Dr. Jaya Prakash CHAMPATI

Dr. Jaya Prakash CHAMPATI

Research Assistant Professor

    • PhD - University of Toronto, Canada
  • Joining date: November 2020


Hi there! I am Jaya Prakash — you can call me Jaya or JP. I hail from Malkipuram, a small coastal village in Andhra Pradesh, India. I received my PhD from the Department of Electrical and Computer Engineering, University of Toronto, Canada 2017. Before joining PhD, I was part of the Mobile and Wireless Group developing the LTE MAC layer at Broadcom Communications, Bangalore, India. I received my master’s degree from the Indian Institute of Technology (IIT) Bombay, India, in 2010 and my undergraduate degree from the National Institute of Technology (NIT) Warangal, India, in 2008.  Before joining IMDEA, I was a postdoc in the Information Science and Engineering Division, EECS, KTH Royal Institute of Technology, Sweden.

My Motto: Research is our search for Truth and Truth doesn’t differentiate race, religion, country, caste, creed, etc.

(“The greatest name man ever gave to God is Truth” – Swami Vivekananda)


I am interested in decision-making, learning, and resource allocation/scheduling problems that arise in networking and information systems, in general. My current research focus is on efficient inference in Edge AI systems, working on Hierarchical Inference, Inference Offloading, and the Age of Information. Some of the mathematical tools used in my research so far include Regret Analysis, Design and Analysis of Approximation Algorithms, Queuing Theory, Stochastic Network Calculus,  and Markov Decision Processes.

Feb 2024: Presented Improved Decision Module for Hierarchical Inference at AAAI Deployable AI workshop.

Feb 2024: Our first work on Hierarchical Inference is published in IEEE Transaction on Machine Learning in Communications and Networking (TMLCN). Congrats Vishnu! Pdf available on arXiv.

Feb 2024: Happy to be recognized as a Distinguished Member of INFOCOM 2024 TPC!

October 2023: Invited talk: “Getting the Best of Both Worlds (IoT and Edge/cloud) using Hierarchical Inference”, IEEE World Forum on IoT, Oct. 2023.

October 2023: Poster: Improved Decision Module Selection for Hierarchical Inference in Resource-Constrained Edge Devices, Mobicom 2023.

May 2023: The Case for Hierarchical Deep Learning Inference at the Network Edge is accepted NetAI workshop, MobiSys 2023.

April 2023: Our work on Offloading Algorithms for ML inference offloading was accepted to IEEE Transactions on Parallel and Distributed Systems (TPDS). Congrats Andrea Fresa!

March 2023: Our work on Online Algorithms for Hierarchical Inference at the Network Edge is available on arXiv.

January 2023: Getting the Best of Both Worlds (IoT and Edge) using Hierarchical Inference, invited talk at Indian Institute of Science (IISC), Bengaluru, India.

Research projects


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