mike wu

PhD Candidate
Computer Science
Stanford University

Room 334
Jordan Hall
Stanford, CA 94025
wumike [at] stanford [dot] edu

about     github     blog    

I am a PhD student at Stanford, where I work with Noah Goodman and Stefano Ermon. My current research interests are in bayesian deep learning, sampling methods, and inference in generative models. I am supported by the NSF GRFP grant.

I completed my undergrad in computer science at Yale University ('16). I also briefly spent time abroad at University of Oxford with Frank Wood, and at Harvard with Finale Doshi-Velez.


Conference Papers
Mike Wu, Yura Perov, Frank Wood, Hongseok Yang, William Smith. Spreadsheet Probabilistic Programming. The International Conference on Probabilistic Programming (PROBPROG), 2018.

Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez. Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. Association for the Advancement of Artificial Intelligence (AAAI), 2018. Spotlight presentation.

Marzyeh Ghassemi, Mike Wu, Michael C. Hughes, Finale Doshi-Velez. Predicting intervention onset in the ICU with switching statespace models. Joint Summits on Translational Science (AMIA), 2017. Nominated for Clinical Informatics Research Award.

Mike Wu, Marzyeh Ghassemi, Mengling Feng, Leo Anthony Celi, Peter Szolovitz, Finale Doshi-Velez. Understanding vasopressor intervention and weaning: Risk prediction in a public heterogeneous clinical time series database. Journal of the American Medical Informatics Association (JAMIA), 2016.

Mike Wu, Madhu Krishnan. Edge-based Crowd Detection from Single Image Datasets. International Journal of Computer Science Issues (IJCSI), 2013.

Madhu Krishnan, Mike Wu, Young Kang, Sarah Lee. Autonomous Mapping and Navigation through Utilization of Edge-based Optical Flow and Time-to-Collision. ARPN Journal of Engineering and Applied Sciences, 2012.

Unpublished Preprints
Mike Wu, Jessica Cisewski, Larry Wasserman, Brittany Fasy, Mark Lovell, Wojciech Hellwing. Topological Hypothesis Tests for Large-Scale Structure of the Universe. Work in progress.

Mike Wu. Financial Market Prediction Using Self-Organizing Maps. arXiv, 2015.

Stephen Yu, Mike Wu. Position and Vector Detection of Blind Spot motion with the Horn-Schunck Optical Flow. arXiv, 2011. Intel ISEF Finalist: Third place category award, 2011. Siemens Semifinalist, 2012. XSEDE Best student poster, 2011.


Teaching Assistantships
CPSC437: Operating System Concepts (Yale Spring 2016) with Avi Silberschatz
MGT656: Management of Software Development (Yale Fall 2015) with Kyle Jensen


Visiting engineer at Facebook Applied Machine Learning (AML) group.
Software engineer at Lattice.
Co-founder at Invrea.
Intern at Ionis Pharma.


Probabilistic programming workshop University of Southampton 2016
Generative models in the medical domain OpenAI 2016
Introduction to deep learning Yale Technology Conference 2015


Co-founded YHack in 2013.
Augmented reality prize. Angelhack, 2018.
Telesign API 1st place prize. API World hackathon, 2017.
First place prize. Truface.ai hackathon, 2017.
Top 8 projects. Dropbox API prize. HackMIT, 2014.