Summary
Yasar Nasir is a research scientist in the San Francisco Bay Area with eight years of experience at the intersection of machine learning, wireless communications, and large-scale resource management. Currently at Meta on AI Personalization, he brings deep expertise in multi-agent deep reinforcement learning and software-defined radios grounded in a PhD and MS from Northwestern and a near-perfect academic record. His background includes internships at Facebook, Qualcomm, Nokia Bell Labs and Fraunhofer, and he was a key member of a DARPA Spectrum Collaboration Challenge finalist team—evidence of both applied research impact and systems-level thinking. Comfortable bridging theory and production, he has prototyped distributed PyTorch communication hooks and contributed to RF and FPGA implementations, signaling a rare mix of ML, networking, and hardware skills. Colleagues value his ability to translate complex resource-allocation problems into scalable algorithmic solutions for next-generation cellular networks.
8 years of coding experience
5 years of employment as a software developer
Exchange Programme, Electrical Engineering and Computer Science, Exchange Programme, Electrical Engineering and Computer Science at Case Western Reserve University
Master of Science - MS, Electrical Engineering and Computer Science, 4.00/4.00, Master of Science - MS, Electrical Engineering and Computer Science, 4.00/4.00 at Northwestern University
Bachelor of Science (BS), Electrical and Electronics Engineering, 3.98/4.00, Bachelor of Science (BS), Electrical and Electronics Engineering, 3.98/4.00 at Bilkent Üniversitesi
TED Ankara Koleji
Turkish, English