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Academic Experts

Dr. Himanshu Agrawal

Biography

Dynamic professional experience of nearly 15 years as an academician. An excellent track record and significant contributions to teaching and research mark the academic journey. The research areas are Artificial Intelligence, Machine Learning, and Wireless Networks. Currently supervising one PhD scholar and successfully guided two Master's theses.

Dr. Himanshu Agrawal holds certifications from prestigious organisations like Wipro India Pvt. Ltd, and Dell. A committed team-builder and communicator, he integrates leadership and innovation into his academic endeavours.

Research Highlights

Dr. Himanshu Agrawal has made significant research contributions in Wireless Networks, Smart Grid, Machine Learning and Recommendation Systems. His work primarily focuses on decision-making protocols using various optimisation techniques to improve spectrum utilisation. Dr. Agrawal’s research addresses realworld challenges in dynamic networks. It demonstrates mathematical and complexity analysis in optimisation algorithms, earning him recognition in the national and international academic fraternity.

Areas of Interest
  • Cellular & Ad-hoc Networks
  • Wireless Sensor Networks
  • Mobile Intelligent Networks
  • Cognitive Networks
  • Work Experience: Teaching Experience: About 5 Years
  • Presently working as Lecturer in Department of Computer Science & Engineering at Jaypee Institute of Information Technology (JIIT)
  • Sector 128
  • Noida
  • U.P. from 10-12-2011 to till date.
  • Worked as Lecturer in Department of Computer Science & Engineering (CSE) at UIT
  • RGPV
  • Bhopal
  • M.P. from 09/2008 to 05/2009 (07 months).
  • Worked as Lecturer in Department of Computer Science & Engineering (CSE) at Samrat Ashok Technological Institute
  • Vidisha
  • M.P. from 09/2007 to 08/2008 (11 months).
Publications
  • Chandola, Deeksha, et al. "Forecasting directional movement of stock prices using deep learning." Annals of Data Science 10.5 (2023): 1361-1378.
  • Agrawal, Himanshu, and Krishna Asawa. "Distributed learning algorithm with synchronized epochs for dynamic spectrum access in unknown environment using multi-user restless multi-armed bandit." Journal of King Saud University-Computer and Information Sciences 34.8 (2022): 5435-5447.
  • Jain, Rupali, et al. "A hybrid bio-inspired computing approach for buzz detection in social media." Evolutionary Intelligence 15.1 (2022): 349-367.
  • Pilani, A., Mathur, K., Agrawald, H., Chandola, D., Tikkiwal, V. A., & Kumar, A. (2021). Contextual Bandit Approachbased Recommendation System for Personalized Web-based Services. Applied Artificial Intelligence, 35(7), 489– 504.
  • H. Agrawal and K. Asawa, "Decentralized Learning for Opportunistic Spectrum Access: Multiuser Restless Multiarmed Bandit Formulation," in IEEE Systems Journal, vol. 14, no. 2, pp. 2485-2496, June 2020,