Students

Current

I am fortunate to work with many terrific students, including:

  • Ciara Zogheib is a PhD candidate in the Faculty of Information at the University of Toronto.

Past

In the past I have worked closely with many students, including (in rough reverse chronological order):

  • Lindsay Katz graduated with a Masters in Statistics from the Department of Statistical Sciences at the University of Toronto. We worked together for a year, and she completed a variety of projects, most notably developing a tested dataset of what was said in the Australian parliament.
  • Annie Collins graduated from the University of Toronto with an undergraduate degree specializing in applied mathematics and statistics with a minor in history and philosophy of science. We worked together for about eighteen months during which she worked on many projects including: ‘An Introduction to DoSStoolkit’ and ‘Reproducibility of COVID-19 pre-prints’. Her first job after graduation was as a data scientist at Giving Tuesday.
  • Callie Moore graduated from the University of Toronto with an undergraduate degree in engineering science. I supervised Callie’s undergraduate thesis entitled ““. Her first job after graduation was as a developer at the Investigative Journalism Foundation.
  • A Mahfouz worked with me as a Master of Information student at the University of Toronto with a background in geography. Their prior work has been largely concerned with data pipelines. A contributed to many projects including heapsofpapers.
  • Ke-Li Chiu worked with me as a Master of Information student at the University of Toronto interested in natural language processing. Ke-Li worked on: ‘On consistency scores in text data with an implementation in R’ and ‘Detecting Hate Speech with GPT-3’.
  • Paul Hodgetts worked with me as a Master of Information student at the University of Toronto. Paul put together cesR, which is an R package that makes it easier to gather and use the Canadian Election Study surveys from 1965 through to 2019, described here: https://osf.io/preprints/socarxiv/a29h8/. Paul additionally put together a fantastic logo. Paul’s first job works as a data scientist at Kingston.

Future

Current Toronto undergrad or masters students

If you are a Toronto undergrad or masters student and would like to work with me, then the best way is to do well in a course that I teach and then get in touch. That said, I do advertise for positions from time to time and you should also keep an eye out for those. Impressive applicants:

  1. Have GitHub repos that show off their best work.
  2. Can write well.
  3. Support the claims they make in a cover letter with evidence.

Current Toronto PhD students

I am open to supervising PhD students. If you are already admitted, then please email me.

Prospective PhD students

If you are not yet a Toronto PhD student:

  • Having gone through it myself, I do understand that grad school applications are stressful and there is a lot of conflicting advice.
  • While I understand that practices differ across disciplines and universities, in my case, there is no point contacting me before you apply.
  • I am open to supervising PhD students, but can only help once you are admitted. Admission decisions are made at a department/faculty level, before they are made at an individual level, and there is little I can do to help you until you are through that first hurdle.
  • Again, the first step is to apply to a PhD program. In my case that means either Information or Statistical Sciences.
  • As part of the application you will have the option to list faculty with whom you would like to work. You should include my name in that list so that your application is routed to me.

Reference letters

I only provide reference letters to students that:

  1. work with me; or
  2. get an A+ in a course that I taught.

If you are in either of those categories, then I would be happen to write you reference letters. Please send me an email and I will send you a form to fill out with the details that I need from you.