Banupriya N | Computer Science | Young Researcher Award

Published-on by Indian Scientist

Dr. Banupriya N | Computer Science | Young Researcher Award

R.M.K. Engineering College, India

Dr. N. Banupriya is an accomplished academician and researcher in Computer Science and Engineering, currently serving as an Assistant Professor at R.M.K. Engineering College. She holds advanced degrees in Computer Science and is pursuing doctoral research, reflecting her commitment to academic excellence. With extensive teaching experience, she has contributed significantly to research in Artificial Intelligence, Machine Learning, Data Analytics, and Brain-Computer Interface. She has published in reputed journals and conferences and received recognitions including Infosys Campus Connect certifications. Her work demonstrates dedication to innovation, impactful research, and academic leadership.

Citation Metrics (Scopus)

15
10
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Citations
4

Documents
12

h-index
1

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Featured Publications

ADRIJIT GOSWAMI | Computer Science | Research Excellence Award

Published-on by Indian Scientist

ADRIJIT GOSWAMI | Computer Science | Research Excellence Award

Indian Institute of Technology Kharagpur India, India

Prof. Dr. Adrijit Goswami is a distinguished academic in Mathematics at the Indian Institute of Technology Kharagpur, specializing in Operations Research and Optimization. He earned his doctorate from Jadavpur University and has extensive teaching and research experience. His interests include supply chain management, fuzzy systems, vehicle routing, cryptography, and data analytics. A recipient of multiple academic honors, he has supervised numerous doctoral scholars and published widely. His work significantly advances mathematical modeling, optimization science, and impactful decision-making research.

Research Metrics (Google Scholar)

8000
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Citations
7384

h-index
45

i10-index
109

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Featured Publications


A secure biometrics-based multi-server authentication protocol using smart cards

V Odelu, AK Das, A Goswami – IEEE Transactions on Information Forensics and Security
Cited by: 489 · Year: 2015


An EOQ model for deteriorating items with linear time-dependent demand rate and shortages under inflation and time discounting

S Bose, A Goswami, KS Chaudhuri – Journal of the Operational Research Society
Cited by: 354 · Year: 1995


An EOQ model for deteriorating items with shortages and a linear trend in demand

A Goswami, KS Chaudhuri – Journal of the Operational Research Society
Cited by: 343 · Year: 1991


Multiobjective transportation problem with interval cost, source and destination parameters

SK Das, A Goswami, SS Alam – European Journal of Operational Research
Cited by: 281 · Year: 1999


A deterministic inventory model for deteriorating items with stock-dependent demand rate

S Pal, A Goswami, KS Chaudhuri – International Journal of Production Economics
Cited by: 269 · Year: 1993

Rounak Raman | Information Technology | Research Excellence Award

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Mr. Rounak Raman | Information Technology | Research Excellence Award

Netaji Subhas University of Technology | India

Rounak Raman is a technology researcher and engineering innovator with a strong academic background in Information Technology and a multidisciplinary portfolio spanning artificial intelligence, machine learning, generative AI, computer vision, IoT systems, wireless sensor networks, and network security. He has gained significant research and development experience through contributions at DRDO-INMAS, where he worked on EEG-based cognitive analytics and neurofeedback systems, and at NSUT, where he designed advanced IoT protocols including energy-aware clustering, trust-based opportunistic communication, and secure hierarchical key-rotation mechanisms. His technical work extends into generative AI solutions, semantic search systems, real-time computer vision applications, and large-scale image and document intelligence models. He has led impactful projects such as PRAGATI smart parking, SyntheX document analysis framework, and QuickTag for AI-driven product taxonomy. His achievements include securing positions in national innovation challenges, hackathons, entrepreneurship competitions, and international fellowship programs. Alongside industry-recognized certifications in data science, system design, and cybersecurity, he has also held leadership roles in student organizations, mentoring teams, guiding open-source contributions, and facilitating research collaboration. His research interests include GenAI, NLP, IoT security, WSNs, cryptography, edge intelligence, and autonomous network optimization. He remains committed to creating scalable, socially impactful technological solutions.

Profiles: Google Scholar

Featured Publication

Raman, R., Yadav, A., Kukreja, D., & Sharma, D. K. (2025). CONTEXT-NET: A context-aware nexus-based aggregation protocol for opportunistic networks. Internet of Things, 101809.

Raman, R., Yadav, A., & Kukreja, D. (2025). ARMor-IoT: Aggregated reliable mechanism for optimized trust in IoT. In International Conference on Artificial Intelligence and Its Application (pp. 229–241).

Padmini Sankaramurthy | Energy | Research Excellence Award

Published-on by Indian Scientist

Dr. Padmini Sankaramurthy | Energy | Research Excellence Award

SRM Institute of Science and Technology | India

Dr. S. Padmini is an accomplished academic and researcher with a strong foundation in Electrical and Electronics Engineering, advanced training in Power Systems Engineering, and doctoral work centered on intelligent algorithms for hydrothermal scheduling, further strengthened by an ongoing postdoctoral fellowship in multidisciplinary AI applications. With extensive teaching and research experience in a premier institution, she has contributed significantly to curriculum development, research supervision, academic leadership, and large-scale institutional activities. Her scholarly output includes publications indexed in major databases, patents, major project proposals, international collaborations, and diverse technical contributions across intelligent systems, power systems optimization, energy economics, and AI-driven engineering solutions. She has delivered numerous courses, created substantial digital learning resources, and guided students at multiple academic levels. Her research has earned citations totalling 341, along with an h-index of 10 and an i10-index of 10, demonstrating meaningful global impact. She is recognized for excellence through multiple awards, including distinguished scientific honours, innovation-driven recognitions, and accolades for academic contributions. Her ongoing collaborations across global universities reflect her commitment to advancing multidisciplinary research. Dr. Padmini’s work continues to integrate engineering intelligence, sustainable energy solutions, and advanced computational methods to support emerging technological needs and societal progress.

Profiles: Google Scholar | Orcid | Scopus

Featured Publication

Jeevadason, A. W., Padmini, S., Bharatiraja, C., & Kabeel, A. E. (2022). A review on diverse combinations and Energy-Exergy-Economics (3E) of hybrid solar still desalination. Desalination, 527, 115587.

Rebecca, B., Kumar, K. P. M., Padmini, S., Srivastava, B. K., Halder, S., & Boopathi, S. (2024). Convergence of Data Science-AI-Green Chemistry-Affordable Medicine: Transforming Drug Discovery. In Handbook of Research on AI and ML for Intelligent Machines and Systems (pp. 348–373).

Venkatesh, B., Sankaramurthy, P., Chokkalingam, B., & Mihet-Popa, L. (2022). Managing the demand in a micro grid based on load shifting with controllable devices using hybrid WFS2ACSO technique. Energies, 15(3), 790.

Lakshmi, K., Amaran, S., Subbulakshmi, G., Padmini, S., Joshi, G. P., & Cho, W. (2025). Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images. Scientific Reports, 15(1), 690.

Sankaramurthy, P., Chokkalingam, B., Padmanaban, S., Leonowicz, Z., … Padmini, S. (2019). Rescheduling of generators with pumped hydro storage units to relieve congestion incorporating flower pollination optimization. Energies, 12(8), 1477.

Sivakamasundari | Computer Science | Best Researcher Award

Published-on by Indian Scientist

Ms. Sivakamasundari | Computer Science | Best Researcher Award

SRM Institute of Science and Technology | India

Ms. P. Sivakamasundari is a dedicated academic and researcher in Computer Science and Engineering, recognized for her contributions to deep learning-based medical image analysis. With qualifications spanning Diploma, Bachelor’s, and Master’s degrees in Computer Science and Engineering, she is currently pursuing her Ph.D. at SRM Institute of Science and Technology. She has extensive teaching experience as an Assistant Professor for more than a decade, during which she has guided students in core computing subjects including algorithms, computation theory, compiler design, and image classification. Her research focuses on advanced deep learning frameworks for healthcare applications, particularly diabetic retinopathy and diabetic foot ulcer detection, resulting in book chapters, conference publications, and journal manuscripts under review. She has published and filed patents related to medical imaging and automated disease detection systems, demonstrating her innovation-driven approach. Her scholarly presence includes 1 citation, 1 h-index, and 0 i10-index, indicating emerging research visibility. She has completed multiple professional certifications and participated in workshops, FDPs, and internships in machine learning, biometrics, accelerated computing, and high-performance healthcare analytics. Her work reflects strong commitment toward applying AI for societal benefit, and she continues to advance her expertise through active research and academic contributions.

Profile: Google Scholar

Featured Publications

Sivakamasundari, P., Anandhi, S., Kumaran, A. A., Vijayakumar, K., Birnica, Y. J., & others. (2024). Early detection of glaucoma utilizing retinal nerve fiber layer (RNFL) investigation. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2025). An automatic detection and classification of diabetic foot ulcers using Chebyshev chaotic ladybug beetle optimized extended Swin Transformer–InceptionV3 model. Biomedical Signal Processing and Control, 110, 108268.

Gomathi, G., Sumathy, V., Sivakamasundari, P., & Deepa, R. (2024). A various approaches of machine learning algorithms for kidney disease prediction. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2024). Diabetic foot ulcer classification using deep learning approach. International Conference on Computer, Communication and Signal Processing (ICCCSP).

Sivakamasundari, P., & Niranjana, G. (2023). A critique on deep learning methodologies employed for the identification of diabetic retinopathy using fundus images. Intelligent Computing and Control for Engineering and Business Systems (ICCEBS).

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

Gautam Garai | Optimization Algorithms | Best Researcher Award

Published-on by Indian Scientist

Prof. Dr. Gautam Garai | Optimization Algorithms | Best Researcher Award

Saha Institute of Nuclear Physics, India

Author Profile

SCOPUS

🎓 EARLY ACADEMIC PURSUITS

Dr. Gautam Garai embarked on his academic journey with a strong foundation in computer science. He completed his Ph.D. in Computer Science & Engineering from Jadavpur University in 2008. Prior to that, he earned an M.E. in Computer Science & Engineering (1991) from the same institution and B.E. in Computer Science & Technology (1987) from the prestigious Bengal Engineering College, under Calcutta University. His exceptional academic record is marked by top-class ranks and national scholarships during his schooling years.

🏢 PROFESSIONAL ENDEAVORS

Dr. Garai has served at the Saha Institute of Nuclear Physics (SINP), Kolkata, for over three decades, steadily rising through the ranks from Scientist ‘B’ in 1988 to Scientist ‘G’ since 2009. Prior to joining SINP, he began his career as an Assistant Systems Engineer at M.N. Dastur & Co. in 1987. Throughout his tenure, he held numerous administrative and technical leadership roles including:

  • Head of Computer Section

  • Project Leader of in-house software development

  • Liaison Officer for SC/ST and PWD affairs

  • Member of multiple key institutional committees

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN OPTIMIZATION ALGORITHMS

Dr. Garai’s primary research interests lie in optimization algorithms, evolutionary computation, pattern recognition, and bioinformatics. He is well-known for his application of genetic algorithms in diverse fields including:

  • Data Clustering

  • Function Optimization

  • Shape Recognition

  • Scientific Problem Solving

His contributions have been translated into impactful book chapters, such as his 2022 publication with IntechOpen, and the VDM Verlag monograph on cascaded genetic algorithms.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

  • Over 100+ citations on Google Scholar for his research work in applied computing and optimization.

  • Awarded the STATE AWARD for PWD – Role Model by Govt. of West Bengal (2010).

  • Honored with a Certificate of Special Mention at EAIT 2006, and recipient of National Scholarships in 1981 and 1983.

  • Distinctions in Indian Classical Music from Sangeet Bhushan, showcasing his multidisciplinary talents.

🌍 IMPACT AND INFLUENCE

A Senior Member of IEEE and active participant in the Computer Society of India, IAPR, and other organizations, Dr. Garai has built a strong international presence. He has:

  • Reviewed papers for over 15 reputed journals including IEEE Transactions, Pattern Recognition, and Information Sciences.

  • Served on program committees of international conferences in the USA, Singapore, and India.

  • Chaired IEEE TENCON 2009 and various global sessions.

  • Delivered invited talks on optimization and computational techniques in India and abroad.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Dr. Garai’s legacy lies in his long-standing service at SINP, driving digital transformation through E-Governance modules such as:

  • Leave Management

  • Pension & Salary Processing

  • Online Medical Bill Systems

  • E-Attendance & No Dues Certificate Generation

These systems significantly enhanced operational transparency and efficiency.

As a research mentor, academic reviewer, and software innovator, his future contributions are poised to further the fields of bioinformatics, AI-driven optimization, and institutional automation.

 ✅CONCLUSION

Dr. Gautam Garai exemplifies academic brilliance, leadership, and technical ingenuity. Through his innovative application of optimization algorithms, decades of dedicated scientific service, and impactful digital initiatives, he continues to inspire excellence within India’s scientific and academic ecosystem.

🔬NOTABLE PUBLICATION:

Title: A Novel Differential Evolution Algorithm for Tone Reservation based PAPR Reduction Technique in OFDM Systems

Authors: Mahua Rakshit, Gautam Garai

Journal: Swarm and Evolutionary Computation (Elsevier)

Year: 2022