Michael (Mike) Gelbart

Instructor, Department of Computer Science
Co-Director, Master of Data Science program Vancouver Option

The University of British Columbia
Room 225, ICICS/CS Building
2366 Main Mall, Vancouver, BC V6T 1Z4, Canada

mgelbart (ta) cs (tod) ubc (tod) ca

LinkedIn, CV of failures

Hello! I am the ~40 trillion gut bacteria, plus some smaller number of human cells, collectively known as Mike Gelbart. I was born and raised in beautiful Vancouver, British Columbia, Canada. As an undergraduate student at Princeton University, I studied physics and worked on research projects in biophysics. In graduate school I switched fields to computer science and received my PhD from the machine learning group at Harvard University. At UBC, I teach for the Department of Computer Science and the Master of Data Science program.


I oversee and contribute to the UBC MDS blog.

I created a course on linear classifiers for DataCamp.

I posted my lectures from CPSC 340 (Machine Learning and Data Mining), taught at UBC in the January 2018 session.

I wrote Rhomboid, a set of Python scripts used to deliver courses via GitHub. There is also a demo video.

I was one of the developers of Spearmint, a package for optimizing expensive functions using Bayesian optimization.

I wrote some blog posts for the HIPS group blog.

I wrote Embryo Development Geometry Explorer (EDGE), an image processing software package for developmental biology.

I co-created Youth Canada, a database of enrichment opportunities and articles for Canadian high school students.

I wrote The Magnum Opiate: a story of mystery, and intriguing.

This time lapse video from 2011 demonstrates a new shaving technique that I developed. Photography and editing by Oren Rippel.

This is my speech for a Chinese speech competition that I participated in as part of Princeton in Beijing in 2009.

UBC Teaching

Undergrad courses:

CPSC 340: Machine Learning and Data MiningSpring 2017, Summer 2017, Spring 2018, Fall 2018 [course website]
CPSC 303: Numerical Approximation and DiscretizationSpring 2016 [course website]
Science One Computer Science2015-2016 [program website] [course website]
APSC 160: Introduction to Computation in Engineering DesignFall 2015

Master of Data Science courses (4 weeks each):

DSCI 571: Supervised Learning IFall 2018
DSCI 551: Descriptive Statistics and Probability for Data ScienceFall 2018
DSCI 563: Unsupervised LearningSpring 2018
DSCI 572: Supervised Learning IISpring 2017, Spring 2018
DSCI 511: Programming for Data ScienceFall 2016
DSCI 521: Computing Platforms for Data ScienceFall 2016


Machine Learning:

A Case for Efficient Accelerator Design Space Exploration via Bayesian Optimization. IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2017. With Brandon Reagen, José Miguel Hernández-Lobato, Robert Adolf, Paul Whatmough, David Brooks and Gu-Yeon Wei. [BibTeX]

A General Framework for Constrained Bayesian Optimization using Information-based Search. Journal of Machine Learning Research (JMLR), 17(160):1-53, 2016. With José Miguel Hernández-Lobato, Ryan P. Adams, Matthew W. Hoffman, and Zoubin Ghahramani. [PDF] [BibTeX]

Constrained Bayesian Optimization and Applications. PhD Thesis, 2015. [PDF] [BibTeX] [defense slides]

Predictive Entropy Search for Bayesian Optimization with Unknown Constraints. In International Conference on Machine Learning (ICML), 2015. With José Miguel Hernández-Lobato, Matthew W. Hoffman, Ryan P. Adams, and Zoubin Ghahramani. [PDF] [Supplement] [BibTeX]

Bayesian Optimization with Unknown Constraints. In Uncertainty in Artificial Intelligence (UAI), 2014. With Jasper Snoek and Ryan P. Adams. [PDF] [BibTeX]

Learning Ordered Representations with Nested Dropout. In International Conference on Machine Learning (ICML), 2014. With Oren Rippel and Ryan P. Adams. [PDF] [BibTeX]

Segmentation Fusion for Connectomics. In International Conference on Computer Vision (ICCV), 2011. With Amelio Vázquez-Reina, Daniel Huang, Jeff Lichtman, Eric Miller, and Hanspeter Pfister. [PDF] [BibTeX]


Volume conservation principle involved in cell lengthening and nucleus movement during tissue morphogenesis. Proceedings of the National Academy of Sciences (PNAS), 2012. With Bing He, Adam C. Martin, Stephan Thiberge, Eric F. Wieschaus, and Matthias Kaschube. [PDF] [Supplement] [BibTeX]

Filament Depolymerization Can Explain Chromosome Pulling during Bacterial Mitosis. PLoS Computational Biology, 2011. With Edward J. Banigan, Zemer Gitai, Ned S. Wingreen, and Andrea J. Liu. [PDF] [BibTeX]

Integration of contractile forces during tissue invagination. Journal of Cell Biology (JCB), 2010. With Adam C. Martin, Rodrigo Fernandez-Gonzalez, Matthias Kaschube, and Eric F. Wieschaus. [PDF] [BibTeX]

Foraging Strategies for Dictyostelium discoideum. Undergraduate Thesis, 2010. [PDF] [BibTeX] [Thesis reflections essay]