Mehran Shakerinava

Email: mehranshakerinava (at) gmail.com / mehran.shakerinava (at) mail.mcgill.ca
Affiliation: School of Computer Science, McGill University, Montreal, Canada

CV

I am a 4th year PhD candidate at McGill University and Mila, supervised by Prof. Siamak Ravanbakhsh. My research lies at the intersection of machine learning, optimization, and geometry, with a focus on theoretical foundations and practical applications of symmetry in learning algorithms. Prior to McGill, I received a Bachelor's degree in computer engineering from Sharif University of Technology in Iran. If you'd like to discuss research, potential collaboration, or just connect, feel free to email me.

Research Interests

Design and analysis of machine learning algorithms
Symmetry and geometry in machine learning and optimization
Statistical learning theory and theoretical foundations
Utility theory and reinforcement learning

Publications

Weight-Sharing Regularization
Mehran Shakerinava*, Motahareh Sohrabi*, Siamak Ravanbakhsh, Simon Lacoste-Julien
AISTATS 2024
[paper] [arXiv] [code]
Structuring Representations Using Geometric Invariants
Mehran Shakerinava*, Arnab K. Mondal*, Siamak Ravanbakhsh
NeurIPS 2022
[paper]
Utility Theory for Sequential Decision Making
Mehran Shakerinava, Siamak Ravanbakhsh
ICML 2022
[paper] [arXiv]
Equivariant Networks for Pixelized Spheres
Mehran Shakerinava, Siamak Ravanbakhsh
ICML 2021
[paper] [arXiv] [code]

Older Publications

Harnessing Pairwise-Correlating Data Prefetching With Runahead Metadata
Fatemeh Golshan, Mohammad Bakhshalipour, Mehran Shakerinava, Ali Ansari, Pejman Lotfi-Kamran, Hamid Sarbazi-Azad
Computer Architecture Letters (CAL) 2020
[paper]
Bingo Spatial Data Prefetcher
Mohammad Bakhshalipour, Mehran Shakerinava, Pejman Lotfi-Kamran, Hamid Sarbazi-Azad
International Symposium on High-Performance Computer Architecture (HPCA) 2019
[paper] [code]

Preprints

Newman's Theorem via Carathéodory
Yaqiao Li, Ali Mohammad Lavasani, Mehran Shakerinava
arXiv preprint 2024
[arXiv]

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