About Me

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Hi! I'm Jalani Williams, a first-year PPFP Postdoctoral Fellow working in the Electrical Engineering and Computer Science (EECS) department at the University of Michigan, where I mainly work with Lei Ying. Before I came to Michigan, I was a PhD student in the Computer Science department at Carnegie Mellon, advised by Weina Wang. If you're interested, you can find my thesis proposal here and a copy of my thesis here.

Research Interests

Broadly, I'm interested in applying techniques from applied probability and decision making under uncertainty to guide the development of robust data-driven systems. In my thesis work, I focused on investigating how the energy-saving methods being used in today’s datacenters affect the fundamental characteristics of their latency performance. Recently, I've been interested in representation learning in reinforcement learning;

Publications [Google Scholar]

  1. The M/M/k with Deterministic Setup Times. Jalani K. Williams, Mor Harchol-Balter, Weina Wang. ACM SIGMETRICS 2023. [pdf]
  2. Probing to Minimize Weina Wang, Anupam Gupta, Jalani K. Williams (random author order). ITCS 2022. [link]
  3. The Mouse Action Recognition System (MARS) software pipeline for automated analysis of social behaviors in mice. Cristina Segalin, Jalani Williams, Tomomi Karigo, et al. eLife 2021. [link]