• You may also want to check out our shiny group website.  Also, this website continues to lack older things from my PhD; that is on my old website.

    Interests

    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)

    Finale Doshi-Velez is a Gordon McKay Professor in Computer Science at the Harvard Paulson School of Engineering and Applied Sciences.  She completed her MSc from the University of Cambridge as a Marshall Scholar, her PhD from MIT, and her postdoc at Harvard Medical School.  Her interests lie at the intersection of machine learning, healthcare, and interpretability.
     
    Selected Additional Shinies: BECA recipient, AFOSR YIP and NSF CAREER recipient; Sloan Fellow; IEEE AI Top 10 to Watch
     

    Getting in touch

    In person: My office hours are currently 10-11am on MONDAYS, but my 2022 schedule is still somewhat in flux.  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.