Sehoon Ha

If you want to join our lab, please read this document first. docs.google.com/document/d/1Sv…

FYI.... docs.google.com/document/d/1Sv…

Georgia Tech’s School of Interactive Computing is launching a major search for a new faculty member in Computer Graphics this year. Despite a challenging job market, we are committed to recruiting an exceptional colleague who will help shape the future of our graphics community.

We are especially interested in candidates who
• have a strong presence in the Computer Graphics / SIGGRAPH community, and
• bring research directions that complement—not overlap with—our current faculty (Sehoon Ha, Bo Zhu, Greg Turk).
If you know outstanding scholars, we would be grateful for your recommendations. We warmly encourage applicants from all backgrounds and institutions.
📌 Official posting: ic.gatech.edu/faculty-hiring
📩 Contact: sehoonha@gatech.edu / bo.zhu@gatech.edu / turk@cc.gatech.edu

What if we can take the periodic style of model-based controllers and the robustness of learning-based policies?

In our #RAL paper, PPF: Pre-training and Preservative Fine-tuning of Humanoid Locomotion via Model-Assumption-based Regularization, we address this challenge.

🔑 Key idea: Imitate the model-based controller and then Fine-tune with RL, while preserving motion style via Model-Assumption-based Regularization (MAR) to avoid forgetting.

Our controller is verified through comprehensive simulation tests and hardware experiments on a full-size humanoid robot, Digit, demonstrating a forward speed of 1.5 m/s and robust locomotion across diverse terrains, including slippery, sloped, uneven, and sandy terrains. 🙋Authors: Hyunyoung Jung* @hyunyoungjung, Zhaoyuan Gu* @gu_zy14, Ye Zhao @GT_LIDAR, Hae-Won Park, and Sehoon Ha @sehoonha
🌐 Website: hyunyoungjung.github.io/projects/ppf/p…

📄 arXiv: arxiv.org/abs/2508.134443

📢 The Proceedings of the 2025 Conference on Robot Learning (CoRL 2025) are now available through PMLR!
Discover the latest advances in robot learning research presented at this year’s conference.
🔗 proceedings.mlr.press/v305

#CoRL2025 #RobotLearning #PMLR #MachineLearning #Robotics