Research Scientist (2020-22)
Visiting Researcher (2019-20)
MS/PhD Student (2014-19)
Ashkan currently lives in New York, likes pasta and art, and follows a versatile daily workout routine 😎. His friends and family know him by his smile. He thinks ... read more
More work-related 🥱, he is currently a Research Scientist at Meta AI. Working in Responsible AI org, he develops technologies for privacy-preserving machine learning and federated learning. He contributes to Opacus, an open-source library that enables training deep learning models with differential privacy, and FLSim, an open-source library for simulating federated learning systems. He publishes papers too and is an author of couple of highly cited papers.
He was a Visiting Researcher at University of California, Berkeley and member of the Berkeley Artificial Intelligence Research (BAIR). When he was at UC Berkeley, he contributed to FLOW, an open-source deep reinforcement learning-enabled framework for simulation of autonomous and manned cars.
Ashkan earned his PhD (and MS, while in PhD direct program) in Computer Science at the University of Texas at Dallas. His work was on the intersection of Systems, Edge Computing, and Machine Learning, specifically, on improving quality of service in IoT and deep learning Applications through Fog Computing. He won the UT Dallas Best Dissertation Award. While at UT Dallas, he created Fog Computing Conference Hub.
He was an instructor (lecturer) for Discrete Mathematics at UT Dallas for a year and a two-time recipient of Best Teaching Assistant Award. He likes to contribute the open-source community. Ashkan has served as technical program committee for FL-ICML, FL-NeurIPS, AIChallengeIoT, and reviewer of several international journals and conferences, including ICML, NeurIPS, IEEE/ACM TON, IEEE TNSM, TMC, NETWORK, TSC, IoTJ, INFOCOM, and ICDCS.
Prior to all these, Ashkan was a web-design freelancer for several years ... read more