Adam Wierman is the Carl F. Braun Professor of Computing and Mathematical Sciences and a key member of the Computer Science faculty at CalTech - California Institute of Technology. He earned his B.S. in Computer Science with an additional major in Mathematics in 2001, M.S. in Computer Science in 2004, and Ph.D. in Computer Science in 2007 from Carnegie Mellon University, where his dissertation addressed 'Scheduling for today’s computer systems: Bridging theory and practice.' Wierman joined Caltech in 2007 as Assistant Professor, was promoted to Professor in 2012, and appointed Braun Professor in 2024. He served as Executive Officer of the Department of Computing and Mathematical Sciences from 2015 to 2020 and Director of Information Science and Technology from 2016 to 2025. Additionally, he has advised the Linde Institute of Economic and Management Sciences and the Resnick Institute for Sustainability.

Wierman's research develops mathematical tools in machine learning, optimization, control, and economics to enhance the sustainability and resilience of networked systems, including data centers, electricity grids, and transportation networks. He co-authored the book The Fundamentals of Heavy Tails: Properties, Emergence, and Estimation (Cambridge University Press, 2022). Prominent publications encompass 'Robustness and Consistency in Linear Quadratic Control with Untrusted Predictions' (ACM Sigmetrics, 2022), 'Online Optimization with Feedback Delay and Nonlinear Switching Cost' (ACM Sigmetrics, 2022), 'Scalable Reinforcement Learning for Multi-Agent Networked Systems' (Operations Research, 2022), and 'Transparency and Control in Platforms for Networked Markets' (Operations Research, 2022). His achievements include the 2025 ACM Fellowship, 2024 IEEE Fellowship for contributions to algorithms and scheduling theory in sustainable computing, ACM Distinguished Member recognition, ACM Sigmetrics Rising Star Award (2011), NSF CAREER Award (2009), IEEE William R. Bennett Prize (2014), and multiple best paper awards from conferences such as IEEE INFOCOM, ACM Sigmetrics, IFIP Performance, and NeurIPS spotlights. Wierman has received teaching awards from Caltech and Carnegie Mellon, served as Associate Editor for INFORMS Journal of Computing, ACM TOMPECS, and IEEE Transactions on Networking, and chaired programs for ACM e-Energy (2022) and ACM Sigmetrics (2018). His algorithms have influenced industry practices in sustainable data centers.

Professional Email: adamw@caltech.edu