Nathaniel Hudson, Ph.D.
A brief introduction.

312 John Crerar Library
5730 S Ellis Ave
Chicago, IL 60637
I am a computer scientist, currently serving as a Postdoctoral Scholar at Globus Labs out of the University of Chicago’s Department of Computer Science.
A high-level description of my research is the design of systems for serving AI on edge computing infrastructure — i.e., Edge Intelligence (EI) — for smart city applications. More specifically, my research centers around challenges related to resource limitations available at the edge for supporting EI. Trade-offs between latency, accuracy, resource usage, etc. are common themes in my work.
Some areas of study my research touches include (but are not limited to):
- federated learning
- service placement and request scheduling
- lossy compression techniques
- social mining
- modeling of information diffusion processes
- interdependent and complex networks
- cyber-physical systems
recent news
Feb 27, 2023 | I am thrilled to once again be serving as a TPC member for the 2023 IEEE SECON conference. |
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Jan 11, 2023 | I will be serving as a TPC member for the 2023 IEEE EDGE conference. |
Jan 5, 2023 | Short paper on balancing trade-offs in federated learning has been accepted for the Work-in-Progress session of the 2023 IEEE PerCom Conference in Atlanta, GA. |
Nov 1, 2022 | I will be attending the 2022 ACM/IEEE Supercomputing Conference in Dallas Texas. |
Sep 26, 2022 | I will be serving as a TPC member for the 2023 IEEE DCOSS-IoT conference. |
Sep 1, 2022 | I will serve as a TPC member for the 2023 IEEE PerCom Work-In-Progress (WIP) session. |
Aug 4, 2022 | I will be attending Department of Energy Advanced Research Directions on AI for Science and Security (AI4SES) summer workshop series from August 16-18. |
May 25, 2022 | I was selected to serve as a TPC member for the 2022 IEEE SECON conference. |
Apr 13, 2022 | I successfully defended my doctoral dissertation entitled, “Smart Decision-Making via Edge Intelligence for Smart Cities”. |
Apr 11, 2022 | My paper entitled, “Smart Edge-Enabled Traffic Light Control: Improving Reward-Communication Trade-Off with Federated Reinforcement Learning,” has been accepted for publication through the main conference track of IEEE SMARTCOMP 2022. |