Meet The Team

I am a graduate student in computer science at MILA and University of Montreal, supervised by Prof. Irina Rish. My research interests include Natural Language Processing, Causal Inference, scaling laws, explainability, and Transformer based Language models. I aim to develop technologies and agents that can reason about their environment and communicate via natural language. I am also curious about economics, psychology, and philosophy.

I am a Masters in Computer Science student from the University of Texas at Austin with a strong focus on Machine Learning and Deep Learning. With extensive research internships at Google, IBM, ETH Zurich, University of Oregon, and IIT Kharagpur, I have developed expertise in data in the text, image, and audio modalities, and are particularly interested in making large language models feasible for deployment. I did my Bachelor’s degree in Computer Science from Indian Institute of Technology Kharagpur (2017-21).

Irina Rish is a Full Professor at the Université de Montréal (UdeM), where she leads the Autonomous AI Lab, and a core faculty member of MILA - Quebec AI Institute. She holds Canada Excellence Research Chair (CERC) and a CIFAR Chair. Irina leads the US DoE’s INCITE project on Scalable Foundation Models on Summit supercomputer at OLCF. She is a co-founder and CSO of Nolano.ai.

Irina’s current research interests include neural scaling laws and emergent behaviors (capabilities and alignment) in foundation model, as well as continual learning, out-of-distribution generalization, and robustness. Before joining UdeM in 2019, Irina was a research scientist at the IBM T.J. Watson Research Center, where she worked on various projects at the intersection of neuroscience and AI, and led the Neuro-AI challenge. She received IBM Eminence & Excellence Award and IBM Outstanding Innovation Award (2018), IBM Outstanding Technical Achievement Award (2017), and IBM Research Accomplishment Award (2009). She holds 64 patents, over 120 research papers, several book chapters, three edited books, and a monograph on Sparse Modeling.