Mike Gelbart

Computer science educator @

University of British Columbia

Biography

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 computer science and data science. My official job titles are Instructor in the Department of Computer Science and Option Co-Director of the Master of Data Science Program (Vancouver). For a non-exhaustive list of things that didn’t work out along the way, see my CV of Failures.

Projects

Professional Projects

I oversee and contribute to the UBC MDS blog.
I recorded my lectures from CPSC 340 (Machine Learning and Data Mining), taught at UBC in the January 2018 session.
I created a course on linear classifiers for DataCamp.
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 (now disbanded) Harvard Intelligent Probabilistic Systems group’s blog.
I wrote Embryo Development Geometry Explorer (EDGE), an image processing software package for developmental biology.

Personal Projects

I wrote The Magnum Opiate: a story of mystery, and intriguing.
I invented a new shaving technique in 2011. Photography and editing by Oren Rippel.
I participated in a Chinese speech competition as part of Princeton in Beijing in 2009.
I co-created Youth Canada, a database of enrichment opportunities and articles for Canadian high school students.

Teaching

UBC undergraduate courses:

CPSC 340: Machine Learning and Data Mining (Spring 2017, Summer 2017, Spring 2018, Fall 2018)
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 572: Supervised Learning II (Spring 2017, Spring 2018, Spring 2019)
DSCI 571: Supervised Learning I (Fall 2018)
DSCI 551: Descriptive Statistics and Probability for Data Science (Fall 2018)
DSCI 563: Unsupervised Learning (Spring 2018)
DSCI 511: Programming for Data Science (Fall 2016)
DSCI 521: Computing Platforms for Data Science (Fall 2016)

Contact

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