S.S.Subashka Ramesh | Medicinal Chemistry | Best Researcher Award-duplicate-1

Published-on by Indian Scientist

Dr. S.S. Subashka Ramesh | Data Science and Machine learning | Best Researcher Award

SRM Institute of Science and Technology india, India

Dr. S.S. Subashka Ramesh is an accomplished academic and researcher in Computer Science and Engineering with a strong foundation in advanced computing and data-driven technologies. Holding doctoral and postgraduate qualifications, she has extensive teaching and research experience, mentoring scholars and contributing to impactful innovations. Her research interests include machine learning, artificial intelligence, edge computing, and medical imaging. With notable publications, patents, and academic leadership, she has earned professional recognition and continues to advance knowledge through research, collaboration, and technology-driven solutions for real-world challenges.

Citation Metrics (Google Scholar)

700
500
20
10
0

Citations
641

h-index
11

i10index
13

Citations

h-index

i10-index

Featured Publications

Deepti Deshwal | Artificial Intelligence | Women Researcher Award

Published-on by Indian Scientist

Dr. Deepti Deshwal | Artificial Intelligence | Women Researcher Award

Maharaja Surajmal Institute of Technology New Delhi | India

Dr. Deepti Deshwal is an accomplished Assistant Professor in Electronics & Communication Engineering with extensive teaching experience and expertise in Artificial Intelligence, Machine Learning, speech processing, biomedical image analysis, and computer vision. She holds a Ph.D. in AI and has contributed significantly through SCI/SCIE publications, editorial roles, and funded research projects. Recognized with multiple research awards, she actively mentors Ph.D. students and fosters innovation through IPR initiatives, conferences, and technical workshops. Her work bridges academic excellence with practical AI applications, driving technology-driven societal impact.

Citation Metrics (Scopus)

350
300
20
10
0

Citations
306

h-index
9

Documents
22

Citations

h-index

Documents

Featured Publications


Economic analysis of lithium ion battery recycling in India


– Wireless Personal Communications · 64 citations · 2022


Feature extraction methods in language identification: a survey


– Wireless Personal Communications · 59 citations · 2019


Isolated word language identification system with hybrid features from a deep belief network


– International Journal of Communication Systems · 34 citations · 2023
Citation counts may vary across databases; links redirect to publisher pages or Google Scholar search results for accessibility.

Chellavelu Vijayakumaran | Computer Vision | Research Excellence Award

Published-on by Indian Scientist

Dr. Chellavelu Vijayakumaran | Computer Vision | Research Excellence Award

SRM Institute of Science and Technology | India

Dr. Rajesh Pandiyan is a dedicated researcher and academic with expertise spanning microbiology, biochemistry, materials engineering, and pharmaceutical technology. He has served in progressive teaching and research roles across leading institutions, contributing significantly to interdisciplinary advancements. His research journey includes extensive work in nanocomposite-based ultrafiltration membranes, magnetic nanomaterials for targeted drug delivery, medicinal plant-based therapeutics, and biochemical models for autoimmune and inflammatory diseases. He has also worked on environmental biotechnology, wastewater remediation, tissue engineering, and drug discovery. With a strong academic foundation built through doctoral and postgraduate training in microbiology, biochemistry, and chemistry, he has developed a wide research portfolio combining materials chemistry with biological applications. His scholarly contributions include 67 peer-reviewed research and review articles, supported by an H-index of 19, i10-index of 27, and more than 1300 citations, reflecting global recognition of his work. He has delivered invited talks, chaired scientific sessions, and served as a resource person for various scientific forums, in addition to contributing as an editorial member for reputed journals. His awards span excellence in research, oral and poster presentations, and international recognition for scientific contributions. Overall, his work integrates innovation and multidisciplinary approaches aimed at solving challenges in healthcare, environment, and materials science.

Profile: Google Scholar

Featured Publications

Vijayakumaran, C., Muthusenthil, B., & Manickavasagam, B. (2020). A reliable next generation cyber security architecture for industrial internet of things environment. International Journal of Electrical and Computer Engineering, 10(1), 387.

Alagurajan, M., & Vijayakumaran, C. (2020). ML methods for crop yield prediction and estimation: An exploration. International Journal of Engineering and Advanced Technology, 9(3), 1–5.

Karthikeyan, L., Vijayakumaran, C., Chitra, S., & Arumugam, S. (2021). Saldeft: Self-adaptive learning differential evolution based optimal physical machine selection for fault tolerance problem in cloud. Wireless Personal Communications, 118(2), 1453–1480.

Chinnappa Annamalai, H. K., Vijayakumaran, C., & Vijayakumar, P. (2023). Optimal ElGamal encryption with hybrid deep-learning-based classification on secure Internet of Things environment. Sensors, 23(12), 5596.

Sweetline, B. C., Vijayakumaran, C., & Samydurai, A. (2024). Overcoming the challenge of accurate segmentation of lung nodules: A multi-crop CNN approach. Journal of Imaging Informatics in Medicine, 37(3), 988–1007.

Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

Published-on by Indian Scientist

Mr. Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

Techno College Hooghly | India

Subhodeep Moitra is a computer science researcher focused on advancing artificial intelligence through the fusion of human-like visual perception and cognition. His academic foundation spans computer applications at both undergraduate and postgraduate levels, where he built strong expertise in machine learning, deep learning, computer vision, neural networks, adversarial robustness, and cognitive modeling. His research explores self-supervised reconstruction, adversarial recovery, AGI-oriented theoretical computing, medical prediction systems, and environmental forecasting, with publications in journals, conferences, preprint platforms, and book chapters. He has contributed to projects ranging from temperature forecasting and brain-stroke detection to adversarially robust autoencoders and AGI theory. His professional experience includes serving as a visiting faculty member, teaching programming, mentoring research projects, and engaging in active collaborative work. His technical skills extend across Python, deep learning frameworks, MERN stack development, and cloud-based AI tools, supported by multiple certifications from NASA, NVIDIA, CERN, IBM, Oracle, and Coursera. He has presented papers at international conferences and earned best paper presentation awards for his contributions in machine learning–driven forecasting and adversarial perception. His long-term research interest lies in building unified AI systems capable of perceiving, reasoning, and adapting with human-inspired intelligence, aiming to push the boundaries of next-generation cognitive AI.

Profile: Google Scholar

Featured Publications

Moitra, S., & Banerjee, D. (n.d.). Robustness as Latent Symmetry: A Theoretical Framework for Semantic Recovery in Deep Learning. OSF.

Moitra, S., & Banerjee, D. (n.d.). Are We Even on the Right Track? A Theoretical Framework for AGI Beyond Classical Computation. Authorea Preprints.

Moitra, S., & Banerjee, D. (n.d.). Skip the Chaos: A Self-Supervised Learning-Powered Autoencoder for Adversarial Recovery. OSF.

Pintu, P., Subhodeep, M., & Deblina, B. (n.d.). The mystery of Neural Network: Linked with quantum mechanics and universe. ResearchGate.

Pal, P., Moitra, S., & Banerjee, D. (n.d.). The mystery of Neural Network: Linked with quantum mechanics and universe.

Tejinder Kaur | Computer Science | Best Researcher Award

Published-on by Indian Scientist

Dr. Tejinder Kaur | Computer Science | Best Researcher Award

MM Institute of Computer Technology & Business Management | India

Dr. Tejinder Kaur is an accomplished academic and researcher in Computer Science and Engineering, currently serving as an Associate Professor with extensive teaching and research experience in artificial intelligence, machine learning, big data, and software engineering. She holds a Ph.D. from Thapar University and an M.Tech from Chandigarh University, with postdoctoral research in progress from a reputed public university. Her work has earned significant scholarly recognition with over 54,815 citations, an h-index of 65, and an i10-index of 148, reflecting her impactful contributions to scientific research and innovation. Dr. Kaur has authored and reviewed numerous research papers and book chapters and has guided several postgraduate theses in areas like vehicular networks, routing protocols, and wireless sensor networks. Her research interests span artificial intelligence, IoT, cybersecurity, and advanced computing systems. She has published over 277 papers, filed and been granted multiple national and international patents, and received prestigious awards, including honors from IEEE, Infosys, and SAP. A committed educator and innovator, Dr. Kaur continues to inspire through academic excellence and research leadership. Her outstanding academic record, extensive publication portfolio, and technological innovations highlight her as a dynamic professional dedicated to advancing computing and intelligent systems.

Profiles: Google Scholar | Scopus

Featured Publications

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). Observation of gravitational waves from a binary black hole merger. Physical Review Letters, 116(6), 061102. https://doi.org/10.1103/PhysRevLett.116.061102

Aasi, J., Abbott, B. P., Abbott, R., Abbott, T., Abernathy, M. R., Ackley, K., Adams, C., et al. (2015). Advanced LIGO. Classical and Quantum Gravity, 32(7), 074001. https://doi.org/10.1088/0264-9381/32/7/074001

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). GW151226: Observation of gravitational waves from a 22-solar-mass binary black hole coalescence. Physical Review Letters, 116(24), 241103. https://doi.org/10.1103/PhysRevLett.116.241103

Abbott, R., Abbott, T. D., Acernese, F., Ackley, K., Adams, C., Adhikari, N., et al. (2023). GWTC-3: Compact binary coalescences observed by LIGO and Virgo during the second part of the third observing run. Physical Review X, 13(4), 041039. https://doi.org/10.1103/PhysRevX.13.041039

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). Tests of general relativity with GW150914. Physical Review Letters, 116(22), 221101. https://doi.org/10.1103/PhysRevLett.116.221101