I head the Data to Actionable Knowledge (DtAK) group at Harvard Computer Science. We use probabilistic methods to address many decision-making scenarios involving humans and AI. Our work spans specific application domains (health and wellness) as well as broader socio-technical questions around human-AI interaction, AI accountability, and responsible and effective AI regulation. Our work falls into three major areas:
Probabilistic modeling and inference (especially Bayesian models): How can we characterize the uncertainty in large, heterogeneous data? How can we fit models that will be useful for downstream decision-making? How can we build models and inference techniques that will behave in expected and desired ways?
Decision-making under uncertainty (especially sequential decision-making): How can we optimize policies given batches of heterogeneous data? How can we provide useful information, even if we can't solve for a policy? How can we characterize the limits of our ability to provide decision support?
Interpretability and statistical methods for validation: How can we estimate the quality of a policy from batch data? How can we expose key elements of a model or policy for expert inspection?
Short Bio (+ CV, photo)
Getting in touch
In person: My office hours are generally 3:30-4:30 on TUESDAYS. When I have my office hour, please come in (don't wait outside!!) even if other people are inside. I will ask everyone about what they want to discuss, and discuss similar topics together. I usually give class-related questions first priority, then switch over to general topics and then back again. If you have a form that needs signing, just interrupt. I will continue holding office hours via zoom. Link: https://harvard.zoom.us/j/768366874, code 112358. Sometimes there are very few/no people, sometimes there are many. Especially if there are many, it helps if you can think of ways to succinctly share thoughts/questions to enable everyone to have a chance. I welcome people waiting to provide thoughtful input on whatever is being discussed; if you don't want others hearing, please request a break-out.
Email: I get a lot of email, and my inbox is
generally an absolute disaster. Unfortunately, many times I don't even have a chance to read all my email. Please help me by reading my website first, having an informative subject line, and pinging again if you feel like I might have lost your mail. Office hours don't require an email first, and are a great time to also catch me in person.
Phone: I don't have an office phone any more. Please email or stop by in person.