Fan Yang | Computational Mathematics | Best Researcher Award

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Prof. Fan Yang | Computational Mathematics | Best Researcher Award

Professor at Lanzhou University of Technology, China

Professor Fan Yang 🎓, born in April 1976, is a distinguished mathematician at the School of Science, Lanzhou University of Technology, China. With a solid academic foundation—earning his B.Sc., M.Sc., and Ph.D. from Lanzhou University—he has emerged as a notable expert in inverse problems 🔍 and fractional diffusion equations 🌐. His research contributions span over 14 impactful publications in internationally recognized journals, showcasing innovative regularization techniques like Tikhonov, mollification, and quasi-boundary methods 🧮. His work significantly enhances computational stability in solving complex physical models, particularly heat and Poisson equations 🔥➕. Professor Yang collaborates closely with scholars like Chu-Li Fu and Xiao-Xiao Li, reflecting his team-driven approach and scientific synergy 🤝. While his global visibility could be further amplified, his technical depth, precision, and dedication place him among the front-runners in applied mathematics. A trailblazer in mathematical physics, Prof. Yang continues to illuminate intricate problems with clarity and rigor ✨.

Professional Profile 

Scopus Profile
ORCID Profile

📘 Education

Professor Fan Yang 🎓 embarked on his academic path at Lanzhou University, a premier institution in China 🇨🇳. He obtained his Bachelor’s degree in Mathematics in 2000, deepening his analytical foundations. Committed to advancing knowledge, he earned his Master’s degree in 2007 and later achieved his Doctoral degree in 2014, specializing in mathematical physics equations. This progressive academic journey illustrates a firm dedication to mathematical excellence 📐. His scholarly roots at Lanzhou University equipped him with the skills to explore abstract theories and practical modeling 🧠. The consistent pursuit of higher education across nearly 15 years showcases his unwavering commitment to mastering complexity and innovation. His academic development has been vital in shaping him into a respected voice within the mathematical research community 🔍.

💼 Professional Experience

Professor Fan Yang currently holds a prestigious role at the School of Science, Lanzhou University of Technology 🏫, where he serves as a full professor. With a career rooted in academia, he has accumulated decades of teaching, mentorship, and research leadership 📊. Over the years, he has played a central role in guiding both undergraduate and postgraduate students, helping nurture the next generation of mathematical minds 👨‍🏫. His collaborative efforts with other scholars and his role in departmental research initiatives reflect his deep integration into academic life 🧩. Prof. Yang’s dedication to fostering scientific thought and problem-solving capacity makes him a pillar of his department. His evolving role from student to faculty leader exemplifies his rise through perseverance, expertise, and scholarly drive 🚀.

🔬 Research Interest

Prof. Fan Yang’s research orbits around inverse problems and fractional diffusion equations, niche yet powerful areas within applied mathematics 🧠. His work primarily addresses ill-posed problems in mathematical physics, especially those modeling heat and source detection phenomena 🔥🧊. His innovative application of regularization techniques—such as Tikhonov, truncation, and mollification—enhances stability and solution accuracy in computational models. He focuses on determining unknown parameters from partial data, contributing solutions to real-world problems in geophysics, medical imaging, and thermal analysis 🌍💡. This niche research supports the broader scientific community in understanding and interpreting complex systems. With publications in high-impact journals and a track record of meaningful inquiry, Prof. Yang continues to redefine mathematical boundaries, blending theory and application in impactful, forward-thinking ways 📈🔎.

🏅 Awards and Honors

Though specific awards and honors are not listed in detail, Professor Fan Yang’s academic recognition is evident through consistent publications in reputable international journals 📰. Journals such as Applied Mathematical Modelling, Journal of Inverse and Ill-Posed Problems, and Computational and Applied Mathematics have showcased his findings, underscoring the scholarly value of his work 🏆. His research has earned collaboration with distinguished mathematicians, a subtle indicator of peer recognition and respect 🤝. Serving as a professor at a top Chinese university further indicates institutional acknowledgment of his contributions 🎖️. While formal accolades may not be detailed here, Prof. Yang’s enduring presence in high-level research forums and his intellectual influence make him a quiet achiever whose work speaks volumes through citations and scholarly impact 🌟.

📌 Conclusion

Professor Fan Yang is a dedicated scholar whose academic path, professional evolution, and focused research agenda reflect a life devoted to scientific advancement 🔭. From tackling complex inverse problems to refining numerical solutions for fractional equations, his work resonates across mathematical physics and engineering realms 🌐. With a foundation built at Lanzhou University and a professorship at Lanzhou University of Technology, his influence continues to grow 📘💡. While he may remain understated in accolades, his scholarly contributions are undeniable—spanning critical journals and collaborative research 🧩. Prof. Yang exemplifies how dedication, precision, and thoughtful inquiry can shape the modern mathematical landscape. As a thinker, mentor, and innovator, he is undoubtedly a valuable figure in advancing computational mathematics and applied sciences 💫🧮.

Publications Top Notes

🔹 Title: Simultaneous Inversion of the Source Term and Initial Value of the Multi-Term Time Fractional Slow Diffusion Equation
Authors: L. Qiao, R. Li, Fan Yang, X. Li
Year: 2025 🗓️
Journal: Journal of Applied Analysis and Computation 🏫📚

🔹 Title: Fractional Landweber Regularization Method for Identifying the Source Term of the Time Fractional Diffusion-Wave Equation
Authors: Z. Liang, Q. Jiang, Q. Liu, L. Xu, Fan Yang
Year: 2025 🗓️
Journal: Symmetry 📐📚

🔹 Title: PINN Neural Network Method for Solving the Forward and Inverse Problem of Time-Fractional Telegraph Equation
Authors: Fan Yang, H. Liu, X. Li, J. Cao
Year: 2025 🗓️
Citations: 2 📚
Journal: Results in Engineering ⚙️

🔹 Title: Two Regularization Methods for Identifying the Initial Value of Time-Fractional Telegraph Equation
Authors: Y. Liang, Fan Yang, X. Li
Year: 2025 🗓️
Citations: 2 📚
Journal: Computational Methods in Applied Mathematics 📊

🔹 Title: Two Regularization Methods for Identifying the Unknown Source of Sobolev Equation with Fractional Laplacian
Authors: Fan Yang, L.L. Yan, H. Liu, X. Li
Year: 2025 🗓️
Citations: 4 📚
Journal: Journal of Applied Analysis and Computation 🏫

🔹 Title: Two Regularization Methods for Identifying the Source Term of Caputo-Hadamard Type Time Fractional Diffusion-Wave Equation
Authors: Fan Yang, R. Li, Y. Gao, X. Li
Year: 2025 🗓️
Journal: Journal of Inverse and Ill-Posed Problems 🔄📚

🔹 Title: Effect of Surface Effect on Linear Bending Behavior of Nano-Switch Structure
Authors: Fan Yang, X. Wang, C. Li
Year: 2024 🗓️
Journal: Yingyong Lixue Xuebao (Chinese Journal of Applied Mechanics) 🔧📚

🔹 Title: Simultaneous Identification of the Unknown Source Term and Initial Value for the Time Fractional Diffusion Equation with Local and Nonlocal Operators
Authors: L. Qiao, Fan Yang, X. Li
Year: 2024 🗓️
Citations: 3 📚
Journal: Chaos, Solitons and Fractals 🌀

🔹 Title: Analysis of Nonlinear Bending Behavior of Nano-Switches Considering Surface Effects
Authors: Fan Yang, X. Wang, X. Song, W. Yang
Year: 2024 🗓️
Journal: Discover Nano 🔬📚

Raja Rani Titti | Applied Mathematics | Best Researcher Award

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Dr. Raja Rani Titti | Applied Mathematics | Best Researcher Award

Deputy Head of FPD at Military Technological College, Oman

Dr. T Raja Rani is a distinguished researcher and academician with extensive contributions to mathematics, artificial intelligence, IoT, and biomedical engineering. With 65 research papers, a book published by Taylor & Francis (CRC Press, UK), and multiple international award presentations, she has established herself as a leader in her field. She has served as a reviewer and editorial board member for reputed journals and has supervised PhD scholars and student research projects. As the Principal Investigator for government-funded projects from the Ministry of Higher Education and Ministry of Defence, she has led innovative studies in AI-driven healthcare and smart automation. She has also held key academic roles, contributing to institutional research development. Recognized for her interdisciplinary expertise and global collaborations, Dr. Raja Rani is a strong candidate for the Best Researcher Award, with future potential in high-impact publications, industry partnerships, and international research funding.

Professional Profile

Google Scholar
ORCID Profile

Education

Dr. T Raja Rani holds a strong academic background in mathematics and computational sciences, equipping her with expertise in applied mathematics, artificial intelligence, and IoT-based systems. She earned her degrees from prestigious institutions, specializing in differential equations, machine learning applications, and biomedical engineering research. Her academic journey has been marked by a passion for interdisciplinary research, combining theoretical and practical knowledge to address complex real-world challenges. With a commitment to continuous learning, she has also actively participated in professional development programs, workshops, and research collaborations to enhance her expertise. Her educational foundation has played a crucial role in shaping her research contributions, enabling her to publish high-quality journal articles, lead innovative projects, and mentor students in advanced research fields. Dr. Raja Rani’s dedication to academia and research has made her a respected scholar in her domain, contributing significantly to advancements in mathematical modeling, AI, and IoT applications.

Professional Experience

Dr. T Raja Rani has an extensive academic and research career spanning over two decades in reputed institutions across India and Oman. She has served as a lecturer, associate professor, and research coordinator, contributing to curriculum development, student mentorship, and institutional research initiatives. She worked at Military Technological College, Higher College of Technology, and Ibri College of Technology in Oman, where she played a pivotal role in mathematics program coordination, research development, and quality assurance. She has also contributed as an interview panelist for academic recruitment and has mentored several undergraduate and PhD scholars in AI-driven biomedical and IoT projects. In addition, she has actively participated in international awards, journal editorial boards, and funded research projects. Her career is marked by a dedication to bridging the gap between theoretical research and practical applications, making her an invaluable contributor to academia and industry collaborations.

Research Interest

Dr. T Raja Rani’s research interests lie at the intersection of applied mathematics, artificial intelligence, IoT, and biomedical engineering. She specializes in differential equations, machine learning algorithms, and computational modeling, applying these techniques to solve real-world problems in healthcare, automation, and smart city infrastructure. Her work explores AI-driven predictive analytics for medical diagnosis, IoT-based automation systems, and mathematical simulations for engineering applications. She has led multiple interdisciplinary projects, including the development of IoT-based home automation, hydroponic farming solutions, and AI models for cardiovascular disease prediction. Her passion for cutting-edge research is reflected in her numerous publications, book authorship, and government-funded projects. By integrating AI and mathematics, she aims to develop smart, efficient, and sustainable solutions for various industries. Moving forward, she seeks to expand her research into high-impact AI applications, industry collaborations, and global research partnerships to further drive technological innovation.

Awards and Honors

Dr. T Raja Rani has received significant recognition for her research contributions, academic leadership, and interdisciplinary expertise. She has authored 65+ research papers in reputed international journals and awards, securing funded projects from the Ministry of Higher Education and Ministry of Defence in Oman. Her book publication with Taylor & Francis (CRC Press, UK) highlights her expertise in differential equations and computational analysis. As a reviewer and editorial board member for international journals, she has played a key role in shaping academic research in her field. Her award presentations, including at WCE-2014 in London, have established her as a global researcher. Her work in IoT, AI-driven healthcare solutions, and mathematical modeling has positioned her as a leading scholar. These achievements make her a deserving candidate for prestigious research awards and further opportunities in high-impact global collaborations and research funding.

Conclusion

Dr. T Raja Rani is an accomplished researcher and academician, with a career dedicated to mathematical modeling, AI, and IoT applications. With extensive research contributions, government-funded projects, and academic leadership, she has significantly advanced interdisciplinary research. Her expertise spans machine learning, biomedical applications, and automation technologies, leading to impactful innovations in healthcare, engineering, and smart infrastructure. She has also been a mentor, reviewer, and institutional research coordinator, fostering academic excellence. Moving forward, she aims to strengthen industry collaborations, high-impact journal publications, and international research funding to further elevate her contributions. With her proven track record, Dr. Raja Rani is a strong candidate for the Best Researcher Award, and her work will continue to shape advancements in AI-driven research and technological innovation.

Publications Top Noted

  • Title: ML-based Approach to Predict Carotid Arterial Blood Flow Dynamics
    Authors: TR Rani, A Al Shibli, M Siraj, W Srimal, NZS Al Bakri, TSL Radhika
    Year: 2009
    Citations: 2
    Source: Contemporary Mathematics

  • Title: Approximate Analytical Methods for Solving Ordinary Differential Equations
    Authors: TSL Radhika, TKV Iyengar, TR Rani
    Year: 2014
    Citations: 25
    Source: CRC Press

  • Title: Econophysics and Fractional Calculus: Einstein’s Evolution Equation, the Fractal Market Hypothesis, Trend Analysis, and Future Price Prediction
    Authors: J Blackledge, D Kearney, M Lamphiere, R Rani, P Walsh
    Year: 2019
    Citations: 15
    Source: Mathematics, 7 (11), 1057

  • Title: Effect of Radiation and Magnetic Field on Mixed Convection at a Vertical Plate in a Porous Medium with Variable Fluid Properties and Varying Wall Temperature
    Authors: TR Rani, CNB Rao, VL Prasannam
    Year: 2010
    Citations: 6
    Source: Proceedings of the International Multiaward of Engineers and Computer Science

  • Title: The Effects of Viscous Dissipation on Convection in a Porous Medium
    Authors: TR Rani, TSL Radhika, JM Blackledge
    Year: 2017
    Citations: 5
    Source: Mathematica Aeterna, 7 (2), 131-145

  • Title: MHD Free Convective Heat Transfer Flow Past a Vertical Plate Embedded in a Porous Medium with Effects of Variable Fluid Properties in the Presence of Heat Source
    Authors: TR Rani, R Palli
    Year: 2014
    Citations: 4
    Source: Proceedings of the World Congress on Engineering

  • Title: Measuring Software Design Class Metrics: A Tool Approach
    Authors: T Rani, M Sanyal, S Garg
    Year: 2012
    Citations: 4
    Source: International Journal of Engineering Research & Technology (IJERT)

  • Title: Free Convection in a Porous Medium with Magnetic Field
    Authors: V Lakshmi Prasannam, T Raja Rani, R CNB
    Year: 2009
    Citations: 4
    Source: International Journal of Computational Mathematical Ideas

  • Title: Quantile Loss Function Empowered Machine Learning Models for Predicting Carotid Arterial Blood Flow Characteristics
    Authors: TR Rani, W Srimal, A Al Shibli, NZS Al Bakri, M Siraj, TSL Radhika
    Year: 2023
    Citations: 3
    Source: WSEAS Transactions on Biology and Biomedicine

  • Title: On a Study of Flow Past Non-Newtonian Fluid Bubbles
    Authors: TSL Radhika, TR Rani
    Year: 2021
    Citations: 3
    Source: WSEAS Transactions on Fluid Mechanics

  • Title: Creeping Flow of a Viscous Fluid Past a Pair of Porous Separated Spheres
    Authors: TSL Radhika, T Raja Rani, D Dwivedi
    Year: 2020
    Citations: 3
    Source: BPAS Publications, 39 (1), 58-76

  • Title: Stochastic Modelling for Lévy Distributed Systems
    Authors: J Blackledge, TR Rani
    Year: 2017
    Citations: 3
    Source: Technological University Dublin

  • Title: Time-Dependent Flow of a Couple Stress Fluid in an Elastic Circular Cylinder with Application to the Human Circulatory System
    Authors: TSL Radhika, TR Rani, A Karthik
    Year: 2020
    Citations: 2
    Source: Academic Journal of Applied Mathematical Sciences, 6 (7), 126-135

  • Title: Comparison of HAM and Numerical Solutions for a Free Convection Problem with Variable Fluid Properties, Heat Source/Sink, and Radiation
    Authors: T Raja Rani, TSL Radhika, R Palli
    Year: 2016
    Citations: 2
    Source: Journal of Information and Optimization Sciences, 37 (3), 405-422

  • Title: An Application of HAM for MHD Heat Source Problem with Variable Fluid Properties
    Authors: TR Rani, TSL Radhika, R Palli
    Year: 2014
    Citations: 2
    Source: Advances in Theoretical and Applied Mechanics, 7 (2), 79-89

  • Title: Mixed Convection in a Porous Medium with Magnetic Field, Variable Viscosity, and Varying Wall Temperature
    Authors: CNB Rao, VL Prasannam, T Raja Rani
    Year: 2010
    Citations: 2
    Source: International Journal of Computational Mathematical Ideas, 2 (1), 13-21

  • Title: Shor’s Algorithm – How Does It Work on Perfect Squares
    Authors: TSL Radhika
    Year: 2024

  • Title: Enhancing Crude Oil Pipeline Design Efficiency Through Explainable AI: A COMSOL Simulation Approach
    Authors: BJ Jose, P Jain, TR Rani
    Year: 2025
    Source: Innovative and Intelligent Digital Technologies

 

B. Meenakshi Sundaram | Computational Mathematics | Best Researcher Award

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Dr. B. Meenakshi Sundaram | Computational Mathematics | Best Researcher Award

Professor at T. John Group of Institutions India

Prof. Dr. B. Meenakshi Sundaram is a distinguished academician and researcher with over 25 years of experience in teaching, research, and administration across India and the UAE. He has made significant contributions to computer science, specializing in machine learning, IoT, cloud security, and semantic web mining. With 25+ publications in SCOPUS and IEEE-indexed journals and presentations at 20+ international awards, his research has garnered global recognition. He actively supervises PhD scholars and has mentored over 100 undergraduate and postgraduate research projects. As a curriculum developer, he has aligned academic programs with national and international standards. He holds key research identifiers, including a Scopus ID and an h-index of 4. His expertise extends to industry collaborations, technical writing, and consultancy services. While enhancing high-impact research and funded projects could further strengthen his profile, his vast academic and research contributions make him a strong contender for the Best Researcher Award.

Professional Profile:

Google Scholar
ORCID Profile 

Education:

Prof. Dr. B. Meenakshi Sundaram holds a Ph.D. in Computer Science from Bharathiar University, Coimbatore (2017), showcasing his expertise in advanced computing research. He earned his M.Tech in Information Technology (2009) from Manonmaniam Sundaranar University, securing First Class with Distinction. His academic journey began with a B.Sc. in Physics with Electronics (1996) and an M.Sc. in Computer Science (1998), both from Madurai Kamaraj University, where he excelled with distinction. Additionally, he pursued an M.Phil in Computer Science (2006) to deepen his research acumen. Beyond formal degrees, he has completed specialized professional certifications, including NPTEL courses from IIT Kharagpur and IIT Madras, as well as industry-relevant training from Infosys, Wipro, and IBM. His diverse educational background, spanning core science, engineering, and computing disciplines, has enabled him to make significant contributions to academia, research, and curriculum development at both national and international levels.

Professional Experience:

Prof. Dr. B. Meenakshi Sundaram has over 25 years of extensive experience in teaching, research, and academic administration across India and the UAE. He has served as a Professor, Associate Professor, Academic Program Manager, and Exam Controller at prestigious institutions, including New Horizon College of Engineering, Karunya University, and Syscoms College, Abu Dhabi. His expertise lies in curriculum development, faculty enrichment, industry-academic collaboration, and research supervision. He has played a key role in designing and aligning Bachelors and Masters programs with national and international accreditation standards. As a researcher, he has supervised PhD scholars, guided 100+ postgraduate and undergraduate research projects, and published 25+ research papers in SCOPUS and IEEE-indexed journals. He has also been actively involved in consultancy services, technical writing, and faculty training programs. With a strong commitment to academic excellence, he continues to contribute to cutting-edge research in computer science, artificial intelligence, and cloud computing.

Research Interest:

Prof. Dr. B. Meenakshi Sundaram’s research interests encompass a wide range of cutting-edge areas in computer science, artificial intelligence, and cybersecurity. His work primarily focuses on semantic web mining, machine learning, IoT, cloud security, and data analytics, addressing critical challenges in intelligent systems and computational frameworks. He has made significant contributions to ontology-based information retrieval, cloud integration, and security frameworks, with an emphasis on developing efficient and scalable solutions for real-world applications. His research also extends to imbalanced data classification, deep learning, and digital innovation in education, exploring novel methodologies to enhance computational intelligence and cybersecurity mechanisms. With a strong commitment to interdisciplinary research, he actively engages in AI-driven enterprise security, intelligent decision-making systems, and web service optimizations, aiming to bridge the gap between academia and industry. His research efforts contribute to advancing smart computing, digital transformation, and next-generation AI technologies.

Award and Honor:

Prof. Dr. B. Meenakshi Sundaram is a distinguished academician and researcher with a remarkable career spanning over 25 years in teaching, research, and administration. His contributions to computer science, particularly in machine learning, IoT, cloud security, and semantic web mining, have earned him recognition in national and international forums. He has published 25+ research papers in reputed SCOPUS and IEEE-indexed journals, presented at 20+ awards, and actively mentors PhD scholars and postgraduate students. As a professional member of IEEE and Institution of Engineers (India), he has contributed to global research collaborations and curriculum development initiatives. He has received certifications from IIT Madras, IIT Kharagpur, and other reputed institutions, further showcasing his dedication to academic excellence. His significant contributions to academia, research supervision, and international collaborations make him a highly deserving candidate for prestigious awards in research and innovation.

Conclusion:

Prof. Dr. B. Meenakshi Sundaram is a distinguished academician and researcher with 25 years of experience in teaching, research, and administration. His extensive contributions to computer science, particularly in semantic web mining, IoT, and cloud security, are reflected in his 25+ publications in reputed journals, including SCOPUS and IEEE-indexed papers. As a mentor, he has guided numerous research scholars and postgraduate students, fostering academic excellence. His involvement in curriculum development, international collaborations, and industry-academia partnerships further solidifies his impact on higher education. While his research credentials are strong, expanding high-impact publications, securing funded projects, and increasing citation metrics can enhance his global research standing. Nevertheless, his academic leadership, interdisciplinary research, and commitment to knowledge dissemination make him a highly deserving candidate for the Best Researcher Award. His dedication to innovation and scholarly excellence continues to shape the future of computing and technology-driven education.

Publications Top Noted:

  • Face recognition based automated remote proctoring platform
    • Authors: N Sasikala, BM Sundaram, VN Kumar, J Sumanth, S Hrithik
    • Year: 2022
    • Citations: 7
  • Survey of latest technologies on Decentralized applications using Blockchain
    • Authors: N Sasikala, BM Sundaram, S Biswas, AS Nikhil, VS Rohith
    • Year: 2022
    • Citations: 6
  • Disaster relief compensation computational framework
    • Authors: BM Sundaram, B Rajalakshmi, BA Singh, RS Kumar, R Arsha
    • Year: 2022
    • Citations: 6
  • More Accurate Organ Recipient Identification Using Survey Informatics of New Age Technologies
    • Authors: BM Sundaram
    • Year: 2021
    • Citations: 6
  • Fall detection among elderly using deep learning
    • Authors: BM Sundaram, B Rajalakshmi, RK Mandal, S Nair, SS Choudhary
    • Year: 2023
    • Citations: 4
  • An Analysis on Security Threats in Cloud Computing
    • Authors: AP Nirmala, R Prema, BM Sundaram
    • Year: 2019
    • Citations: 4
  • A Roadmap to Application Integration using IoT Cloud Platform
    • Authors: DT Dr. BM Sundaram
    • Year: 2020
    • Citations: 3
  • Cross Domain Composition of Web Service Workflows using a Provenance Ontology with an automated Re-planning
    • Authors: BM Sundaram, D Manimegalai
    • Year: 2015
    • Citations: 3
  • Semantic Interoperable EHR mapping with syndromic surveillance to anticipate regional outbreak
    • Authors: BM Sundaram
    • Year: 2020
    • Citations: 2
  • Fuzzy-XDDS: A Fuzzy Based Cross-Domain Services Matchmaker for Semantic Web Services
    • Authors: BM Sundaram, D Manimegalai
    • Year: 2015
    • Citations: 2
  • AirGuard AI: Revolutionizing Air Cargo Inspection through Pygame and YOLOv8 Simulation
    • Authors: BM Sundaram, B Rajalakshmi, A Saxena, B Vasumati
    • Year: 2024
    • Citations: 1
  • Deep learning implemented communication system for the auditory and verbally challenged
    • Authors: B Chempavathy, BM Sundaram, A Shaynam, A Goswami, S Bindya
    • Year: 2023
    • Citations: 1
  • Malware Exposed: An In-Depth Analysis of its Behavior and Threats
    • Authors: C Anand, S Korada, S Raksha, BM Sundaram, B Rajalakshmi
    • Year: 2023
    • Citations: 1
  • Modeling crime prediction using ML
    • Authors: BM Sundaram, B Rajalakshmi, B Anusha, MK Bindu, BL Keerthi
    • Year: 2022
    • Citations: 1
  • Cardiovascular disease detection using machine learning-a survey
    • Authors: BM Sundaram, B Rajalakshmi, Eshwar, Tanith, L Emmanuel
    • Year: 2022
    • Citations: 1
  • A holistic redesign of web elements using CATWOE analysis
    • Authors: R Jayakumar, BM Sundaram, MA Sankaridevi
    • Year: 2019
    • Citations: 1
  • Dual Tree Complex Wavelet based Regularized Deconvolution for Medical Images
    • Authors: R Murugesan, V Thavavel, BM Sundaram
    • Year: 2007
    • Citations: 1
  • Smart City Traffic Management
    • Authors: BM Sundaram, JG Chowdary, R Gonela, B Rajalakshmi
    • Year: 2024
    • Citations: 1
  • Retinal Authentication for E-Voting
    • Authors: LS Hanne, BM Sundaram, M Rakshitha, V Kishore, A Meenakshi
    • Year: 2024
    • Citations: 1
  • DRS-UNET: A Deep Learning Approach for Diabetic Retinopathy Detection and Segmentation from Fundus Images
    • Authors: RS Gound, BM Sundaram, SK BV, PA Azmat, MNU Habib, A Garg
    • Year: 2023
    • Citations: 1