Department of Computer Science

Research

Our group is the place for AI scientists and industry experts to work closely with each other

We would like to develop complex automation workflows that involve humans interacting with machines safely. To do so our systems have to learn in a more detailed manner. Using a mixture of input data from simulation as well as sensor data from real-world industry environments, we develop algorithms that learn like humans.

Research Interests:

  • Deep reinforement learning
  • Distributed learning
  • Offline reinforcement learning
  • Sim2real
  • Robotic

Every day, we engage in the following activities:

  • Creating environments in various simulations, including Pybullet and Nvidia Isaac
  • Innovate novel techniques to enhance reinforcement learning model performance
  • Train 100s of experiement per day
  • Compare experiments side by side and see the impact of different approaches on our results