Summary
Omid Askarisichani is a Senior ML/AI Software Engineer with 12 years of experience building large-scale, production ML systems at Google and Google DeepMind, following a PhD in Computer Science from UC Santa Barbara. He specializes in designing scalable, dynamic models for real-world problems in mapping, advertising, and social/financial networks, and has a track record of accelerating models (e.g., 3x speedups in counterfactual search-behavior prediction) and deploying counterfactual and streaming approaches. His research blends data mining, network science, and deep learning to model diffusion, structural balance, and team dynamics—work that produced novel convex optimization methods and empirical evidence linking network balance to performance. Prior roles span industry and academia, from modeling information cascades at Max Planck to leading risk-analysis software for a bank, showing an unusual mix of theoretical depth and hands-on engineering. Based in Mountain View and a U.S. permanent resident, he pairs rigorous research publications with production-grade implementation skills, often translating complex academic ideas into high-impact, deployable systems.
12 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at UC Santa Barbara
Bachelor of Science (BSc), Computer Software Engineering, Bachelor of Science (BSc), Computer Software Engineering at University of Isfahan
Master of Science (MSc), Artificial Intelligence, Master of Science (MSc), Artificial Intelligence at Sharif University of Technology
English, Persian