Research Focus

Distributed machine learning, security and fault-tolerance, neural computation, bio-inspired distributed algorithms, blockchains, autonomous cars, algorithm design

Education

  • PhD, Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 2017
  • MS, Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 2014

Honors & Awards

  • NSF CAREER Award, 2023
  • Best Student Paper Award Finalist, DISC 2016
  • Best Student Paper Award, SSS 2015
  • Rising Stars EECS 2018

Research Overview

Distributed machine learning, security and fault-tolerance, neural computation, bio-inspired distributed algorithms, blockchains, autonomous cars, algorithm design

Efficient and Robust Distributed Machine Learning Laboratory

Efficient and Robust Distributed Machine Learning Laboratory

Selected Research Projects

Research Centers and Institutes

Selected Publications

  • L. Su, N.H. Vaidya, Non-Bayesian Learning in the Presence of Byzantine Adversaries, Distributed Computing, Springer, 32(4), 2019, 277-289
  • L. Su, P. Yang, On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective, Neural Information Processing Systems (NIPS), 2019, 2641-2650
  • L. Su, J. Xu, Securing Distributed Gradient Descent in High Dimensional Statistical Learning, ACM on Measurement and Analysis of Computing Systems, 3(1), 2019, 12
  • L. Su, C.-J. Chang, N. Lynch, Spike-Based Winner-Take-All Computation: Fundamental Limits and Order-Optimal Circuits, Neural Computation, The MIT Press, 31(12), 2019, 2523-2561
  • Y. Chen, L. Su, J. Xu, Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent,
    ACM on Measurement and Analysis of Computing Systems, 1(2), 2017, 44

Faculty

Sep 10, 2026

Su and Fu Receive Best Paper Award at ECCV DriveX Workshop

ECE Assistant Professor Lili Su and Professor Raymond Fu, alongside their research group, received the DriveX@ECCV 2026 Best Paper Award at the DriveX Workshop during the European Conference on Computer Vision (ECCV) 2026 in Malmö for their paper titled “Post-Training in End-to-End Autonomous Driving: Taxonomy, Methods, and Challenges.”

Faculty

Aug 06, 2026

Understanding What Causes Autonomous AI Systems to Misbehave

ECE Assistant Professor Lili Su explains that recent incidents of autonomous AI systems acting out of bounds stem from training gaps and human configuration errors rather than malicious intent.

Faculty

Jan 09, 2024

Su Receives NSF CAREER Award To Strengthen Federated Learning

ECE Assistant Professor Lili Su was awarded a $611,000 NSF CAREER award for “Strengthening the Theoretical Foundations of Federated Learning: Utilizing Underlying Data Statistics in Mitigating Heterogeneity and Client Faults.”

Lili Su

Faculty

Sep 02, 2020

New Faculty Spotlight: Lili Su

Lili Su joins the Electrical and Computer Engineering department in August 2020 as an Assistant Professor.

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