Ozgur S. Oguz

I’m an Asst. Prof. in the area of AI & Robotics at Bilkent University and the lead of the Learning for Intelligent Robotic Agents (LiRA) Lab in the Dept. of Computer Engineering.

In my research, I focus on algorithms that can enrich the skill set of autonomous agents. This entails endowing intelligent systems with effective learning, reasoning, and planning capabilities. Robotics, and a range of other domains that require autonomous decision-making, provide a perfect test-bed for the investigation and application of such methods.

Prior to joining Bilkent U., I was a postdoctoral researcher at the Learning and Intelligence Systems Lab working with Marc Toussaint. I was affiliated with Uni Stuttgart & Max Planck Institute for Intelligent Systems, and working within the Cluster of Excellence: IntCDC. I received my PhD degree from TU Munich, where I focused on HRI in close-proximity scenarios. I studied computer science at UBC and Koç Uni.

available positions

Post-doc position is available
Motivated graduate / undergraduate students wanted. Contact me if you are interested in deep learning, (deep) perception, robotics, in general any topics in artificial intelligence. !!!

news

Sep 28, 2024	Our work Diffusion-based Curriculum Reinforcement Learning got accepted for NeurIPS’24. pdf
Sep 15, 2024	24-Fall: CS 449 / 549: Learning for Robotics course - Moodle
Sep 15, 2024	24-Fall: CS 461: Artificial Intelligence course - Moodle
Jun 13, 2024	Our preprint (on Deep Reinforcement Learning) is out CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms - pdf.
May 01, 2024	Our work on Deep RL, Contact Energy Based Hindsight Experience Prioritization, got accepted for IEEE ICRA’24 - pdf.

selected publications

22-braun-IROS

RHH-LGP: Receding Horizon And Heuristics-Based Logic-Geometric Programming For Task And Motion Planning

Cornelius V. Braun, Joaquim Ortiz-Haro, Marc Toussaint, and 1 more author

In IEEE IROS, 2022

arXiv Bib

@inproceedings{22-braun-IROS,
  title = {{RHH}-{LGP}: {Receding} {Horizon} {And} {Heuristics}-{Based} {Logic}-{Geometric} {Programming} {For} {Task} {And} {Motion} {Planning}},
  author = {Braun, Cornelius V. and Ortiz-Haro, Joaquim and Toussaint, Marc and Oguz, Ozgur S.},
  booktitle = {IEEE IROS},
  year = {2022},
}

22-hartmann-TRO

Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly

Valentin Noah Hartmann, Andreas Orthey, Danny Driess, and 2 more authors

IEEE TRO - Transactions on Robotics, 2022

arXiv Bib

@article{22-hartmann-TRO,
  title = {Long-{Horizon} {Multi}-{Robot} {Rearrangement} {Planning} for {Construction} {Assembly}},
  author = {Hartmann, Valentin Noah and Orthey, Andreas and Driess, Danny and Oguz, Ozgur S. and Toussaint, Marc},
  journal = {IEEE TRO - Transactions on Robotics},
  year = {2022},
}

21-schubert-NeurIPS

Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics

Ingmar Schubert, Driess, Danny, Ozgur S. Oguz, and 1 more author

NeurIPS - Conf. on Neural Information Processing Systems, 2021

arXiv Bib Code

@article{21-schubert-NeurIPS,
  title = {Learning to {Execute}: {Efficient} {Learning} of {Universal} {Plan}-{Conditioned} {Policies} in {Robotics}},
  shorttitle = {Learning to {Execute}},
  author = {Schubert, Ingmar and {Driess, Danny} and Oguz, Ozgur S. and Toussaint, Marc},
  journal = {NeurIPS - Conf{.} on Neural Information Processing Systems},
  year = {2021},
}