Adam Wierman’s research strives to make the networked systems that govern our world sustainable and resilient. His lab develops new mathematical tools in machine learning, optimization, control, and economics and applies these tools to design new algorithms and markets with provable guarantees that can be deployed in data centers, the electricity grid, transportation systems, and beyond.
For information on joining the lab as an undergraduate, graduate, or postdoc, see here.
I actively look for new graduate students and postdocs every year, especially at the intersection of learning and control and in the broad area of smart grid markets and control. Info about applying and reaching out to me is here.
Virtual talks are a great way to keep up with research. Some that I attend and recommend are SNAPP (which bridges INFORMS APS and Sigmetrics), INFORMS AMD (which bridges OR/CS/Econ), Games Decisions and Networks, and the Math Foundations of Data Science series. At Caltech, during quarantine, we organized the “Control meets Learning” virtual seminar series and the Economic Theory at the Time of Cholera series. The LA Probability Forum is another great series.
I keep office hours during the term on Fridays from 4-5pm PT. I am available during this time for discussions with my undergraduate advisees and for any students/postdocs who would like to meet. Typically, these meetings are held in my office (ANB 215) but, during periods when Caltech is virtual, please email me or my assistant (info below) for the zoom info. You can feel free to just drop in; however, emailing ahead of time to schedule a time is preferred.