Hamidreza Kasaei

hamidreza.kasaei@rug.nl

I am an Assistant Professor in the Department of Artificial Intelligence at the University of Groningen, the Netherlands. My research group focuses on Lifelong Interactive Robot Learning (IRL-Lab), which we work at the cutting edge of robotics research. My main research interests lie in the area of 3D Object Perception, Grasp Affordance, and Object Manipulation. These days, I am particularly interested in enabling robots to incrementally learn from past experiences and intelligently and safely interact with non-expert human users using data-efficient open-ended machine-learning techniques.

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Latest News


* March. 2022: Our paper titled Lifelong 3D Object Recognition and Grasp Synthesis using Dual Memory Recurrent Self-Organization Networks got accepted to Neural Networks Journal! Congrats Krishna!
* Jan. 2022: Hamidreza Kasaei is serving as associate editor for the IEEE/RSJ IROS 2022!
* Oct. 2021: Our paper titled Local-HDP: Interactive open-ended 3D object category recognition in real-time robotic scenarios got accepted to Robotics and Autonomous Systems (RAS)! Congrats Hamed!
* Sep. 2021: Hamidreza Kasaei is serving as associate editor for the IEEE/RSJ ICRA 2022!
* July 2021: We will organize a full-day workshop on 4th Robot Learning Workshop: Self-Supervised and Lifelong Learning at NeruIPS2021.
* July. 2021: Our paper titled The State of Lifelong Learning in Service Robots: Current Bottlenecks in Object Perception and Manipulation got accepted to Journal of Intelligent & Robotic Systems
* May. 2021: I gave an invited talk on Lifelong Robot Learning in Human-centric Environments: From Object Perception to Object Manipulation at the University of Lincoln, UK
* May. 2021: Our paper titled Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces got accepted to IEEE-RAS International Conference on Humanoid Robots (Humanoids2020)! Congrats Nils!
* April. 2021: Our paper titled 3D_DEN: Open-ended 3D Object Recognition Using Dynamically Expandable Networks got accepted to IEEE Transactions on Cognitive and Developmental Systems! Congrats Sudhakaran!
* March. 2021: Our paper titled Self-Imitation Learning by Planning got accepted to ICRA2021! Congrats Sha!
* Feb. 2021: I am serving as associate editor for the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021)
* Feb. 2021: I gave an invited talk at the Bosch Center for Artificial Intelligence (BCAI) on Robots Beyond the Factory: Open-ended Robot Learning in Human-Centric Environments!

Research & Publication

My research interests focus on the intersection of robotics, machine learning and machine vision. I am interested in developing algorithms for intelligent robotic systems based on lifelong/continual learning and interactive environment exploration to capable robots to demonstrate strong performance in helping humans in household and care-taking tasks, manufacturing and logistics, transportation and monitoring, and many other unstructured and human-centric environments. I have been investigating on active perception and manipulation, where robots use their mobility and manipulation capabilities to model the world better. I have evaluated my works on different platforms including PR2, robotic arms, and humanoid robots. Please navigate the publications pages of my research group (IRL-Lab), if you are intersted to know more our research.

In IRL-Lab, we mainly focus on interactive robot learning to make robots capable of learning in an open-ended fashion by interacting with non-expert human users. More specifically, we have been developing this goal over six particular research directions:

1 - Perception and Perceptual Learning

We are interested in attaining a 3D understanding of the world around us. In particular, the perception system provides important information that the robot has to use for interacting with users and environments.

2- Object Grasping and Object Manipulation

A service robot must be able to interact with the environment as well as human users. We are interested in fundamental research in object-agnostic grasping, affordance detection, task-informed grasping, and object manipulation.

3- Lifelong Interactive Robot Learning

A service robot must be able to interact with the environment as well as human users. We are interested in fundamental research in object-agnostic grasping, affordance detection, task-informed grasping, and object manipulation.

4- Dual-Arm Manipulation

A dual-arm robot has very good manipulability and maneuverability which is necessary to accomplish a set of everyday tasks (dishwashing, hammering). We are interested in efficient imitation learning, collabrative manipulation, and large object manipulation.

5- Dynamic Robot Motion Planning

We are interested in attaining fully reactive manipulation functionalities in a closed-loop manner. Reactive systems have to continuously check if they are at risk of colliding while planners should check every configuration that the robot may attempt to use.

6- Exploiting Multimodality

A service robot may sense the world through different modalities that may provide visual, haptic or auditory cues about the environment. In this vein, we are interested in exploiting multimodality for learning better representations to improve robot's performance.

Open Positions

We are actively looking for students to work on amazing robotic projects that involve:

Deep learning-based method for 3D object perception.
Visual representation learning for physical interaction (grasping and manipulation).
Deep reinforcement and imitation learning-based methods for planning & control.
Dual-arm object manipulation.
Lifelong Robot learning.
Efficient Supervision for Robot Learning.
Learning from Demonstration.
Multi-Task multimodal learning.
Simulation to real-world transfer learning (Sim2Real).

If you are interested in doing your PhD/Master/Bachelor thesis in one of the above areas, or working on a project with me, please send me an e-mail including:

  • Short CV
  • Short motivation letter

The motivation letter should state (½ - 1 page):

  • Topics that you are interested in
  • Type of project (theoretical/applied)
  • Intended starting date
  • Your relevant experiences


Seld-funded (externally funded) PhD, Master and Visiting Scholar

Good self-founded PhD, Master, and intern will be considered on a case by case basis. If you are interested in doing your PhD at Interactive Robot Learning Lab and you have founding from your Government (e.g., China Scholarship Council (CSC) scholarship), we can consider your application.

Contact



Dr. Hamidreza Kasaei
Artificial Intelligence Department,
University of Groningen,
Bernoulliborg building,
Nijenborgh 9 9747 AG Groningen,
The Netherlands.
Office: 340
Tel: +31-50-363-33926
Email: hamidreza.kasaei@rug.nl