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 also been interested in the tail latency behavior in queueing systems and in hierarchical, contrastive, and goal-conditioned reinforcement learning, with an eye towards practical generalization performance in procedurally-generated environments.

Publications [Google Scholar]

  1. An Upper Bound on the M/M/k Queue With Deterministic Setup Times. Jalani K. Williams, Mor Harchol-Balter, Weina Wang. Oper. Res. (2025). Submitted. [pdf]
  2. The M/M/k with Deterministic Setup Times. Jalani K. Williams, Mor Harchol-Balter, Weina Wang. ACM SIGMETRICS (2023). [pdf]
  3. Probing to Minimize Weina Wang, Anupam Gupta, Jalani K. Williams (random author order). ITCS 2022. [link]
  4. 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]