Abolfazl Hashemi
Computer Science · Purdue University West Lafayette
Publications
118
Citations
484
Est. group size
~2
Recurring co-author estimate
Active years
32
Publishing since 1995
Abolfazl Hashemi works on mathematical foundations of optimization and machine learning, including distributed and stochastic optimization algorithms, sensor and feature selection, and fairness/robustness in federated learning (a setting where multiple devices collaboratively train a model without sharing raw data). Much of the work is theoretical, focused on designing algorithms with provable performance guarantees, though some applied projects touch on areas like battery health prediction and structural engineering.
Publication output has fluctuated year to year over the last decade but shows a generally active and slightly increasing pace, with a notable peak in 2024 and lower counts in 2025-2026 (possibly reflecting incomplete recent indexing).
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- A Failure-efficient Prediction of Remaining Useful Life
Machine Learning Engineering · 2026
- Novel differential voltage features based machine learning approach to lithium-ion batteries SOH prediction at various C-rates
Energy · 2025
- Determination of 3D Stress State Using a Novel Integrated Diametrical Core Deformation and Ultrasonic Analysis
Rock Mechanics and Rock Engineering · 2025
- Optimization via First-Order Switching Methods: Skew-Symmetric Dynamics and Optimistic Discretization
arXiv (Cornell University) · 2025
- Strong Antithetic Variance Reduction Inequalities
2025
- Exploring Ant Colony Optimization for Feature Selection: A Comprehensive Review
Springer tracts in nature-inspired computing · 2024
- Multi-objective Optimization for Feature Selection: A Review
Springer tracts in nature-inspired computing · 2024
- Accelerated Distributed Stochastic Nonconvex Optimization Over Time-Varying Directed Networks
IEEE Transactions on Automatic Control · 2024
- Randomized greedy methods for weak submodular sensor selection with robustness considerations
Automatica · 2024
- Localized Distributional Robustness in Submodular Multi-Task Subset Selection
IEEE Transactions on Signal Processing · 2024
- Submodular Maximization Approaches for Equitable Client Selection in Federated Learning
arXiv (Cornell University) · 2024
- FedNMUT -- Federated Noisy Model Update Tracking Convergence Analysis
arXiv (Cornell University) · 2024
- Equitable Client Selection in Federated Learning via Truncated Submodular Maximization
2024
- Randomized Greedy Methods for Weak Submodular Sensor Selection with Robustness Considerations
arXiv (Cornell University) · 2024
- Localized Distributional Robustness in Submodular Multi-Task Subset Selection
arXiv (Cornell University) · 2024
- arXiv (Cornell University)×51
- IEEE Transactions on Automatic Control×5
- Springer tracts in nature-inspired computing×2
- IEEE Transactions on Signal Processing×2
- IEEE Access×2
- Miaolan Xie
Computer Science · Purdue University West Lafayette
- Kaiyi Ji
Computer Science · The Ohio State University
- Anuran Makur
Computer Science · Purdue University West Lafayette
- Anindya Bijoy Das
Computer Science · Purdue University West Lafayette
- Haoyu Wang
Computer Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile