Baijun Chen

Core Developer of Robotwin and RoboDojo, Luma AI

Baijun Chen is an incoming Ph.D. student at Shanghai Jiao Tong University. His research focuses on embodied intelligence and robotic manipulation, with particular interests in robotic simulation, data generation, visuo-tactile perception, and sim-to-real transfer. He is a co-first author of RoboTwin 2.0, a scalable simulation and benchmarking platform for robotic manipulation, published at ICML 2026. He also leads the development of UniVTAC, a unified visuo-tactile simulation framework that received the Best Paper Award at ViTac 2026. Previously, he conducted research with MMLab at the University of Hong Kong and ScaleLab at Shanghai Jiao Tong University, gaining extensive experience in robotic simulation, manipulation task development, and multimodal perception.

Chao Wu

Embodied Intelligence Algorithm Engineer,  AMD AI DevMaster Hackathon 2026 2nd Place Winner

Chao Wu is an embodied intelligence algorithm engineer at D-Robotics, covering the full robot algorithm pipeline from cloud-based training to on-device deployment. He works with customers and partners to deliver integrated cloud-to-edge solutions built on the D-Robotics software platform. He was part of the three-person team that won 2nd Place in the Physical AI Track at the AMD AI DevMaster Hackathon 2026.

Ran Cheng

Associate Head, Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University

Cheng Ran Peter is Associate Head in the Department of Data Science and Artificial Intelligence at The Hong Kong Polytechnic University. His research spans evolutionary computation, adaptive AI systems, and their applications in complex physical environments. He initiated the EvoX open-source ecosystem and explores how computational intelligence can continuously evolve through execution, evaluation, and feedback. His work covers engineering design, robotic control, and software evolution. He received the 2025 IEEE Computational Intelligence Society Outstanding Early Career Award and was named a Clarivate Highly Cited Researcher.

Hao Lin

Lead Researcher, Infinigence AI

Hao Lin is a Lead Researcher at Infinigence AI, where he works on large-scale training systems. He is the maintainer of RLinf, an open-source distributed reinforcement learning system for embodied and agentic intelligence. His work has appeared in top-tier conferences like OSDI, SOSP, NSDI and SIGCOMM, and has been recognized with the ACM SIGCOMM Best Student Paper Award and a SIGMOBILE Research Highlight.

Rick Hou

Senior Machine Learning Engineer, Ultralytics

Rick Hou (Bowei Hou) is a Senior Machine Learning Engineer at Ultralytics and a key contributor to Ultralytics YOLO models shaping the future of computer vision. He is the creator of the YOLOX-Pose algorithm, contributed to monocular depth estimation in Ultralytics YOLO26, and specializes in optimizing and deploying CNN-based models on a variety of AI chips, leveraging advanced techniques like AutoML, NAS, and quantization to maximize performance.