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.

Citation Metrics (Google Scholar)

20
15
10
5
0

Citations
19

Documents
11

h-index
3

Citations

Documents

h-index

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.

Research Metrics (Google Scholar)

8000
6000
4000
2000
0

Citations
7384

h-index
45

i10-index
109

Citations

h-index

i10-index

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

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).

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