David Rolnick

Mila > About Mila > Team > David Rolnick
Core Academic Member
David Rolnick
Assistant Professor, McGill University
David Rolnick

I am an Assistant Professor in the School of Computer Science at McGill University and a Core Academic Member at Mila. I also serve as co-founder and chair of Climate Change AI. My research foci are:

  • Deep learning theory: Mathematical understanding of the properties of neural networks.
  • Machine learning and climate change: Applications of machine learning to mitigate and adapt to the climate crisis.

Previously, I was an NSF Mathematical Sciences Postdoctoral Research Fellow at the University of Pennsylvania, working with Konrad Körding. I received my PhD in Applied Math from MIT in 2018, co-advised by Nir Shavit, Max Tegmark, and Ed Boyden. Before that, I was a Fulbright Scholar at the Freie Universität Berlin and an undergraduate at MIT.

Publications

2021-03

Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification
Charles, Kantor, Marta Skreta, Brice Rauby, Léonard Boussioux, Emmanuel Jehanno, Alexandra Luccioni, David Rolnick and Hugues Talbot
arXiv preprint arXiv:2103.11285
(2021-03-21)
arxiv.orgPDF

2019-06

Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig... (2 more)
arXiv preprint arXiv:1906.05433
(2019-06-10)
ui.adsabs.harvard.eduPDF

Publications collected and formatted using Paperoni

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