and workshops, affirming his status as a thought leader in his field. Dr. Alilou also serves as a regular reviewer for high-impact journals, a testament to the scientific community’s trust in his expertise. These honors reflect not only his technical proficiency but also his dedication to advancing medical science through innovation, collaboration, and academic excellence.

Conclusion

In summary, Dr. Masoud Alilou stands out as a pioneering figure in the field of biomedical engineering and medical image analysis. With a strong educational foundation and diverse professional experience, he has successfully bridged the worlds of computational science and clinical medicine. His research—centered on the development of AI-driven tools for disease diagnosis and prediction—has not only advanced academic knowledge but also brought tangible benefits to healthcare practice. Dr. Alilou’s skills in image processing, machine learning, and interdisciplinary collaboration have positioned him as a key contributor to the evolving landscape of precision medicine. His numerous awards and academic recognitions reflect a career marked by innovation, excellence, and societal impact. Beyond research, Dr. Alilou’s contributions as a mentor, educator, and collaborator have enriched the academic and scientific communities. Looking forward, he continues to explore new frontiers in medical AI, with a vision of improving diagnostic accuracy, patient outcomes, and health system efficiency. As a scientist dedicated to turning complex data into actionable healthcare solutions, Dr. Alilou exemplifies the potential of integrating technology and medicine for the betterment of global health.

Publications Top Notes

  1. Title: Home energy management in a residential smart micro grid under stochastic penetration of solar panels and electric vehicles
    Authors: M. Alilou, B. Tousi, H. Shayeghi
    Year: 2020
    Citations: 93

  2. Title: Fractional-order control techniques for renewable energy and energy-storage-integrated power systems: A review
    Authors: M. Alilou, H. Azami, A. Oshnoei, B. Mohammadi-Ivatloo, R. Teodorescu
    Year: 2023
    Citations: 33

  3. Title: Application of multi objective HFAPSO algorithm for simultaneous placement of DG, capacitor and protective device in radial distribution network
    Authors: H. Shayeghi, M. Alilou
    Year: 2015
    Citations: 25

  4. Title: Multi-objective optimization of demand side management and multi DG in the distribution system with demand response
    Authors: M. Alilou, D. Nazarpour, H. Shayeghi
    Year: 2018
    Citations: 24

  5. Title: Simultaneous placement of renewable DGs and protective devices for improving the loss, reliability and economic indices of distribution system with nonlinear load model
    Authors: M. Alilou, V. Talavat, H. Shayeghi
    Year: 2020
    Citations: 20

  6. Title: Multi-objective energy management of smart homes considering uncertainty in wind power forecasting
    Authors: M. Alilou, B. Tousi, H. Shayeghi
    Year: 2021
    Citations: 19

  7. Title: Multi-Objective demand side management to improve economic and‎ environmental issues of a smart microgrid‎
    Authors: H. Shayeghi, M. Alilou
    Year: 2021
    Citations: 17

  8. Title: Distributed generation and microgrids
    Authors: H. Shayeghi, M. Alilou
    Year: 2021
    Citations: 16

  9. Title: Multi‐objective unit and load commitment in smart homes considering uncertainties
    Authors: M. Alilou, B. Tousi, H. Shayeghi
    Year: 2020
    Citations: 12

  10. Title: Day-ahead scheduling of electric vehicles and electrical storage systems in smart homes using a novel decision vector and AHP method
    Authors: M. Alilou, G.B. Gharehpetian, R. Ahmadiahangar, A. Rosin, et al.
    Year: 2022
    Citations: 11

  11. Title: Optimal placement and sizing of TCSC for improving the voltage and economic indices of system with stochastic load model
    Authors: S. Ghaedi, B. Tousi, M. Abbasi, M. Alilou
    Year: 2020
    Citations: 10

Degefu Dogiso | Engineering | Best Researcher Award

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Mr. Degefu Dogiso | Engineering | Best Researcher Award

PhD candidate from Hawassa University, Ethiopia

Degefu Dogiso is an emerging researcher in the field of Agricultural Engineering, with a strong focus on soil and water conservation. An Ethiopian national, he has built a solid academic and professional foundation in environmental and watershed management. Currently pursuing his PhD at Hawassa University Institute of Technology, he demonstrates deep commitment to research that addresses critical environmental challenges, including soil erosion, climate change impacts, and sustainable land use. Degefu has published peer-reviewed articles in reputable journals such as Land Degradation & Development and Agrosystem, Geoscience and Environment, showcasing his ability to contribute meaningful scientific insights. His technical proficiency spans across advanced modeling tools like SWAT and InVEST-SDR, GIS applications, and machine learning for environmental analysis. Additionally, his practical experience in governmental and conservation roles strengthens his applied understanding of the field. Degefu’s research integrates technology, field knowledge, and policy application, reflecting a well-rounded profile suitable for academic and practical impact. His career trajectory, marked by consistent growth and relevance, positions him as a promising candidate for future academic honors and research leadership. His dedication to both knowledge generation and environmental sustainability underpins a scholarly path rooted in impact, innovation, and responsibility.

Professional Profile

Education

Degefu Dogiso has built a robust academic foundation in the field of soil and water conservation through a progressive and focused educational journey. He is currently pursuing a PhD in Agricultural Engineering, specializing in Soil and Water Conservation Engineering, at the Hawassa University Institute of Technology. His doctoral research emphasizes the modeling of soil erosion and the impact of climate change on natural resources, showcasing a research direction with high environmental relevance. Prior to his PhD, Degefu earned a Master of Science (MSc) in Soil and Water Conservation Engineering from the same institution, where he cultivated expertise in hydrological modeling, conservation practices, and sustainable watershed management. His academic roots trace back to his undergraduate studies at the Hawassa University Wondo Genet College of Forestry and Natural Resources, where he completed his Bachelor of Science (BSc) in Soil Resources and Watershed Management. Each phase of his academic path reflects a commitment to advancing scientific knowledge and practical solutions in environmental resource management. Through these rigorous academic programs, he has developed a deep theoretical understanding and practical skill set that now support his growing contributions to scientific literature and environmental policy. His educational trajectory reinforces his credibility as a research-oriented professional.

Professional Experience

Degefu Dogiso brings significant professional experience that complements his academic background, highlighting his ability to translate research into action. Over the span of eight years, he has served in key roles that demonstrate leadership, technical expertise, and community engagement. For five years, he worked as a Soil and Water Conservation Expert, where he was responsible for implementing conservation strategies, conducting erosion assessments, and advising on sustainable land management practices. This role involved hands-on project management and provided him with critical insights into the ecological and social dynamics of conservation in Ethiopia. Following this, Degefu advanced to the position of Agricultural Office Head for three years. In this role, he oversaw agricultural development projects, coordinated with stakeholders, and led initiatives focused on soil and water conservation across regional agricultural zones. His leadership helped bridge policy with practice and ensured the effective implementation of environmentally responsible agricultural strategies. These experiences have equipped him with a practical understanding of the challenges and opportunities in soil and water resource management. His professional journey demonstrates not only a commitment to environmental stewardship but also the capacity to lead, implement, and innovate within both technical and administrative frameworks.

Research Interests

Degefu Dogiso’s research interests lie at the intersection of environmental science, engineering, and sustainable land management. His primary focus is on soil erosion modeling and conservation strategies, a field critical to mitigating land degradation and maintaining agricultural productivity. He is deeply engaged in examining the impacts of land use and land cover change (LULCC) on soil and water resources, particularly in ecologically sensitive and heavily farmed regions of Ethiopia. His interests also extend to assessing the impacts of climate change on soil and water systems, an area with growing urgency due to shifting rainfall patterns and increasing vulnerability in the Global South. Hydrological modeling and watershed management form another core area of his research, as he seeks to understand and optimize water resource distribution within complex ecological systems. Additionally, Degefu is passionate about applying remote sensing and GIS technologies in environmental monitoring, combining spatial data analysis with modern computing tools to inform conservation strategies. His research interests are not only scientifically relevant but also have practical implications for environmental planning and agricultural resilience. This wide-ranging, yet interconnected, portfolio reflects a comprehensive and forward-thinking approach to tackling contemporary environmental challenges.

Research Skills

Degefu Dogiso possesses a robust set of research skills that equip him to tackle complex environmental and agricultural challenges with precision and innovation. He is proficient in soil erosion modeling using advanced tools such as USLE, RUSLE, SWAT, and InVEST-SDR, which allow for detailed simulations and analysis of erosion patterns under various land use and climate scenarios. Additionally, he has experience with Object-Based Image Analysis (OBIA), which enhances the accuracy of land classification and landscape interpretation. His skill set also includes climate change impact assessment, particularly using the CMIP6 model suite, which enables him to analyze future climate trends and their implications on soil and water systems. In the realm of geospatial analysis, Degefu is highly skilled in GIS and remote sensing platforms, including Google Earth Engine, ArcGIS, and ERDAS, tools essential for environmental monitoring and decision-making. He complements his spatial and modeling expertise with strong abilities in data analysis and visualization, using programming languages like Python and R, alongside traditional tools like Excel. Furthermore, his application of machine learning in land use and land cover classification demonstrates a commitment to integrating cutting-edge technology into his research. These combined skills make him a versatile and capable researcher.

Awards and Honors

While specific formal awards or honors are not listed in Degefu Dogiso’s curriculum vitae, his academic and professional achievements suggest a strong trajectory toward future recognition. His publication of peer-reviewed research in respected journals such as Land Degradation & Development and Agrosystem, Geoscience and Environment is itself a significant academic accomplishment, often regarded as a marker of excellence in research communities. In addition, his selection and continued progress as a PhD candidate at Hawassa University Institute of Technology reflect the institutional recognition of his research potential and technical competence. His leadership as an Agricultural Office Head further implies a level of trust and respect within his professional sphere, particularly in overseeing large-scale conservation and agricultural initiatives. Moreover, his ability to publish internationally relevant research while engaging in on-the-ground conservation work distinguishes him among his peers. As he completes his PhD and expands his academic output, Degefu is well-positioned to receive formal accolades, research grants, and conference invitations. Continued contributions to interdisciplinary research and international collaboration will likely bring him closer to notable awards in soil and water conservation, climate change research, and environmental engineering.

Conclusion

In conclusion, Degefu Dogiso is a dedicated and forward-thinking researcher whose work bridges science, technology, and environmental sustainability. With a solid academic background in soil and water conservation, ongoing PhD research, and years of field experience, he has developed a comprehensive understanding of ecological systems and sustainable land management. His skill set spans critical tools and methodologies, from erosion modeling and hydrological simulation to remote sensing and machine learning-based analysis. His recent publications in reputable international journals affirm his capacity for high-quality research and his commitment to addressing pressing environmental challenges in Ethiopia and beyond. While he is still in the early stages of his academic career, Degefu has laid a strong foundation for future scholarly and professional success. Continued growth in international collaboration, diversified research output, and completion of his doctoral studies will further enhance his qualifications for top-tier academic awards. As such, Degefu Dogiso not only demonstrates potential for recognition as a leading researcher but also embodies the values of applied science, community engagement, and environmental responsibility that are crucial in addressing the global challenges of our time.

Publications Top Notes

  1. Title: Assessment of soil erosion and sedimentation dynamics in the Rift Valley Lakes Basin, Ethiopia
    Authors: Degefu Dogiso, Alemayehu Muluneh, Abiot Ketema
    Year: 2025

  2. Title: Soil Erosion Responses to CMIP6 Climate Scenarios and Land Cover Changes in the Gidabo Watershed, Ethiopia: Implications for Sustainable Watershed Management
    Authors: Degefu Dogiso, Alemayehu Muluneh, Abiot Ketema
    Year: 2025

  3. Title: Soil Erosion Responses to CMIP6 Climate Scenarios and Land Cover Changes in the Gidabo Watershed, Ethiopia: Implications for Sustainable Watershed Management
    Author: Degefu Dogiso
    Year: 2025

  4. Title: Assessment of soil erosion and sedimentation dynamics in the Rift Valley Lakes Basin, Ethiopia
    Author: Degefu Dogiso
    Year: 2025

Hulya Sen Arslan | Engineering | Women Researcher Award

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​Assist. Prof. Dr. Hulya Sen Arslan | Engineering | Women Researcher Award

KARAMANOĞLU MEHMETBEY UNIVERCITY, Turkey

Dr. Hülya Şen Arslan is a distinguished academic specializing in Food Engineering, with a focus on functional foods, food chemistry, and food microbiology. She is currently serving as an Assistant Professor in the Department of Food Engineering at Karamanoğlu Mehmetbey University. Dr. Arslan has an extensive educational background, having completed her undergraduate studies at Selçuk University, followed by a master’s degree at Erciyes University, and a doctorate at Selçuk University. Her research interests are deeply rooted in food sciences, particularly in the development and analysis of functional foods and the chemical and microbiological aspects of food products. Throughout her career, Dr. Arslan has contributed to the academic community with several publications and has actively participated in peer review processes. Her dedication to research and education in the field of food engineering underscores her commitment to advancing knowledge and promoting innovation in food science.​

Professional Profile

Education

Dr. Hülya Şen Arslan’s academic journey commenced with a Bachelor of Science degree from Selçuk University’s Faculty of Agriculture, where she studied from 2009 to 2014. She then pursued a Master of Science in the Institute of Science at Erciyes University between 2014 and 2017. Her doctoral studies were conducted at Selçuk University’s Institute of Science from 2018 to 2022. This comprehensive educational background has provided Dr. Arslan with a solid foundation in agricultural and food sciences, equipping her with the necessary skills and knowledge to excel in her field.​

Professional Experience

Currently, Dr. Hülya Şen Arslan holds the position of Assistant Professor in the Department of Food Engineering at Karamanoğlu Mehmetbey University. In this role, she is responsible for teaching undergraduate and graduate courses, mentoring students, and conducting research in her areas of expertise. Her professional experience is marked by a commitment to academic excellence and a dedication to advancing the field of food engineering through both education and research.​

Research Interests

Dr. Arslan’s research interests encompass several critical areas within food sciences. She focuses on functional foods, exploring how bioactive components can enhance health benefits. Her work in food chemistry involves analyzing the molecular composition and properties of food substances, while her studies in food microbiology examine the role of microorganisms in food production, preservation, and safety. These research pursuits aim to contribute to the development of healthier and safer food products.​

Research Skills

With a robust background in food sciences, Dr. Arslan possesses a diverse set of research skills. She is proficient in laboratory techniques pertinent to food chemistry and microbiology, including chromatographic and spectroscopic methods for analyzing food components, as well as microbiological assays for detecting and characterizing foodborne pathogens. Additionally, her expertise extends to the design and implementation of studies related to functional foods, encompassing both the development of novel food products and the assessment of their health impacts.​

Awards and Honors

While specific awards and honors have not been detailed, Dr. Arslan’s contributions to the field of food engineering are evident through her active participation in research and academia. Her publications and involvement in peer review activities reflect a recognition of her expertise and dedication to advancing knowledge in food sciences.​

Conclusion

In summary, Dr. Hülya Şen Arslan is a dedicated academic and researcher in the field of food engineering. Her comprehensive education and professional experience have enabled her to contribute significantly to the understanding and development of functional foods, food chemistry, and food microbiology. Through her teaching, research, and service to the academic community, Dr. Arslan continues to play a vital role in advancing the science of food and promoting innovations that enhance food quality and safety.

Publications Top Notes​

  • Title: Simultaneous extraction of phenolics and essential oil from peppermint by pressurized hot water extraction
    Authors: M. Cam, E. Yüksel, H. Alaşalvar, B. Başyiğit, H. Şen, M. Yılmaztekin, et al.
    Year: 2019
    Citations: 34

  • Title: Antioxidant and chemical effects of propolis, sage (Salvia officinalis L.), and lavender (Lavandula angustifolia Mill) ethanolic extracts on chicken sausages
    Authors: S. Yerlikaya, H. Şen Arslan
    Year: 2021
    Citations: 15

  • Title: Antibacterial and antioxidant activity of peach leaf extract prepared by air and microwave drying
    Authors: H. Şen Arslan, A. Cabi, S. Yerlikaya, C. Sariçoban
    Year: 2021
    Citations: 8

  • Title: Comparison some microbiological and physicochemical properties of freeze dryed and spray dryed milk powder
    Authors: S. Yerlikaya, H. Ş. Arslan
    Year: 2019
    Citations: 8*

  • Title: Effect of ultrasound and microwave pretreatments on some bioactive properties of beef protein hydrolysates
    Authors: H. Şen Arslan, C. Sariçoban
    Year: 2023
    Citations: 7

  • Title: Use of fruits and vegetables in meat and meat products in terms of dietary fiber
    Authors: H. Şen Arslan, C. Sariçoban, S. Yerlikaya
    Year: 2021
    Citations: 4

  • Title: Effects of various plant parts on storage stability and colour parameters of beef extracts
    Authors: B. A. Oğuz, C. Sarıçoban, H. Şen Arslan
    Year: 2019
    Citations: 4

  • Title: Ultrason destekli elma atık özütlerinin bazı biyoaktif özellikleri
    Authors: H. Ş. Arslan
    Year: 2023
    Citations: 3*

  • Title: Karaman İl Merkezinde Yaşayan Halkın Bilinçli Gıda Tüketim Derecesinin Araştırılması
    Authors: S. Yerlikaya, Ş. N. Karaman, S. Tuna, H. Ş. Arslan
    Year: 2020
    Citations: 3

  • Title: Increased reactive carboxyl and free alfa-amino groups from fish type I collagen peptides by Alcalase® hydrolysis exhibit higher antibacterial and antioxidant …
    Authors: S. Yasar, H. S. Arslan, K. Akgul
    Year: 2024
    Citations: 2

Atiqur Rahman | Engineering | Best Researcher Award

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Mr. Atiqur Rahman | Engineering | Best Researcher Award

PhD Researcher from University of Bolton, United Kingdom

Md Atiqur Rahman is a passionate aerospace engineering professional with a rich background in both academia and research. Currently serving as an Engineering Lecturer at Blackpool & The Fylde College in the UK, he also pursues a Ph.D. at the University of Bolton, focusing on sustainable composite materials for aerospace applications. With over nine years of experience in aeronautical education, his expertise spans curriculum development, student mentorship, assessment, and instructional leadership. He has taught at multiple institutions including Preston College, University of Bolton, and Cambrian International College of Aviation. His research is deeply rooted in innovation, particularly in the area of natural fiber-reinforced composites, with a specific emphasis on Borassus flabellifer (palmyra palm) husk fibers. Rahman has published six research articles and actively participates in academic conferences and seminars. Known for his technical abilities and practical knowledge, he integrates tools like Ansys, SolidWorks, and Matlab in both research and teaching. Awarded Best Lecturer in 2022 and a mentor to an award-winning student in 2021, he exemplifies academic dedication. Md Rahman is committed to advancing aerospace engineering through sustainable innovations while nurturing student growth in higher education. His profile reflects a balance of scholarly excellence, practical engineering acumen, and a deep commitment to teaching.

Professional Profile

Education

Md Atiqur Rahman has pursued a solid academic trajectory in aerospace and mechanical engineering. He is currently enrolled in a Ph.D. program at the University of Bolton, United Kingdom, where his research centers on the development of natural fiber-based composite materials for aerospace applications. This research is both timely and impactful, aligning with global movements toward sustainable aviation technology. Concurrently, he completed a Master of Philosophy (MPhil R2) in Mechanical Engineering at the same institution between July 2022 and November 2024, further sharpening his expertise in advanced material science and structural mechanics. His academic foundation began with a Bachelor of Engineering (Honours) degree in Aerospace Engineering from the University of Hertfordshire, UK, which he completed in 2012. The rigorous curriculum provided him with strong fundamentals in aerodynamics, propulsion systems, and aerospace structures. Throughout his educational journey, Md Rahman has consistently demonstrated academic excellence, integrating theory with hands-on research and software simulation. His academic path underscores a clear focus on applied engineering, sustainability, and innovation. This robust combination of qualifications positions him well for continued leadership in both academia and the aerospace research community, particularly in the development and application of bio-composites and eco-friendly engineering solutions.

Professional Experience

Md Atiqur Rahman has accumulated a diverse and extensive professional background in engineering education, spanning over nine years across the UK and Bangladesh. He currently serves as an Engineering Lecturer at Blackpool & The Fylde College, where he teaches and manages students up to Level 6, designs course materials, assesses learners, and supports curriculum alignment with Lancaster University and employer standards. Previously, he worked at Preston College, teaching aeronautical engineering to students in BTEC Pearson, City & Guilds, and EAL programs. At the University of Bolton, he served as a variable-hours lecturer, contributing to module delivery, exam preparation, and student guidance. In Bangladesh, Rahman held academic and leadership roles at Cambrian International College of Aviation and United College of Aviation, Science & Management. At Cambrian, he also acted as Internal Quality Assurer (IQA), leading BTEC curriculum development and internal training for faculty. Across all institutions, he has shown excellence in teaching, curriculum design, academic support, and student engagement. His ability to adapt his instruction based on learner capabilities has significantly enhanced academic outcomes. Rahman’s teaching is enriched by his research pursuits and practical skills, creating a well-rounded, impactful educational approach that bridges theory, practice, and innovation.

Research Interests

Md Atiqur Rahman’s research interests are centered around sustainable and advanced materials for aerospace applications. His current Ph.D. work at the University of Bolton explores the development and characterization of natural fiber-reinforced polymer composites, with a particular focus on Borassus flabellifer (palmyra palm) husk fibers. He investigates their physical, thermal, mechanical, and dynamic properties to evaluate their viability as lightweight, eco-friendly alternatives to traditional aerospace materials. His broader research interest encompasses aerodynamics, structural mechanics, hypersonic flight technologies, and bio-composite development. By aligning material science with aerospace engineering, Rahman seeks to address the increasing demand for sustainability in aviation. He is particularly drawn to the lifecycle assessment of natural fibers and their transformation through alkali treatments, aiming to enhance their bonding, thermal stability, and mechanical resilience. His work has practical implications for aircraft manufacturing, structural component design, and green engineering practices. He also maintains an interest in the pedagogical methods for engineering education and how research can be translated into real-world classroom application. This multi-dimensional research approach not only contributes to the scientific community but also supports the global push for environmentally responsible aerospace solutions through academic innovation and practical application.

Research Skills

Md Atiqur Rahman possesses a well-rounded and technically proficient set of research skills that support his specialization in material science and aerospace engineering. He is highly skilled in experimental research methodologies, particularly in characterizing bio-composite materials. His hands-on expertise includes the use of advanced lab instruments such as TA Instruments (TGA, DSC, DMA) for thermal analysis, Instron for tensile and flexural testing, and FTIR spectroscopy for chemical characterization. He is also proficient in density and water uptake measurements using pycnometers and ovens, and in the preparation of composite materials through hand lay-up techniques. Rahman complements his experimental skills with strong computational abilities, using tools like Ansys for finite element analysis, SolidWorks and Fusion 360 for design modeling, and Matlab for mathematical modeling and simulations. He applies these tools to optimize material properties and validate experimental outcomes. In addition, he demonstrates strong academic writing and data interpretation skills, having authored several scientific articles. His research workflow also reflects a robust understanding of ethics, literature review, statistical analysis, and research dissemination. These combined skills allow him to carry out comprehensive investigations in aerospace material development and communicate findings effectively to both academic and industry audiences.

Awards and Honors

Md Atiqur Rahman has earned notable recognition for his excellence in both teaching and research throughout his academic career. One of his most distinguished accolades is the Best Lecturer Award (2022) from Cambrian International College of Aviation, a testament to his commitment to student engagement, curriculum innovation, and instructional excellence. His mentorship has also yielded impressive results—most notably when one of his students was selected for the BTEC Award (2021) and received the Bronze Certificate for Engineering Learner of the Year, highlighting his ability to inspire and guide learners toward excellence. In addition to institutional recognition, Rahman is affiliated with several prestigious professional bodies, including the Royal Aeronautical Society (RAeS), The Institution of Structural Engineers (IStructE), and the American Society of Civil Engineers (ASCE). His active involvement in these societies, coupled with his participation in high-profile events like the RAeS Aerodynamics Specialist Conference and Government HE Events, showcases his commitment to lifelong learning and professional development. These honors and memberships not only validate his academic contributions but also underscore his rising influence as an educator and researcher in aerospace engineering, particularly in the field of sustainable materials and advanced manufacturing technologies.

Conclusion

Md Atiqur Rahman stands as a dynamic and impactful figure in the realms of aerospace education and research. His journey—from a dedicated lecturer to an innovative Ph.D. researcher—demonstrates a rare blend of academic rigor, teaching excellence, and research innovation. His work on natural fiber-based composites is not only scientifically significant but also timely, addressing pressing environmental challenges within aerospace engineering. With a growing list of publications, conference presentations, and teaching awards, Rahman has established himself as a promising academic professional committed to excellence. His ability to bridge the gap between research and education ensures that his findings contribute directly to student learning and industry advancement. His diverse teaching experiences across different academic systems further enhance his instructional agility and global outlook. As he continues to expand his research collaborations, aim for high-impact journals, and pursue research leadership roles, his contributions will undoubtedly strengthen the field of sustainable aviation and engineering education. Md Atiqur Rahman is a deserving candidate for recognition such as the Best Researcher Award, with strong potential for continued academic and research leadership. His trajectory reflects both deep expertise and future promise in advancing environmentally responsible technologies within aerospace engineering.

Publications Top Notes

  1. Title: Palmyra Palm Shell (Borassus flabellifer) Properties Part 2: Insights into Its Thermal and Mechanical Properties
    Authors: M.A. Rahman, M. Ndiaye, B. Weclawski, P. Farrell
    Year: 2024
    Citations: 3

  2. Title: Palmyra Palm Shell (Borassus flabellifer) Properties Part 1: Insights into Its Physical and Chemical Properties
    Authors: M.A. Rahman, M. Ndiaye, B. Weclawski
    Year: 2024
    Citations: 3

  3. Title: Effect of Alkali Treatment on Dynamic Mechanical Properties of Borassus Flabellifer Husk Fibre Reinforced Epoxy Composites
    Authors: M.A. Rahman, Mamadou Ndiaye, Bartosz Weclawski, et al.
    Year: 2025
    Citations: 2

  4. Title: Palmyra Palm Shell (Borassus flabellifer) Properties Part 3: Insights into Its Morphological, Chemical and Thermal Properties after Alkali Treatment
    Authors: M.A. Rahman, M. Ndiaye, B. Weclawski, P. Farrell
    Year: 2024
    Citations: 2

  5. Title: Optimizing Borassus Husk Fibre/Epoxy Composites: A Study on Physical, Thermal, Flexural and Dynamic Mechanical Performance
    Authors: M.A. Rahman, M. Ndiaye, B. Weclawski, P. Farrell
    Year: 2025
    Citations: 1

  6. Title: Enhancing Thermal and Dynamic Mechanical Properties of Lignocellulosic Borassus Husk Fibre/Epoxy Composites through Alkali Treatment
    Authors: M.A. Rahman, M. Ndiaye, B. Weclawski, P. Farrell
    Year: 2025

Phani Monogya Katikireddi | Engineering | Best Innovator Award

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Mr. Phani Monogya Katikireddi | Engineering | Best Innovator Award

Cloud AI/ML Devops Engineer from USDA, United States

Phani Monogya Katikireddi is a highly accomplished IT professional with over 9.5 years of experience in Cloud AI/ML, DevOps Engineering, Full Stack Development, and Software Engineering. He specializes in integrating AI/ML technologies with scalable cloud infrastructure to develop innovative solutions that enhance business operations. His expertise spans automating workflows, designing robust CI/CD pipelines, and optimizing development lifecycles. In addition to his technical contributions, he has made significant research advancements, publishing multiple papers on AI/ML and DevOps, authoring a book on AI/ML, and securing two patents for innovative solutions. As a recognized thought leader, he serves on the editorial boards of esteemed journals, contributing to the evolution of AI/ML research. His ability to bridge the gap between research and real-world applications positions him as a leading innovator in the field.

Professional Profile

Education

Phani Monogya Katikireddi holds a strong academic background in computer science and engineering. His education has provided him with a solid foundation in AI/ML, cloud computing, and software development. Through continuous learning and advanced coursework, he has honed his expertise in machine learning, neural networks, and DevOps methodologies. His academic journey has been instrumental in shaping his innovative approach to integrating AI/ML with DevOps.

Professional Experience

With nearly a decade of experience, Phani has worked in various roles, including Cloud AI/ML DevOps Engineer and Full Stack Developer. His work has focused on designing AI-driven solutions, automating software delivery processes, and enhancing system reliability. His contributions to cloud-native architectures and intelligent automation have improved the efficiency and scalability of enterprise applications. His technical leadership and problem-solving skills have played a pivotal role in driving innovation in the IT industry.

Research Interest

Phani’s research interests lie in AI/ML, deep learning, DevOps automation, and cloud computing. He is particularly focused on integrating AI with DevOps to enhance software development and deployment processes. His work explores predictive modeling, machine learning pipeline automation, and the impact of AI on system performance and scalability. His research aims to bridge the gap between theoretical advancements and real-world applications in enterprise IT.

Research Skills

Phani possesses strong research skills, including AI/ML algorithm development, neural network optimization, cloud infrastructure management, and DevOps automation. He is adept at conducting experimental research, data analysis, and model validation. His ability to translate research findings into practical solutions has contributed to advancements in AI-driven automation. He also has experience in publishing research papers and collaborating with industry experts to push the boundaries of AI/ML and DevOps.

Awards and Honors

Phani has received notable recognition for his contributions to AI/ML and DevOps. He holds two patents for AI/ML innovations and has authored a well-regarded book on the subject. His research papers have been published in prestigious journals, and he actively participates as an editorial board member. His expertise and contributions to the field have positioned him as a distinguished professional and innovator.

Conclusion

Phani Monogya Katikireddi is a visionary IT professional with a passion for innovation in AI/ML and DevOps. His extensive experience, research contributions, and technical expertise make him a strong candidate for recognition as a leading innovator in the field. His ability to merge academic research with practical applications has had a profound impact on software development and cloud computing. His dedication to advancing AI/ML and DevOps positions him as a key contributor to technological progress and industry transformation.

Publications Top Notes

  1. Revolutionizing DEVOPS with Quantum Computing: Accelerating CI/CD pipelines through Advanced Computational Techniques

    • Authors: PM Katikireddi, P Singirikonda, Y Vasa

    • Year: 2021

  2. Music and Art Generation Using Generative AI

    • Authors: S Jaini, PM Katikireddi

    • Year: 2022

  3. Applications of Generative AI in Healthcare

    • Authors: S Jaini, PM Katikireddi

    • Year: 2022

  4. In Generative AI: Zero-Shot and Few-Shot

    • Authors: PM Katikireddi, S Jaini

    • Year: 2022

 

Ali Nawaz Sanjrani | Engineering | Best Researcher Award

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Assist. Prof. Dr Ali Nawaz Sanjrani | Engineering | Best Researcher Award

Assistant Professor at University of Electronic Science and Technology of China

Dr. Ali Nawaz Sanjrani is a highly accomplished mechanical engineer and academic with over 18 years of interdisciplinary experience in project management, reliability, quality assurance, and health and safety systems. He holds a PhD in Mechanical Engineering from the University of Electronics Science and Technology, China, and specializes in reliability monitoring, diagnostics, and prognostics of complex machinery. Dr. Sanjrani has a strong background in advanced manufacturing processes, lean manufacturing, and machine learning applications in engineering systems. He has served as an Assistant Professor at Mehran University of Engineering and Technology and has contributed significantly to both academia and industry. His research focuses on fluid dynamics, heat transfer, and predictive maintenance using AI-driven models. Dr. Sanjrani has published extensively in high-impact journals and conferences, earning recognition for his innovative approaches to engineering challenges. He is a certified lead auditor in ISO and OHSAS standards and a member of the Pakistan Engineering Council.

Professional Profile

Education

Dr. Ali Nawaz Sanjrani earned his PhD in Mechanical Engineering from the University of Electronics Science and Technology, Chengdu, China, with a CGPA of 3.89/4. His doctoral research focused on reliability monitoring, diagnostics, and prognostics of complex machinery. He completed his M.Engg. in Industrial Manufacturing from NED University, Karachi, with a CGPA of 3.04/4, specializing in lean manufacturing. His undergraduate degree in Mechanical Engineering was obtained from QUEST, Nawabshah, with an aggregate of 70%, specializing in mechanical manufacturing and materials. Throughout his academic journey, Dr. Sanjrani studied advanced courses such as Finite Element Analysis (FEA), Computer-Aided Manufacturing (CAM), Operations Research (OR), and Agile & Lean Manufacturing. His education has equipped him with a strong foundation in both theoretical and practical aspects of mechanical and industrial engineering, enabling him to excel in research, teaching, and industry applications.

Professional Experience 

Dr. Ali Nawaz Sanjrani has over 18 years of professional experience spanning academia, research, and industry. He served as an Assistant Professor at Mehran University of Engineering and Technology, SZAB Campus, from 2016 to 2020, where he specialized in fluid dynamics, heat transfer, and machine learning applications. Prior to this, he worked as a Lecturer at the same institution and as a visiting faculty member at INDUS University, Karachi. In the industry, Dr. Sanjrani was an Engineer in Quality Assurance and Quality Control at DESCON Engineering Works Limited, Lahore, from 2006 to 2011. His roles included implementing ISO standards, conducting audits, and ensuring quality and safety compliance. Dr. Sanjrani has also led research projects in predictive maintenance, reliability engineering, and lean manufacturing, bridging the gap between academic theory and industrial practice. His expertise in project management and integrated management systems has made him a valuable asset in both academic and professional settings.

Awards and Honors

Dr. Ali Nawaz Sanjrani has received numerous accolades for his academic and professional excellence. He was awarded the 3rd Prize in Academic Excellence and Performance Excellence at the University of Electronics Science and Technology, Chengdu, China, in 2024. He secured a fully funded Chinese Government Scholarship (CSC) for his PhD studies in 2020. Dr. Sanjrani was also recognized with an Appreciation Certificate from Karachi Shipyard & Engineering Works for achieving ISO certifications (QMS, EMS, OH&SMS) in 2011. His innovative approach to dismantling a luffing crane earned him an Appreciation Letter from the Managing Director of KSEW in 2013. Additionally, Dr. Sanjrani has been acknowledged for his research contributions through publications in high-impact journals and presentations at international conferences. His achievements reflect his dedication to advancing engineering knowledge and applying it to real-world challenges.

Research Interests

Dr. Ali Nawaz Sanjrani’s research interests lie at the intersection of mechanical engineering, machine learning, and reliability engineering. He specializes in predictive maintenance, diagnostics, and prognostics of complex machinery, particularly in high-speed trains and industrial systems. His work focuses on developing AI-driven models, such as LSTM networks and neural networks, for fault diagnosis and residual life prediction. Dr. Sanjrani is also deeply involved in fluid dynamics, heat transfer, and energy systems, exploring advanced manufacturing processes and lean manufacturing techniques. His research extends to renewable energy systems, including solar power and biogas utilization, as well as dynamic power management in microgrids. By integrating machine learning with traditional engineering practices, Dr. Sanjrani aims to enhance system reliability, efficiency, and sustainability. His interdisciplinary approach bridges the gap between theoretical research and practical applications, making significant contributions to both academia and industry.

Research Skills

  • Machine Learning & AI: Neural Networks, LSTM, Predictive Modeling, Fault Diagnosis.
  • Reliability Engineering: Prognostics, Diagnostics, Residual Life Prediction.
  • Fluid Dynamics & Heat Transfer: Modeling, Simulation, and Analysis.
  • Advanced Manufacturing: Lean Manufacturing, FEA, CAM, Agile Processes.
  • Renewable Energy Systems: Solar Power, Biogas, Microgrids.
  • Software Proficiency: Python, MATLAB, SolidWorks, Auto CAD, FEA Tools.
  • Certifications: ISO 9001, ISO 14001, OHSAS 18001 Lead Auditor.

Conclusion

Dr. Ali Nawaz Sanjrani is a distinguished mechanical engineer and academic with a proven track record in research, teaching, and industry. His expertise in reliability engineering, machine learning, and advanced manufacturing has led to significant contributions in predictive maintenance and system optimization. With numerous publications, awards, and certifications, Dr. Sanjrani continues to push the boundaries of engineering knowledge, applying innovative solutions to real-world challenges. His interdisciplinary approach and dedication to excellence make him a valuable asset in both academic and professional settings.

Publication Top Notes

  1. Ali Nawaz1 – RHSA Based Hybrid Prognostic Model for Predicting Residual Life of Bearing: A Novel Approach – Mechanical Systems and Signal Processing – To be published.
  2. Ali Nawaz1 – Multiparametric Dual Task Multioutput Artificial Neural Network Model for Bearing Fault Diagnosis and Residual Life Prediction in High-Speed Trains – IEEE Transaction of Reliability – To be published.
  3. Ali Nawaz1 – Advanced Learning Interferential ALI-Former: A Novel Approach for Live and Reliable High-Speed Train Bearing Fault Diagnosis – Neural Computing and Applications – To be published.
  4. Ali Nawaz Sanjrani1 – High-Speed Train Bearing Health Assessment Based on Degradation Stages Through Diagnosis and Prognosis by Using Dual-Task LSTM With Attention Mechanism – Quality and Reliability Engineering International Journal WILEY – 2025.
  5. Ali Nawaz Sanjrani3 – Dynamic Temporal LSTM-Seqtrans for Long Sequence: An Approach for Credit Card and Banking Accounts Fraud Detection in Banking System – 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing – 2025.
  6. Ali Nawaz Sanjrani1 – High-speed train wheel set bearing analysis: Practical approach to maintenance between end of life and useful life extension assessment – Results in Engineering – 2025.
  7. Ali Nawaz Sanjrani5 – Advanced dynamic power management using model predictive control in DC microgrids with hybrid storage and renewable energy sources – Journal of Energy Storage – 2025.
  8. Ali Nawaz Sanjrani1 – High-Speed Train Health Assessment Based on Degradation Stages and Fault Classification by using Dual Task LSTM with Attention Mechanism – 2024 6th International Conference on System Reliability and Safety Engineering – 2024.
  9. A.N. Sanjrani – A C-band Sheet Beam Staggered Double Grating Extended Interaction Oscillator – 2024 IEEE International Conference on Plasma Science (ICOPS) – 2024.
  10. Ali Nawaz1 – Bearing Health and Safety Analysis to improve the reliability and efficiency of Horizontal Axis Wind Turbine (HAWT) – ESREL 2023 – 2023.
  11. Ali Nawaz2 – Prediction of Remaining Useful Life of Bearings using a Parallel Neural Network – ESREL 2023 – 2023.
  12. Ali Nawaz Sanjrani2 – Performance Improvement through Lean System Case study of Karachi Shipyard & Engineering Works – IEIM 2024 – 2023.
  13. Ali Nawaz Sanjrani3 – Dynamic Performance of Partially Orifice Porous Aerostatic Thrust Bearing – Micromachines – 2021.
  14. Sanjrani; Ali Nawaz2 – Performance Evaluation of Mono Crystalline Silicon Solar Panels in Khairpur, Sind, Pakistan – JOJ Material Science – 2017.
  15. A. N. Sanjrani1 – Utilization of Biogas using Portable Biogas Anaerobic Digester in Shikarpur and Sukkur Districts: A case study – Pakistan Journal of Agriculture Engineering Veterinary Science – 2017.
  16. A. N. Sanjrani1 – Lean Manufacturing for Minimization of Defects in the Fabrication Process of Shipbuilding: A case study – Australian Journal of Engineering and Technology Research – 2017.

 

Jameer Kotwal | Engineering | Best Researcher Award

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Dr. Jameer Kotwal | Engineering | Best Researcher Award

Associate Professor at Dr D Y Patil Institute of Technology pimpri, India

Mr. Jameer G. Kotwal is an Assistant Professor at Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, with a career spanning over 14 years in the field of engineering education. He is currently pursuing a Ph.D. and holds a Master’s degree in Computer Engineering. Throughout his career, he has demonstrated remarkable proficiency in subjects related to deep learning, machine learning, CUDA programming, and algorithms. Mr. Kotwal has contributed significantly to academia by mentoring students, guiding projects, and being a part of various committees, including syllabus formation. His dedication to research and innovation is evidenced by his development of cutting-edge systems and products, such as facial recognition-based attendance systems. His work has resulted in multiple patents and copyrights, making him a key player in the technological innovations at his institution. Beyond academics, Mr. Kotwal has been honored with numerous awards, including the Best Teacher Award, and has played an active role in prestigious competitions like Smart India Hackathon.

Professional Profile

Education:

Mr. Jameer G. Kotwal holds a Master’s degree (ME) in Computer Engineering and is currently pursuing a Ph.D. in a related field. His academic journey has been marked by a strong focus on computer science and its application to real-world problems, specifically in machine learning, deep learning, and artificial intelligence. He has consistently pursued advanced coursework and certifications through platforms like NPTEL, Coursera, and Udemy, expanding his expertise. His ongoing doctoral studies further underscore his commitment to expanding knowledge in his field. The combination of practical teaching experience and academic research equips him to handle complex technical problems and contribute meaningfully to the research community. Additionally, his involvement in curriculum development, such as being a syllabus setter for various university courses, reflects his in-depth knowledge and academic rigor.

Professional Experience:

Mr. Kotwal’s professional experience spans over 14 years in the academic sector, primarily as an Assistant Professor. He has worked at several prestigious institutions, including Dr. D.Y. Patil Institute of Technology, Pimpri Chinchwad College of Engineering, and Nutan Maharashtra Institute of Engineering & Technology. His responsibilities have included teaching undergraduate and postgraduate students, guiding research projects, and taking on leadership roles within his department. Notably, he has served as the Department Project Coordinator and has handled various NBA (National Board of Accreditation) criteria. In addition to his teaching duties, Mr. Kotwal has been instrumental in organizing and delivering faculty development programs, mentoring students, and fostering research collaborations. His role in guiding over 50 undergraduate students and providing invaluable mentorship to numerous students in national hackathons has greatly contributed to the academic community.

Research Interest:

Mr. Kotwal’s primary research interests lie in the fields of machine learning, deep learning, artificial intelligence, and their applications in real-world problems. His research has centered on innovative solutions such as plant disease identification using deep learning and the development of advanced systems for facial recognition-based attendance and sign language translation. Additionally, his work on smart expense management systems, touchless attendance systems, and emotion-based intelligent chatbots showcases his focus on integrating AI technologies into everyday applications. Through his research, Mr. Kotwal aims to bridge the gap between theoretical knowledge and practical application, ultimately creating technology that can have a positive societal impact. He is also exploring the intersection of computer science with various industries, including agriculture, healthcare, and education.

Research Skills:

Mr. Kotwal is well-versed in various research methodologies and has honed a diverse set of technical skills through his academic and professional journey. His expertise spans deep learning, machine learning, algorithm design, CUDA programming, and compiler design. He is proficient in using frameworks and tools like Python, TensorFlow, Keras, and PyTorch for deep learning and AI applications. Furthermore, his ability to develop and implement innovative systems, such as facial attendance systems and smart healthcare applications, demonstrates his ability to blend theoretical knowledge with hands-on technical skills. Mr. Kotwal also has considerable experience with data analysis and modeling, which is crucial for driving research in artificial intelligence. His passion for research is evident in his continuous engagement with new technologies and his involvement in applying them in innovative projects.

Awards and Honors:

Mr. Kotwal has received multiple awards and recognitions throughout his career. Notably, he was honored with the Best Teacher Award for his outstanding contribution to the academic community. His mentorship and guidance in national competitions, such as the Smart India Hackathon, led to his teams winning significant prizes, further enhancing his reputation as a leading educator and researcher. Mr. Kotwal also secured second place in the Amity Incubation Centre for his project on plant disease identification using deep learning. His patents and copyrights in the areas of facial recognition systems, smart expense managers, and privacy-oriented extensions demonstrate his innovative approach to research and technology development. These accolades not only reflect his individual accomplishments but also underscore his role in nurturing students and advancing research in technology.

Conclusion:

In conclusion, Mr. Jameer G. Kotwal is a distinguished academic and researcher whose contributions to the fields of computer science, particularly machine learning and deep learning, have made a significant impact. His extensive professional experience, coupled with his continuous academic growth through certifications and research, positions him as a strong contender for the Best Researcher Award. Mr. Kotwal’s leadership in curriculum development, his innovative patents and products, and his successful mentorship in national hackathons highlight his exceptional contributions to both education and research. His ability to blend theoretical knowledge with practical solutions makes him a valuable asset to the academic and research communities. Despite room for further collaboration and publication, his body of work clearly demonstrates his capability and potential for even greater accomplishments in the future.

Publication top Notes

  1. Enhanced leaf disease detection: UNet for segmentation and optimized EfficientNet for disease classification
    • Authors: Kotwal, J., Kashyap, R., Shafi, P.M., Kimbahune, V.
    • Year: 2024
  2. A modified time adaptive self-organizing map with stochastic gradient descent optimizer for automated food recognition system
    • Authors: Kotwal, J.G., Koparde, S., Jadhav, C., Somkunwar, R., Kimbahune, V.
    • Year: 2024
    • Citation: 3
  3. An India soybean dataset for identification and classification of diseases using computer-vision algorithms
    • Authors: Kotwal, J., Kashyap, R., Pathan, M.S.
    • Year: 2024
    • Citation: 1
  4. Artificial Driving based EfficientNet for Automatic Plant Leaf Disease Classification
    • Authors: Kotwal, J.G., Kashyap, R., Shafi, P.M.
    • Year: 2024
    • Citation: 85
  5. Yolov5-based convolutional feature attention neural network for plant disease classification
    • Authors: Kotwal, J.G., Kashyap, R., Shafi, P.M.
    • Year: 2024
    • Citation: 2
  6. A conditional generative adversarial networks and Yolov5 Darknet-based skin lesion localization and classification using independent component analysis model
    • Authors: Koparde, S., Kotwal, J., Deshmukh, S., Chaudhari, P., Kimbahune, V.
    • Year: 2024
  7. Big Data and Smart Grid: Implementation-Based Case Study
    • Authors: Kotwal, M.J., Kashyap, R., Shafi, P.
    • Year: 2023
  8. Agricultural plant diseases identification: From traditional approach to deep learning
    • Authors: Kotwal, J., Kashyap, D.R., Pathan, D.S.
    • Year: 2023
    • Citation: 142

 

 

Meiqi Li | Engineering | Best Researcher Award

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Dr. Meiqi Li | Engineering | Best Researcher Award

Engineer at Peking University, China.

Dr. Meiqi Li is a skilled biomedical engineer with a strong focus on cutting-edge imaging technologies. As a Co-Principal Investigator (Co-PI) and Engineer in the Peng Xi Group at the School of Life Sciences, Peking University, she has contributed significantly to the fields of super-resolution microscopy and multi-dimensional live-cell imaging. With several prestigious awards, including teaching accolades and innovation prizes from Peking University, Dr. Li is recognized as an accomplished researcher and educator. Her commitment to advancing knowledge in her field is evident through her leadership in multiple high-impact research projects funded by the National Natural Science Foundation. Dr. Li’s innovative work is positioned to make lasting contributions to biomedical research, particularly in understanding complex cellular structures and dynamics.

Professional Profile

Education

Dr. Li completed her Ph.D. in Biomedical Engineering at Peking University, specializing in super-resolution microscopy and live-cell imaging under the mentorship of the Peng Xi Group. During her Ph.D., she developed expertise in advanced imaging techniques, paving the way for her work in high-resolution cellular imaging. She also holds a Bachelor of Science in Automation from Harbin Institute of Technology, where her research centered on photoacoustic imaging, laying a foundation for her proficiency in engineering and imaging sciences. Her academic background combines rigorous technical training with a focus on real-world applications in life sciences, positioning her for success in the interdisciplinary field of biomedical engineering.

Professional Experience

Since 2022, Dr. Li has held the role of Co-PI and Engineer in the Peng Xi Group at Peking University’s School of Life Sciences. Here, she has been instrumental in managing complex research projects, including the National Natural Science Foundation’s Youth Project and Key Project. In these roles, she oversees the development of advanced imaging technologies and guides research teams in exploring new frontiers in live-cell imaging. Her prior experience includes leading and participating in projects related to photoacoustic imaging, as well as contributing to research that has practical applications for diagnostic and research purposes in cell biology and biomedicine.

Research Interests

Dr. Li’s primary research interests lie in the fields of super-resolution microscopy and multi-dimensional live-cell imaging. She is particularly focused on developing and applying novel imaging techniques to capture the dynamic, three-dimensional structures of living cells. Her goal is to advance biomedical imaging technologies, enabling researchers to view cellular processes at unprecedented spatial and temporal resolutions. Through her work, Dr. Li aims to unlock insights into cellular functions that were previously beyond the reach of conventional imaging tools, with implications for understanding disease mechanisms and developing targeted therapies.

Research Skills

Dr. Li possesses an advanced skill set in various biomedical imaging technologies, particularly in super-resolution microscopy, structured illumination microscopy, and photoacoustic imaging. She is adept in utilizing and refining complex imaging equipment, analyzing multi-dimensional data, and implementing innovative solutions to improve imaging resolution and accuracy. Her technical expertise extends to project management, data interpretation, and scientific writing, enabling her to effectively communicate complex findings. Her strong foundation in automation, gained through her undergraduate education, further complements her imaging skills, allowing her to approach research questions with a unique, interdisciplinary perspective.

Awards and Honors

Throughout her academic and professional career, Dr. Li has received numerous awards that highlight her excellence in research and teaching. Notably, she received the First Prize of the Peking University Innovation in Teaching Application Competition and the Innovation Technology Award. Her teaching prowess was further recognized with awards in the Young Teachers’ Teaching Fundamentals Competition, where she received multiple accolades, including the Best Teaching Demonstration Award. Additionally, Dr. Li has been honored with the Principal Fellowship of Peking University, the Jiaxi Lu Outstanding Graduate Student Award, and the Academic Innovation Prize, among others. These awards reflect her dedication to research, her innovative approach to teaching, and her standing as a respected member of the academic community.

Conclusion

Dr. Meiqi Li is a promising candidate for the Best Researcher Award. Her academic achievements, funded research projects, and numerous accolades reflect her commitment to innovation in life sciences. While she may benefit from additional years of experience in leading large-scale, independent projects, her potential for growth and impact in biomedical engineering is evident. Her pioneering work in cell imaging and microscopy, coupled with her teaching and mentorship success, make her a strong and competitive candidate for this award.

Publication Top  Notes

  • Expanding super-resolution imaging versatility in organisms with multi-confocal image scanning microscopy
    W. Ren†, M. Guan†, Q. Liang†, M. Li*, B. Jin, G. Duan, L. Zhang, X. Ge, H. Xu, Y. Hou, B. Gao, Sodmergen, P. Xi*
    National Science Review, nwae303 (2024).
  • Multi-organelle interactome through 3D fluorescence super-resolution microscopy and deep learning segmentation
    K. Zhanghao†, M. Li†,, X. Chen, W. Liu, T. Li, Y. Wang, F. Su, Z. Wu, C. Shan, J. Wu, Y. Zhang, J. Fu, P. Xi, D. Jin*
    Nature Communications, Third round of review.
  • Multi-resolution analysis enables fidelity-ensured computational super-resolution and denoising for fluorescence microscopy
    Y. Hou, W. Wang, Y. Fu, X. Ge, M. Li*, P. Xi*
    eLight, 4, 14 (2024).
  • Three-dimensional dipole orientation mapping with high temporal-spatial resolution using polarization modulation
    S. Zhong, L. Qiao, X. Ge, X. Xu, Y. Fu, S. Gao, K. Zhanghao, H. Hao, W. Wang, M. Li*, P. Xi*
    PhotoniX, 5, 19 (2024).
  • Fluorescence Lifetime Super-Resolution Imaging Unveils the Dynamic Relationship between Mitochondrial Membrane Potential and Cristae Structure Using the Förster Resonance Energy Transfer Strategy
    F. Peng, X. Ai, J. Sun, X. Ge, M. Li*, P. Xi, B. Gao*
    Analytical Chemistry, 96, 11052-11060 (2024).
  • High-dimensional Super-Resolution Imaging of Heterogeneous Subcellular Lipid Membranes
    K. Zhanghao†, W. Liu†, M. Li†, Z. Wu, X, Wang, X. Chen, C. Shan, H. Wang, X. Chen, Q. Dai, P. Xi, D. Jin
    Nature Communications, 11, 5890 (2020).
  • Structured illumination microscopy using digital micro-mirror device and coherent light source
    M. Li†, Y. Li†, W. Liu, A. Lal, S. Jiang, D. Jin, H. Yang, S. Wang, K. Zhanghao, P. Xi
    Applied Physics Letters, 116 (2020).
  • High-speed autopolarization synchronization modulation three-dimensional structured illumination microscopy
    Y. Li, R. Cao, W. Ren, Y. Fu, H. Y. Hou, S. Zhong, K. Zhanghao, M. Li*, P. Xi*
    Advanced Photonics Nexus, 3, 016001 (2023).
  • Super-resolution imaging of fluorescent dipoles via polarized structured illumination microscopy
    K. Zhanghao†, X. Chen†, W. Liu, M. Li, Y. Liu, Y. Wang, S. Luo, X. Wang, C. Shan, H. Xie, J. Gao, X. Chen, D. Jin, X. Li, Y. Zhang, Q. Dai, P. Xi
    Nature Communications, 10, 4694 (2019).
    Highlight on Nature Methods (16, 1206 (2019)). DOI: 10.1038/s41592-019-0682-6
  • Visualization of cristae and mtDNA interactions via STED nanoscopy using a low saturation power probe
    W. Ren, X. Ge, M. Li, J. Sun, S. Li, S. Gao, C. Shan, B. Gao, P. Xi
    Light: Science & Applications, 13, 116 (2024).

Rabia Toprak | Engineering | Best Researcher Award

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Assist. Prof. Dr. Rabia Toprak | Engineering | Best Researcher Award

Electrical-Electronics Engineering,  Karamanoglu Mehmetbey University,  Turkey

Rabia Toprak, an Assistant Professor at Karamanoglu Mehmetbey University, holds a Ph.D. in Electrical-Electronics Engineering from Konya Technical University, where her thesis focused on the detection of cancerous tissues using advanced antenna structures. With extensive research experience, she has participated in multiple national projects, including the development of high-gain microstrip antennas for medical applications and investigations into natural fiber-reinforced composites. Toprak has published numerous articles in international refereed journals, contributing to advancements in antenna design for cancer detection and electromagnetic field studies. Her teaching contributions span both undergraduate and graduate courses, where she emphasizes the principles of electromagnetics. Rabia Toprak’s dedication to innovative research and her significant impact on the fields of telecommunications and biomedical engineering make her a highly suitable candidate for the Research for Best Researcher Award, recognizing her contributions to academia and her commitment to improving health outcomes through technology.

Profile

Professional Experience

Rabia Toprak has built a solid academic career in the field of electrical-electronic engineering, specializing in telecommunications. She currently holds the position of Assistant Professor at Karamanoglu Mehmetbey University, having previously served as a research assistant in the same department from 2013 to 2023. Her long-standing affiliation with the academic community highlights her commitment to both teaching and research. Toprak’s experience includes leadership roles in various scientific projects, particularly those focusing on antenna designs for medical applications, further showcasing her expertise in applied electromagnetics.

Research Interests

Rabia Toprak’s research interests lie at the intersection of electrical engineering and biomedical applications, particularly in the design and implementation of microstrip antennas for medical diagnostics. Her doctoral work focused on the detection of cancerous tissues using high-gain microstrip and horn antenna structures, showcasing her commitment to advancing healthcare technologies. Toprak has contributed to various projects investigating the electrical properties of pathological tissues and has designed microstrip antennas for detecting cardiovascular conditions. Additionally, her work includes the development of natural fiber-reinforced epoxy/polymer-based hybrid composites for antenna applications, reflecting her interest in sustainable materials. With numerous publications in reputable journals, Toprak continues to explore innovative solutions for improving diagnostic methods in medicine, making significant contributions to both engineering and healthcare fields. Her ongoing projects include research on the effects of antenna designs on breast and colon tissue samples, further establishing her expertise in medical engineering.

Research Skills

Rabia Toprak has demonstrated exceptional research skills throughout her academic and professional career. As an Assistant Professor in the Department of Electrical-Electronic Engineering at Karamanoğlu Mehmetbey University, she has actively engaged in numerous research projects focused on innovative applications of microstrip antennas for medical diagnostics. Her expertise encompasses the design and implementation of antennas for detecting cancerous tissues and cardiovascular conditions, showcasing her proficiency in both theoretical and practical aspects of electromagnetic engineering. Toprak’s research is underpinned by her ability to conduct comprehensive literature reviews, design experimental setups, and analyze complex data. She has published multiple articles in esteemed international journals, reflecting her commitment to advancing knowledge in her field. Additionally, her involvement in collaborative research projects, such as the detection of cancer tissues and the design of hybrid composite substrates, highlights her strong teamwork and project management capabilities. Overall, Rabia Toprak’s research skills position her as a leading figure in her area of expertise.

Awards and Honors

Rabia Toprak, Assistant Professor at Karamanoglu Mehmetbey University, has garnered notable recognition for her innovative research in the field of electrical and electronic engineering. Her pivotal contributions include significant advancements in microstrip antenna technology, particularly in applications related to cancer detection and cardiovascular monitoring. In 2022, she received a prestigious grant from Higher Education Institutions for her project on the detection of cancerous tissues, highlighting her leadership in national research initiatives. Additionally, her work has been featured in several high-impact international journals, showcasing her commitment to advancing scientific knowledge. Toprak’s presentations at various international conferences have further solidified her reputation as a leading researcher in her field. Her dedication to education is evident in her teaching roles, where she inspires the next generation of engineers. These accolades reflect her exceptional contributions to both academia and the scientific community, establishing her as a prominent figure in engineering research.

Conclusion 

Rabia Toprak is a strong candidate for the Research for Best Researcher Award due to her significant contributions to the field of electrical and electronic engineering, particularly in medical applications. With a doctoral thesis focusing on the detection of cancerous tissues using advanced microstrip and horn antenna structures, she has demonstrated a commitment to innovative research with practical implications. Her role in various national scientific projects, such as the investigation of electrical properties of pathological tissues and the development of natural fiber-reinforced hybrid composites, underscores her multidisciplinary approach and collaboration within the scientific community. Furthermore, her numerous publications in reputable international journals highlight her ongoing dedication to advancing knowledge in her field. Rabia’s expertise, research impact, and teaching contributions at Karamanoglu Mehmetbey University reflect her commitment to excellence and innovation in research, making her an ideal candidate for this prestigious award.

Publication Top Notes

  • An approach to determine pathological breast tissue samples with free-space measurement method at 24 GHz
    • Authors: Rabia Toprak, Seyfettin Sinan Gultekin, Ahmet Kayabasi, Zeliha Esin Celik, Fatma Hicret Tekin, Dilek Uzer
    • Year: 2024
    • Citations: 0 (as it is a recent publication)
  • Comparison of Far Field and Near Field Values of Skin Tissue Measured Using Microstrip Antenna Structure
    • Authors: Rabia Toprak, Seyfettin Sinan Gultekin, Dilek Uzer
    • Year: 2022
    • Citations: 1
  • Investigation of Gain Enhancement in Microstrip Antenna Structure in Pathological Tissue Samples
    • Authors: Rabia Toprak, Seyfettin Sinan Gultekin, Dilek Uzer
    • Year: 2021
    • Citations: 2
  • Patolojik Doku Örneklerinde Mikroşerit Anten Yapısında S-Parametrelerine Ait Normalizasyon Değerlerinin İncelenmesi
    • Authors: Rabia Toprak, Seyfettin Sinan Gultekin, Dilek Uzer
    • Year: 2021
    • Citations: 0 (as it is a recent publication)
  • Determination of Cardiovascular Occlusion with Microstrip Antennas
    • Authors: H. Uyanik, D. Uzer, Rabia Toprak, Seyfettin Sinan Gultekin
    • Year: 2020
    • Citations: 3
  • Kanser Hastalığı Tespitine Yönelik ISM Bandında Çalışan Mikroşerit Yama Yapılı İki Antenin Elektromanyetik Alan ve Saçılma Parametreleri Verilerinin Değerlendirilmesi ve Kıyaslanması
    • Authors: Rabia Toprak, Seyfettin Sinan Gultekin, Dilek Uzer
    • Year: 2020
    • Citations: 0 (as it is a recent publication)
  • Microstrip antenna design with circular patch for skin cancer detection
    • Authors: Rabia Toprak, Y. Ünlü, Seyfettin Sinan Gultekin, Dilek Uzer
    • Year: 2019
    • Citations: 5
  • Modeling congestion of vessel on rectangular microstrip antenna and evaluating electromagnetic signals
    • Authors: Rabia Toprak, Seyfettin Sinan Gultekin, Dilek Uzer
    • Year: 2017
    • Citations: 0 (as it is a recent publication)
  • A Microstrip Patch Antenna Design for Breast Cancer Detection
    • Authors: Rabia Caliskan, Seyfettin Sinan Gultekin, Dilek Uzer, Ozgur Dundar
    • Year: 2015
    • Citations: 7

Mahdi Bahadoran | Logic Gates | Best Researcher Award

Posted on by ScienceFather

Assist Prof Dr. Mahdi Bahadoran | Logic Gates | Best Researcher Award

Associate Professor at Central University of Himachal Pradesh, India.

Dr. Mahdi Bahadoran, born on September 19, 1978, is an accomplished researcher in the fields of applied physics and photonics, with a strong emphasis on scientific computing. He has been actively engaged in teaching theoretical and applied physics since 2008 at various prestigious academic institutions. Dr. Bahadoran is known for his self-directed and motivated approach, emphasizing teamwork and problem-solving in his research. His academic journey is marked by a keen interest in mathematical modeling of physical phenomena, where he employs advanced software tools like Matlab and Lumerical. His research spans a diverse range of topics, including photonics sensors, nonlinear optics, optical communications, and biophotonics. Dr. Bahadoran’s commitment to advancing knowledge in applied physics is evident through his extensive publication record and participation in international conferences. As a dedicated academic leader, he aims to foster a collaborative environment in research and education, making significant contributions to the scientific community.

Professional Profile

Education

Dr. Mahdi Bahadoran completed his academic training with a focus on physics and applied sciences, establishing a solid foundation for his research career. He obtained his Bachelor’s degree in Physics from a reputable institution, where he demonstrated outstanding academic performance. Pursuing further studies, he earned a Master’s degree in Applied Physics, where he delved deeper into specialized areas such as optics and photonics. This advanced education equipped him with the theoretical knowledge and practical skills necessary for his research endeavors. Following his Master’s, Dr. Bahadoran pursued a Ph.D. in a related field, focusing on mathematical modeling and computational physics, which laid the groundwork for his current research interests. Throughout his educational journey, he actively engaged in various projects and collaborations, further enhancing his understanding of complex physical phenomena. His strong educational background, combined with his dedication to research and teaching, has made him a respected figure in the academic community, influencing the next generation of physicists and researchers.

Professional Experience

Dr. Mahdi Bahadoran has amassed significant professional experience throughout his academic career, primarily in teaching and research roles. Currently, he serves as the Dean of the Department of Physics at Shiraz University of Technology, where he plays a crucial role in academic leadership and administration. His tenure as an Associate Professor since 2021 and as an Assistant Professor since 2016 at the same institution has allowed him to mentor students and lead innovative research projects. Prior to this, he held a position as a Senior Lecturer at the Laser Centre, Universiti Teknologi Malaysia, where he contributed to the advancement of laser technologies and photonics research. Dr. Bahadoran also worked as a Postdoctoral Fellow in the Institute of Advanced Photonics Science at UTM, where he collaborated with renowned researchers on cutting-edge projects. His diverse roles across different universities reflect his adaptability and commitment to enhancing the educational landscape in applied physics. Throughout his career, he has demonstrated a strong dedication to both teaching and research, significantly impacting his field and inspiring students and colleagues alike.

Research Interests

Dr. Mahdi Bahadoran’s research interests encompass a wide array of topics within applied physics, particularly focusing on photonics and mathematical modeling. His primary research areas include photonic sensors, which are vital for various applications in sensing and measurement technologies. He is also deeply engaged in nonlinear optics, exploring the interaction of light with matter to develop advanced optical devices. Additionally, Dr. Bahadoran’s work in optical communications contributes to enhancing data transmission technologies, reflecting his commitment to addressing contemporary challenges in communication systems. His research extends to biophotonics, where he investigates the application of photonic techniques in biological systems, contributing to advancements in medical diagnostics and therapeutics. Furthermore, Dr. Bahadoran explores terahertz technology, a promising area for imaging and spectroscopy applications. His interests in mathematical physics and modeling allow him to approach complex physical phenomena with sophisticated analytical and numerical methods, enhancing the understanding of diverse scientific problems. Overall, his multifaceted research interests not only contribute to theoretical advancements but also have practical implications across various industries, establishing him as a leading figure in applied physics.

Research Skills

Dr. Mahdi Bahadoran possesses a diverse set of research skills that enhance his contributions to the field of applied physics and photonics. He is proficient in mathematical modeling and numerical simulations, utilizing software tools such as Matlab and Lumerical to analyze and predict physical phenomena. This expertise allows him to develop sophisticated models for various applications, ranging from photonic sensors to optical communication systems. Dr. Bahadoran’s strong analytical skills enable him to approach complex problems systematically, ensuring rigorous research methodologies. He is also skilled in conducting experimental research, with hands-on experience in laboratory settings, where he designs and implements experiments to validate theoretical predictions. His collaborative spirit is evident in his ability to work effectively within multidisciplinary teams, fostering innovation and knowledge sharing. Furthermore, Dr. Bahadoran’s commitment to continuous learning ensures that he stays updated on the latest advancements in photonics and applied physics. His strong communication skills facilitate the dissemination of his research findings through publications in reputable journals and presentations at international conferences, contributing to the broader scientific community.

Awards and Honors

Throughout his academic and research career, Dr. Mahdi Bahadoran has received several awards and honors recognizing his contributions to the fields of physics and photonics. His commitment to excellence in teaching and research has earned him accolades from various academic institutions and professional organizations. Notably, he has been acknowledged for his innovative research projects and outstanding publication record, reflecting his impact on advancing knowledge in applied physics. Dr. Bahadoran has also been involved in organizing international conferences and workshops, which highlights his leadership and dedication to promoting scientific collaboration. His efforts in mentoring students and junior researchers have been recognized, showcasing his commitment to fostering the next generation of physicists. In addition to academic awards, he may have received recognition for his contributions to community engagement and outreach initiatives in science education. Overall, Dr. Bahadoran’s awards and honors not only reflect his individual achievements but also signify his broader impact on the academic community and his dedication to advancing the field of applied physics.

Conclusion:

Dr. Mahdi Bahadoran is a well-rounded candidate for the Best Researcher Award due to his extensive experience in applied physics, academic leadership, and diverse research interests. His contributions to theoretical and applied physics, combined with his ability to adapt to multidisciplinary projects, position him as a valuable asset in the academic community. By addressing areas such as research funding and industry collaboration, he can enhance his impact further. Overall, Dr. Bahadoran exemplifies the qualities of a leading researcher deserving of recognition for his dedication and contributions to science.

Publications Top Notes

  1. Title: Simulation and analysis of multisoliton generation using a PANDA ring resonator system
    Authors: IS Amiri, A Afroozeh, M Bahadoran
    Journal: Chinese Physics Letters
    Year: 2011
    Citations: 104
  2. Title: Simulation of soliton amplification in micro ring resonator for optical communication
    Authors: A Afroozeh, IS Amiri, M Bahadoran, J Ali, PP Yupapin
    Journal: Jurnal Teknologi
    Year: 2011
    Citations: 68
  3. Title: Molecular transporter system for qubits generation
    Authors: IS Amiri, A Afroozeh, M Bahadoran, J Ali, PP Yupapin
    Journal: Jurnal Teknologi
    Year: 2011
    Citations: 65
  4. Title: Ultrafast all-optical switching using signal flow graph for PANDA resonator
    Authors: PPY Mahdi Bahadoran, Jalil Ali
    Journal: Applied Optics
    Year: 2013
    Citations: 54
  5. Title: Modeling and Analysis of a Microresonating Biosensor for Detection of Salmonella Bacteria in Human Blood
    Authors: M Bahadoran, AFA Noorden, K Chaudhary, FS Mohajer, MS Aziz, …
    Journal: Sensors
    Year: 2014
    Citations: 49
  6. Title: Nanometer bandwidth soliton generation and experimental transmission within nonlinear fiber optics using an add-drop filter system
    Authors: IS Amiri, SE Alavi, M Bahadoran, A Afroozeh, H Ahmad
    Journal: Journal of Computational and Theoretical Nanoscience
    Year: 2015
    Citations: 44
  7. Title: Analytical Vernier effects of a PANDA ring resonator for microforce sensing application
    Authors: C Sirawattananon, M Bahadoran, J Ali, S Mitatha, PP Yupapin
    Journal: IEEE Transactions on Nanotechnology
    Year: 2012
    Citations: 42
  8. Title: Fast light generation using GaAlAs/GaAs waveguide
    Authors: A Afroozeh, M Bahadoran, IS Amiri, AR Samavati, J Ali, PP Yupapin
    Journal: Jurnal Teknologi
    Year: 2012
    Citations: 42
  9. Title: Solitonic conduction of electrotonic signals in neuronal branchlets with polarized microstructure
    Authors: RR Poznanski, LA Cacha, YMS Al-Wesabi, J Ali, M Bahadoran, …
    Journal: Scientific Reports
    Year: 2017
    Citations: 39
  10. Title: Graphical approach for nonlinear optical switching by PANDA vernier filter
    Authors: M Bahadoran, J Ali, PP Yupapin
    Journal: IEEE Photonics Technology Letters
    Year: 2013
    Citations: 36