2024-PresentAtlanta, GA
PhD in Machine Learning
Georgia Institute of Technology, ISyE
Supervised by Pascal Van Hentenryck.
CV
My work sits at the intersection of machine learning, optimization, and decision-making systems, with a focus on GPU computing and distributed optimization for large-scale problems in supply chain, logistics, manufacturing, and solver workflows.
Research Interests
Education
2022-2024Toronto, ON
MASc in Industrial Engineering
University of Toronto, MIE Department
Supervised by Elias Khalil.
2018-2022Toronto, ON
BASc in Engineering Science
Machine Learning, University of Toronto
Experience
Fall 2026Luxembourg, LU
Applied Scientist
Amazon SCOT
Summer 2026San Francisco, CA
Applied Scientist
Salesforce
2024-PresentAtlanta, GA
Graduate Researcher
AI Institute for Advances in Optimization
Summer 2023Vancouver, BC
Research Engineer
Huawei Technologies Canada
Selected Publications
Distributed Linear Programming on GPU Clusters at Extreme Scale
Deza, A., Dey, S., & Van Hentenryck, P. (2026). "Distributed Linear Programming on GPU Clusters at Extreme Scale." arXiv preprint arXiv:2609.09108.
PaperLearn2Aggregate: Supervised Generation of Chvatal-Gomory Cuts Using Graph Neural Networks
Deza, A., Khalil, E. B., Fan, Z., Zhou, Z., & Zhang, Y. (2025). "Learn2Aggregate: Supervised Generation of Chvatal-Gomory Cuts Using Graph Neural Networks." AAAI.
PaperMachine Learning for Cutting Planes in Integer Programming: A Survey
Deza, A., & Khalil, E. B. (2023). "Machine Learning for Cutting Planes in Integer Programming: A Survey." IJCAI (Survey Track).
PaperFast Matrix Multiplication Without Tears: A Constraint Programming Approach
Deza, A., Liu, C., Vaezipoor, P., & Khalil, E. B. (2023). "Fast Matrix Multiplication Without Tears: A Constraint Programming Approach." CP.
Paper