About
I am an AI Scientist (Senior Staff Data Scientist) at GE Healthcare, where my research focuses on pre- and post-training of multi-modal reasoning models for 2D and 3D medical images, with an emphasis on vision-language large models (VLLMs) and self-training techniques.
Prior to joining GE Healthcare, I was a Senior Applied ML Researcher at Biogen, where I worked on pre-training and fine-tuning large language models for drug discovery, leveraging reinforcement learning from human feedback (RLHF) and direct preference optimization (DPO). Before that, I was a Postdoctoral Research Associate in the Computer Science Department at Yale University, supervised by Prof. Amin Karbasi, with research spanning distributionally robust optimization, fairness in large-scale machine learning, and federated learning.
I received my Ph.D. in Electrical Engineering and Computer Science from Pennsylvania State University in 2021, under the supervision of Prof. Mehrdad Mahdavi and Prof. Viveck Cadambe, where my dissertation focused on federated learning, fairness in machine learning, and large-scale high-performance computing.
Publications
Foundational Model Pretraining
Multi Anatomy X-Ray Foundation Model
Nishank Singla, Krisztian Koos, Farzin Haddadpour, Amin Honarmandi Shandiz, Lovish Chum, Xiaojian Xu, Erhan Bas
Submitted, arXiv 2025
Decipher-MR: A Vision-Language Foundation Model for 3D MRI Representations
Zhijian Yang, Noel DSouza, Istvan Megyeri, Xiaojian Xu, Amin Honarmandi Shandiz, Farzin Haddadpour, Krisztian Koos, Laszlo Rusko, Emanuele Valeriano, Bharadwaj Swaminathan, Lei Wu, Parminder Bhatia, Taha Kass-Hout, Erhan Bas
Submitted, arXiv 2025
Robust & Fair Machine Learning
Learning Distributionally Robust Models at Scale via Composite Optimization
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi
ICLR 2022
Efficient Fair Principal Component Analysis
Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati, Mehrdad Mahdavi
Journal of Machine Learning, 2021
Generalization Error
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
Konstantinos E. Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios S. Kalogerias
ICLR 2023
Black-Box Generalization
Konstantinos E. Nikolakakis, Farzin Haddadpour, Dionysios S. Kalogerias, Amin Karbasi
NeurIPS 2022
Federated & Large-Scale Machine Learning
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi
AISTATS 2021
FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching
Farzin Haddadpour, Belhal Karimi, Ping Li, Xiaoyun Li
arXiv 2020
On the Convergence of Local Descent Methods in Federated Learning
Farzin Haddadpour, Mehrdad Mahdavi
arXiv 2019
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe
NeurIPS 2019
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe
ICML 2019
Fault-Tolerant Large-Scale ML
On the Optimal Recovery Threshold of Coded Matrix Multiplication
Sanghamitra Dutta*, Mohammad Fahim*, Farzin Haddadpour*, Haewon Jeong*, Viveck Cadambe, Pulkit Grover (*equal contribution)
IEEE Transactions on Information Theory
Cross-Iteration Coded Computing
Farzin Haddadpour, Yaoqing Yang, Viveck R. Cadambe, Pulkit Grover
Allerton 2018
Codes for Distributed Finite Alphabet Matrix-Vector Multiplication
Farzin Haddadpour, Viveck R. Cadambe
IEEE ISIT 2018
On the Optimal Recovery Threshold of Coded Matrix Multiplication
Mohammad Fahim, Haewon Jeong, Farzin Haddadpour, Sanghamitra Dutta, Viveck Cadambe, Pulkit Grover
Allerton 2017
Straggler-Resilient and Communication-Efficient Distributed Iterative Linear Solver
Farzin Haddadpour, Yaoqing Yang, Malhar Chaudhari, Viveck R. Cadambe, Pulkit Grover
arXiv 2018
Information and Coding Theory
Low Complexity Generalized Belief Propagation Algorithm
Farzin Haddadpour, Mahdi Jafari Siavoshani, Mohammad Noshad
ISIT 2016
On AVCs with Quadratic Constraints
Farzin Haddadpour, Mahdi Jafari Siavoshani, Mayank Bakshi, Sidharth Jaggi
ISIT 2013
When Is It Possible to Simulate a DMC Channel from Another?
Farzin Haddadpour, Mohammad Hossein Yassaee, Mohammad Reza Aref, Amin Gohari
ITW 2013
Coordination via a Relay
Farzin Haddadpour, Mohammad Hossein Yassaee, Amin Gohari, Mohammad Reza Aref
ISIT 2012
Simulation of a Channel with Another Channel
Farzin Haddadpour, Mohammad Hossein Yassaee, Salman Beigi, Amin Gohari, Mohammad Reza Aref
IEEE Transactions on Information Theory
Services
Reviewer: ICML, NeurIPS, ICLR, AISTATS, ISIT
Program Committee: ICML Workshop on Federated Learning (2021), AAAI Workshop on Federated Learning (2022)