Yaniv Yacoby


PhD Student @ Harvard CS


I am a PhD student in Machine Learning at Harvard University, working with Professor Finale Doshi-Velez at the Data to Actionable Knowledge Lab (DtAK). I work on uncertainty quantification and tractable approximate inference for deep Bayesian latent variable models with applications in health-care.

Before joining DtAK, I got a MM in Contemporary Improvisation from the New England Conservatory in 2016 and a AB in Computer Science from Harvard College in 2015. You can find my music page here.


You can find the most updated list on my google scholar page.

Teaching & Mentoring

I created and organized a workshop for incoming PhD students at Harvard about managing the multi-faceted challenges of being a PhD student (Fall 2020).  Workshop content can be found here.

I was a final project mentor, as well as a research mentor for students continuing their research after completing “Stochastic Methods for Data Analysis – Inference and Optimization” (AM207) (Fall 2019 - present).

I am a mentor for the Women in Data Science (WiDS) Cambridge datathon workshop, 2019-2020.

I previously served as a teaching fellow for a number of courses at Harvard: Advanced Machine Learning (CS281) Fall 2018, Systems Programming and Machine Organization (CS61) Fall 2015, and Intro to Computer Science I (CS50) Fall 2012.


Email: yanivyacoby [AT] g [DOT] harvard [DOT] edu