Mila - C2084
6666 rue Saint-Urbain
Montréal, QC H2S 3H1, Canada
schmidtv 🌀 mila.quebec
💡 I am a final year PhD student interested mostly in applications of AI in the fight against climate change. This has led me to explore various areas, from computer vision and GANs to geometric graphs for materials modeling.
1️⃣ My first PhD project focused on creating AI visualizations of what your home could look like if climate-related extreme events (floods, wildfires or smog events) happened there. It’s not about climate projections, it’s about empathy: a climate in which every address in the world is experiencing floods, wildfires and smog at the same time does not exist. But the one we have is getting warmer, more dangerous, and everyone’s actions have global consequences. This is why we published ClimateGAN (ICLR 2022) and deployed it on This Climate Does Not Exist.
2️⃣ The second project I’ve worked on for almost 2 years now is about using AI for materials discovery. The long-term goal is to contribute to the discovery of more efficient electro-catalysts that would improve the energy efficiency of a wide range of chemical reactions. To that end, I have worked on graph neural networks for materials property prediction: PhAST (under review at JMLR) and FAENet (ICML 2023). I am now focusing on using this work within a generative model (GFlowNet) to efficiently explore the huge space of potential electro-catalysts.
3️⃣ Finally, I wanted to keep an eye on my own community and work towards quantifying the carbon emissions of machine learning. This lead to a workshop paper (Climate Change AI workshop, NeurIPS 2019) and its online emissions calculator, and a Python open-source library:
Beyond publishing, I try to be a good member of our community.
- Student Lab Representative for 3 consecutive years at Mila
- TA for 2 consecutive years for the UdeM IFT 3710/6759 Advanced projects in Machine Learning course,
- I contribute a module on AI & Climate Change to an upcoming MOOC by the Geography Department of Université de Montréal (with the amazing Mélisande Teng) and I like writing tutorials (from as early as 2015 or more recently an introduction to Pytorch).
Prior to this PhD, I was a student at École polytechnique, France (Engineering degree - 2012→2016), and at University College London, UK (MSc. in Machine Learning - 2016→2017). I also worked for about a year as a Public Interest Entrepreneur at the French Ministry for the Econommy and Finance (2018).
I also love creating open-source libraries. I tend to be the kind of persons who will spend a week or a month automating something that takes a couple hours, and then make an open-source project out ouf it. This is how I came to build PaperMemory a web-based automated reference manager,
minydra a minimalist Python argument parser,
ntfy-wrapper a simple notification wrapper around the ntfy.sh service, or
gitmopy an interactive CLI to make pretty commits following the Gitmoji specification.
In a previous life, I also created metada.org, a website to visualize the hierarchies of ownership in the French media.
ClimateGAN: Raising Climate Change Awareness by Generating Images of FloodsICLR, 2022
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst DesignIn AI for Accelerated Materials Design NeurIPS 2022 Workshop, 2022
FAENet: Frame Averaging Equivariant GNN for Materials ModelingICML 2023, 2023
torchgfn: A PyTorch GFlowNet libraryarXiv preprint arXiv: 2305.14594, 2023
Quantifying the Carbon Emissions of Machine LearningClimate Change AI workshop, NeurIPS, 2019