Bahman Abolhassani

About Me

I’m currently a Presidential Postdoctoral Fellow at Virginia Tech, where I’m collaborating with the Link + License + Launch department to commercialize a GPU-based ultra-fast scheduler. We’ve secured a proof-of-concept grant and are actively working toward launching a startup around this technology.

As a researcher, I work at the intersection of machine learning and wireless communications. My recent projects include using reinforcement learning to counteract jamming attacks, optimizing URLLC/eMBB multiplexing strategies, and reducing the cost of LLM APIs through efficient caching techniques.

I’m passionate about building practical systems grounded in solid theoretical foundations.

Projects

• Ultrafast Scheduler for 5G/NextG: A GPU-accelerated scheduler for real-time radio networks.
• RL-based URLLC/eMBB Puncturing: Reinforcement learning for traffic multiplexing in 5G systems.
• Multi Agent Reinforcement Learning for Cobatting ammer and Interference over the wireless edge: We developed off-policy and on-policy approached and compared their advantages and disadvantages.

Publications

• Model-Based and Model-Free Learning-Based Caching for Dynamic Content – MILCOM 2024
• Cyrus: A DRL-based puncturing solution to URLLC/eMBB multiplexing in O-RAN – ICCCN 2024
• Optimal push and pull-based edge caching for dynamic content – IEEE/ACM TON 2024
• SwiftCache: Model-based learning for dynamic content caching in CDNs – arXiv preprint 2024
• Optimal load-splitting and distributed-caching for dynamic content over the wireless edge – IEEE/ACM TON 2023
• Fresh caching of dynamic content over the wireless edge – IEEE/ACM TON 2022
• Single vs distributed edge caching for dynamic content – IEEE/ACM TON 2021
• Optimal load-splitting and distributed-caching for dynamic content – WiOpt 2021
• Fresh caching for dynamic content – IEEE INFOCOM 2021
• Delay gain analysis of wireless multicasting for content distribution – IEEE/ACM TON 2020
• Achieving freshness in single/multi-user caching of dynamic content – WiOpt 2020
• Wireless multicasting for content distribution: Stability and delay gain analysis – IEEE INFOCOM 2019
• Statistical studies of fading in underwater wireless optical channels – IEEE Transactions on Communications 2018
• Resource Allocation in Ultra-low Latency and Ultra-reliable 5G Wireless Networks – Sharif University Thesis, 2017

Education

• Ph.D. in Electrical and Computer Engineering, The Ohio State University – Aug. 2017 – May. 2023
• Master’s Degree in Electrical and Computer Engineering, Sharif University of Technology – Sep. 2015 – Aug. 2017
• Bachelor’s Degree in Electrical and Computer Engineering, Sharif University of Technology – Sep. 2010 – Sep. 2015

Work Experience

• Presidential Postdoctoral Fellow, Virginia Tech – May 2023 – Present
  • Led the commercialization of a state-of-the-art scheduler for NextG networks.
  • Authored and submitted multiple federal and state grant proposals.
• Research Assistant, IPS Lab – Aug 2017 – May 2023
  • Designed ML algorithms for optimizing caching and latency in IoT networks.
• Research Assistant, ONRL – Sep 2015 – Aug 2017
  • Simulated and modeled underwater optical wireless channels under turbulence.

Blog

Coming soon! I'll be sharing thoughts on AI research, engineering workflows, and lessons from books I read.

Get In Touch

You can reach me at your@email.com or message me on LinkedIn.