Ayshika Kapoor | Computer Science | Women Researcher Award

Published-on by Indian Scientist

Dr. Ayshika Kapoor | Computer Science | Women Researcher Award

Indian Institute of Technology Roorkee,  India

Dr. Ayshika Kapoor is a researcher in Electronics and Communication Engineering with a Ph.D. specializing in privacy-preserving and communication-efficient federated learning. Her work focuses on secure AI, urban sensing systems, and domain-adaptive learning. She has experience as a research scientist, contributing to intelligent mobility and autonomous systems. With multiple high-impact publications, conference presentations, and a granted copyright, she has earned prestigious fellowships and research recognition. Her contributions advance scalable, secure, and efficient AI solutions for real-world applications.

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Featured Publications


A resource adaptive secure aggregation protocol for federated learning based urban sensing systems


– Joint International Conference on Data Science (Cited by 6 · Year: 2023)


Optimization of user resources in federated learning for urban sensing applications


– Federated Learning for Distributed Data Mining Workshop (Cited by 3 · Year: 2023)

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.

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7384

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45

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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

Published-on by Indian Scientist

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).

Priyanka Upadhyay | Robust Navigation | Best Researcher Award

Published-on by Indian Scientist

Ms. Priyanka Upadhyay | Robust Navigation | Best Researcher Award

Netaji Subhas University of Technology | India

Priyanka Upadhyay is a researcher in Electrical Engineering with growing contributions in autonomous robotics, intelligent navigation, and control systems. She is pursuing a doctoral degree focused on robust navigation of autonomous robots and holds postgraduate and undergraduate qualifications in Electrical Power Systems and Electrical & Electronics Engineering. Her research record includes publications on hybrid path-planning algorithms, enhanced Bezier-based trajectory modeling, autonomous mobile robot navigation, and control strategies for multi-link manipulators. Her work has gained academic attention, reflected in 16 citations, an h-index of 2, and i10-index of 0, demonstrating steadily increasing scholarly visibility with 8 citations since 2020. She has prior teaching experience as a faculty member in Electrical Engineering and has participated in several conferences, faculty development programs, and short-term courses related to artificial intelligence, optimization, robotics, renewable integration, and power electronics. Her technical expertise is strengthened by hands-on training in tools such as MATLAB and experience in industrial settings. She has earned recognition including a Silver Medal for an NPTEL Robotics certification and reviewer certification from an international robotics journal. Her research interests include electrical machines, robotic navigation, path planning, and intelligent control. She continues to advance her academic profile with a commitment to innovation, learning, and collaborative research.

Profile: Google Scholar

Featured Publications

Upadhyay, P., Rajesh, N., Garg, N., & Singh, A. (2015). Evaluating seed germination monitoring system by application of wireless sensor networks: A survey. In Computational Intelligence in Data Mining—Volume 2: Proceedings of the … (Cited by: 3).

Upadhyay, P., Singh, A., & Garg, N. (2014). Modeling software maintainability and quality assurance in the agile environment. International Journal of Database Theory and Application, 7(3), 83–90. (Cited by: 3).

Singh, P., Upadhyay, P., & Singh, S. K. (2025). Unlocking the economic potential of potato cultivars for mini-tuber production under aeroponic culture. Potato Research, 1–24. (Cited by: 2).

Upadhyay, P., Singh, R., & Rani, A. (2023). Reliable autonomous navigation of mobile robot in unconstrained environment. In 2023 10th International Conference on Signal Processing and Integrated Networks (SPIN) (pp. 531–537). IEEE. (Cited by: 2).

Upadhyay, P., Patil, K. U., Kuber, R., Kulkarni, V., & Singh, A. (2014). Evaluation of hypoxic-ischaemic events in preterm neonates using trans cranial ultrasound. International Journal of Healthcare and Biomedical Research, 3, 67–72. (Cited by: 2).

Runu Banerjee Roy | Artificial Intelligence | Best Researcher Award

Published-on by Indian Scientist

Dr. Runu Banerjee Roy | Artificial Intelligence | Best Researcher Award

Jadavpur University| India

Dr. Runu Banerjee Roy is a Professor in Instrumentation and Electronics Engineering at Jadavpur University, widely recognized for her contributions to electronic olfaction, taste sensing, molecular imprinting, sensor development, and artificial intelligence–based instrumentation. She has an extensive research profile with 1213 citations, an h-index of 17, and an i10-index of 25, reflecting her strong scholarly impact and research productivity. Her publication record includes more than 50 peer-reviewed journal papers, around 40 conference papers, multiple book chapters, and several patents that are granted, published, or filed. She has successfully guided doctoral and postgraduate research scholars and completed multiple sponsored research projects funded by major scientific agencies, focusing on portable sensing devices, electronic nose and tongue systems, and electrochemical detection technologies for applications in food quality and safety. In academics, she has served in leadership roles such as Head of Department, NBA accreditation coordinator, and curriculum committee member, contributing to program development and quality enhancement. Her work has earned recognition through competitive research awards, scientific prizes, and support for international research presentations. With strong expertise spanning instrumentation, intelligent sensing systems, and applied electronics, she continues to advance innovative research, academic excellence, and technology-driven solutions in modern sensor engineering.

Profile: Google Scholar | Scopus

Featured Publications

Roy, R. B., Tudu, B., Shaw, L., Jana, A., Bhattacharyya, N., & Bandyopadhyay, R. (2012). Instrumental testing of tea by combining the responses of electronic nose and tongue. Journal of Food Engineering, 110(3), 356–363.

Banerjee, M. B., Roy, R. B., Tudu, B., Bandyopadhyay, R., & Bhattacharyya, N. (2019). Black tea classification employing feature fusion of E-Nose and E-Tongue responses. Journal of Food Engineering, 244, 55–63.

Banerjee, R., Tudu, B., Bandyopadhyay, R., & Bhattacharyya, N. (2016). A review on combined odor and taste sensor systems. Journal of Food Engineering, 190, 10–21.

Roy, R. B., Chattopadhyay, P., Tudu, B., Bhattacharyya, N., & Bandyopadhyay, R. (2014). Artificial flavor perception of black tea using fusion of electronic nose and tongue response: A Bayesian statistical approach. Journal of Food Engineering, 142, 87–93.

Nag, S., Pradhan, S., Naskar, H., Roy, R. B., Tudu, B., Pramanik, P., … et al. (2021). A simple nano cerium oxide modified graphite electrode for electrochemical detection of formaldehyde in mushroom. IEEE Sensors Journal, 21(10), 12019–12026.