Felix Sadyrbaev | Applied Mathematics | Best Researcher Award

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Prof. Felix Sadyrbaev | Applied Mathematics | Best Researcher Award

Researcher at Institute of Mathematics and Computer Science, University of Latvia (LU MII abbreviated), Latvia

Professor Felix Sadyrbaev is a distinguished mathematician specializing in dynamical systems, boundary value problems, and mathematical modeling, particularly in network theory and gene regulatory networks. He earned his Ph.D. from Belorussian State University (1982) and completed his habilitation at Latvian State University (1995). Currently, he serves as the Head of Laboratory at the Institute of Mathematics and Computer Science, University of Latvia, and as a Professor and Director of the Doctorate Program in Mathematics at Daugavpils University. With over 190 scholarly publications and active participation in multiple International Congresses of Mathematicians, he has significantly contributed to mathematical research and education. A member of the Latvian and American Mathematical Societies, he also serves on editorial boards of international mathematical journals. Recognized for his contributions, he was elected a Full Member of the Academy of Sciences of Latvia in 2021, further solidifying his impact on the global mathematical community.

Professional Profile 

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Education

Professor Felix Sadyrbaev completed his undergraduate studies at Latvian State University (Riga, former USSR) and later pursued his Ph.D. in Mathematics at Belorussian State University (Minsk) in 1982. His doctoral research focused on dynamical systems, particularly boundary value problems and qualitative theory. In 1995, he earned his habilitation from Latvian State University, further advancing his expertise in mathematical modeling and optimization theory. His academic journey reflects a strong foundation in both theoretical and applied mathematics, enabling him to contribute significantly to various research domains. His education in leading institutions of the former USSR provided him with rigorous training in mathematical analysis, which has been instrumental in shaping his research career. Over the years, his academic background has allowed him to bridge different areas of mathematics, making significant contributions to network theory, gene regulatory networks, and mathematical optimization. His expertise continues to drive innovative research in applied and theoretical mathematics.

Professional Experience

Professor Sadyrbaev has had a distinguished career in academia and research spanning over four decades. Since 1978, he has been affiliated with the Institute of Mathematics and Computer Science at the University of Latvia, where he currently serves as the Head of Laboratory. In 1999, he joined Daugavpils University as a Professor and Director of the Doctorate Program in Mathematics, contributing significantly to the academic development of future researchers. His leadership roles have involved mentoring Ph.D. students, directing mathematical research initiatives, and fostering collaborations with international institutions. As an expert in dynamical systems and mathematical modeling, he has played a key role in advancing the field both locally and globally. His participation in international awards and research projects underscores his commitment to academic excellence. His long-standing association with multiple institutions highlights his dedication to fostering innovation, research collaboration, and the advancement of mathematical sciences.

Research Interest

Professor Sadyrbaev’s research interests lie in the areas of dynamical systems, boundary value problems, and mathematical modeling, with a strong focus on network theory and gene regulatory networks. His work in qualitative theory and optimization has been instrumental in advancing mathematical methods for solving complex real-world problems. He has contributed significantly to differential equations, stability analysis, and nonlinear dynamics, providing insights into critical mathematical frameworks. His interdisciplinary approach bridges applied mathematics, computational techniques, and theoretical modeling, making his research highly relevant across various scientific domains. His contributions to mathematical modeling in biology and engineering have led to significant applications, particularly in understanding complex network systems. With over 190 publications and numerous plenary talks, his research has influenced both academia and industry. His ongoing work continues to explore innovative mathematical methods for solving contemporary challenges, reinforcing his impact on the global mathematical community.

Awards and Honors

Professor Sadyrbaev has received prestigious recognition for his outstanding contributions to mathematics. In 2021, he was elected a Full Member of the Academy of Sciences of Latvia, a testament to his significant impact on mathematical research and education. His participation in major International Congresses of Mathematicians (ICM) across different countries, including Berlin, Beijing, Bangalore, Seoul, and São Paulo, highlights his global academic influence. He has also served as a delegate to the International Mathematical Union (IMU) General Assembly, representing the Latvian Mathematical Society in key international discussions. Additionally, he is a member of the Latvian Mathematical Society and the American Mathematical Society, further cementing his standing in the international mathematical community. His editorial board memberships in several international mathematical journals reflect his role in shaping contemporary mathematical research. His numerous honors underscore his dedication to advancing mathematical sciences through research, mentorship, and academic leadership.

Conclusion

Professor Felix Sadyrbaev is a highly accomplished mathematician with extensive contributions to dynamical systems, mathematical modeling, and network theory. His distinguished career spans over four decades, with significant roles in research, academic leadership, and international collaborations. His election as a Full Member of the Academy of Sciences of Latvia, numerous publications, and participation in prestigious international congresses solidify his reputation as a leading expert in his field. His influence extends beyond research, as he plays a key role in mentoring future mathematicians and fostering interdisciplinary collaborations. As a respected figure in the mathematical community, his work continues to shape contemporary mathematical theory and applications. Through his editorial roles, award participation, and research impact, he remains a driving force in the advancement of mathematical sciences. His remarkable career serves as an inspiration for young researchers and highlights the importance of mathematics in solving real-world challenges.

Publications Top Noted

  • On differential equations with exponential nonlinearities

    • Authors: Armands Gritsans, Felix Sadyrbaev
    • Year: 2025
    • Source: Applied Numerical Mathematics

  • Remarks on Modeling of Neural Networks

    • Authors: Felix Sadyrbaev
    • Year: [No year mentioned]
    • Source: [No source information available]

  • In Search of Chaos in Genetic Systems

    • Authors: Olga Kozlovska, Felix Sadyrbaev
    • Year: 2024
    • Source: Chaos Theory and Applications

  • Comparative Analysis of Models of Genetic and Neuronal Networks

    • Authors: Diana Ogorelova, Felix Sadyrbaev
    • Year: 2024
    • Source: Mathematical Modelling and Analysis

  • Editorial: Mathematical modeling of gene networks

    • Authors: Jacques François Demongeot, Felix Sadyrbaev, Inna Samuilik
    • Year: 2024
    • Source: Frontiers in Applied Mathematics and Statistics

  • On Period Annuli and Induced Chaos

    • Authors: Svetlana Atslega, Olga Kozlovska, Felix Sadyrbaev
    • Year: 2024
    • Source: WSEAS Transactions on Systems

  • A New 3D Chaotic Attractor in Gene Regulatory Network

    • Authors: Olga Kozlovska, Felix Sadyrbaev, Inna Samuilik
    • Year: 2024
    • Source: Mathematics

  • On Solutions of the Third-Order Ordinary Differential Equations of Emden-Fowler Type

    • Authors: Felix Sadyrbaev
    • Year: 2023
    • Source: Dynamics

  • On Coexistence of Inhibition and Activation in Genetic Regulatory Networks

    • Authors: Felix Sadyrbaev, Valentin Sengileyev, Albert Silvans
    • Year: [No year mentioned]

 

Halima Bensmail | Applied Mathematics | Best Researcher Award

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Prof. Dr. Halima Bensmail | Applied Mathematics | Best Researcher Award

Principal scientist at Qatar Computing Research Institute, Qatar

Dr. Halima Bensmail is a distinguished Principal Scientist at the Qatar Computing Research Institute, specializing in machine learning, bioinformatics, biostatistics, and statistical modeling. With a Ph.D. in Statistics (Summa Cum Laude) from the University Pierre & Marie Curie, she has made significant contributions to Bayesian inference, multivariate analysis, and precision medicine. She has an impressive research record with an H-index of 31, i10-index of 54, and around 140 publications in prestigious journals such as Nature Communications, JASA, and IEEE TNNLS. As the founder of the Statistical Machine Learning and Bioinformatics group at QCRI, she has led groundbreaking projects, including the development of open-source data-driven tools like the PRISQ pre-diabetes screening model and MCLUST clustering algorithm. With extensive academic experience in the USA, France, and the Netherlands, she has mentored numerous postdocs and students, shaping the next generation of researchers. Her expertise and leadership make her a key figure in data science and precision health.

Professional Profile 

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Education

Dr. Halima Bensmail holds a Ph.D. in Statistical Machine Learning (Summa Cum Laude) from the University Pierre & Marie Curie (Paris 6), where she specialized in Bayesian inference, spectral decomposition, and mixture models. Her thesis focused on deterministic and Bayesian model-based clustering and classification for data science applications. Prior to that, she earned an M.S. in Machine Learning from the same university, with a focus on probability, financial modeling, and stochastic processes. She also holds a Bachelor’s degree in Applied Mathematics and Statistics from the University Mohammed V in Morocco, where she gained expertise in numerical analysis, stochastic processes, topology, and mathematical programming. Throughout her academic journey, she was mentored by esteemed professors and developed a strong foundation in theoretical and applied statistics. Her educational background has laid the groundwork for her pioneering research in machine learning, bioinformatics, and data-driven modeling for real-world applications.

Professional Experience

Dr. Bensmail is currently a Principal Scientist at the Qatar Computing Research Institute (QCRI), where she leads research in bioinformatics, statistical machine learning, and artificial intelligence. She also serves as a Full Professor in the College of Science and Engineering at Hamad Bin Khalifa University and a Visiting Full Professor at Texas A&M University at Qatar. Previously, she held tenured faculty positions at Virginia Medical School and the University of Tennessee, where she contributed significantly to public health and business administration research. She has also worked as a Research Scientist at the University of Leiden, a scientist at the Fred Hutchinson Cancer Research Center, and a postdoctoral researcher at the University of Washington. With decades of experience across academia and research institutions in the U.S., Europe, and the Middle East, she has built expertise in developing statistical and AI-driven solutions for biomedical and computational challenges.

Research Interests

Dr. Bensmail’s research spans statistical machine learning, bioinformatics, and precision medicine. She has developed novel clustering algorithms, such as an advanced Bayesian clustering model implemented in the MCLUST package, and statistical methods for analyzing Next-Generation Sequencing (NGS) data. She is also interested in computational biology, specifically protein-protein interactions, protein solubility, and structural biology. Her work includes dimensionality reduction techniques like nonnegative matrix factorization and discriminative sparse coding for domain adaptation. In the field of precision medicine, she has designed PRISQ, a statistical model for pre-diabetes screening. Her broader interests include Bayesian statistics, functional data analysis, information theory, and high-dimensional data modeling. With a strong focus on developing real-world data-driven tools, she actively contributes to statistical methodologies that enhance decision-making in medicine, genomics, and artificial intelligence applications.

Awards and Honors

Dr. Bensmail has received numerous accolades for her contributions to machine learning, bioinformatics, and statistical modeling. Her work has been widely recognized, with over 140 peer-reviewed publications and an H-index of 31, demonstrating the impact of her research. She has secured research grants and led major projects in AI-driven healthcare solutions. Her contributions to the field have been acknowledged through invitations to serve as a keynote speaker at international awards and as an editorial board member for high-impact journals. She has also been instrumental in mentoring young researchers, postdoctoral fellows, and doctoral students, fostering the next generation of scientists in AI, statistics, and bioinformatics. Additionally, her work on statistical methods for precision medicine and biomedical informatics has gained international recognition, positioning her as a leading expert in the field of data science for healthcare and computational biology.

Conclusion

Dr. Halima Bensmail is a pioneering researcher in machine learning, statistical modeling, and bioinformatics, with a career spanning leading institutions in the U.S., Europe, and the Middle East. Her contributions to clustering algorithms, high-dimensional data analysis, and precision medicine have made a lasting impact on the fields of AI and computational biology. As a mentor and leader, she has shaped numerous young scientists and postdocs, driving innovation in data science applications. With a robust publication record, influential research projects, and a dedication to developing real-world AI-driven solutions, she stands as a leading figure in statistical machine learning. Her expertise and contributions continue to push the boundaries of knowledge in bioinformatics, artificial intelligence, and healthcare analytics, making her a strong candidate for prestigious research awards and recognition in scientific communities worldwide.

Publications Top Noted

 

Saif Ur Rehman | Applied Mathematics | Best Researcher Award

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Dr. Saif Ur Rehman | Applied Mathematics | Best Researcher Award

Research Assistant at Consiglio Nazionale delle Ricerche (CNR), Genoa, Italy, Pakistan.

Saif Ur Rehman is a dedicated researcher in Computational Fluid Dynamics (CFD), Numerical Analysis, and Partial Differential Equations, with a strong academic and research background. He has worked as a Research Assistant at the National Research Council, Italy, and previously at the University of Calabria, Italy, and the University of Management and Technology, Pakistan. His research focuses on nanofluid dynamics, MHD flows, bioconvection, and heat transfer, leading to multiple Q1 and Q2 publications in high-impact journals such as Nanomaterials, Mathematics, and Waves in Random and Complex Media. He has received merit-based scholarships and a Research Publication Award, demonstrating his academic excellence. Additionally, he possesses strong technical skills in Python, MATLAB, C++, and LaTeX, aiding in his numerical modeling research. With international research exposure and a growing publication record, Saif Ur Rehman is an emerging scholar in applied mathematics, aiming to expand his contributions to mathematical modeling and computational sciences.

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Education

Saif Ur Rehman holds a Master of Science in Mathematics from the University of Management and Technology, Lahore, Pakistan (2019–2021), where he specialized in Advanced Numerical Analysis, Fluid Dynamics, and Differential Equations. His master’s thesis focused on the MHD Williamson Nanofluid Flow over a Slender Elastic Sheet in the Presence of Bioconvection. Before this, he earned a Bachelor of Science in Mathematics from Government College University, Faisalabad (2015–2019), securing a 3.55/4.00 GPA. His undergraduate studies included Fluid Mechanics, Numerical Analysis, Real and Complex Analysis, and C++ Programming, laying a strong foundation for his research in computational mathematics. Throughout his academic journey, he received multiple merit-based scholarships, including the Punjab Education Endowment Fund Scholarship (PEEF) and a fully funded master’s scholarship, reflecting his dedication and academic excellence. His education has equipped him with expertise in mathematical modeling, numerical simulations, and applied mathematics, which he continues to explore in his research.

Professional Experience

Saif Ur Rehman has gained extensive research experience through multiple roles at renowned international institutions. He is currently a Research Assistant at the National Research Council, Genoa, Italy (2024–Present), working on Optimal Robust Shape Control for Distributed Parameter Systems. Previously, he was a University Research Assistant at the University of Calabria, Italy (2023–2024), focusing on applications of heat and mass transfer. His earlier role as a Research Assistant at the University of Management and Technology, Pakistan (2021–2023) involved a major research project on Numerical Methods for Partial Differential Equations, where he contributed to multiple high-impact publications. Alongside research, he worked as a Visiting Lecturer in Mathematics (2021–2022), teaching Calculus, Linear Algebra, Fluid Dynamics, and Numerical Analysis at the undergraduate level. His professional experience demonstrates his ability to conduct applied mathematics research, develop numerical solutions, and contribute to theoretical and computational fluid dynamics.

Research Interest

Saif Ur Rehman’s research is deeply rooted in Computational Fluid Dynamics (CFD), Numerical Analysis, and Partial Differential Equations (PDEs), with a strong focus on heat and mass transfer, MHD flows, and bioconvection. He has extensively studied the dynamics of nanofluids, micropolar fluids, and dusty fluids under various physical constraints, contributing significantly to theoretical and computational modeling in applied mathematics. His work integrates Artificial Neural Networks (ANNs) and Machine Learning techniques to enhance numerical simulations and solve complex mathematical physics problems. His research contributions, published in Q1 and Q2 impact factor journals, cover topics such as the effects of Lorentz and Coriolis forces, Darcy–Forchheimer flow models, and stability analysis of fluid flows. With expertise in Python, MATLAB, C++, and LaTeX, he continues to explore innovative numerical methods for solving real-world mathematical problems, aiming to bridge the gap between theory and industrial applications.

Awards and Honors

Saif Ur Rehman has received multiple scholarships and research excellence awards in recognition of his academic achievements. He was honored with the Research Publication Award (2022) at the University of Management and Technology, Pakistan, for his outstanding contributions to applied mathematics research. His academic journey has been supported by fully funded merit-based scholarships, including the Punjab Education Endowment Fund Scholarship (PEEF) during his bachelor’s studies and a fully funded master’s scholarship for his postgraduate studies. Additionally, he was awarded a Prime Minister’s Laptop under the Government of Pakistan’s Higher Education Initiative, recognizing his academic excellence. Beyond research, he has demonstrated leadership and management skills, serving as a class representative throughout his bachelor’s studies and actively participating in academic societies and awards. His awards reflect his dedication to mathematical research, academic excellence, and contributions to the global scientific community.

Conclusion

Saif Ur Rehman is an emerging researcher in Computational Fluid Dynamics, Numerical Analysis, and Partial Differential Equations, with a strong academic background and international research exposure. His work in nanofluid dynamics, MHD flows, and heat transfer has resulted in high-impact publications and significant contributions to applied mathematics. His expertise in Python, MATLAB, and numerical modeling techniques has strengthened his research capabilities. Having worked at renowned institutions in Italy and Pakistan, he has gained experience in both theoretical and applied research, positioning himself as a promising scholar in mathematical modeling and computational sciences. His awards, scholarships, and research achievements demonstrate his dedication to scientific innovation. Moving forward, he aims to further his research in numerical simulations, machine learning applications in CFD, and advanced mathematical modeling, contributing to both academic advancements and real-world engineering applications.

Publications Top Noted

  • Title: Insight into significance of bioconvection on MHD tangent hyperbolic nanofluid flow of irregular thickness across a slender elastic surface

    • Authors: MZ Ashraf, SU Rehman, S Farid, AK Hussein, B Ali, NA Shah, W Weera
    • Year: 2022
    • Citations: 92
    • Source: Mathematics, 10(15), 2592

  • Title: Numerical computation of buoyancy and radiation effects on MHD micropolar nanofluid flow over a stretching/shrinking sheet with heat source

    • Authors: SU Rehman, A Mariam, A Ullah, MI Asjad, MY Bajuri, BA Pansera, et al.
    • Year: 2021
    • Citations: 86
    • Source: Case Studies in Thermal Engineering, 25, 100867

  • Title: Micropolar dusty fluid: Coriolis force effects on dynamics of MHD rotating fluid when Lorentz force is significant

    • Authors: Q Lou, B Ali, SU Rehman, D Habib, S Abdal, NA Shah, JD Chung
    • Year: 2022
    • Citations: 84
    • Source: Mathematics, 10(15), 2630

  • Title: The Casson dusty nanofluid: Significance of Darcy–Forchheimer law, magnetic field, and non-Fourier heat flux model subject to stretch surface

    • Authors: SU Rehman, N Fatima, B Ali, M Imran, L Ali, NA Shah, JD Chung
    • Year: 2022
    • Citations: 72
    • Source: Mathematics, 10(16), 2877

  • Title: MHD Williamson nanofluid flow over a slender elastic sheet of irregular thickness in the presence of bioconvection

    • Authors: F Wang, MI Asjad, SU Rehman, B Ali, S Hussain, TN Gia, T Muhammad
    • Year: 2021
    • Citations: 63
    • Source: Nanomaterials, 11(9), 2297

  • Title: Significance of dust particles, nanoparticles radius, Coriolis and Lorentz forces: The case of Maxwell dusty fluid

    • Authors: Y Wei, SU Rehman, N Fatima, B Ali, L Ali, JD Chung, NA Shah
    • Year: 2022
    • Citations: 36
    • Source: Nanomaterials, 12(9), 1512

  • Title: Computational analysis for bioconvection of microorganisms in Prandtl nanofluid Darcy–Forchheimer flow across an inclined sheet

    • Authors: J Wang, Z Mustafa, I Siddique, M Ajmal, MMM Jaradat, SU Rehman, B Ali, et al.
    • Year: 2022
    • Citations: 23
    • Source: Nanomaterials, 12(11), 1791

  • Title: First solution of fractional bioconvection with power law kernel for a vertical surface

    • Authors: MI Asjad, S Ur Rehman, A Ahmadian, S Salahshour, M Salimi
    • Year: 2021
    • Citations: 18
    • Source: Mathematics, 9(12), 1366

  • Title: Dynamics of Eyring–Powell nanofluids when bioconvection and Lorentz forces are significant: The case of a slender elastic sheet of variable thickness with porous medium

    • Authors: A Manan, SU Rehman, N Fatima, M Imran, B Ali, NA Shah, JD Chung
    • Year: 2022
    • Citations: 13
    • Source: Mathematics, 10(17), 3039

  • Title: Hydrodynamical study of couple stress fluid flow in a linearly permeable rectangular channel subject to Darcy porous medium and no-slip boundary conditions

    • Authors: M Ishaq, SU Rehman, MB Riaz, M Zahid
    • Year: 2024
    • Citations: 10
    • Source: Alexandria Engineering Journal, 91, 50-69

 

DEEPA R | Computational Mathematics | Women Researcher Award

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Dr. DEEPA R | Computational Mathematics | Women Researcher Award

Professor at Nehru Institute of Engineering and Technology, India

Dr. R. Deepa is a distinguished academic leader and researcher in Electronics and Communication Engineering with extensive expertise in next-generation communication systems, signal processing, and AI-driven healthcare. Serving as the Head of Academic Affairs and Director of IQAC, she has been instrumental in driving strategic accreditation, curriculum innovation, and research excellence. She has secured multiple research grants, holds patents in advanced sensor and medical technologies, and has an impressive portfolio of Q1 and Q2 journal publications. Her contributions extend to industry collaborations, editorial board memberships, and faculty upskilling programs. Recognized with prestigious awards, including the United Nations Award for Human Excellence in Education, Dr. Deepa actively mentors doctoral scholars and champions student entrepreneurship initiatives. With a forward-thinking approach, she continues to shape academic policies, foster interdisciplinary research, and bridge the gap between academia and industry, making a significant impact on education and technological advancements.

Professional Profile 

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Education

Dr. R. Deepa holds a Ph.D. in Information & Communication Engineering from Anna University, Chennai, awarded in March 2013. Her dissertation focused on “Certain Investigations on Power Allocation Schemes for Transmission of JPEG Compressed Images Using MIMO-OFDM Systems,” under the guidance of Dr. K. Baskaran. She earned her Master of Engineering (M.E.) in Communication Systems from PSG College of Technology, Coimbatore, in June 2002, where she worked on the implementation of a USB device controller for her thesis. She completed her Bachelor of Engineering (B.E.) in Electronics & Communication Engineering from Sri Ramakrishna Engineering College, Coimbatore, in March 2000, with a thesis on the speed control of a DC motor using fuzzy logic. Dr. Deepa’s strong academic foundation in communication systems, signal processing, and emerging technologies has paved the way for her extensive contributions to research, innovation, and academic leadership in higher education institutions.

Professional Experience

Dr. R. Deepa is a distinguished academician and researcher with extensive experience in electronics and communication engineering. Currently serving as the Head of Academics, Director of IQAC, and Professor at the Nehru Institute of Engineering and Technology, she has played a pivotal role in academic leadership, quality assurance, and curriculum innovation. With a career spanning over two decades, she has held key positions, including Professor & Head at Nehru Institute of Technology and Assistant Professor at Amrita Vishwa Vidyapeetham. Her expertise lies in strategic academic planning, research promotion, and skill development in AI, IoT, and Industry 4.0 technologies. She has been instrumental in fostering student engagement, industry collaboration, and entrepreneurship through initiatives like NGI-TBI and NewGen IEDC. Additionally, she has served as a mentor, consultant, and editorial board member, contributing significantly to institutional growth, research advancements, and the holistic development of students and faculty.

Research Interest

Dr. R. Deepa’s research interests span next-generation communication systems, signal processing algorithms, and AI-driven healthcare. Her work focuses on advancing MIMO-OFDM systems, adaptive power allocation, and channel equalization techniques to enhance wireless communication efficiency. She explores artificial intelligence applications in medical diagnostics, particularly in early detection of diseases such as skin cancer, cardiovascular conditions, and diabetic retinopathy. Her research also includes AI-driven predictive analytics for market trends, UAV-based beamforming optimization, and blockchain-based cybersecurity frameworks for IoT networks. With numerous publications in reputed journals, she has contributed significantly to the intersection of communication engineering and intelligent systems. Additionally, her patents and funded projects reflect her commitment to developing real-world solutions, including assistive devices for the visually impaired and AI-powered medical instruments. Through her multidisciplinary approach, Dr. Deepa aims to bridge technological advancements with societal impact, fostering innovation in healthcare, cybersecurity, and wireless communication.

Award and Honor

Dr. R. Deepa has been recognized for her outstanding contributions to academia, research, and innovation through numerous prestigious awards and honors. She received a United Nations Award for Human Excellence in Education and Humanitarian Works (2018) and the NGI Women Excellence Award (2024) for her exceptional leadership in education. Her dedication to research and innovation was acknowledged with multiple research grants, including ₹10 lakhs from the Ministry of Consumer Affairs, India (2024) and ₹2.5 lakhs from NewGEN IEDC, DST, New Delhi (2022) for her startup idea “INTELLILENS.” She was also honored as an Advanced Institute Ambassador under the Institute Innovation Council (2025) and serves as a mentor for the Coimbatore BIS Standards Club, Ministry of Consumer Affairs, India (2024). Additionally, she holds editorial positions in esteemed journals, including being an Editorial Board Member of Math Scientist Awards (2025) and an Editor for Inderscience Journal Special Issues (2016).

Conclusion

Dr. R. Deepa is a distinguished academician, researcher, and leader in electronics and communication engineering, with a strong commitment to academic excellence, research innovation, and institutional quality enhancement. Her extensive experience in academic governance, curriculum development, and research promotion has significantly contributed to the advancement of higher education. She has secured multiple research grants, published extensively in reputed journals, and actively contributed as an editor and reviewer for leading scientific publications. Her expertise in next-generation communication systems, AI-driven healthcare, and signal processing has led to impactful innovations, including patents and consultancy roles in industry collaborations. Dr. Deepa’s dedication to student development, skill enhancement, and fostering research culture is evident in her leadership of various institutional initiatives. With numerous accolades, including the United Nations Award for Human Excellence in Education, she continues to shape the future of academia with her visionary approach and unwavering commitment to excellence.

Publications Top Noted

  • Division Multiplexing System Using Arithmetic Optimization Algorithm
    • Authors: R Deepa, R Karthick, J Velusamy, R Senthilkumar
    • Year: 2025
    • Citations: 31
  • Study of Spatial Diversity Schemes in Multiple Antenna Systems
    • Authors: R Deepa, K Baskaran, P Unnikrishnan, A Kumar
    • Year: 2009
    • Citations: 20
  • Healthcare’s New Frontier: AI-driven Early Cancer Detection for Improved Well-being
    • Authors: R Deepa, S Arunkumar, V Jayaraj, A Sivasamy
    • Year: 2023
    • Citations: 8
  • Patient Counselling at Aravind Eye Hospital
    • Authors: R Deepa, P Pradhan
    • Year: 2002
    • Citations: 8
  • Advancements in Early Detection of Diabetes and Diabetic Retinopathy Screening Using Artificial Intelligence
    • Authors: DAS Dr. R. Deepa
    • Year: 2023
    • Citations: 7
  • Performance Analysis of Decoding Algorithms in Multiple Antenna Systems
    • Authors: I Ammu, R Deepa
    • Year: 2011
    • Citations: 6
  • Performance of Possible Combinations of Detection Schemes with V-BLAST for MIMO OFDM Systems
    • Authors: R Deepa, S Iswarya, G DivyaShri, P MahathiKeshav, P JaganyaVasan
    • Year: IEEE
    • Citations: 6
  • MIMO Based Efficient JPEG Image Transmission and Reception by Multistage Receivers
    • Authors: R Deepa, K Baskaran
    • Year: 2010
    • Citations: 5
  • Early Detection of Skin Cancer Using AI: Deciphering Dermatology Images for Melanoma Detection
    • Authors: Dr. Deepa Rangasamy
    • Year: 2024
    • Citations: 3