CKSRI Seminar Series 2026 "Learning Generalizable Robotic Assembly Policies for Complex Objects"

CKSRI Seminar Series 2026
"Learning Generalizable Robotic Assembly Policies for Complex Objects"

Date: 31 March 2026
Time: 11:00 AM - 12:00 PM
Venue: LTG, HKUST

Event Format: Seminar, Lecture, Talk
Speaker: Prof. Ziqi Wang

ABSTRACT
Assembly is a cornerstone of modern manufacturing and construction, enabling the creation of complex, large-scale products from modular components. Despite its importance, assembly remains a labor-intensive process often requiring hundreds of intricate steps. While robots are increasingly used to automate these tasks, most current systems rely on rigid, pre-programmed procedures that struggle with the "long-horizon" nature of complex assembly.

In this seminar, Prof. Ziqi Wang explores the potential of leveraging Artificial Intelligence to revolutionize robotic planning. Drawing inspiration from the transformative success of large-scale pretraining and reinforcement learning (RL) fine-tuning in large language models (LLMs), Prof. Wang will introduce a novel framework designed to develop robotic assembly policies that are safe, efficient, and highly adaptive to new objects and environments.

About the Speaker
Prof. Ziqi Wang is an Assistant Professor at the Division of Integrative Systems and Design (ISD) at HKUST. Before joining HKUST, he worked as a postdoctoral researcher at EPFL (2024) and ETH Zurich (2022–2024). He earned his Ph.D. in Computer Science from EPFL in 2021 and completed his bachelor’s degree in Mathematics at the University of Science and Technology of China (USTC) in 2017.