About
I am a Senior ML Engineer at Meta Reality Labs working on developing large vision language models for Meta smart glasses. Prior to that I spent a few years as an AI researcher at Samsung and J.P. Morgan working on large language models, adversarial ML and reinforcement learning. I received my Ph.D. degree in the ECE Department at New York University, advised by Elza Erkip. My Ph.D. research was in information theory and wireless communications with an emphasis on caching for wireless video delivery, and applications for the next generation of cellular systems.
Interests
- Artificial Intelligence
- Generative AI
- Machine Learning
- Reinforcement Learning
- Adversarial Machine Learning
Education
PhD in Electrical Engineering
New York University
BSc in Electrical Engineering
Sharif University of Technology, Iran
Experience
Senior ML Engineer
Meta Reality LabsMultimodal AI
- Large Vision Language Models on Smart Glasses (Ray-Ban Meta)
Senior AI Scientist
Samsung SDS AmericaGenerative AIAI Research Scientist
JPMorgan Chase & Co- Robust Multi-Agent Reinforcement Learning
- Privacy-Preserving Generative Models
- Stochastic Sequential Assignment for Fraud Detection
Graduate Research Assistant
New York University- Scalable correlated content delivery over cache-aided broadcast networks
- Distributed image classification with deep neural networks in bandwidth limited settings
- Sectoring in multi-cell massive MIMO systems to combat pilot contamination
Research Intern
Alcatel-Lucent, Bell LabsCorrelation-aware content delivery in caching networks
Education
PhD in Electrical Engineering
New York UniversityBSc in Electrical Engineering
Sharif University of Technology, Iran
Selected Publications
(2024).
Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation.
Proceedings of the 41st International Conference on Machine Learning (ICML 2024).
(2023).
Sequential Fair Resource Allocation under a Markov Decision Process Framework.
Proceedings of the Fourth ACM International Conference on AI in Finance (ICAIF 2023).
(2023).
Certifiably Robust Multi-agent Reinforcement Learning against Adversarial Communication.
Proceedings of the International Conference on Learning Representations (ICLR 2023).
(2022).
Generative Models with Information-Theoretic Protection Against Membership Inference Attack.
ICML 2022 Workshop on New Frontiers in Adversarial Machine Learning.
(2022).
Optimal Admission Control for Multiclass Queues with Time-Varying Arrival Rates via State Abstraction.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2022).
(2021).
Non-parametric Stochastic Sequential Assignment with Random Arrival Times.
Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2021).
(2020).
Centralized Caching and Delivery of Correlated Contents over Gaussian Broadcast Channels.
IEEE Transactions on Communications.
(2020).
Rate-Memory Trade-Off for Caching and Delivery of Correlated Sources.
IEEE Transactions on Information Theory.
(2018).
On Coding for Cache-Aided Delivery of Dynamic Correlated Content.
IEEE Journal on Selected Areas in Communications (JSAC 2018).
(2017).
Rate-Memory Trade-off for the Two-User Broadcast Caching Network with Correlated Sources.
Proceedings of the International Symposium on Turbo Codes and Iterative Information Processing (ISIT 2017).
Honors and Awards
- JPMorgan Innovation Award, JPMorgan Chase & Co., 2022
- Alexander Hessel Award for the Best Ph.D. Dissertation, ECE Department, NYU, 2020
- Class Representative for Tandon School of Engineering at the NYU Commencement, 2019
- David Goodman Research Award, ECE Department, New York University, 2019
- Student Leader Award, WoMentorship Program, NYU, 2019