Summary
Hany Hamed is a research engineer based in Italy with eight years of experience specializing in reinforcement learning and robotics, focused on building agents that generalize robustly to unseen and diverse settings. He has applied model-based RL and sim-to-real techniques across manipulation and humanoid locomotion, contributing to projects at KAIST, Istituto Italiano di Tecnologia, and Generative Bionics. His work spans torque-control for humanoids, diffusion-based planning for long-horizon tasks, and mask-based goal representations, reflecting a blend of theoretical RL and hands-on robot integration. Hany’s background includes developing differentiable simulators, ROS-based systems, and custom mapping hardware (handheld LiDAR), showing an uncommon mix of software research and embedded system prototyping. He has taught and mentored students in ROS and advanced ML topics, and co-authored publications on zero-shot task generalization and intrinsic motivation for hierarchical agents. Curious and pragmatic, he often bridges academic research with practical sim-to-real challenges to accelerate robot deployment.
8 years of coding experience
4 years of employment as a software developer
Bachelor's degree Computer Science - Robotics track, Bachelor's degree Computer Science - Robotics track at Innopolis University
Egyptian Secondary Education Science section - Math division, Egyptian Secondary Education Science section - Math division at El-Tabary Roxy Secondary School
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Korea Advanced Institute of Science and Technology
Arabic, English, German, Russian