Ayshika Kapoor | Computer Science | Women Researcher Award

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)

IndukuriMani Varma | Network Security | Research Excellence Award

Mr. IndukuriMani Varma | Network Security | Research Excellence Award

IIT Roorkee | India

Mr. IndukuriMani Varma is a doctoral scholar in Computer Science and Engineering at a premier technical institute, specializing in security of software-defined vehicular networks. With strong academic training in computer science and information security, the researcher has industry experience in computer networking and embedded systems. Research interests include vehicular networks, network and information security, applied cryptography, blockchain, SDN, and IoT. Contributions include high-impact journal and conference publications, granted patents, funded research exposure, and active academic service. The work aims to advance secure, intelligent, and socially impactful mobile network systems.

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Citation counts may vary across databases; links redirect to Google Scholar or publisher-accessible pages.