GeezerVison is showing alirezalm.github.io — Alireza Olama — Machine Learning Systems & High-Performance Computing What I work onMachine learning engineer with a background in mathematical optimization and high-performance computing. Focused on building scalable algorithms and high-performance systems for AI workloads, numerical optimization, and distributed computing. Interests include LLM training and inference, GPU computing, and performance engineering.
News- Jul 2026Joined QuTwo in Helsinki as a Member of Technical Staff.
- Jul 2026Presented PsFiT at TKTP2026, the 43rd Annual Symposium of Computer Science, in Turku.
- Dec 2025PruneX preprint online: hierarchical communication-efficient distributed CNN training.
- Autumn 2025Launched the master's-level GPU Programming course at Åbo Akademi University.
- Spring 2025Ran an HPC workshop on the Mahti supercomputer for graduate students and researchers.
Selected workPruneXHierarchical communication-efficient distributed CNN training. Co-designs a structured-sparsity algorithm (H-SADMM) with cluster topology, so the pruning decision and the Allreduce pattern reinforce each other. CodePaper PsFiTDistributed sparse machine learning training under a hard ℓ₀ constraint via Bi-cADMM, with no relaxation. Data is sharded across nodes while features are partitioned across GPUs. Code SCOTC++17 distributed solver that reformulates sparse convex problems exactly as mixed-integer programs (DiPOA, DiHOA). Benchmarked on 140 problems against state-of-the-art MINLP solvers. Code SHOT(contributor)Gave this COIN-OR convex MINLP solver a thread-pool execution model, so primal heuristics run concurrently with the dual search instead of blocking it. Code
Selected publications- PsFiT: A GPU-Accelerated Distributed Framework for Scalable Sparse Machine Learning TrainingWith A. Lundell, J. Kronqvist, E. Ahmadi, J. Björkqvist. TKTP 2026.
- PruneX: A Hierarchical Communication-Efficient System for Distributed CNN Training with Structured PruningWith A. Lundell, I. El Hajj, J. Lilius, J. Björkqvist. arXiv:2512.14628, 2025.
- A GPU-Accelerated Bi-linear ADMM Algorithm for Distributed Sparse Machine LearningWith A. Lundell, J. Kronqvist, E. Ahmadi, E. Camponogara. arXiv:2405.16267, 2024.
- Sparse Convex Optimization Toolkit: A Mixed-Integer FrameworkWith E. Camponogara, J. Kronqvist. Optimization Methods and Software, 38(6), 2023.
- A Distributed Primal Outer Approximation Algorithm for Sparse Convex Programming with Separable StructuresWith E. Camponogara, P. R. C. Mendes. Journal of Global Optimization, 86(3), 2023.
- A Tracking Augmented Lagrangian Method for ℓ₀ Sparse Consensus OptimizationWith G. Carnevale, G. Notarstefano, E. Camponogara. CoDIT 2023.
All 15 publications on Google Scholar → |