Summary
Gal Dalal is a Senior Research Scientist with a PhD in reinforcement learning and a decade of experience translating cutting-edge ML research into production-grade systems. Currently at NVIDIA, he publishes in top venues (NeurIPS, ICML, ICLR), files patents on RL-driven systems for congestion control, GPU cache/power, and efficient tree search, and mentors the next generation through volunteer AI education. Previously he co-founded an AI startup that was acquihired into Ford/SAIPS, where he helped build simulation and RL driving policies for L3/L4 vehicles, and interned at DeepMind on safe RL for datacenter cooling. Technion-trained summa cum laude with an exchange stint at Carnegie Mellon, he blends deep theoretical rigor with practical impact across industry and research. Notably, his work spans both academic publication and applied IP, reflecting a rare ability to move RL from papers into deployed systems.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science (BSc), Electrical and Electronics Engineering, Summa cum laude, 95.3 GPA. Formal class ranking: #3 out of 180 EE students., Bachelor of Science (BSc), Electrical and Electronics Engineering, Summa cum laude, 95.3 GPA. Formal class ranking: #3 out of 180 EE students. at Technion - Israel Institute of Technology
Exchange student, Electrical and Computers Engineering, 4.0 GPA, Exchange student, Electrical and Computers Engineering, 4.0 GPA at Carnegie Mellon University