About CLeAR

Collaborative, Learning, and Adaptive Robots Lab at NUS

At CLeAR, we seek to improve people’s lives through intelligent robotics. We advance the science and engineering of collaborative robots that fluently interact with us to perform tasks. Our central focus has been on developing physical and social skills for robots. For the former, we’re working on new tactile perception and control methods for robots. In the latter, we’re developing better human trust models and social-projection-based communication.

A final third research thread is dedicated towards curiosity-driven machine-learning research. This leads to “out-of-the-box” ideas and methods for developing robot skills over a longer horizon. We have devised novel methods for regularizing deep networks with symbolic knowledge, which we later showed improved robot imitation learning for a cooking task. Our work on sample refinement using gradient flows provides us a way to meld physical and social skills for tasks such as semantic grasping. These methods not only contribute to the wider machine-learning literature, but form a unique suite of methods CLeAR uses to advance the state-of-the-art on trustworthy collaborative robots.

Join CLeAR

If all this sounds interesting to you, join us:

Postdoctoral Research Fellows and Research Assistants

Send Harold an email with your CV and a brief cover letter describing your research interests. We are currently recruiting self-motivated research fellows interested in the following research areas

  • Human-Centric Sample-Efficient Imitation Learning: This position is available for 3 years. Initial appointment for 1 year and extended upon mutual agreement. Key Skills: Machine Learning, Human-Robot Interaction. Apply Now
  • Assistive Robotics via Human Models: Two positions are open immediately. Initial appointment for 1 year. Key Skills: Machine Learning, Model-based Reinforcement Learning, Human-Robot Interaction. Apply Now
  • Tactile Sensing and Learning: One position is open immediately. Initial appointment for 1 year. Key Skills: Tactile Sensors, Machine Learning for tactile data. Apply Now

Students and Interns

If you’re a NUS graduate student in CS, send us an email indicating your research interests along with a CV. Have a look at our open projects or you can propose a topic.

If you’re a NUS undergraduate student, email us and mention you’re interested in a FYP or UROP project. We sometimes hire NUS interns during term-time and summer break, but this depends on availability of projects and funds.

If you’re not a NUS student, then please apply to the NUS School of Computing or the Data Science Institute IDS Scholarship , or NUS Graduate School ISEP Programme ISEP Scholarship. We are typically unable to work with you unless you’re a NUS student or an official exchange student. Please note that admission decisions are made by the department so, we are not unable to guarantee you a place in the PhD/Masters program.

Note: If you’re not a NUS nor an exchange student, we are afraid we are unable to accommodate you at the moment. Please do not send emails asking for summer internships as we are unable to respond to each of them individually.