Saif Ur Rehman | Mathematics | Best Researcher Award

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Dr. Saif Ur Rehman | Mathematics | Best Researcher Award

Assistant Professor from Gomal University, Pakistan

Dr. Saif Ur Rehman is a highly accomplished academic and researcher specializing in electrical engineering, energy systems, and sustainable technologies. With a solid academic background and a prolific research portfolio, he has contributed significantly to the advancement of renewable energy integration, smart grid technologies, and power system optimization. His work bridges theoretical innovation and practical application, addressing some of the most pressing challenges in energy infrastructure and environmental sustainability. Over the years, Dr. Rehman has authored numerous peer-reviewed articles and has presented his findings at renowned international conferences. He is recognized for his collaborative approach to multidisciplinary research and his commitment to academic excellence. In addition to his research, Dr. Rehman is a dedicated educator and mentor, guiding undergraduate and postgraduate students in various domains of electrical engineering. He also plays an active role in academic reviewing and editorial responsibilities for international journals, reflecting his standing in the scholarly community. His expertise continues to influence policy and technical practices in the energy sector. Through his leadership and scholarly activities, Dr. Saif Ur Rehman exemplifies a model of academic integrity and innovation, working towards a more energy-efficient and technologically empowered future.

Professional Profile

Education

Dr. Saif Ur Rehman holds an extensive academic background in the field of electrical engineering and energy systems. He earned his Bachelor’s degree in Electrical Engineering from a reputable institution, where he built a strong foundation in electronics, power systems, and communication. Driven by a passion for innovation and sustainable energy solutions, he pursued a Master’s degree in Electrical Engineering with a specialization in Energy Systems, during which he gained in-depth knowledge of power generation, grid stability, and renewable technologies. His quest for advanced research led him to obtain a Ph.D. in Electrical Engineering, where his doctoral thesis focused on integrating renewable energy sources into smart grid systems with improved efficiency and reliability. Throughout his academic journey, Dr. Rehman has consistently demonstrated academic excellence, earning various accolades and scholarships for his performance. He has also completed certifications and training in emerging technologies, such as smart grids, artificial intelligence in power systems, and energy management. His robust educational background has equipped him with both the theoretical and practical tools necessary to address real-world energy challenges, positioning him as a key contributor to the development of sustainable energy infrastructure and intelligent power systems.

Professional Experience

Dr. Saif Ur Rehman has amassed a wealth of professional experience in academia, research, and the energy industry. He has served in various academic positions, including Lecturer, Assistant Professor, and Research Fellow at esteemed universities, where he has been actively involved in teaching core electrical engineering courses and supervising undergraduate and postgraduate theses. His pedagogical approach emphasizes practical application and critical thinking, earning him recognition from both students and peers. Beyond teaching, Dr. Rehman has played integral roles in funded research projects focused on smart grids, energy storage, and sustainable energy systems. His experience includes collaboration with governmental bodies and private energy firms, contributing to the development and implementation of innovative energy solutions. He has also held consulting roles, providing expert advice on power distribution, system optimization, and renewable integration. His multidisciplinary experience allows him to bridge gaps between theoretical models and industry needs effectively. Additionally, Dr. Rehman has been actively involved in organizing academic workshops, seminars, and conferences, further enhancing knowledge dissemination and networking. His professional journey showcases a dynamic blend of research, teaching, and real-world impact, underscoring his role as a thought leader in the energy and engineering sectors.

Research Interests

Dr. Saif Ur Rehman’s research interests lie at the intersection of electrical engineering, sustainable energy, and emerging technologies. His primary focus is on smart grid technologies, including the integration of renewable energy sources such as solar and wind into conventional power systems. He is deeply invested in developing models that ensure efficient, reliable, and resilient grid operation under varying environmental and demand conditions. Another key area of his research involves energy storage systems and their role in grid stability and demand-side management. Dr. Rehman also explores artificial intelligence and machine learning applications in energy systems for predictive maintenance, load forecasting, and fault detection. Additionally, he investigates power quality improvement techniques and optimization algorithms for energy efficiency. His interdisciplinary approach often involves collaboration with computer scientists, environmental engineers, and policymakers to craft comprehensive solutions for energy sustainability. He is also keen on examining the socio-economic implications of energy transitions and smart infrastructure deployment in developing regions. Dr. Rehman’s research not only contributes to scientific knowledge but also addresses practical challenges, paving the way for more sustainable and intelligent energy solutions. His work supports global goals for clean energy and carbon neutrality, aligning with contemporary needs for environmental stewardship and technological innovation.

Research Skills

Dr. Saif Ur Rehman possesses a diverse and advanced set of research skills that empower his investigations into sustainable energy systems and smart grid technologies. His technical expertise includes power system analysis, energy modeling, and simulation using software tools such as MATLAB/Simulink, PSCAD, ETAP, and PSS/E. He is proficient in designing and optimizing energy networks and conducting load flow, stability, and fault analysis. Dr. Rehman is skilled in applying artificial intelligence and machine learning techniques to solve energy-related problems, including neural networks and evolutionary algorithms for predictive analytics and optimization. His strong background in data analysis and statistical modeling enables him to handle large datasets and derive actionable insights. He is also adept at technical writing, having authored numerous scholarly articles, conference papers, and technical reports. Furthermore, his project management capabilities allow him to coordinate multidisciplinary research teams, manage budgets, and meet project deliverables. He has demonstrated excellence in grant writing and securing research funding from national and international agencies. With experience in experimental design, laboratory testing, and field implementation, Dr. Rehman’s research skills are both broad and deep, enabling him to contribute effectively to academic and industrial innovations in energy systems.

Awards and Honors

Dr. Saif Ur Rehman has been the recipient of numerous awards and honors that reflect his academic excellence, research contributions, and professional leadership. He has received multiple Best Paper Awards at international conferences for his groundbreaking research on smart grid integration and renewable energy systems. His doctoral research was recognized with academic distinction and garnered attention from the global energy research community. He has also been awarded research fellowships and travel grants from respected scientific institutions, enabling him to present his work at prestigious forums and engage in collaborative research. Dr. Rehman has received commendations from his affiliated universities for excellence in teaching and mentoring, as well as for his active role in student development. He serves on editorial boards and peer-review committees for leading journals in electrical engineering and energy, further demonstrating the high regard in which he is held by his peers. Additionally, he has been invited as a keynote speaker at various academic and industrial events, underlining his authority in the field. These accolades collectively signify his dedication, innovation, and impact in advancing knowledge and practice in electrical engineering and sustainable energy technologies.

Conclusion

In conclusion, Dr. Saif Ur Rehman stands out as a dynamic and visionary scholar in the field of electrical engineering and energy systems. His multifaceted career, spanning research, teaching, consultancy, and international collaboration, reflects a deep commitment to advancing sustainable energy solutions and empowering future engineers. His academic journey and professional experience underscore a rare combination of theoretical rigor and real-world relevance, allowing him to address contemporary energy challenges effectively. With an extensive publication record, impressive research achievements, and numerous accolades, Dr. Rehman continues to shape the discourse on renewable energy integration, smart grids, and intelligent power systems. His dedication to mentoring and educational excellence ensures the continuous growth of his students and research teams, fostering the next generation of innovators in engineering. Moreover, his interdisciplinary approach and global outlook position him as a catalyst for innovation in the transition to clean energy. Dr. Saif Ur Rehman’s work not only contributes to academic advancement but also provides valuable solutions to societal and environmental challenges. As he continues to expand his research and influence, his contributions will remain pivotal to the development of resilient, efficient, and sustainable energy infrastructures worldwide.

Publications Top Notes

  1. Generalized Unique Fixed Point Results in Generalized Fuzzy Metric Spaces

  • Authors: Saif T. Ur-Rehman, Abeer M.M. Jaradat, Sidra Akbar, Boško Damjanović, Mohammed Mahmoud M. Jaradat

  • Journal: Journal of Mathematical Analysis

  • Year: 2024

2. Effects of Tyloxapol in the Amelioration of Endotoxemic Effects of Pasteurella multocida During Hemorrhagic Septicemia in Water Buffaloes

  • Authors: Muhammad Nadeem Shahzad, Muhammad Arif Zafar, Adnan Hassan Tahir, Saif T. Ur-Rehman

  • Journal: Pakistan Veterinary Journal

  • Year: 2024

3. Some New Rational Contractions Approach to the Solution of Integral Equations via Unique Common Fixed Point Theorems in Complex Valued Gb−Metric Spaces

  • Authors: Sidra Akbar, Saif T. Ur-Rehman, Mohammed Mahmoud M. Jaradat, Faryal Gul

  • Journal: Asia Pacific Journal of Mathematics

  • Year: 2024

 

 

Gayrat Urazboev | Mathematics | Best Scholar Award

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Prof. Gayrat Urazboev | Mathematics | Best Scholar Award

Professor at Urgench State University, Uzbekistan

Gayrat Urazboev is a distinguished mathematician specializing in nonlinear evolution equations, soliton theory, and integrability. With a Doctor of Science in Mathematics, he has made significant contributions to mathematical physics, particularly in inverse scattering methods and direct analytical approaches. He currently serves as the Vice Rector for International Relations and Professor at Urgench State University in Uzbekistan. Throughout his career, he has held research positions at prestigious institutions in Germany, Spain, and Italy. His extensive academic collaborations, leadership roles, and involvement in international research projects have established him as a key figure in the field. He has organized several international conferences and contributed to academic community building through his role as an editor and reviewer for mathematical journals. His dedication to education and research is reflected in his involvement with ERASMUS+, TEMPUS, and other global academic initiatives. Recognized with multiple research fellowships and grants, he has played a crucial role in advancing mathematical sciences in Uzbekistan. His expertise in differential equations and mathematical physics, coupled with his strong leadership and mentorship, make him an influential scholar in the global academic community.

Professional Profile

Education

Gayrat Urazboev earned his Diploma (equivalent to an M.S.) in Mathematics and Applied Mathematics from Moscow State University, Russia, in 1992. His master’s thesis focused on optimal control of singular distributed systems, laying the foundation for his future research in nonlinear mathematical physics. He pursued a Ph.D. at the Romanovskiy Mathematical Institute, Academy of Sciences of Uzbekistan, where he defended his dissertation in 2001 on the integration of the Korteweg-de Vries equation with self-consistent sources. This research played a crucial role in understanding nonlinear wave equations. In 2007, he completed his Doctor of Science (Doctor Habilitatus) at the National University of Uzbekistan, where he further advanced his studies on nonlinear evolution equations with self-consistent sources. His doctoral research significantly contributed to the field of soliton theory and integrable systems. His academic journey across prestigious institutions has equipped him with profound expertise in mathematical modeling, differential equations, and applied mathematics. Through continuous professional development, he has remained at the forefront of mathematical research and has played an instrumental role in promoting mathematical education and research excellence in Uzbekistan and beyond.

Professional Experience

Dr. Gayrat Urazboev has an extensive academic and research career spanning over three decades. He is currently the Vice Rector for International Relations and a Professor in the Department of Physics and Mathematics at Urgench State University, a position he has held since 2019. Previously, he served as a full professor at the same institution from 2011 to 2018. His international research experience includes roles as a Scientific Researcher at the University of Duisburg-Essen, Germany, in 2011, and as a Postdoctoral Researcher at the University of Santiago de Compostela, Spain, in 2009. Additionally, he served as Vice-Rector and Head of the Department of Mathematical Physics and Applied Mathematics at Urgench State University. His professional contributions extend beyond academia, as he has been involved in multiple international research collaborations and projects, including Erasmus+ and TEMPUS. As a key figure in higher education, he has played a crucial role in curriculum development, faculty training, and research capacity building in Uzbekistan. His expertise in nonlinear mathematical physics, coupled with his leadership in academic administration, has significantly influenced mathematical research and education at both national and international levels.

Research Interests

Dr. Gayrat Urazboev’s research interests lie in the fields of nonlinear evolution equations, inverse scattering methods, soliton theory, and integrability. His work focuses on the development of direct and inverse methods for solving complex partial differential equations with self-consistent sources. He has made significant contributions to the mathematical analysis of solitons, particularly in the study of nonlinear wave phenomena and their applications in physics. His research explores the integration of nonlinear evolution equations, which are fundamental in mathematical physics and engineering. His expertise extends to spectral theory and its applications to differential operators, helping advance the theoretical understanding of wave propagation, fluid dynamics, and quantum mechanics. As a researcher dedicated to mathematical physics, he continuously explores innovative techniques for analyzing and solving nonclassical partial differential equations. His work has been instrumental in advancing the study of integrable systems and has contributed to the development of mathematical tools for tackling real-world problems in science and engineering. Through collaborations with international scholars and participation in global research initiatives, he has expanded the scope of his research, making a lasting impact on the mathematical community.

Research Skills

Dr. Urazboev possesses a strong set of research skills that make him a leading expert in mathematical physics and applied mathematics. His expertise includes analytical and numerical methods for solving nonlinear differential equations, with a focus on integrability and soliton theory. He is proficient in advanced mathematical modeling techniques used in the study of wave dynamics and inverse scattering methods. His computational skills include proficiency in MATLAB, Mathematica, Maple, and LaTeX, which he utilizes for complex mathematical simulations and research documentation. He has extensive experience in academic writing, peer reviewing, and editing mathematical publications, serving as a reviewer for Mathematical Reviews and an editor for the Open Journal of Mathematical Sciences. His ability to design and implement interdisciplinary research projects is evident through his involvement in international collaborations such as Erasmus+ and TEMPUS. Additionally, his strong problem-solving skills, combined with his ability to mentor and guide research students, have contributed to the development of new mathematical theories and applications. His research skills, combined with his leadership in academia, continue to shape the future of mathematical sciences.

Awards and Honors

Dr. Urazboev has been the recipient of numerous prestigious awards and research fellowships, recognizing his contributions to mathematical sciences. In 2020, he was awarded the Weiser Professional Development Fellowship by the University of Michigan, USA, acknowledging his leadership in research and academic development. His international research achievements have been supported by multiple DAAD research scholarships in Germany (2011, 2016) and Erasmus Mundus academic staff mobility scholarships from European institutions such as the University of Graz, Austria, and the University of Santiago de Compostela, Spain. He was also awarded the National Scholarship Programme of the Slovak Republic in 2015. His excellence in research was recognized by the Ministry of Higher and Secondary Special Education of Uzbekistan, which named him Young Doctor of Science in 2007. Additionally, he received the prestigious Istedod Foundation Award from the President of Uzbekistan in 2006. These accolades highlight his global recognition and contributions to the advancement of mathematical research. His numerous research grants and fellowships reflect his dedication to fostering academic excellence and international collaboration in the field of mathematics.

Conclusion

Dr. Gayrat Urazboev is a highly accomplished mathematician with a distinguished career in nonlinear evolution equations, soliton theory, and integrability. His extensive research experience, combined with his leadership roles in academia, has made a significant impact on mathematical sciences. His international collaborations, numerous research grants, and contributions to mathematical education highlight his commitment to advancing the field. His proficiency in mathematical modeling, analytical techniques, and computational tools underscores his technical expertise. While his research output is impressive, further expanding his publication record in high-impact journals and enhancing his English proficiency would strengthen his global influence. His dedication to mentoring young researchers, organizing conferences, and participating in international research programs demonstrates his commitment to academic development. Recognized with prestigious awards and fellowships, he has played a pivotal role in promoting mathematical research and education both in Uzbekistan and internationally. As a researcher and academic leader, he continues to contribute to the field of mathematical physics, making him a strong candidate for research excellence awards and further academic recognition.

Publication Top Notes

  1. Title: “Analysis of the Solitary Wave Solutions of the Negative Order Modified Korteweg–de Vries Equation with a Self-Consistent Source”

    • Authors: G.U. Urazboev, I.I. Baltaeva, Shoira E. Atanazarova
    • Year: 2025

  2. Title: “Integration of the Negative Order Nonlinear Schrödinger Equation in the Class of Periodic Functions”

    • Authors: G.U. Urazboev, Muzaffar M. Khasanov, Aygul K. Babadjanova
    • Year: 2024

  3. Title: “Integration of Negative-Order Modified Korteweg–de Vries Equation with an Integral Source”

    • Authors: G.U. Urazboev, Muzaffar M. Khasanov, O.B. Ismoilov
    • Year: 2024

 

 

Issa Bamia | Mathematics | Best Researcher Award

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Mr. Issa Bamia | Mathematics | Best Researcher Award

Data Scientist at African Institute for Mathematical Sciences, Mali.

Issa Bamia is a mathematician and data scientist with a deep passion for advancing research in adversarial machine learning and AI security. His expertise spans data engineering, digital health solutions, and cloud-based pipeline architecture, with a focus on addressing real-world issues in healthcare and telecommunications. With significant hands-on experience, Issa has optimized data collection processes, improved decision-making tools, and contributed to impactful projects that prioritize AI safety. His work as a data engineer for Muso Health demonstrates his commitment to using data-driven insights for tangible improvements in public health. Furthermore, he has a strong foundation in advanced data science and machine learning techniques, including proficiency with large language models (LLMs), security frameworks, and virtualization. This experience, combined with his commitment to ongoing research and development, positions Issa as a promising figure in the fields of AI safety and adversarial machine learning.

Professional Profile

Education

Issa Bamia holds a Master’s in Mathematical Sciences with a specialization in Data Science from the African Institute for Mathematical Sciences (AIMS), an institution renowned for its focus on African mathematicians and scientists. His education at AIMS included a rigorous curriculum that equipped him with the analytical and technical skills needed for advanced data science research and practical applications. He gained specialized knowledge in AI and adversarial machine learning, which he applied in his professional projects to develop data-driven solutions that impact digital health. Before this, he completed a Bachelor’s degree in Electronic Information Engineering from Tianjin University, where he gained foundational knowledge in data management and engineering principles. Issa’s educational background is complemented by certifications, including a professional certification in Large Language Models (LLMs) from Databricks, which has further refined his ability to work with complex AI models and large datasets. His diverse academic and practical training has laid a strong foundation for his research and professional pursuits in data science and AI security.

Professional Experience

Issa Bamia has a diverse professional background spanning data engineering, software development, and account management. Currently, he works as a data engineer for Muso Health, where he streamlines data collection, optimizes cloud-based data pipelines, and develops dashboards for real-time healthcare data analysis. His work here has been instrumental in improving medication stock management and reducing stockouts, enhancing healthcare delivery for underserved populations. Prior to this, Issa worked as an account manager with Huawei Technologies, where he customized technological solutions to meet telecom operators’ needs, ensuring smooth service delivery and strong client relations. Earlier, he was a software engineer with Whale Cloud Technologies, where he worked on the deployment and maintenance of cloud-based software products and managed system and database maintenance. Throughout these roles, Issa demonstrated an ability to handle complex data infrastructures and security protocols, showcasing his expertise in data science and its applications in both healthcare and telecommunications.

Research Interest

Issa Bamia’s primary research interests lie in adversarial machine learning, AI safety, and the development of secure, resilient AI models. His focus is on understanding and mitigating vulnerabilities in AI systems, particularly those posed by adversarial attacks, which can manipulate machine learning models to produce inaccurate or biased outcomes. He is passionate about exploring solutions that bolster the security and reliability of AI, especially in applications related to digital health, where data integrity is critical for decision-making. Issa is also interested in the ethical and practical implications of AI security, as well as the ongoing evolution of AI governance and control frameworks. Additionally, he seeks to apply his expertise in large language models (LLMs) to further enhance AI’s adaptability and reliability. His dedication to AI safety underscores a commitment to building AI systems that prioritize both performance and ethical responsibility, which is particularly significant in fields like healthcare, where secure and trustworthy AI systems are essential.

Research Skills

Issa possesses a robust set of research skills that are integral to his work in adversarial machine learning and AI security. He is proficient in cloud-based technologies and data pipeline design, with extensive experience in platforms such as Google Cloud Platform (GCP) and Apache Airflow. His technical repertoire includes advanced machine learning frameworks and tools for large language models (LLMs), containerization through Docker, and security protocols that support secure data architectures. In addition to data engineering skills, he has a strong command of SQL, NoSQL, Linux, and various programming languages including Python and JavaScript. Issa is adept at working with virtualization, networking, and incident response, which are crucial in managing and securing complex data systems. His hands-on experience with tools like Looker, Spark, and Hadoop further enhances his capability to analyze, optimize, and visualize large datasets, supporting his research pursuits in AI and data security. His skills in agile project tracking and stakeholder engagement also enable him to lead projects effectively and ensure that his research aligns with organizational goals.

Awards and Honors

Throughout his career, Issa has earned recognition for his contributions to data science and digital health innovation. His academic achievements include a Master’s degree in Mathematical Sciences (Data Science) from the African Institute for Mathematical Sciences (AIMS), an honor that highlights his academic commitment to data science research. While at AIMS, Issa developed a data-driven solution for medication stock management at Muso Health, a project that successfully reduced stockouts and improved patient care outcomes, marking a significant professional achievement in public health. His commitment to professional growth is also evident in his completion of the Databricks Professional Certificate in Large Language Models (LLMs), which reflects his proficiency in implementing, fine-tuning, and managing LLMs in various AI applications. This certification is a testament to his dedication to staying updated with advancements in AI, particularly in AI security, which is a key area of his research focus. These achievements underscore Issa’s commitment to both academic excellence and impactful, socially relevant research.

Conclusion

Issa Bamia’s background in adversarial machine learning, practical impact in digital health, and strong technical skill set make him a strong contender for the Best Researcher Award. His work on AI safety, coupled with impactful public health solutions, aligns well with the criteria for this award. Strengthening his research profile with further publications and collaborations would elevate his contributions in this competitive field. Overall, he demonstrates the qualities of an innovative and impactful researcher.

 

Syed Anwar | signal processing | Best Researcher Award

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Syed Anwar | signal processing | Best Researcher Award

Principal Investigator at Childrens National Hopsital, United States.

Syed Muhammad Anwar is a distinguished researcher in the fields of medical imaging, deep learning, and computer vision. He is currently a Principal Investigator at the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National Hospital in Washington, DC, and serves as an Associate Professor at George Washington University. With over two decades of academic and professional experience, Dr. Anwar has co-founded tech ventures and contributed significantly to cutting-edge research in machine learning and medical image analysis. His expertise spans across multiple countries and academic institutions, with an impressive h-index of 38 and over 6,800 citations. A prolific scholar and inventor, he has secured numerous grants and awards for his research contributions in both academia and industry, particularly in the development of healthcare technologies. His leadership roles in education, research, and industry highlight his commitment to innovation and interdisciplinary collaboration in emerging technology fields.

Profile👤

Scopus

ORCID

Education📝

Dr. Anwar’s educational background showcases an impressive academic journey through prestigious institutions. He earned his PhD in Electronic and Electrical Engineering from the University of Sheffield, UK, in 2012, where his research focused on detecting neuronal fields using MR imaging. Prior to that, he obtained a distinction in his MS in Data Communications, also from the University of Sheffield. His undergraduate education was completed at the University of Engineering and Technology (UET), Taxila, where he graduated with honors in Computer Engineering, finishing with the second-highest percentage in his class. In 2019-2020, he was awarded a prestigious Fulbright Fellowship at the University of Central Florida, focusing on deep learning for medical image analysis. His diverse and interdisciplinary academic foundation, spanning engineering and medical technology, forms the basis of his expertise in cutting-edge research areas like artificial intelligence, machine learning, and medical image computing.

Experience👨‍🏫

Dr. Anwar’s career spans a wide array of academic and industry positions. Currently, he serves as Principal Investigator at Children’s National Hospital and Associate Professor at George Washington University. He was previously an Associate Professor at the University of Engineering and Technology, Taxila, where he held numerous administrative and advisory roles. He has also worked internationally, including as a Research Fellow at the University of Surrey, UK, and a Research Associate at the University of Central Florida, USA. Dr. Anwar has extensive experience in the tech industry, having co-founded several companies, including EcoEdge AI and Sense Digital Pvt. Ltd., where he served as CTO. His industrial roles have focused on deep learning, medical imaging, and healthcare solutions. Additionally, he has mentored entrepreneurs and served as an advisor at national incubation centers, underscoring his role as a bridge between academia and industry in technology and innovation.

Research Interest🔬 

Dr. Anwar’s research interests are deeply rooted in medical image analysis, artificial intelligence, and deep learning. His work primarily focuses on utilizing deep learning models to improve medical diagnostics, especially in fields such as brain tumor segmentation, pediatric health, and cardiac health monitoring. He is particularly interested in applying machine learning techniques to enhance medical imaging technologies, exploring areas like brain-computer interfaces and wearable health technologies. His projects also delve into federated learning for medical imaging security and using AI to predict health outcomes, such as in sickle cell disease management. Throughout his career, Dr. Anwar has sought to bridge the gap between medical science and computational technology, aiming to create innovative, data-driven healthcare solutions. His interdisciplinary research has earned him international recognition, positioning him as a key figure in advancing AI-driven medical applications.

Awards and Honors🏆

Dr. Anwar has received numerous prestigious awards and honors throughout his career. He was a Fulbright Fellow at the University of Central Florida, USA, where he focused on applying deep learning to medical image analysis. He has also been awarded several research grants, including a $220,000 seed grant from IGNITE for his work in fashion retrieval using deep learning and a $1200 grant from NVIDIA for hardware development. His contributions to academia have been widely recognized, with multiple travel grants awarded by the Higher Education Commission of Pakistan for presenting his research at international conferences. Additionally, Dr. Anwar has played a leading role in student mentorship, entrepreneurship, and incubation programs, where he has been recognized as a mentor at national incubation centers and the Pak-US Alumni Network. His leadership roles and innovative research projects have earned him a reputation for academic excellence and contribution to the global research community.

Skills🛠️

Dr. Anwar possesses a robust set of technical and leadership skills. His core expertise lies in deep learning, medical image analysis, and artificial intelligence. He is proficient in applying machine learning algorithms to a variety of real-world problems, especially in healthcare technologies. His strong background in software and hardware engineering includes experience with EEG-based systems, brain-computer interfaces, and remote health monitoring. Additionally, Dr. Anwar is skilled in research design, grant writing, and project management, having secured significant funding for his projects. His entrepreneurial abilities are demonstrated through his co-founding of tech startups and his role as CTO, where he has led development teams in creating innovative AI solutions. He also excels in academic mentoring, having supervised multiple PhD students and contributed to curriculum development in machine learning and computer vision at universities.

Conclusion 🔍 

Dr. Syed Muhammad Anwar is a highly accomplished researcher whose contributions to medical image analysis, deep learning, and AI in healthcare make him a strong candidate for the Best Researcher Award. His distinguished career, which spans academia, industry, and entrepreneurial ventures, highlights his ability to blend research innovation with real-world applications. His extensive publication record, high citation count, and successful leadership in numerous research projects underscore his academic impact. Dr. Anwar’s interdisciplinary approach, combining engineering with healthcare solutions, and his ability to secure significant research funding demonstrate his excellence in research and innovation. With a deep commitment to advancing technology for medical applications, Dr. Anwar’s work continues to influence both academic research and the practical development of AI-driven healthcare systems.

Publication Top Notes

Title: BPMN extension evaluation for security requirements engineering framework
Authors: Zareen, S., Anwar, S.M.
Year: 2024
Citation Count: 1

Title: Development of a Modular Real-time Shared-control System for a Smart Wheelchair
Authors: Ramaraj, V., Paralikar, A., Lee, E.J., Anwar, S.M., Monfaredi, R.
Year: 2024
Citation Count: 0

Title: An automated framework for pediatric hip surveillance and severity assessment using radiographs
Authors: Lam, V.K., Fischer, E., Jawad, K., Cleary, K., Anwar, S.M.
Year: 2024
Citation Count: 0

Title: Quantitative Metrics for Benchmarking Medical Image Harmonization
Authors: Parida, A., Jiang, Z., Packer, R.J., Anwar, S.M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: MR to CT Synthesis Using 3d Latent Diffusion
Authors: Tapp, A., Parida, A., Zhao, C., Anwar, S.M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: Zero-Shot Pediatric Tuberculosis Detection in Chest X-Rays Using Self-Supervised Learning
Authors: Capellan-Martin, D., Parida, A., Gomez-Valverde, J.J., Ledesma-Carbayo, M.J., Anwar, S.M.
Year: 2024
Citation Count: 0

Title: Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: A two-center study
Authors: Liu, X., Jiang, Z., Roth, H.R., Bornhorst, M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: EEG-Based Emotion Recognition during Mobile Gameplay
Authors: Khan, S.H., Raheel, A., Majid, M., Anwar, S.M., Arsalan, A.
Year: 2024
Citation Count: 0

Title: CHILD FER: DOMAIN-AGNOSTIC FACIAL EXPRESSION RECOGNITION IN CHILDREN USING A SECONDARY IMAGE DIFFUSION MODEL
Authors: Lee, E., Lee, E.-J., Anwar, S.M., Yoo, S.B.
Year: 2024
Citation Count: 0

Title: Self-Supervised Learning for Seizure Classification using ECoG spectrograms
Authors: Lam, V., Oliugbo, C., Parida, A., Linguraru, M.G., Anwar, S.M.
Year: 2024
Citation Count: 0

Laxmi Rathour | Mathematics | Young Scientist Award

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Laxmi Rathour | Mathematics | Young Scientist Award

Research Scholar at National Institute of Technology Mizoram, India.

Laxmi Rathour is an emerging scholar in the field of mathematics, currently serving as a researcher at the National Institute of Technology (NIT), Mizoram. With a strong academic background and a focused research agenda, her expertise lies in both pure and applied mathematics, particularly in areas such as Multi-Attribute Decision Making (MADM), Multi-Criteria Decision Making (MCDM), and Nonlinear Analysis. She is actively involved in research, contributing to journals and collaborating internationally as a reviewer for prestigious publications like Mathematical Reviews (USA) and Zentralblatt Math (Germany). As she continues to pursue her Ph.D., Rathour is deeply engaged in advancing mathematical theory and its practical applications. Her research presence is growing on platforms such as SCOPUS and ResearchGate, and she is quickly establishing herself as a dedicated and impactful researcher in her field, making significant strides in her academic and professional career.

Profile👤

Scopus

ORCID

Education📝

Laxmi Rathour holds a Master’s degree in Mathematics from the Indira Gandhi National Tribal University in Amarkantak, Madhya Pradesh, India. She pursued her postgraduate studies from July 2019 to August 2021, during which she developed her foundational knowledge and research skills in various mathematical disciplines. Currently, she is furthering her academic pursuits by working toward a Ph.D., with a focus on advanced mathematical topics such as Meta Heuristic algorithms and Fractional Calculus. Her educational background has provided her with a strong grounding in both theoretical and applied aspects of mathematics, equipping her to explore complex mathematical problems. Rathour’s academic journey reflects her dedication to research and her desire to contribute new knowledge to the field of mathematics. Her ongoing Ph.D. studies are expected to deepen her expertise and enhance her impact as a researcher.

Experience👨‍🏫

Laxmi Rathour has been affiliated with the National Institute of Technology (NIT), Mizoram, since July 2023, where she serves as a researcher in the Department of Mathematics. Her role involves conducting research in specialized areas such as Multi-Objective Transportation Problems (MOTP) and Nonlinear Analysis. Prior to joining NIT, Rathour was actively involved in research during her master’s studies at Indira Gandhi National Tribal University, where she began developing her interests in optimization and decision-making algorithms. Additionally, she has gained experience as a voluntary reviewer for international mathematical publications, enhancing her exposure to global academic standards. This role has provided her with valuable insights into current trends in mathematical research, as well as opportunities to engage with complex theoretical concepts and methodologies, which have contributed to her growth as a researcher.

Research Interest🔬 

Laxmi Rathour’s research interests lie in a variety of mathematical disciplines, primarily focusing on applied and pure mathematics. Her areas of expertise include Multi-Attribute Decision Making (MADM), Multi-Criteria Decision Making (MCDM), and Multi-Objective Transportation Problems (MOTP), which are important in the context of optimization and decision-making processes. Additionally, she explores Fractional Calculus, Nonlinear Analysis, and Meta Heuristic algorithms. Rathour’s work in Fixed Point Theory and Approximation Theory contributes to solving complex mathematical models, with applications in both academic and real-world problems. Her research is oriented toward advancing mathematical theory while also seeking practical applications in optimization and decision-making, making her contributions valuable in a wide range of industries and scientific disciplines.

Awards and Honors🏆

Though specific awards and honors are not explicitly listed, Laxmi Rathour’s academic achievements and professional engagements highlight her growing recognition in the field of mathematics. She has earned respect as a reviewer for leading mathematical journals, including Mathematical Reviews (USA) and Zentralblatt Math (Germany). These roles demonstrate her expertise and the recognition she has gained within the global mathematical community. In addition to her reviewer positions, Rathour’s research has been published in several national and international journals, further indicating her contributions to her field. As her career progresses, it is likely that she will continue to earn accolades for her research and academic achievements, solidifying her status as an accomplished mathematician.

Skills🛠️

Laxmi Rathour possesses a diverse skill set that complements her research in mathematics. Her technical expertise includes proficiency in decision-making algorithms such as MADM and MCDM, as well as optimization techniques involving Multi-Objective Transportation Problems (MOTP). Additionally, she is skilled in using Meta Heuristic algorithms and advanced mathematical methods such as Fractional Calculus and Nonlinear Analysis. These skills are crucial for tackling complex mathematical problems, particularly in the areas of optimization and decision-making. Beyond her technical capabilities, Rathour also has strong analytical and problem-solving abilities, which are essential for conducting high-level research. Her role as a reviewer further underscores her critical thinking and editorial skills, making her a well-rounded researcher with both theoretical and applied mathematical expertise.

Conclusion 🔍 

Laxmi Rathour is a promising researcher in the field of mathematics, with a particular focus on decision-making algorithms, optimization, and advanced mathematical theories. Her academic journey, which began at Indira Gandhi National Tribal University and continues with her Ph.D. studies, reflects her dedication to expanding her knowledge and contributing to the global body of mathematical research. Her current role at the National Institute of Technology, Mizoram, allows her to further her research in specialized areas while also engaging with the broader academic community through publications and peer-review activities. As she continues to develop her skills and expertise, Rathour is poised to make significant contributions to both the theoretical and applied aspects of mathematics, positioning herself as an influential figure in the field.

Publication Top Notes

A simple and efficient preprocessing step for convex hull problem
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). A simple and efficient preprocessing step for convex hull problem. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S179383092350091X

Tracing roots and linkages: Harnessing graph theory and social network analysis in genealogical research, based on the kin naming system
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). Tracing roots and linkages: Harnessing graph theory and social network analysis in genealogical research, based on the kin naming system. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S1793830924500678

On r-dynamic k-coloring of ladder graph families
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). On r-dynamic k-coloring of ladder graph families. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S1793830924500356

Duality under novel generalizations of the D-Type-I functions for multiple objective nonlinear programming problems
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). Duality under novel generalizations of the D-Type-I functions for multiple objective nonlinear programming problems. Scientific African. https://doi.org/10.1016/j.sciaf.2024.e02067

A Time-Sequential Probabilistic Hesitant Fuzzy Approach to a 3-Dimensional Green Transportation System
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). A Time-Sequential Probabilistic Hesitant Fuzzy Approach to a 3-Dimensional Green Transportation System. In book: Smart Green Innovations for Sustainable Development. https://doi.org/10.1007/978-3-031-56304-1_9

Generalized Rational Type Contraction and Fixed Point Theorems in Partially Ordered Metric Spaces
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Generalized Rational Type Contraction and Fixed Point Theorems in Partially Ordered Metric Spaces. Journal of Advances in Applied & Computational Mathematics. https://doi.org/10.15377/2409-5761.2023.10.13

Integration of Rational Functions
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Integration of Rational Functions. Journal of Multidisciplinary Applied Natural Science. https://doi.org/10.47352/jmans.2774-3047.186

Possible directions of increasing the efficiency of the health system through software development
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Possible directions of increasing the efficiency of the health system through software development. Brazilian Journal of Science. https://doi.org/10.14295/bjs.v3i1.450

A Newton-like Midpoint Method for Solving Equations in Banach Space
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). A Newton-like Midpoint Method for Solving Equations in Banach Space. Foundations. https://doi.org/10.3390/foundations3020014

Coupled Fixed Point Theorems with Rational Type Contractive Condition via C-Class Functions and Inverse Ck-Class Functions
Author: Laxmi Rathour
Year: 2022
Citation: Rathour, L. (2022). Coupled Fixed Point Theorems with Rational Type Contractive Condition via C-Class Functions and Inverse Ck-Class Functions. Symmetry. https://doi.org/10.3390/sym14081663

 

Rizwan Gul | Mathematics | Best Researcher Award

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Dr. Rizwan Gul | Mathematics | Best Researcher Award

Research Scholar at Quaid-i-Azam University, Islamabad, Pakistan.

Rizwan Gul is a Ph.D. candidate in Pure Mathematics at Quaid-i-Azam University, Islamabad, Pakistan. He has an M.Phil. and a BS in Mathematics from the same institution and Kohat University of Science & Technology, respectively. His research interests include fuzzy algebraic structures, decision-making theory, soft and rough sets, and their applications. Rizwan has published extensively in ISI-listed journals with high impact factors, focusing on advanced mathematical models such as (α, β)-multi-granulation bipolar fuzzified rough sets and their applications in decision-making. He has also contributed to the field of algebraic cryptography. His work has been recognized with several awards, including a merit scholarship and a distinction award. Proficient in multiple programming and mathematical tools, Rizwan is actively involved in reviewing for international journals and has presented his research at various conferences. His contributions to mathematics demonstrate a strong foundation and innovative approach in his field.

Profile

Education🎓

Rizwan Gul has a strong academic background in Mathematics, culminating in a Ph.D. in Pure Mathematics from Quaid-i-Azam University, Islamabad, which he is expected to complete between 2020 and 2024. His doctoral research focuses on advanced topics such as (α, β)-Multi-Granulation Bipolar Fuzzified Rough Sets and their applications in decision-making. Prior to his Ph.D., Rizwan earned an M.Phil. in Pure Mathematics from the same institution between 2018 and 2020, where he conducted significant research on Modified Rough Bipolar Soft Sets. His academic journey began with a Bachelor of Science in Mathematics from Kohat University of Science & Technology, Kohat, completed between 2013 and 2017. During his undergraduate studies, he developed a strong foundation in mathematical theories, culminating in his thesis on Quivers and Path Algebras of Finite Connected Acyclic Quivers. His consistent academic excellence is evident through the distinctions and merit scholarships he received throughout his studies.

Professional Experience 🏢

Rizwan Gul is currently associated with the Department of Mathematics at Quaid-i-Azam University, Islamabad, where he is pursuing his Ph.D. in Pure Mathematics. His academic journey at Quaid-i-Azam University also includes completing an M.Phil. in Pure Mathematics, during which he contributed significantly to research in fuzzy algebraic structures, decision-making theory, and soft sets. Rizwan has an impressive portfolio of research publications, many of which are listed in high-impact ISI journals. His expertise extends to refereeing and reviewing for reputable journals like the Journal of Intelligent & Fuzzy Systems and Computational and Applied Mathematics. Throughout his academic career, he has delivered seminars and participated in workshops and conferences that further enriched his knowledge and research skills. Rizwan’s professional experience is marked by a strong foundation in mathematical theory and its applications, particularly in the areas of fuzzy sets and their hybrid structures.

Research Interests 🔬

Rizwan Gul’s research interests lie in the field of pure mathematics, with a particular focus on fuzzy algebraic structures, decision-making theory, and their applications. His work explores fuzzy sets and their generalizations, such as rough sets, soft sets, and their hybrid algebraic structures. Rizwan is deeply engaged in the study of aggregation operators and algebraic cryptography, contributing to the development of advanced mathematical models that address complex decision-making problems. His research includes the application of these mathematical frameworks to multi-criteria group decision-making, providing innovative solutions to challenges in various fields. Through his work, Rizwan aims to push the boundaries of mathematical theory while offering practical tools for real-world problems, particularly in the realm of decision-making under uncertainty. His contributions are published in high-impact journals, reflecting the significance and relevance of his research in the mathematical community.

Award and Honors

Rizwan Gul has demonstrated exceptional academic and research prowess, earning several accolades throughout his career. Notably, he received a Merit Scholarship during his BS studies at Kohat University of Science & Technology (KUST), Pakistan, in recognition of his outstanding performance in the final four semesters. His academic excellence also earned him a Silver Medal distinction from KUST, further solidifying his status as a top-performing student. In 2016, he was awarded a merit-based laptop under the Prime Minister’s Laptop Scheme, highlighting his academic achievements at the national level. These honors underscore his dedication to his studies and his contributions to the field of mathematics, particularly in areas such as fuzzy algebraic structures and decision-making theories. Rizwan Gul’s consistent recognition for academic excellence is a testament to his hard work and his potential for making significant contributions to mathematical research.

Research Skills

Rizwan Gul possesses a robust set of research skills, particularly in the field of Pure Mathematics, with a focus on fuzzy algebraic structures, decision-making theory, and their hybrid applications. His expertise spans various advanced mathematical concepts, including rough sets, soft sets, and their generalizations. He has demonstrated proficiency in mathematical modeling, especially in the development and application of bipolar fuzzified rough sets in decision-making. Rizwan is adept at using computational tools such as AMS-LaTeX, Maple, Matlab, and Mathematica, which enhances his ability to solve complex mathematical problems and present his findings effectively. His research contributions are well-documented in numerous ISI-listed journals with significant impact factors, reflecting his ability to conduct high-quality research. Moreover, his experience in reviewing and refereeing for reputable journals further underscores his analytical skills and deep understanding of contemporary mathematical research trends. These skills collectively position him as a capable and innovative researcher in his field.

Conclusion

Rizwan Gul is a strong candidate for the Research for Best Researcher Award, with a robust academic background, significant research contributions, and a strong publication record in high-impact journals. His research is highly specialized and has potential applications in decision-making and cryptography, which are important fields in both theoretical and applied mathematics. To further enhance his profile, Rizwan should consider increasing his international presence, expanding the interdisciplinary applications of his research, and participating in teaching or mentoring roles. Overall, his current achievements make him a competitive nominee for this award.

Publications Top Notes 📚
  • Modified Rough Bipolar Soft Sets
    • Authors: M Shabir, R Gul
    • Journal: Journal of Intelligent & Fuzzy Systems
    • Year: 2020
    • Citations: 21
    • Volume: 39 (3), Pages 4259-4283
  • Roughness of a Set by -Indiscernibility of Bipolar Fuzzy Relation
    • Authors: R Gul, M Shabir
    • Journal: Computational and Applied Mathematics
    • Year: 2020
    • Citations: 20
    • Volume: 39 (3), Page 160
  • Medical Decision-Making Techniques Based on Bipolar Soft Information
    • Authors: N Malik, M Shabir, TM Al-shami, R Gul, A Mhemdi
    • Journal: AIMS Math
    • Year: 2023
    • Citations: 8
    • Volume: 8 (8), Pages 18185-18205
  • A Novel Approach Toward Roughness of Bipolar Soft Sets and Their Applications in MCGDM
    • Authors: R Gul, M Shabir, M Naz, M Aslam
    • Journal: IEEE Access
    • Year: 2021
    • Citations: 8
    • Volume: 9, Pages 135102-135120
  • Rough Bipolar Fuzzy Ideals in Semigroups
    • Authors: N Malik, M Shabir, TM Al-shami, R Gul, M Arar, M Hosny
    • Journal: Complex & Intelligent Systems
    • Year: 2023
    • Citations: 7
    • Volume: 9 (6), Pages 7197-7212
  • Multigranulation Modified Rough Bipolar Soft Sets and Their Applications in Decision-Making
    • Authors: R Gul, M Shabir, M Aslam, S Naz
    • Journal: IEEE Access
    • Year: 2022
    • Citations: 7
    • Volume: 10, Pages 46936-46962
  • A Comprehensive Study on -Bipolar Fuzzified Rough Set Model Based on Bipolar Fuzzy Preference Relation and Corresponding Decision-Making Applications
    • Authors: R Gul, M Shabir, M Naeem
    • Journal: Computational and Applied Mathematics
    • Year: 2023
    • Citations: 6
    • Volume: 42 (7), Page 310
  • A Study on Soft Multi-Granulation Rough Sets and Their Applications
    • Authors: S Ayub, W Mahmood, M Shabir, ANA Koam, R Gul
    • Journal: IEEE Access
    • Year: 2022
    • Citations: 5
    • Volume: 10, Pages 115541-115554
  • Another Approach to Linear Diophantine Fuzzy Rough Sets on Two Universes and Its Application Towards Decision-Making Problems
    • Authors: S Ayub, M Shabir, R Gul
    • Journal: Physica Scripta
    • Year: 2023
    • Citations: 4
    • Volume: 98 (10), Article 105240
  • A Novel Decision-Making Technique Based on T-Rough Bipolar Fuzzy Sets
    • Authors: N Malik, M Shabir, TM Al-shami, R Gul, M Arar
    • Journal: Journal of Mathematical and Computational Science
    • Year: 2024
    • Citations: 3
    • Volume: 33, Pages 275-289