Research Scientist (2020-22)
Visiting Researcher (2019-20)
Ph.D. Student (2014-19)
Ashkan lives in California, likes pasta and art, and follows a versatile daily workout routine 😎. His friends and family know him by his smile ... 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. He also publishes 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, a framework for deep reinforcement learning in traffic control.
Ashkan finished his Masters and PhD in Computer Science at the University of Texas at Dallas. His research was on intersection of Systems, Edge Computing, and Machine Learning, and he worked on improving quality of service in IoT and Deep Leanring Applications through Fog Computing. While at UT Dallas, he created Fog Computing Conference Hub.
He was an instructor for Discrete Mathematics at UT Dallas. He has served as technical program committee for FL-ICML, AIChallengeIoT, and reviewer of several 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