About
I am a Senior ML Scientist at Samsung SDS working on generative AI, and prior to that I spent a few years as an AI researcher at J.P. Morgan working on advesarial ML and reinforcement learning. I received my Ph.D. degree in 2019 in the Electrical and Computer Engineering Department at the Tandon School of Engineering at New York University, advised by Dr. 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
- Machine Learning
- Generative AI
- Adversarial Machine Learning
- Reinforcement Learning
Education
PhD in Electircal Engineering, 2019
New York University
BSc in Electircal Engineering, 2013
Sharif Uinversity of Technology, Iran
Experience
Senior ML Scientist
Samsung SDS America
- Generaitive AI (Uncertainty in Language Models, Business analytics with text-to-SQL)
AI 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
Blue Danube Systems
RF-coherency in massive MIMO systems in cellular networks
Research Intern
Alcatel-Lucent, Bell Labs
Correlation-aware content delivery in caching networks
Selected Publications
(2022).
Certifiably Robust Multi-agent Reinforcement Learning against Adversarial Communication.
In Proceedings of the International Conference on Learning Representations (ICLR 2023).
(2022).
Generative Models with Information-Theoretic Protection Against Membership Inference Attack.
In 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.
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2022).
(2022).
Scalable Delivery of Correlated Video Content over Cache-Aided Broadcast Networks.
In Edge Caching for Mobile Networks.
(2021).
Tradeoffs in Streaming Binary Classification under Limited Inspection Resources.
In Proceedings of the ACM International Conference on AI in Finance (ICAIF 2021).
(2021).
Non-parametric Stochastic Sequential Assignment with Random Arrival Times.
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2021).
(2020).
Centralized Caching and Delivery of Correlated Contents over Gaussian Broadcast Channels.
In IEEE Transactions on Communications.
(2020).
Rate-Distortion-Memory Trade-offs in Heterogeneous Caching Networks.
In IEEE Transactions on Wireless Communications.
(2020).
Rate-Memory Trade-Off for Caching and Delivery of Correlated Sources.
In IEEE Transactions on Information Theory.
(2018).
On Coding for Cache-Aided Delivery of Dynamic Correlated Content.
In IEEE Journal on Selected Areas in Communications.
(2017).
Broadcast Caching Networks with Two Receivers and Multiple Correlated Sources.
In Proceedings of the Asilomar Conference on Signals, Systems, and Computers (Asilomar 2017).
(2017).
Rate-Memory Trade-off for the Two-User Broadcast Caching Network with Correlated Sources.
In Proceedings of the International Symposium on Turbo Codes and Iterative Information Processing (ISIT 2017).
(2015).
Distortion-Memory Tradeoffs in Cache-Aided Wireless Video Delivery.
In Proceedings of the Allerton Conference on Communication, Control, and Computing (Allerton 2015).
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
Professional & Academic Service
- IEEE Young Professionals Representative for Information Theory Society, 2020-2022
- Student and Outreach Subcommittee member for Information Theory Society, 2020-2022
- Capstone Mentoring, Columbia Univeristy & Carnegie Mellon university, 2020 and 2021.
Contact
- parisah (at) nyu (dot) edu