Snekhalatha Umapathy | Engineering | Excellence in Research Award

Prof. Dr. Snekhalatha Umapathy | Engineering | Excellence in Research Award

Professor and Head from SRM Institute of Science and Technology, India

Dr. Snekhalatha Umapathy is a distinguished Professor in the Department of Biomedical Engineering at SRM Institute of Science and Technology. With a research career spanning over a decade, she has made substantial contributions to biomedical instrumentation, biosensors, medical image and signal processing, and artificial intelligence applications in healthcare. She has authored over 145 publications, including 55 in SCI-indexed journals and 54 in the Web of Science, showcasing her consistent academic productivity. Her research is highly interdisciplinary, integrating engineering, medicine, and advanced computing techniques. Dr. Umapathy’s work has led to the granting of five patents and the publication of three more, underscoring her commitment to innovation and translational research. She has successfully supervised six Ph.D. scholars and continues to mentor three more, indicating her dedication to academic leadership and student development. Her most recent studies focus on quantum machine learning and wearable biosensors, areas of increasing importance in personalized medicine. Through her extensive involvement in international conferences, book publications, and impactful journals, she maintains a strong academic presence. Overall, Dr. Umapathy stands out as a highly accomplished researcher whose work bridges fundamental research and clinical application, positioning her as a leading expert in the biomedical engineering domain.

Professional Profile

Education

Dr. Snekhalatha Umapathy’s academic background is rooted in a strong foundation in engineering and interdisciplinary science. She pursued her higher education in fields that aligned closely with biomedical innovation, integrating elements of electronics, instrumentation, and life sciences. Although specific degree titles and institutions are not listed here, her progression to a professorial role and active research leadership indicates the successful completion of undergraduate and postgraduate degrees in relevant engineering disciplines, followed by a doctorate (Ph.D.) in a field closely related to biomedical engineering. Her educational pathway has allowed her to explore the integration of engineering principles with human physiology, medical diagnostics, and therapeutic technologies. Through rigorous training and advanced coursework, she has developed specialized expertise in areas such as biosensor technology, medical imaging, signal processing, and artificial intelligence applications in medicine. This academic training has been critical in enabling her to publish in high-impact journals, supervise doctoral research, and secure patents in the biomedical technology space. Her educational journey reflects both depth and diversity, providing her with the tools necessary to contribute meaningfully to multidisciplinary research and academic mentorship within the global biomedical engineering community.

Professional Experience

Dr. Snekhalatha Umapathy currently serves as a Professor in the Department of Biomedical Engineering at SRM Institute of Science and Technology, a role that reflects her vast academic experience and leadership capabilities. Over the years, she has played a pivotal role in driving research innovation, mentoring students, and establishing industry-academic linkages within the university setting. Her responsibilities include supervising doctoral scholars, delivering advanced courses in biomedical instrumentation and AI in healthcare, and leading funded research initiatives. With more than 145 publications and several patents to her name, she has consistently demonstrated a capacity to translate academic inquiry into practical, real-world applications. In addition to her research and teaching duties, she actively participates in organizing conferences, delivering keynote addresses, and collaborating with interdisciplinary teams for technological development. Her professional experience extends beyond academia, encompassing collaborative projects with clinicians, engineers, and researchers to design medical devices and diagnostic systems. Dr. Umapathy’s work ethic, combined with her technical insight and administrative contributions, positions her as a highly effective academic leader. Her commitment to fostering innovation and knowledge transfer has not only elevated the research profile of her department but has also contributed significantly to the broader biomedical engineering landscape in India.

Research Interests

Dr. Snekhalatha Umapathy’s research interests lie at the intersection of engineering, healthcare, and computational science. Her primary focus areas include biosensors, point-of-care diagnostic devices, biomedical signal and image processing, and the integration of deep learning and quantum machine learning techniques into healthcare applications. She is particularly interested in developing non-invasive diagnostic tools and wearable biosensors that can monitor biomarkers for diseases such as diabetes, chronic kidney disease, and Alzheimer’s. Her work in medical image processing includes automated classification and detection using AI, contributing to early diagnosis and improved patient outcomes. Dr. Umapathy also explores the use of novel materials, such as graphene-based sensors, in creating affordable and scalable healthcare solutions. A forward-thinking researcher, she is actively investigating the potential of quantum machine learning algorithms to enhance the accuracy and efficiency of medical diagnostic systems. By bridging the gap between technology development and clinical utility, her research addresses pressing global health challenges while contributing to the scientific advancement of biomedical instrumentation and artificial intelligence. Her interdisciplinary approach allows for innovative problem-solving and has led to significant academic recognition, industry relevance, and translational impact.

Research Skills

Dr. Snekhalatha Umapathy possesses a rich array of research skills that position her as a leader in the field of biomedical engineering. She is highly skilled in advanced signal and image processing techniques, enabling her to extract meaningful data from complex physiological signals and imaging modalities. Her expertise in deep learning, convolutional neural networks (CNNs), and machine learning allows her to develop predictive models for disease diagnosis, particularly in applications such as Alzheimer’s detection and rheumatoid arthritis classification. She is also proficient in working with quantum computing frameworks to apply quantum machine learning techniques, which is a highly specialized and emerging area in medical diagnostics. In the laboratory, she demonstrates strong capabilities in biosensor design, materials characterization, and experimental modeling, especially in breath analysis using graphene-based sensor arrays. Dr. Umapathy’s analytical and programming skills extend to MATLAB, Python, and simulation tools used in biomedical signal modeling. In addition, she is experienced in writing grant proposals, publishing scholarly articles, and securing intellectual property rights through patents. Her collaborative approach and project management skills further enhance her ability to lead multidisciplinary teams and contribute meaningfully to high-impact, solution-oriented research.

Awards and Honors

Dr. Snekhalatha Umapathy has been recognized for her academic and research contributions through several awards and honors, although the specific names of the awards are not listed in the provided details. The granting of five patents and the publication of three more reflects her recognition as an innovator in biomedical technology. Her consistent presence in high-impact journals such as Scientific Reports, Analytical Chemistry, and Biomedical Signal Processing and Control suggests acknowledgment by the global academic community. Additionally, her role as a Ph.D. supervisor and her involvement in international conferences and book publications are indicators of her esteemed position in the academic world. It is highly likely that she has received internal and external recognition from academic institutions, professional societies, and funding agencies for her work. Dr. Umapathy’s interdisciplinary research combining AI, biosensing, and biomedical instrumentation places her at the forefront of emerging health technologies. These honors not only validate her research excellence but also serve as an inspiration for future scholars in the field. Her achievements in innovation, publication, and mentoring further solidify her reputation as a leading academic figure in biomedical engineering.

Conclusion

Dr. Snekhalatha Umapathy exemplifies excellence in biomedical engineering through her innovative research, prolific publication record, and dedication to academic mentorship. Her work spans crucial areas such as biosensor development, AI-driven diagnostics, and quantum machine learning, addressing some of the most pressing healthcare challenges of our time. With a robust portfolio of SCI-indexed publications, multiple patents, and successful Ph.D. supervisions, she embodies the qualities of a high-impact researcher. Her collaborative and interdisciplinary approach ensures her work remains both scientifically rigorous and practically relevant. Dr. Umapathy’s research not only advances academic knowledge but also holds tangible benefits for clinical practice and public health. She has established herself as a thought leader, mentor, and innovator who is shaping the future of biomedical research and education. As the healthcare landscape evolves toward personalized and technology-driven care, her contributions are poised to play an influential role. Her candidacy for any prestigious research award, including the Excellence in Research Award, is not only well justified but highly recommended. Her continued dedication to innovation, education, and societal impact makes her a beacon of research excellence in India and beyond.

Publications Top Notes

  • Title: Artificial intelligence-based automated detection of rheumatoid arthritis

  • Title: Computer-aided diagnosis of early-stage Retinopathy of Prematurity in neonatal fundus images using artificial intelligence
    Journal: Biomedical Physics and Engineering Express
    Year: 2025

  • Title: CNN Transformer for the Automated Detection of Rheumatoid Arthritis in Hand Thermal Images
    Citations: 1

  • Title: Artificial intelligence based real time colorectal cancer screening study: Polyp segmentation and classification using multi-house database
    Journal: Biomedical Signal Processing and Control
    Year: 2025
    Citations: 15

  • Title: Corrigendum: Early detection of Alzheimer’s disease in structural and functional MRI
    Journal: Frontiers in Medicine
    Year: 2024

  • Title: Design and Development of Portable Body Composition Analyzer for Children
    Journal: Diagnostics
    Year: 2024

  • Title: ADVANCING COLORECTAL POLYP DETECTION: AN AUTOMATED SEGMENTATION APPROACH WITH COLRECTSEG-UNET
    Authors: [Not specified]
    Journal: Biomedical Engineering Applications Basis and Communications
    Year: 2024
    Citations: 4

  • Title: Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques
    Journal: Scientific Reports
    Year: 2024
    Citations: 8

  • Title: Exploring Reduction Techniques for Graphene Oxide: A Comparative Study of Thermal and Chemical Methods
    Journal: Chemistry Select
    Year: 2024
    Citations: 1

  • Title: RA-XTNet: A Novel CNN Model to Predict Rheumatoid Arthritis from Hand Radiographs and Thermal Images: A Comparison with CNN Transformer and Quantum Computing
    Journal: Diagnostics
    Year: 2024
    Citations: 4

Mehdi Chemseddine FARAH | Engineering | Best Researcher Award

Assist. Prof. Dr. Mehdi Chemseddine FARAH | Engineering | Best Researcher Award

Telecommunications and Digital Signal Processing Laboratory, Djillali Liabes University, Sidi Bel Abbes, Algeria

Dr. FARAH Mehdi Chemseddine is a Lecturer Class B at the Telecommunications and Digital Signal Processing Laboratory, Djillali Liabes University, Sidi Bel Abbès, Algeria. He specializes in the design and optimization of microwave circuits, with a focus on microstrip technology. His research encompasses the development of compact and efficient microwave components such as hybrid couplers, power dividers, low-pass filters, and diplexers. Dr. Chemseddine has authored several publications in reputable journals, including the Journal of Circuits, Systems and Computers and Telecommunications and Radio Engineering. His work is characterized by innovative approaches to improving electrical performance, selectivity, and reducing the footprint of microwave devices. He has also participated in international conferences, presenting his research findings to the global scientific community. Dr. Chemseddine’s contributions to the field of telecommunications engineering demonstrate his commitment to advancing microwave circuit design and his potential as a leading researcher in this domain.

Professional Profile

Education

Dr. Chemseddine’s academic journey began with a Bachelor’s degree in Exact Sciences in 2008. He then pursued a License in Electrical Engineering, specializing in Communication Networks, which he completed in 2014. In 2016, he obtained a Master’s degree in High-Frequency Communication Systems from Djillali Liabes University. His academic pursuits culminated in earning a Ph.D. in Telecommunication Systems from the same university in 2022. Throughout his educational career, Dr. Chemseddine has demonstrated a strong foundation in electrical and communication engineering principles, which has been instrumental in his research endeavors. His academic background has equipped him with the necessary skills and knowledge to contribute significantly to the field of microwave circuit design.

Professional Experience

Dr. Chemseddine began his professional career as a Maître-Assistant Class B at the Faculty of Electrical Engineering, Department of Telecommunications, Djillali Liabes University, in 2023. In 2024, he was promoted to Maître-Conférence Class B at the same institution. His responsibilities include teaching undergraduate and graduate courses, supervising student research projects, and conducting his own research in microwave circuit design. Dr. Chemseddine has also completed internships, including one at the Hubert Curien Laboratory in Saint-Étienne, France, where he designed and implemented a microwave low-pass filter using planar technology. His professional experience reflects a commitment to both education and research in telecommunications engineering.

Research Interests

Dr. Chemseddine’s research interests are centered on the design and optimization of microwave circuits, particularly using microstrip technology. He focuses on developing compact, efficient, and cost-effective components such as hybrid couplers, power dividers, low-pass filters, and diplexers. His work aims to address challenges in electrical performance, selectivity, and device miniaturization. Dr. Chemseddine employs advanced simulation tools like HFSS and ADS to model and analyze microwave components, ensuring their practical applicability in telecommunications systems. His research contributes to the advancement of microwave engineering by providing innovative solutions for modern communication systems.

Research Skills

Dr. Chemseddine possesses a robust set of research skills in microwave circuit design and telecommunications engineering. He is proficient in using simulation and design tools such as HFSS (High-Frequency Structure Simulator), ADS (Advanced Design System), and MATLAB for modeling and analyzing microwave components. His expertise includes designing microstrip-based devices, optimizing their performance parameters, and validating their functionality through simulations and experimental measurements. Dr. Chemseddine’s skills enable him to develop innovative solutions that meet the demands of modern communication systems, emphasizing efficiency, compactness, and cost-effectiveness. His technical competencies are integral to his contributions to the field of microwave engineering.

Awards and Honors

While specific awards and honors are not detailed in the provided information, Dr. Chemseddine’s selection as a nominee for the Best Researcher Award at the International Research Awards on Science, Health, and Engineering underscores his recognition in the scientific community. His publications in reputable journals and presentations at international conferences further attest to his contributions and standing in the field of telecommunications engineering. These accomplishments reflect his dedication to research excellence and his potential for future accolades in his area of expertise.

Conclusion

Dr. FARAH Mehdi Chemseddine is an emerging researcher in the field of microwave circuit design and telecommunications engineering. His academic background, professional experience, and focused research interests have led to significant contributions in developing compact and efficient microwave components. Through his publications and conference presentations, he has demonstrated a commitment to advancing the field and addressing practical challenges in communication systems. Dr. Chemseddine’s proficiency in simulation tools and design methodologies positions him as a valuable contributor to both academic and industry-related projects. His nomination for the Best Researcher Award highlights his potential and the impact of his work in the scientific community.

Publications Top Notes

  1. Title: A Design of a Compact Microwave Diplexer in Microstrip Technology Based on Bandpass Filters Using Stepped Impedance Resonator
    Authors: M.C. Farah, F. Salah-Belkhodja, K. Khelil
    Journal: Journal of Microwaves, Optoelectronics and Electromagnetic Applications
    Year: 2022
    Citations: 6

  2. Title: A Novel Design of a Wilkinson Power Divider Based on the Circular-Shape Resonator
    Authors: R. El Bouslemti, C.M. Farah
    Journal: Frequenz, Vol. 78 (11-12), pp. 621–631
    Year: 2024
    Citations: 3

  3. Title: A Design of Microstrip Low-pass Filter Using Ground-Plane Coplanar Waveguide (GCPW)
    Authors: F.M. Chemseddine, E. Rahmouna, V. Didier
    Journal: Telecommunications and Radio Engineering
    Year: 2024
    Citations: 1

  4. Title: Design of Wilkinson Power Divider for Mobile and WLAN Applications
    Authors: M.C. Farah, F. Salah-Belkhodja
    Source: Proceedings of the International Conference for Pioneering and Innovative Technologies
    Year: 2023
    Citations: 1

  5. Title: A Design of Microstrip 180 Degree Hybrid Coupler Using T-Shape Structure for Monopulse Radar
    Authors: F.M. Chemseddine, S.B. Faouzi, F.Y. Hadj Aissa
    Journal: Journal of Circuits, Systems and Computers
    Year: 2025

  6. Title: Exploring Corrosion Behavior in Different Environments Using a Passive Microstrip Sensor
    Authors: R. El Bouslemti, M.C. Farah
    Journal: Communication Science et Technologie, Vol. 22 (1), pp. 7–17
    Year: 2024

  7. Title: Conception d’un Coupleur Microondes à Branches en Technologie Microstrip
    Authors: M.C. Farah, F. Salah-Belkhodja, Z. Kaldoune, A. Cheikh
    Journal: Communication Science et Technologie, Vol. 21 (1), pp. 13–33
    Year: 2023

  8. Title: Conception en Technologie Microstrip d’un Diplexeur Microondes Basé sur des Filtres à Saut d’Impédance
    Authors: F.M. Chemseddine
    Year: 2022

  9. Title: Conception en Technologie Microstrip d’un Diplexeur Microondes Basé sur des Filtres à Saut d’Impédance
    Authors: M.C. Farah, F. Salah-Belkhodja
    Year: 2022

Weiwei Bai | Engineering | Best Researcher Award

Assoc. Prof. Dr. Weiwei Bai | Engineering | Best Researcher Award

Associate Professor from Dalian Maritime University, China

Dr. Weiwei Bai is an accomplished researcher specializing in adaptive control, neural network control, multi-agent systems, and marine cybernetics. He earned his Ph.D. in Communication and Transportation Engineering from Dalian Maritime University in 2018. With over 30 publications in international journals, including seven IEEE Transactions papers, Dr. Bai has made significant contributions to the field. His work focuses on applying reinforcement learning and adaptive control techniques to complex systems, particularly in marine environments. Dr. Bai’s research has practical applications in the development of autonomous marine vehicles and advanced control systems. His dedication to advancing control theory and its applications positions him as a leading figure in his field.

Professional Profile​

Education

Dr. Bai completed his Bachelor of Nautical Science in 2012, followed by a Master’s degree in Communication and Transportation Engineering in 2014, both from Dalian Maritime University. He continued at the same institution to earn his Ph.D. in Communication and Transportation Engineering in 2018. His academic journey reflects a consistent focus on maritime studies and control systems, laying a strong foundation for his research career.

Professional Experience

Dr. Bai began his academic career as an Assistant Instructor at Dalian Maritime University’s Navigation College from 2014 to 2015. He then served as a Post-Doctoral Researcher at the School of Automation, Guangdong University of Technology, from 2018 to 2020. Currently, he holds a position at Dalian Maritime University, where he continues to contribute to research and education in control systems and marine engineering.​

Research Interests

Dr. Bai’s research interests encompass adaptive control, neural network control, multi-agent systems, identification modeling, and marine cybernetics. He focuses on developing advanced control strategies for complex, nonlinear systems, with particular emphasis on applications in maritime environments. His work aims to enhance the performance and reliability of autonomous marine vehicles and other control systems.​

Research Skills

Dr. Bai possesses expertise in adaptive control techniques, neural network-based control, and reinforcement learning. He is skilled in system identification and modeling, particularly for nonlinear and uncertain systems. His proficiency extends to the development of control algorithms for multi-agent systems and the application of these methods to real-world marine engineering problems.​

Awards and Honors

Dr. Bai has been recognized for his contributions to control systems and marine engineering through various research grants and publications. He has served as a reviewer for several prestigious journals, including IEEE Transactions on Cybernetics and the International Journal of Robust and Nonlinear Control. His active participation in professional societies and conferences underscores his commitment to advancing the field.​

Conclusion

Dr. Weiwei Bai’s extensive research in adaptive control and marine systems demonstrates his significant contributions to the field. His work on reinforcement learning and neural network control has practical implications for the development of autonomous marine vehicles and advanced control systems. Dr. Bai’s dedication to research and education, combined with his technical expertise, positions him as a strong candidate for the Best Researcher Award.​

Publications Top Notes

  1. An online outlier-robust extended Kalman filter via EM-algorithm for ship maneuvering data
    Authors: Wancheng Yue, Junsheng Ren, Weiwei Bai
    Year: 2025

  2. Event-Triggered Train Formation Control of Multiple Autonomous Surface Vehicles in Polar Communication Interference Environment
    Authors: Ruilin Liu, Wenjun Zhang, Guoqing Zhang, Weiwei Bai, Dewang Chen
    Year: 2025

  3. Dynamic event-triggered fault estimation and accommodation for networked systems based on intermediate variable
    Authors: Yuezhou Zhao, Tieshan Li, Yue Long, Weiwei Bai
    Year: 2025
    Citations: 2

  4. Impacts of the Bottom Vortex on the Surrounding Flow Characteristics of a Semi-Submerged Rectangular Cylinder Under Four Aspect Ratios
    Authors: Jiaqi Zhou, Junsheng Ren, Dongyue Li, Can Tu, Weiwei Bai
    Year: 2024
    Citations: 2