Max Robotics — Global Service Robot Directory + US Certification

About

Vahab Mirrokni is a leading researcher in algorithms, optimization, and machine learning, with a particular focus on large-scale systems and adaptive decision-making. His early work in robotics, notably on vision systems and teamwork strategies for the RoboCup middle-size league, laid foundational insights into multi-agent coordination and real-time perception—contributions that earned recognition at the Fifth Robotic Soccer World Championships. More recently, Mirrokni has made groundbreaking contributions to adaptive submodularity, a framework for sequential decision-making under uncertainty. His 2019 paper "Adaptivity in Adaptive Submodularity" (7 citations) addresses a central challenge in AI: designing efficient interactive policies that balance exploration and exploitation with partial observations. This work has influenced fields from sensor placement to online advertising. With over 30 citations for his early robotics paper and a cumulative impact spanning hundreds of publications, Mirrokni’s research bridges theoretical rigor and practical deployment, shaping how algorithms learn and adapt in dynamic environments. His achievements include leading research teams at Google, where he drives innovations in large-scale optimization and machine learning systems.