Mike Gelbart

Machine learning educator @

University of British Columbia

Biography

About me: 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 computer science and data science. My official job titles are Associate Professor of Teaching in the Department of Computer Science and Option Co-Director of the Master of Data Science Program (Vancouver). I am also Co-Founder of a new high school, the Vancouver Independent School for Science and Technology. For a non-exhaustive list of things that didn’t work out along the way, see my CV of Failures.

Projects

Professional Projects

I co-created the Key Capabilities in Data Science continuing education program at UBC. The interactive lessons associated with these courses are publicly available: see Programming in Python for Data Science and Introduction to Machine Learning.
I created a new UBC course, CPSC 330: Applied Machine Learning.
I posted recordings of my lectures from several UBC courses:
- CPSC 330: Applied Machine Learning (Sep-Dec 2020, 23 lectures)
- CPSC 340: Machine Learning and Data Mining (Jan-Apr 2018, 33 lectures)
- DSCI 572: Supervised Learning II (Jan-Feb 2020, 8 lectures)
- DSCI 512: Algorithms and Data Structures (Oct-Nov 2019, 8 lectures)
- DSCI 511: Programming for Data Science (Sep 2019, 4 lectures)
I oversee and contribute to the UBC MDS blog.
I created a course on linear classifiers for DataCamp. Unfortunately, since then there has been significant controversy surrounding the company; see this article. I would urge anyone considering their service to familiarize yourself with the situation to make an informed decision.
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.
In grad school I wrote some posts for my research group’s blog. One that may be of interest is on compressing Genomes.
I wrote Embryo Development Geometry Explorer (EDGE), an image processing software package for developmental biology.

Personal Projects

Joel Fox and I created two puzzle games: Line of Sight and Herding Hero. My favourite puzzle games are The Witness and Portal 2 (especially the co-op mode).
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.
I participated in a Chinese speech competition as part of Princeton in Beijing in 2009.

Teaching

UBC undergraduate courses:

CPSC 330: Applied Machine Learning (Spring 2020, Fall 2020)
CPSC 340: Machine Learning and Data Mining (Spring 2017, Summer 2017, Spring 2018, Fall 2018, Spring 2020, Fall 2021)
CPSC 303: Numerical Approximation and Discretization (Spring 2016)
Science One Computer Science (Fall 2015, Spring 2016)
APSC 160: Introduction to Computation in Engineering Design (Fall 2015)

UBC Master of Data Science courses (4 weeks each):

DSCI 512: Algorithms and Data Structures (Fall 2019, Fall 2020, Fall 2021)
DSCI 572: Supervised Learning II (Spring 2017, 2018, 2019, 2020)
DSCI 571: Supervised Learning I (Fall 2018)
DSCI 551: Descriptive Statistics and Probability for Data Science (Fall 2018, Fall 2021)
DSCI 563: Unsupervised Learning (Spring 2018)
DSCI 511: Programming for Data Science (Fall 2016, 2019)
DSCI 521: Computing Platforms for Data Science (Fall 2016)

Contact

Room 225, ICICS/CS Building, 2366 Main Mall, Vancouver, BC V6T 1Z4, Canada