Jishu Medhi
Assistant Professor
Department of Engineering and Technology
Contact Information
Jishu Medhi
Assistant Professor
Department of Engineering and Technology
Education
- Ph.D. Mechatronics Engineering, Kent State University
- M.S. Aerospace Engineering & Engineering Mechanics, University of Cincinnati
- B.Tech in Mechanical Engineering, National Institute of Technology, Trichy (India)
Research & Academic Interests
- Robotics
- Artificial Intelligence
- Mechatronics
- Unmanned Aerial Vehicles
Publications
- Medhi, J. K., Chen, X., Pan, M., & Li, P. (2026). Secure Outsourcing of Deep Active Learning in the IoT: From Both Sample Selection and Model Update Perspectives. IEEE Transactions on Network Science and Engineering, 13, 2439-2453.
- Medhi, J., Liu, R., Wang, Q., & Chen, X. (2025). A lightweight and efficient intrusion detection system (IDS) for unmanned aerial vehicles. Neural Computing and Applications, 37(20), 15819-15836.
- Medhi, J. K., Liu, R., Wang, Q., & Chen, X. (2023). Robust multiagent reinforcement learning for UAV systems: countering Byzantine attacks. Information, 14(11), 623.
- Medhi, J. K., Ren, P., Hu, M., & Chen, X. (2023). A deep multi-task learning approach for bioelectrical signal analysis. Mathematics, 11(22), 4566.
- Medhi, J. K., Huang, C., Liu, R., & Chen, X. (2023). Byzantine Resilient Reinforcement Learning for Multi-Agent UAV Systems. In AIAA SCITECH 2023 Forum (p. 2472).
- Chen, X., Ren, P., & Medhi, J. (2022). Deep Multi-task Learning Approach for Bioelectrical Signal Analysis. In Computational Intelligence and Image Processing in Medical Applications (pp. 189-212).
- Medhi, J. K., & McGhan, C. L. (2018). Towards a Modular Architecture for Intelligent Aerial Manipulator Systems. In 2018 AIAA Information Systems-AIAA Infotech@ Aerospace (p. 1631).
Education
- Ph.D. Mechatronics Engineering, Kent State University
- M.S. Aerospace Engineering & Engineering Mechanics, University of Cincinnati
- B.Tech in Mechanical Engineering, National Institute of Technology, Trichy (India)
Research & Academic Interests
- Robotics
- Artificial Intelligence
- Mechatronics
- Unmanned Aerial Vehicles
Publications
- Medhi, J. K., Chen, X., Pan, M., & Li, P. (2026). Secure Outsourcing of Deep Active Learning in the IoT: From Both Sample Selection and Model Update Perspectives. IEEE Transactions on Network Science and Engineering, 13, 2439-2453.
- Medhi, J., Liu, R., Wang, Q., & Chen, X. (2025). A lightweight and efficient intrusion detection system (IDS) for unmanned aerial vehicles. Neural Computing and Applications, 37(20), 15819-15836.
- Medhi, J. K., Liu, R., Wang, Q., & Chen, X. (2023). Robust multiagent reinforcement learning for UAV systems: countering Byzantine attacks. Information, 14(11), 623.
- Medhi, J. K., Ren, P., Hu, M., & Chen, X. (2023). A deep multi-task learning approach for bioelectrical signal analysis. Mathematics, 11(22), 4566.
- Medhi, J. K., Huang, C., Liu, R., & Chen, X. (2023). Byzantine Resilient Reinforcement Learning for Multi-Agent UAV Systems. In AIAA SCITECH 2023 Forum (p. 2472).
- Chen, X., Ren, P., & Medhi, J. (2022). Deep Multi-task Learning Approach for Bioelectrical Signal Analysis. In Computational Intelligence and Image Processing in Medical Applications (pp. 189-212).
- Medhi, J. K., & McGhan, C. L. (2018). Towards a Modular Architecture for Intelligent Aerial Manipulator Systems. In 2018 AIAA Information Systems-AIAA Infotech@ Aerospace (p. 1631).