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.

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.

Banushri S | Deep Learning | Best Researcher Award

Published-on by Indian Scientist

Mrs. Banushri S | Deep Learning | Best Researcher Award

Impact College of Engineering and Applied Sciences| India

Dr. Banushri S is an accomplished academician and researcher in Computer Science and Engineering, recognized for her contributions to machine learning, deep learning, image processing, and human activity recognition. She has published impactful research across reputed journals and conferences, contributing to the scientific community with multiple documents, citations, and an evolving h-index that reflects her growing influence in the field. Her academic journey includes strong foundational degrees in engineering and digital electronics, shaping her expertise in logic design, embedded systems, computer architecture, networking, operating systems, programming, and advanced AI-driven technologies. With extensive teaching experience as an Assistant Professor in leading engineering institutions, she has guided numerous undergraduate and postgraduate learners, supervised research projects, and supported curriculum development and departmental academic activities. Her research works span areas such as fall detection, wearable sensor data analysis, transfer learning, and long-range context modeling for human activity recognition, including contributions indexed in Scopus and other reputed platforms. She has actively participated in faculty development programs, workshops, and conferences focusing on artificial intelligence, computer vision, and full-stack technologies, while also being a member of professional bodies like ISTE and CSI. Her work reflects a commitment to advancing intelligent systems research and contributing to academic excellence.

Profile: Scopus

Featured Publications

Banushri, S. (2026). Attention-guided residual shrinkage with gated recurrent unit for human activity recognition. Information Processing and Management.

Shanmugam S | Machine Learning | Best Researcher Award

Published-on by Indian Scientist

Dr. Shanmugam S | Machine Learning | Best Researcher Award

SRM Institute of Science and Technology | India

Dr. Shanmugam S is an academic and researcher in the field of computing technologies with a focus on Artificial Intelligence and Machine Learning. His scholarly portfolio reflects professional engagement with advanced areas including Soft Computing, Transfer Learning, and Quantum Computing. He has completed his doctoral research in Information and Communication, supported by previous postgraduate and undergraduate education in computer science and information technology disciplines. His publication record includes 24 research documents, with 342 citations received from 322 referencing documents, supported by an h-index of 8, highlighting the relevance and impact of his contributions in the research community. He has accumulated significant teaching and research experience, handling courses such as Data Structures, Object-Oriented Programming, Big Data for Machine Learning, Software Engineering, Business Computing, and Philosophy of Engineering. His efforts extend to guiding students, contributing to departmental academic activities, and participating in various scholarly workshops, seminars, and conferences. His research interests continue to explore emerging computational paradigms and their applications in solving real-world challenges. He has received recognition for academic and research contributions, reinforcing his professional standing. Overall, his work contributes to the advancement of intelligent systems and computational innovation.

Profile: Scopus

Featured Publications

Role of hydroxychloroquine in primary glomerular disease – a systematic review and meta-analysis of the current evidence. BMC Nephrology. (2025).

Exploring the ability of emerging large language models to detect cyberbullying in social posts through new prompt-based classification approaches. Information Processing and Management. (2025).