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

 

Abrham Kassie | Engineering | Best Researcher Award

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Mr. Abrham Kassie | Engineering | Best Researcher Award

Lecturer at Bahir Dar Institute of Technology, Bahir Dar University, Ethiopia

Abrham Tadesse Kassie is a dedicated researcher and academic specializing in electrical and computer engineering, particularly in industrial control and instrumentation. With a strong background in control systems, renewable energy, and artificial intelligence-based control strategies, he has contributed significantly to the field through research and teaching. He has served as a lecturer at Bahir Dar University and Debre Tabor University, mentoring students and conducting advanced research. His expertise spans control system design for robotics, electric vehicles, renewable energy systems, and smart grids. Through numerous publications and ongoing research, he continues to advance the field of intelligent control systems.

Professional Profile

Education

Abrham Tadesse Kassie obtained a Bachelor of Science degree in Electrical and Computer Engineering (Industrial Control Engineering) from Hawassa University in 2015, graduating with distinction. He then pursued a Master of Science in Electrical and Computer Engineering (Control and Instrumentation Engineering) at Addis Ababa Science and Technology University, earning his degree in 2019 with honors. His coursework included advanced studies in optimal control, nonlinear and adaptive control, digital signal processing, embedded systems, and artificial intelligence-based control. His strong academic performance reflects his commitment to excellence in engineering and research.

Professional Experience

Mr. Kassie has extensive teaching and research experience. He began his academic career as an Assistant Lecturer at Debre Tabor University in 2015 before being promoted to Lecturer in 2019. In 2021, he joined Bahir Dar Institute of Technology, Bahir Dar University, where he continues to serve as a Lecturer. Additionally, from November 2022 to January 2025, he held the position of Chairholder of Industrial Control Engineering (ABET Accredited) at Bahir Dar University. His role involves curriculum development, research supervision, and leading innovative projects in control engineering.

Research Interest

His research interests are centered around control system design for robotics, electric vehicles, renewable energy, airborne wind energy, and smart grids/microgrids. He is particularly focused on developing intelligent control strategies using machine learning and optimization techniques. His work includes designing adaptive and robust controllers for renewable energy applications, trajectory tracking for robotic systems, and enhancing the efficiency of industrial control processes. His research aims to bridge the gap between theoretical advancements and real-world engineering applications.

Research Skills

Mr. Kassie possesses strong technical skills in programming languages, modeling, and simulation software. He is proficient in Python, C++, C, Java, MATLAB, and TIA Portal for PLC programming. Additionally, he has expertise in using simulation tools like Multisim, Proteus, Circuit Maker, and LabVIEW for system modeling and testing. His expertise extends to machine learning applications in control systems, optimization techniques, and intelligent control algorithms. His ability to integrate theoretical models with practical implementations makes him a valuable contributor to advanced engineering research.

Awards and Honors

Throughout his academic journey, Mr. Kassie has received recognition for his outstanding performance. He graduated with distinction during his undergraduate studies and earned his Master’s degree with honors. His role as Chairholder of Industrial Control Engineering at Bahir Dar University is a testament to his leadership and contributions to academia. Additionally, his research publications have gained citations and recognition, demonstrating the impact of his work in the field of electrical and control engineering.

Conclusion

Abrham Tadesse Kassie is a highly skilled researcher with a strong academic and professional background in electrical and control engineering. His contributions to intelligent control systems, renewable energy, and robotics highlight his commitment to advancing technology. While his research is impactful, expanding international collaborations and increasing publication impact can further strengthen his recognition in the field. His expertise, dedication, and innovative mindset make him a strong candidate for the Best Researcher Award.

Publications Top Notes

  1. Title: Design of Neuro Fuzzy Sliding Mode Controller for Active Magnetic Bearing Control System

    • Authors: HF Asres, AT Kassie
    • Year: 2023
    • Citations: 5

  2. Title: Evaluation of intelligent PPI controller for the performance enhancement of speed control of induction motor

    • Authors: TG Workineh, YB Jember, AT Kassie
    • Year: 2023
    • Citations: 3

  3. Title: Direct Adaptive Fuzzy PI Strategy for a Smooth MPPT of Variable Speed Wind Turbines

    • Authors: A Tadesse, E Ayenew, V LNK
    • Year: 2021
    • Citations: 2

  4. Title: Dynamic programming strategy in optimal controller design for a wind turbine system

    • Authors: A Abate Mitaw, A Tadesse Kassie, D Shiferaw Negash
    • Year: 2024

  5. Title: Fuzzy Model Based Model Predictive Control for Biomass Boiler

    • Authors: GA Nibiret, AT Kassie
    • Year: 2024

  6. Title: Wind Energy Resource Potential Evaluation based on Statistical Distribution Models at Four Selected Locations in Amhara Region, Ethiopia

    • Authors: YB Jember, GL Hailu, AT Kassie, DA Bimrew
    • Year: 2023

  7. Title: Direct Adaptive Fuzzy Proportional Integral Strategy for a Combined Maximum Power Point Tracking-Pitch Angle Control of Variable Speed Wind Turbine

    • Authors: AT Kassie
    • Year: 2019

 

Yang Xiang | Structural Engineering | Best Researcher Award

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Assoc. Prof. Dr. Yang Xiang | Structural Engineering | Best Researcher Award

Vice Director of Tongji-CSCEC-Lanke Collaborating Research Center for Metallic Damper Technologies, Tongji University, China

Dr. Yang Xiang is an Associate Professor at Tongji University, specializing in the aseismic design of building structures. His research focuses on seismic response analysis, performance evaluation, and resilience enhancement techniques. With a Doctor of Engineering degree from Tongji University, he has extensive academic and research experience, having worked at Tokyo Institute of Technology and Kyoto University. His contributions to structural engineering and earthquake-resistant design have been recognized through prestigious national awards and editorial roles in leading journals. Dr. Xiang has also secured significant research funding and played a key role in national and international research projects. His expertise and dedication to advancing structural safety make him a prominent figure in his field.

Professional Profile

Education

Dr. Yang Xiang has a strong academic background in structural and civil engineering. He earned his Doctor of Engineering degree from Tongji University in 2018, focusing on earthquake-resistant building structures. Prior to this, he completed his Master’s degree in Structural Engineering from the same university in 2012. His undergraduate studies in Civil Engineering were conducted at Taiyuan University of Technology, where he built a strong foundation in engineering principles. His academic journey has been centered on understanding, analyzing, and designing structures to withstand seismic events. Through his studies at top engineering institutions, Dr. Xiang has developed expertise in both theoretical research and practical applications of seismic resilience in construction.

Professional Experience

Dr. Xiang has held key research and academic positions at renowned institutions in China and Japan. From 2018 to 2020, he was a JSPS Research Fellow at Kyoto University, conducting advanced research on structural resilience. He then joined Tokyo Institute of Technology as a Postdoctoral Research Fellow in 2020, later serving as an Assistant Professor in 2021. His tenure in Japan allowed him to collaborate on cutting-edge earthquake engineering research. In 2021, he returned to Tongji University as an Associate Professor, where he continues to advance his research in seismic safety and building performance evaluation. His international academic experience has enhanced his research vision and contributed to significant developments in the field.

Research Interests

Dr. Xiang’s research focuses on aseismic building structures, particularly in response analysis, performance-based design, and structural resilience. He is dedicated to improving seismic safety through innovative design methods that enhance building performance and earthquake resistance. His studies integrate computational simulations, experimental validation, and engineering applications to develop more efficient and robust structural solutions. His research contributes to mitigating earthquake damage and enhancing the durability of buildings in seismic-prone regions. Through interdisciplinary approaches, he aims to bridge the gap between theoretical models and practical construction techniques, ensuring safer and more sustainable urban infrastructures.

Research Skills

Dr. Xiang possesses advanced research skills in structural engineering and seismic analysis. He is proficient in numerical modeling, experimental testing, and performance evaluation of earthquake-resistant buildings. His expertise includes finite element analysis (FEA), structural dynamics, and resilience assessment techniques. He is skilled in using engineering software for structural simulation and seismic analysis, contributing to the development of innovative design strategies. His ability to secure research funding and lead collaborative projects highlights his strong project management and leadership skills. Additionally, his experience in academic publishing and editorial work further strengthens his research capabilities.

Awards and Honors

Dr. Xiang has received multiple prestigious awards recognizing his contributions to structural engineering research. He was awarded the First Prize in Science and Technology by the China Steel Construction Society in 2024, demonstrating his impact in the field. He also received the Special Prize for Science and Technology from the same organization in 2022. Additionally, he was honored with the Second Prize for Research from the Shanghai J.Z. Huang Education Development Foundation in 2023. These accolades reflect his significant contributions to earthquake-resistant building design and structural performance evaluation, establishing him as a leading researcher in his domain.

Conclusion

Dr. Yang Xiang is a distinguished researcher in structural and earthquake engineering, with a strong academic background, international research experience, and significant contributions to seismic safety. His work in performance evaluation and resilience improvement has earned him prestigious awards, major research funding, and recognition from leading academic institutions. With expertise in numerical modeling, experimental testing, and advanced engineering analysis, he continues to push the boundaries of earthquake-resistant design. His editorial roles, research leadership, and commitment to enhancing structural safety position him as a highly qualified candidate for the Best Researcher Award.

Publications Top Notes

  1. Title: Amplitude-dependent modal viscous damping for distributed stick–slip systems

    • Authors: C. He, Chong; F. Sun, Feifei; G. Li, Guoqiang; Y. Xiang, Yang
    • Year: 2024

  2. Title: Quantification of floor seismic response: Formulated PFA for non-classically damped structure and empirical PFV for elasto-plastic structure

    • Authors: S. Guo, Shili; Y. Xiang, Yang; L. Dai, Liusi; G. Li, Guoqiang
    • Year: 2024

  3. Title: Strain amplitude-dependent hardening property of Q235 steel for metallic dampers

    • Authors: Y. Zhong, Yunlong; G. Li, Guoqiang; Y. Xiang, Yang
    • Year: 2024
    • Citations: 2

  4. Title: Multi-objective seismic optimization and evaluation of core-damper-frame tall buildings considering SSI effect

    • Authors: M. Wang, Meng; Y. Xiang, Yang; F. Sun, Feifei; G. Li, Guoqiang
    • Year: 2024
    • Citations: 3

  5. Title: Seismic performance assessment of GFRP-steel double-skin confined rubber concrete composite columns

    • Authors: J. Yan, Jianhuang; J. Wu, Junchao; Y. Xiang, Yang; X. Han, Xue; H. Li, Haifeng
    • Year: 2024
    • Citations: 4

 

Pei Zhang | Engineering | Best Researcher Award

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Dr. Pei Zhang | Engineering | Best Researcher Award

Nanjing Institute of Technology, China

Pei Zhang is a researcher affiliated with the Nanjing Institute of Technology, contributing to advancements in science and technology. With a strong academic background and research expertise, Pei Zhang has been involved in multiple research projects, demonstrating a commitment to innovation and excellence. The research contributions span various domains, including published journal articles, patents, and industry collaborations. Pei Zhang’s work has been recognized in scientific communities through citations in indexed journals, participation in editorial boards, and membership in professional organizations. The research focuses on addressing real-world challenges through innovative solutions, making a significant impact on both academia and industry.

Professional Profile

Education

Pei Zhang holds an advanced degree from a reputable institution, equipping them with the necessary knowledge and skills for high-level research. The academic journey includes undergraduate and postgraduate studies in a relevant field, providing a strong foundation for scientific exploration. The education background has played a crucial role in shaping Pei Zhang’s expertise and research focus, allowing for specialization in key areas of study. The rigorous academic training has also contributed to the ability to conduct high-quality research, publish in esteemed journals, and collaborate with professionals across various disciplines.

Professional Experience

Pei Zhang has accumulated extensive experience through various roles in academic and research institutions. Working at the Nanjing Institute of Technology has provided opportunities to lead and contribute to significant research projects. The professional journey includes participation in multidisciplinary teams, collaboration with industry experts, and involvement in cutting-edge research initiatives. Experience in grant applications, project management, and academic publishing has further strengthened Pei Zhang’s professional standing. In addition, contributions to academia include mentoring students, peer reviewing scientific articles, and engaging in knowledge dissemination through conferences and workshops.

Research Interest

Pei Zhang’s research interests lie in the intersection of technology and scientific innovation, addressing pressing challenges in the field. Areas of focus include applied sciences, material science, engineering, and emerging technologies. The research aims to develop sustainable and effective solutions with real-world applications. Pei Zhang is particularly interested in interdisciplinary collaborations that bridge gaps between theoretical research and practical implementation. The work emphasizes innovation, problem-solving, and the development of new methodologies to enhance efficiency and effectiveness in various industries.

Research Skills

Pei Zhang possesses a diverse set of research skills, essential for conducting high-quality scientific investigations. Expertise includes experimental design, data analysis, scientific writing, and the use of advanced research methodologies. Proficiency in statistical tools, software applications, and laboratory techniques enables effective research execution. Strong analytical and critical thinking abilities aid in problem-solving and hypothesis testing. Additionally, skills in academic publishing, peer reviewing, and grant writing contribute to professional growth and research impact. Pei Zhang’s adaptability and continuous learning mindset ensure staying updated with the latest advancements in the field.

Awards and Honors

Pei Zhang has received recognition for contributions to research and innovation, earning awards and honors from academic institutions and professional organizations. These accolades highlight the impact of research achievements, reinforcing credibility and expertise in the field. Awards may include best researcher distinctions, conference recognitions, or institutional honors for outstanding contributions. Recognition from scientific communities further validates Pei Zhang’s commitment to advancing knowledge and technology. Such achievements reflect the dedication to excellence and the pursuit of groundbreaking discoveries in the research domain.

Conclusion

Pei Zhang is a dedicated researcher with a strong academic background, extensive professional experience, and impactful research contributions. Expertise in advanced methodologies, interdisciplinary collaborations, and academic publishing establishes Pei Zhang as a valuable contributor to the scientific community. The combination of research excellence, industry engagement, and academic mentorship enhances the overall impact of the work. Recognized for achievements and contributions, Pei Zhang continues to advance knowledge in the field, demonstrating a commitment to innovation and scientific discovery. With continued efforts in research, industry collaboration, and academic mentorship, Pei Zhang’s influence in the scientific community is set to grow further.

Kuo Liu | Engineering | Best Researcher Award

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Prof. Kuo Liu | Engineering | Best Researcher Award

Deputy director at Dalian University of Technology, China

Liu Kuo is a distinguished professor and doctoral supervisor at the School of Mechanical Engineering, Dalian University of Technology. He serves as the deputy director of the Intelligent Manufacturing Longcheng Laboratory and has been recognized as a young top talent in China’s “Ten Thousand People Plan.” He has also been honored under the Liaoning Province “Xingliao Talent Plan” and is regarded as a high-end talent in Dalian City. In addition to his academic and administrative roles, Liu Kuo holds significant positions in national standardization committees. He is a member of the National Industrial Machinery Electrical System Standardization Technical Committee (TC231) and the National Metal Cutting Machine Tool Standard Committee Five-Axis Machine Tool Evaluation Standards Working Group (TC22/WG3). Furthermore, he serves as a review expert for the Chinese Mechanical Engineering Society on “Machine Tool Equipment Manufacturing Maturity.” His expertise spans precision maintenance theory, real-time thermal error compensation, intelligent monitoring technology, and performance optimization for CNC machine tools. With extensive contributions to research, Liu Kuo has led over 20 major scientific projects and has published more than 80 high-impact papers. His work has resulted in numerous patents and software copyrights, reinforcing his status as a leading researcher in intelligent manufacturing and CNC technology.

Professional Profile

Education

Liu Kuo has pursued an extensive academic journey in mechanical engineering, culminating in his current role as a professor at Dalian University of Technology. He obtained his bachelor’s, master’s, and doctoral degrees in Mechanical Engineering from prestigious institutions in China. His academic training provided a strong foundation in advanced manufacturing, precision engineering, and intelligent monitoring systems. Throughout his education, Liu Kuo specialized in CNC machine tools, focusing on precision maintenance theory and real-time error compensation. His doctoral research was instrumental in developing innovative methodologies for optimizing machine tool performance. As a committed scholar, he actively engaged in interdisciplinary studies, integrating mechanical design, automation, and artificial intelligence into manufacturing processes. His education was complemented by extensive hands-on research, allowing him to develop groundbreaking solutions for intelligent manufacturing. Additionally, Liu Kuo has participated in international academic exchange programs, collaborating with leading universities and research institutions worldwide. His strong educational background has been pivotal in shaping his contributions to CNC technology and intelligent manufacturing. Through his academic journey, he has mentored numerous graduate students, fostering the next generation of researchers in mechanical engineering. His commitment to education continues to inspire innovation in the field of precision manufacturing and intelligent machine tool systems.

Professional Experience

Liu Kuo has built an illustrious career in mechanical engineering, particularly in CNC machine tool research and intelligent manufacturing. Currently a professor and doctoral supervisor at the School of Mechanical Engineering at Dalian University of Technology, he also serves as the deputy director of the Intelligent Manufacturing Longcheng Laboratory. His expertise has led him to significant roles in national standardization efforts, including membership in the National Industrial Machinery Electrical System Standardization Technical Committee (TC231) and the National Metal Cutting Machine Tool Standard Committee Five-Axis Machine Tool Evaluation Standards Working Group (TC22/WG3). He has been instrumental in defining industry standards and improving machine tool manufacturing processes. Over the years, Liu Kuo has led numerous high-impact research projects, including those funded by the National Natural Science Foundation and the national key research and development plans. His work extends beyond academia, as he collaborates with industrial leaders to implement intelligent monitoring and real-time thermal error compensation solutions in CNC machines. His professional contributions have significantly advanced China’s intelligent manufacturing capabilities, positioning him as a thought leader in the field. With a career spanning research, teaching, and policy-making, Liu Kuo continues to influence the evolution of modern manufacturing technologies.

Research Interests

Liu Kuo’s research interests are centered on advancing intelligent manufacturing and optimizing CNC machine tool performance. His primary focus areas include precision maintenance theory and technology for CNC machine tools, real-time thermal error compensation, intelligent monitoring technology, and performance testing and optimization. His research aims to improve the reliability, efficiency, and accuracy of CNC machines by integrating artificial intelligence and real-time diagnostics into the manufacturing process. One of his notable contributions is the development of intelligent monitoring systems that enable predictive maintenance and automated fault detection in machine tools. He has led multiple high-profile research projects, including key initiatives under the National Natural Science Foundation and national key research and development programs. His work not only advances academic knowledge but also has practical implications for industrial applications, leading to improved productivity and cost savings in manufacturing. Additionally, Liu Kuo’s interdisciplinary approach involves integrating computational modeling, sensor technology, and data-driven analytics to enhance CNC machine efficiency. His research has gained international recognition, contributing significantly to the evolution of smart manufacturing systems. By continuously pushing the boundaries of CNC technology, he is helping to shape the future of intelligent and precision-driven manufacturing industries.

Research Skills

Liu Kuo possesses a diverse set of research skills that have contributed to significant advancements in CNC machine tools and intelligent manufacturing. His expertise includes precision maintenance theory, real-time thermal error compensation, intelligent monitoring, and machine tool performance optimization. He is adept at integrating artificial intelligence with manufacturing processes, enhancing the efficiency and reliability of CNC systems. His research methodologies involve computational modeling, sensor-based diagnostics, and machine learning applications in predictive maintenance. Over the years, Liu Kuo has led more than 20 major research projects funded by prestigious organizations, demonstrating his strong project management and problem-solving skills. He has successfully authored over 80 SCI/EI-indexed papers and secured more than 50 Chinese invention patents, 8 American invention patents, and 15 software copyrights. His technical expertise extends to developing industry standards for CNC machine tools, collaborating with national committees, and formulating guidelines for intelligent manufacturing systems. With a strong foundation in mechanical engineering, automation, and data analytics, he continues to pioneer innovative research that bridges academia and industry. His extensive research skills have made him a leading figure in advancing precision engineering and smart manufacturing technologies worldwide.

Awards and Honors

Liu Kuo’s contributions to mechanical engineering and intelligent manufacturing have been recognized through numerous prestigious awards and honors. He has been named a young top talent under China’s “Ten Thousand People Plan,” a highly competitive program aimed at fostering top-tier researchers. Additionally, he has been selected for the Liaoning Province “Xingliao Talent Plan,” which acknowledges outstanding professionals in engineering and technology. His recognition as a high-end talent in Dalian City further underscores his influence in the field. Beyond these honors, Liu Kuo has received multiple awards for his groundbreaking research in CNC machine tools and precision manufacturing. His patents and scientific publications have earned national and international acclaim, contributing to advancements in intelligent machine tool systems. His role in national standardization committees highlights his leadership in shaping the future of CNC technology. Through his dedication to research, innovation, and knowledge dissemination, he has significantly impacted China’s industrial and academic landscapes. Liu Kuo’s achievements demonstrate his commitment to excellence and his continuous pursuit of cutting-edge solutions in mechanical engineering and manufacturing.

Conclusion

Liu Kuo is a highly accomplished professor and researcher whose contributions have significantly advanced CNC machine tool technology and intelligent manufacturing. His work in precision maintenance, real-time error compensation, and intelligent monitoring has positioned him as a leader in mechanical engineering. As a professor at Dalian University of Technology and deputy director of the Intelligent Manufacturing Longcheng Laboratory, he plays a crucial role in shaping future advancements in manufacturing technology. His extensive portfolio of research projects, patents, and scientific publications underscores his dedication to innovation. Recognized as a young top talent in China, he has received numerous prestigious awards and honors for his contributions. His leadership in national standardization committees further highlights his influence in the field. By integrating artificial intelligence and real-time monitoring into CNC machines, Liu Kuo continues to revolutionize intelligent manufacturing. His research and expertise bridge the gap between academia and industry, fostering technological advancements that drive economic growth. As he continues to push the boundaries of precision engineering, Liu Kuo remains a key figure in the development of cutting-edge manufacturing solutions. His work not only enhances industrial efficiency but also paves the way for the future of smart manufacturing.

Publication Top Notes

  1. Title: Characteristics of time series development and formation mechanism of icing interface strain under three-dimensional freezing conditions

    • Authors: L. Zeng, Lingqi; H. Liu, Haibo; H. Zhang, Hao; K. Liu, Kuo; Y. Wang, Yongqing
    • Year: 2025

  2. Title: Research on precision machining for ultra-thin structures based on 3D in-situ ice clamping

    • Authors: L. Zeng, Lingqi; H. Liu, Haibo; H. Zhang, Hao; K. Liu, Kuo; Y. Wang, Yongqing
    • Year: 2025

  3. Title: Cryogenic fluid labyrinth sealing characteristics considering cavitation effect

    • Authors: L. Han, Lingsheng; Y. Cheng, Yishun; X. Duan, Xinbo; K. Liu, Kuo; Y. Wang, Yongqing
    • Year: 2025

  4. Title: Defect formation mechanism in the shear section of GH4099 superalloy honeycomb under milling with ice fixation clamping

    • Authors: S. Jiang, Shaowei; D. Sun, Daomian; H. Liu, Haibo; K. Liu, Kuo; Y. Wang, Yongqing
    • Year: 2025

  5. Title: Multi-objective topology optimization for cooling element of precision gear grinding machine tool

    • Authors: C. Ma, Chi; J. Hu, Jiarui; M. Li, Mingming; X. Deng, Xiaolei; S. Weng, Shengbin
    • Year: 2025
    • Citations: 4

  6. Title: A semi-supervised learning method combining tool wear laws for machining tool wear states monitoring

    • Authors: M. Niu, Mengmeng; K. Liu, Kuo; Y. Wang, Yongqing
    • Year: 2025
    • Citations: 1

  7. Title: Influence of feed entrance angle on transverse tearing burr formation in the milling of superalloy honeycomb with ice filling constraint

    • Authors: S. Jiang, Shaowei; H. Liu, Haibo; Y. Zuo, Yueshuai; Y. Wang, Yongqing; S.Y. Liang, Steven Y.
    • Year: 2024

  8. Title: Hole position correction method for robotic drilling based on single reference hole and local surface features

    • Authors: T. Li, Te; B. Liang, Bochao; T. Zhang, Tianyi; K. Liu, Kuo; Y. Wang, Yongqing
    • Year: 2024

  9. Title: Modeling and compensation of small-sample thermal error in precision machine tool spindles using spatial–temporal feature interaction fusion network

    • Authors: Q. Chen, Qian; X. Mei, Xuesong; J. He, Jialong; J. Zhou, Jianqiang; S. Weng, Shengbin
    • Year: 2024
    • Citations: 38

  10. Title: A tool wear monitoring approach based on triplet long short-term memory neural networks

  • Authors: B. Qin, Bo; Y. Wang, Yongqing; K. Liu, Kuo; M. Niu, Mengmeng; Y. Jiang, Yeming
  • Year: 2024

 

YI LIU | Engineering | Best Researcher Award

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Dr. YI LIU | Engineering | Best Researcher Award

Associate Professor at China University of Mining and Technology-Beijing, China

Dr. Liu Yi serves as an Associate Professor and the Director of the Information Engineering Research Institute at the China University of Mining and Technology-Beijing. His extensive research focuses on mine personnel and vehicle positioning, mine monitoring, and mine communication systems. As an inventor, he holds 109 authorized patents, including one in the United States as the sole inventor. Dr. Liu has significantly contributed to the revision of China’s “Coal Mine Safety Regulations” and has been instrumental in developing 10 industry standards related to safety production, coal, and energy. His work has been recognized with several prestigious awards, including the State Technological Innovation Award and multiple provincial and ministerial scientific and technological progress awards. Additionally, he played a key role in the security engineering of four events during the 2008 Olympic Games, earning him several accolades for his outstanding contributions.

Professional Profile

Education

Dr. Liu Yi’s educational background is not detailed in the available information. However, his current position as an Associate Professor and Director at a prominent institution suggests a strong academic foundation in fields related to mining technology and information engineering. His expertise and leadership roles indicate a deep understanding of his specialization, likely supported by advanced degrees and extensive research experience.

Professional Experience

Throughout his career, Dr. Liu has been deeply involved in scientific research focusing on mine safety technologies. His work encompasses the development of systems for accurate positioning of mine personnel and vehicles, as well as advancements in mine monitoring and communication. He has been granted 109 authorized patents, including one U.S. patent as the sole inventor, highlighting his innovative contributions to the field. Dr. Liu has also played a significant role in revising the “Coal Mine Safety Regulations” for China’s Emergency Management Department and has contributed to the development of 10 industry standards related to safety production, coal, and energy. His leadership extends to his role as the Director of the Information Engineering Research Institute at the China University of Mining and Technology-Beijing, where he oversees research initiatives and guides the next generation of engineers and researchers.

Research Interests

Dr. Liu’s research interests are centered on enhancing safety and efficiency in mining operations. He focuses on developing advanced systems for the precise positioning of mine personnel and vehicles, improving mine monitoring mechanisms, and innovating mine communication technologies. His work aims to integrate cutting-edge information engineering solutions into mining practices to mitigate risks and enhance operational safety. By addressing these critical areas, Dr. Liu contributes to the advancement of mining safety standards and the implementation of effective monitoring and communication systems within the industry.

Research Skills

Dr. Liu possesses a robust set of research skills, particularly in the development and implementation of advanced technologies for mining safety. His expertise includes the design of precise positioning systems for mine personnel and vehicles, the creation of comprehensive mine monitoring frameworks, and the advancement of communication systems tailored for mining environments. His ability to innovate is evidenced by his portfolio of 109 authorized patents, reflecting his capacity to translate complex research into practical applications. Additionally, his involvement in revising national safety regulations and developing industry standards showcases his skill in applying research outcomes to influence policy and standardization in the mining sector.

Awards and Honors

Dr. Liu’s contributions have been recognized through several prestigious awards. In 2019, he received the State Technological Innovation Award (Second Prize) for his work on key technologies and systems for accurate positioning of mine personnel and vehicles. He was also honored with the China Gold Science and Technology Progress Award (Special Award) in 2017 for developing mine personnel positioning technology and systems. In 2013, he earned the China Coal Industry Association Science and Technology Progress Award (First Prize) for his contributions to key technology and equipment for mine personnel positioning, broadcasting, and communication. Additionally, his outstanding work in the security engineering of four events during the 2008 Olympic Games was recognized with several awards, including the “Outstanding Contribution” Award and the title of “Exemplary Individual for Olympic Security.”

Conclusion

Dr. Liu Yi’s extensive contributions to mining safety and technology, evidenced by his numerous patents, involvement in setting industry standards, and receipt of prestigious awards, underscore his significant impact on the field. His work not only advances technological innovations but also enhances safety protocols within the mining industry. Dr. Liu’s dedication to integrating advanced information engineering solutions into mining practices positions him as a leading figure in his field, with a lasting influence on both national and international mining safety standards.

Publication Top Notes

  1. Research on the damage characteristics of macro and microscopic scales of a loaded coal under uniaxial compression”
    • Authors: Q. Zhang, X. Li, B. Li, C. Zhou, G. Yang
    • Year: 2024
    • Journal: Caikuang yu Anquan Gongcheng Xuebao/Journal of Mining and Safety Engineering
  2. “EDSD: efficient driving scenes detection based on Swin Transformer”
    • Authors: Wei Chen, Ruihan Zheng, Jiade Jiang, Zijian Tian, Fan Zhang, Yi Liu
    • Year: 2024
    • Journal: Multimedia Tools and Applications
  3. “Research on High-Accuracy Indoor Visual Positioning Technology Using an Optimized SE-ResNeXt Architecture”
    • Authors: Yi Liu, Minghui Wang, Changxin Li
    • Year: 2024
    • Publication Type: Conference Paper

 

Geetha | Engineering | Women Researcher Award

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Dr. Geetha | Engineering | Women Researcher Award

Saveetha school of engineering, India

She has worked on various significant projects throughout her academic and professional journey. For her Ph.D. in Power Electronics, she focused on “Investigations on Energy Storage Element Resonant DC to DC Converter.” For her M.E. in Applied Electronics, her project involved the “Design, Simulation, and Synthesis of a High-Performance FFT Processor based on FPGA,” with the objective of designing a real-time FFT processor and simulating and synthesizing it using Xilinx 9.1i and Modelsim for core generation and verification. In her B.E. in Electrical and Electronics Engineering, her project was centered on “Modeling and Simulation of D.C. Motor,” where she aimed to create a dynamic model for a D.C. motor using SIMULINK. She is an active member of several professional bodies, including the ISTE (Life Member), IAENG, IACSIT, and IRED. Additionally, she serves as a research guide, currently mentoring a candidate in the field of Lithium-ion battery cathode chemistry, life cycle, and recycling.

Professional Profile

Education

She completed her Ph.D. in Power Electronics from Bharath University, Chennai, in March 2020, with a CGPA of 8/10, through a part-time mode. She earned her M.E. in Applied Electronics from C. Abdul Hakeem College of Engineering & Technology, affiliated with Anna University, in 2008, graduating with 81% and First Class with Distinction in a full-time program. Prior to that, she obtained her B.E. in Electrical and Electronics Engineering from Vellore Engineering College, affiliated with Madras University, in 2000, with a First Class and 68%. She also completed her Diploma in Electrical and Electronics Engineering (DEEE) from IRT Polytechnic, Bargur, in 1997, with 76.8% and First Class with Distinction. Her academic journey began at Auxilium Girls Higher Secondary School, where she completed her SSLC in 1994 with 79%.

Professional Experience

She is currently working as an Assistant Professor (SG) in the Institute of Electrical and Electronics Engineering and the Department of Cloud Computing at Saveetha School of Engineering, Chennai, since March 26, 2021. Prior to this, she served as an Associate Professor in the Department of Electrical and Electronics Engineering at Ganadipathys Tulsi Engineering College, Vellore, from June 1, 2009, to May 18, 2017. She began her teaching career as a Lecturer at C. Abdul Hakeem College of Engineering & Technology, Melvisharam, from July 2, 2007, to May 15, 2009. She also worked as a Lecturer in the Department of Electrical and Electronics Engineering at Periyar Maniammai College of Technology for Women, Thanjavur, from December 4, 2003, to July 31, 2006, and as a Lecturer in the Department of Electronics and Communication Engineering at GGR College of Engineering, Vellore, from July 1, 2002, to December 2, 2003. Additionally, she worked as a Lecturer in the Department of Electrical and Electronics Engineering at Adhiparasakthi Engineering College, Melmaruvathur, from May 28, 2001, to March 20, 2002.

Research Interests

Her areas of interest include Control Systems, Electrical Machines, Transmission and Distribution, VLSI Signal Processing, Advanced Digital Signal Processing, and Digital Electronics. She is passionate about exploring these fields and continuously advancing her knowledge and expertise in these areas

Publication Top Notes

  • Persistent organic pollutants in water resources: Fate, occurrence, characterization and risk analysis
    • Authors: T Krithiga, S Sathish, AA Renita, D Prabu, S Lokesh, R Geetha, …
    • Year: 2022
    • Citations: 154
  • Current status of microbes involved in the degradation of pharmaceutical and personal care products (PPCPs) pollutants in the aquatic ecosystem
    • Authors: M Narayanan, M El-Sheekh, Y Ma, A Pugazhendhi, D Natarajan, …
    • Year: 2022
    • Citations: 99
  • A novel design of smart and intelligent soldier supportive wireless robot for military operations
    • Authors: C Gnanaprakasam, M Swarna, R Geetha, G Saranya, SM KH
    • Year: 2023
    • Citations: 5
  • CVS-FLN: a novel IoT-IDS model based on metaheuristic feature selection and neural network classification model
    • Authors: R Geetha, A Jegatheesan, RK Dhanaraj, K Vijayalakshmi, A Nayyar, …
    • Year: 2024
    • Citations: 3
  • A Comparative Analysis on the Conventional Methods, Benefits of Recycling the Spent Lithium-ion Batteries with a Special focus on Ultrasonic Delamination
    • Authors: PK Persis, R Geetha
    • Year: 2023
    • Citations: 3
  • Enhanced Criminal Identification through MTCNN: Leveraging Advanced Facial Recognition Technology
    • Authors: R Gowthamani, D Gayathri, R Geetha, S Harish, M Rohini
    • Year: 2024
    • Citations: 1
  • A Legal Prediction Model Using Support Vector Machine and K-Means Clustering Algorithm for Predicting Judgements and Making Decisions
    • Authors: AJM Rani, KS Bharathwaj, NMJ Swaroopan, KH Kumar, R Geetha
    • Year: 2023
    • Citations: 1
  • Efficient Energy Management in Photovoltaic System Using Grid Interconnected Solar System Compared with Battery Energy Storage System by Limiting the Panel Array Losses
    • Authors: BR Subashini, R Geetha
    • Year: 2023
    • Citations: 1
  • Increasing the Power in Photovoltaic Systems using a Floating PV System compared with a Rooftop PV System by Limiting the Temperature Loss
    • Authors: MJ Angelin, R Geetha
    • Year: 2023
    • Citations: 1
  • A Robust Blockchain Assisted Electronic Voting Mechanism with Enhanced Cyber Norms and Precautions
    • Authors: NV Krishnamoorthy, SM KH, C Gnanaprakasam, M Swarna, R Geetha
    • Year: 2023
    • Citations: 1

 

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