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Practical matters How to find us S.H. (Hamidreza) Mohades Kasaei, PhD

Research interests

My research interest lies at the intersection of machine learning, robotics, and machine vision, particularly, at the area of open-ended learning, 3D object perception, grasp affordance detection, and object manipulation. I am interested in developing algorithms for an adaptive perception system based on interactive environment exploration and open-ended learning, which enables robots to learn from past experiences and interact with human users. I have been investigating on active perception, where robots use their mobility and manipulation capabilities not only to gain perceptual information to model the world but also to predict the next-best-view for improving object detection and manipulation performances. I have evaluated my works on different robotic platforms, including PR2, robotic arms (UR5e, Kinova, Franka), and humanoid robots. For more details, please check my webpage


Lifelong 3D object recognition and grasp synthesis using dual memory recurrent self-organization networks

Local-HDP: Interactive open-ended 3D object category recognition in real-time robotic scenarios

Reinforcement Learning with Potential Functions Trained to Discriminate Good and Bad States

Self-Imitation Learning by Planning

3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable Networks

Accelerating Reinforcement Learning for Reaching using Continuous Curriculum Learning

Investigating the Importance of Shape Features, Color Constancy, Color Spaces and Similarity Measures in Open-Ended 3D Object Recognition

Learning to Grasp 3D Objects using Deep Residual U-Nets

Local-LDA: Open-Ended Learning of Latent Topics for 3D Object Recognition

The State of Service Robots: Current Bottlenecks in Object Perception and Manipulation

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