Montaser Fathelrhman Hussen Mohammedalamen, MSc

Area of Study / Keywords

reinforcement learning Safety Robotics Artificial Intelligence Machine Learning

About

Montaser is a PhD candidate advised by Michael Bowling, exploring how AI systems can learn in environments where rewards are not always observable. His research focuses on designing autonomous agents that can act cautiously in uncertain scenarios, contributing to advancements in reinforcement learning (RL) for partially observable settings.

Before starting his PhD, Montaser worked as an AI engineer at SonyAI, where he was part of a team developing multi-agent robotic systems. His work included training agents using self-play and goal-conditioned reinforcement learning, transferring learned behaviors from simulations to real-world settings, and integrating them with vision systems and robot control methods.Montaser is passionate about bridging theoretical research with practical applications to create adaptive and intelligent systems for complex environments.

Research

My research focuses on designing autonomous agents that can act cautiously in uncertain scenarios, contributing to advancements in reinforcement learning (RL) for partially observable settings.