Tegan Maharaj



Research Interests

My most recent research aims to bring together the fields of deep learning and theoretical ecology. I have several active projects in ecosystem modeling with deep networks, including work collecting datasets, in multi-agent RL, counterfactual inference, and meta-learning. Please contact me if you are interested in collaborations in this area.

I am broadly interested in understanding the effects on learning behaviour of varying “what goes into” deep models. In my research so far this has included multimodal input data, regularization, and different forms of feedback or environment, with applications to video, natural language, and climate data. I'm concerned and passionate about AI ethics, safety, and the application of ML to environmental management, health, and social welfare.


I started post-secondary education in biology with a focus on health and neuropsychology, but transitioned to a concentration in ecology. Analyzing results for my honour's research in bioremediation, I was introduced to programming for the first time and quickly realized I wanted to do machine learning. I recieved an NSERC scholarship to particpate in a large-scale research project on climate change, and later participated in a number of coding projects and discovered neural networks.

I began an MSc in computer science with Layachi Bentabet, studying biological realism in deep networks. During this time I was awarded a MITACS scholarship to be a machine learning research intern at iPerceptions, exploring semi-supervised learning in predictive models.

In November 2015 I completed my MSc, and in January 2016 began a PhD focused on deep learning research at Mila as an NSERC scholar with Christopher Pal.


My CV can be found here.


Workshops and other contributions

I've co-organized several workshops:

I was a co-founder of the Montreal AI Ethics meetup, and a contributor to SOCML 2017 and 2018, as well as the Montreal Declaration for Responsible AI.

Talks and presentations


I was a TA for the following classes during phd:

During undergrad and master's:

I also worked as a tutor at the Computer Science Help Centre at the end of my BSc/beginning of MSc, and at the ITS Helpdesk (troubleshooting and tech support) throughout my BSc.