Biography

Kenneth is a Ph.D. student in Electrical and Computer Engineering at Purdue University, advised by Professor Murat Kocaoglu. His research centers on causal discovery and its applications in machine learning, with a particular focus on invariant prediction and root cause analysis of failures in microservices. He holds a B.S. in Computer Science and Mathematics from Brigham Young University–Hawaii and an M.S. in Statistics from UC Davis. Kenneth has received best reviewer awards from AISTATS, UAI, and ICLR, and has completed internships at Dell EMC, Newday Investing, Bayer, Experian DataLabs, Genentech, and Amazon.

📰 News

  • May 2025: I was selected as a notable reviewer by ICLR 2025.

  • May 2025: My paper titled ‘Root Cause Analysis of Failures from Partial Causal Structures’ was accepted by UAI 2025.

  • May 2025: My paper titled ‘Constraint-based Causal Discovery from a Collection of Conditioning Sets’ was accepted by UAI 2025.

  • Apr 2025: I was selected as a best reviewer by AISTATS 2025.

  • Jul 2024: I was selected as a top reviewer by UAI 2024.

  • Jun 2024: My paper titled ‘RCPC: A Sound Causal Discovery Algorithm under Orientation Unfaithfulness’ was accepted by the 9th Causal Inference Workshop at UAI 2024.

  • Jun 2024: My paper titled ‘Constraint-based Causal Discovery from a Collection of Conditioning Sets’ was accepted by the 9th Causal Inference Workshop at UAI 2024.

  • Jun 2023: I was awarded a scholarship to attend UAI 2023.

  • May 2023: My paper titled ‘Finding Invariant Predictors Efficiently via Causal Structure’ was accepted by UAI 2023.

📝 Publications ( indicates equal contribution)

  • Root Cause Analysis of Failures from Partial Causal Structures
    A. Ikram , K. Lee , S Mitra, S Saini, S Bagchi, M. Kocaoglu. Uncertainty in Artificial Intelligence (UAI), 2025. [paper] [bibtex]
  • Constraint-based Causal Discovery from a Collection of Conditioning Sets
    K. Lee, B. Ribeiro, M. Kocaoglu. Uncertainty in Artificial Intelligence (UAI), 2025. [paper] [bibtex]
  • RCPC: A Sound Causal Discovery Algorithm under Orientation Unfaithfulness
    K. Lee, M. Kocaoglu. 9th Causal Inference Workshop at UAI, 2024. [paper] [bibtex]
  • Finding Invariant Predictors Efficiently via Causal Structure
    K. Lee, M. M. Rahman, M. Kocaoglu. Uncertainty in Artificial Intelligence (UAI), 2023. [paper] [bibtex]
  • An open repository of real-time COVID-19 indicators
    A. Reinhart, et al. Proceedings of the National Academy of Sciences (PNAS), 2021. [paper] [bibtex]
  • Applying a passive network reconstruction technique to Twitter data in order to identify trend setters
    V. Chetty, N. Woodbury, J. Brewer, K. Lee, S. Warnick. IEEE Conference on Control Technology and Applications (CCTA), 2017. [paper] [bibtex]