About the Lab Reps

Lab Reps are a point of contact to facilitate communication between/among students, interns, postdocs, faculty staff, as well as to enhance student involvement in decision-making processes.

The Lab Reps are elected every year by the students at Mila. While the specific initiatives undertaken by Lab Reps vary each year, depending on current context and interest of the members, they are always working to improve the Mila community.

Some of the Lab Reps roles and responsibilities include:

Supporting students (channeling feedback / helping solve problems)
Providing feedback on Information Technology infrastructure (clusters, wifi, etc.)
Managing social activities (reading groups, tea talks, socials)
Managing physical spaces (relaxation room, student lounge)
Discussing issues around Equity, Diversity and Inclusion
Developing conflict resolution procedures
Voicing opinion about prospective partnerships
Voicing opinion about AI for Humanity research projects

Students in need of advice or resources are welcome and encouraged to reach out to the Lab Reps at any time: reps@mila.quebec

Alekhya Dronavalli

Indian / Professional MSc / alekhya.dronavalli@mila.quebec

I am interested in applied research in representation learning. I am currently adapting self-supervised approaches to segmentation and object detection for obtaining better pre-trained models, making downstream task training more efficient and yielding high-performing models for devices with limited computing capability.

Fun Fact: My decision to pursue a master’s degree is influenced by a line from one of the Harry Potter movies: “What’s life without a little risk?”

Alex Hernandez-Garcia

Spanish / Postdoc / alex.hernandez-garcia@mila.quebec

I research ways of applying machine learning to have a positive social impact and fight climate change. More broadly, I am interested in learning theory, brain-inspired deep learning and computational neuroscience.

Supervisor: Yoshua Bengio

Fun Fact: I play the violin (brokenjugramblers.bandcamp.com) and the bagpipe (lumedebiqueira.es).

Dongyan Lin

Chinese / PhD / lindongy@mila.quebec

My research interest lies at the intersection of neuroscience and AI: I am interested in 1) understanding how the brain works using AI models and ML tools, and 2) using neuroscience principles to build better, more biologically-plausible AI models. I am particularly interested in reinforcement learning and its links to experimental neuroscience, as well as computational models for the hippocampal and visual systems in the brain.

Supervisor: Blake Richards

Fun Fact: My name means “winter beauty” in Chinese. I was born on the winter solstice.

Ezekiel Williams

Canadian / PhD / ezekiel.williams@mila.quebec

My interests revolve around the application of mathematical methods from probability and dynamical systems theory to understand computation in biological and artificial neural networks. As such, my research straddles neuroscience, machine learning, and applied mathematics.

Supervisor: Guillaume Lajoie

Fun Fact: In a past life I was a junior national champion nordic skier!

Kshitij Gupta

Indian / MSc / kshitij.gupta@mila.quebec

My research interest is lifelong reinforcement learning, model-based RL, planning, and systematic generalizations.

Supervisors : Sarath Chandar, Irina Rish

Fun Fact: I love outdoor adventures! I was part of the sailing team and used to also play underwater hockey!

Mandana Samiei

Iranian / PhD / samieima@mila.quebec

My research focuses on the role of memory in reinforcement learning (RL) and how that can fill some of the gaps in the classical deep RL. I am also interested in studying representations learned by the human brain and their contribution to decision-making.

Supervisors: Blake Richards, Doina Precup

Fun Fact: One thing I cannot live without is baking patisserie!

Mashbayar Tugsbayar

Mongolian / MSc / Reach out on Slack

I’m interested in AI as a tool for insight into neuroscience. My current work focuses on building an attention-based neural network modelling the human visual system.

Fun Fact: I love city builder video games, but only if I get to drop a meteor on my city at the end.

Mélisande Teng

French / PhD / tengmeli@mila.quebec

I am interested in using AI to tackle environmental and societal challenges, and I am currently working on biodiversity monitoring using remote sensing and citizen science data. I am also part of the team that developed This Climate Does Not Exist!

Supervisors: Yoshua Bengio, Hugo Larochelle

Fun Fact: My guitar sits on a homemade stand made out of cardboard, and you will never find it tuned in standard tuning!

Nikolaus H. R. Howe

Canadian / PhD / niki.howe@mila.quebec

Broadly speaking, I am interested in safety and AI for good. This includes the development and application of current techniques to address real-world problems, as well as technical and nontechnical work to ensure that future AI systems are beneficial to all. Most recently, I have been leading development of a repository of real-world control tasks, along with techniques for learning dynamics and behaving optimally subject to safety constraints.

Supervisor: Pierre-Luc Bacon

Fun Fact: I love Dance Dance Revolution, and am an increasingly enthusiastic fan of Beat Saber.

Sékou-Oumar Kaba

Canadian / M.Sc. / kabaseko@mila.quebec

My research focuses on how to make machine learning algorithms that can help us understand physics problems. More specifically, predicting the properties of materials before having to perform experiments in a laboratory is a challenge for which artificial intelligence could help in a significant way. These algorithms could greatly accelerate the design process of new materials. I am also interested in studying how machine learning could help us model complex systems evolving in time.

Supervisor : Siamak Ravanbakhsh

Fun Fact: I hosted a radio show in Montréal!

Victor Schmidt

French / PhD / schmidtv@mila.quebec

My research interest is about AI vs. Climate change: generative models and practical tools. I am co-leading a project named Visualizing the Impacts of Climate Change, to create vivid and relatable visualizations of the potential climate-related extreme events: floods, smog, wildfire, etc. In October 2021 we released the website: https://thisclimatedoesnotexist.com! I’m also working on CodeCarbon, a project to measure the carbon emissions of ML, and fluid simulations with ML.