Yaniv Yacoby

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I’m an Assistant Professor of Computer Science at Wellesley College, where I lead the Model-Guided Uncertainty (MOGU) Lab. My research focuses on developing new machine learning methods to advance the understanding, prediction, and prevention of suicide and related behaviors.

Before joining Wellesley, I was a postdoctoral fellow at the Nock Lab in the Department of Psychology at Harvard University and Mass General Hospital. I completed my Ph.D. in Machine Learning at the Data to Actionable Knowledge Lab (DtAK) at Harvard, working with Professor Finale Doshi-Velez. I had the pleasure of interning with the Biomedical-ML team at Microsoft Research New England (Summer 2021). Lastly, I received a Master’s of Music in Contemporary Improvisation from the New England Conservatory (2016) and a Bachelor’s of Arts in Computer Science from Harvard University (2015). I am currently a performing musician.

Selected Publications

For a complete list, see my publications page.

  1. Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders
    Y Yacoby W Pan and F Doshi-Velez
    Accepted @ Workshop at AABI 2024
  2. Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health
    Y Yacoby J Girash and D Parkes
    Accepted @ SIGCSE 2023 Oral Presentation
  3. JMLR ICML UDL
    Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables
    *Y Yacoby *W Pan and F Doshi-Velez
    Accepted @ JMLR 2022
    Previous version accepted @ ICML UDL 2019 Spotlight Talk