Yuanchu (James) Liang

PhD Candidate @ The Australian National University

About Me

Nice to meet you! I am Yuanchu Liang based in Australia, Canberra. I am doing a computer science PhD, supervised by Prof. Hanna Kurniawati, at the Robust Decision Making and Learning Lab, The Australian National Univeristy (ANU). Before this, I finished my high school in Adelaide, and graduated with a double degree in Engineering and Science from the ANU.

My research direction focuses on building robust general purpose sequential decision making systems with application in robotics. It is my hope to see robots becoming an essential ingredient in our daily life in the future, just like smart phones today. To achieve this, I want to extent robots’ capabilities in handling uncertainties from the real world and efficiently learning useful patterns from the environment.

In particular, I am interested in the Partially Observable Markov Decision Process (POMDP) and designing scalable POMDP solution methods for Robotics motion planning under uncertainties. On the learning aspects, I look into sample efficient reinforcement learning algorithms, transfer learnings and generalisations under uncertainties.

Outside of work, I love meeting new people, sharing new ideas, reading books and climbing rocks, the latter has has became my way of meditation :)

Graduate Education

PhD

ANU

2024 - Current

My PhD thesis focuses on designing general, robust and efficient intelligent (AI) systems for robotics. Specifically, I am interested in Partially Observable Markov Decision Process (POMDPs), reinforcement learning (RL) and generative models.

Specific topics include motion planning under uncertainties, provably efficient parametric RL, and diffusion policy fine-tuning with RL.

Broadly speaking, I am pretty interested in any topic related to sequential learning under uncertainties!

Undergraduate Education

Bachelor of Engineering (1st Hon) and Bachelor of Science.

ANU

2019 - 2023

The flexibility offered by ANU allows me to do a double degree in Enginnering and Science.

I specialised in mechatronics engineering and explored areas like control theory, system dynamics, embedded systems and robotics.

Under my science degree, I studied computer science with a focus on AI and ML, and mathematics including analysis, algebra and computational maths.

Publications

Squared Family MDPs Provably Efficient RL with Tractable Representations

Liang, Y., Tsuchida, R., Ong, C., and Kurniawati, H., Squared Family MDPs: Provably Efficient RL with Tractable Representations. In 2026 International Conference on Machine Learning (under review).

Thinking Fast and Far Long Horizon Online POMDP Planning via Rapid State Space Sampling

Liang, Y., Kim, E., Knoll, J, A., Thomason, W., Kingston, Z., Kurniawati, H. and Kavraki, L.E., Thinking Fast and Far: Long-Horizon Online POMDP Planning via Rapid State Sampling. In 2026 International Journal of Robotics Research (IJRR).

Scaling Long-Horizon Online POMDP Planning via Rapid State Space Sampling

Paper Link

Liang, Y., Kim, E., Thomason, W., Kingston, Z., Kurniawati, H. and Kavraki, L.E., 2024. Scaling Long-Horizon Online POMDP Planning via Rapid State Space Sampling. In 2024 International Symposium of Robotics Research (ISRR).

Recurrent Macro Actions Generator for POMDP Planning

Paper Link

Liang, Y. and Kurniawati, H., 2023, October. Recurrent macro actions generator for POMDP planning. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 2026-2033). IEEE.

DRT A Lightweight Single Image Deraining Recursive Transformer

Paper Link

Liang, Y., Anwar, S. and Liu, Y., 2022. DRT: A lightweight single image deraining recursive transformer. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 589-598).

Other Experiences

Maincode AI Residency Program

Diffusion Policy Fine-Tuning with Rinforcement Learning

Mar 2026 - Current

I collaborate with Dr Yue Yang from Maincode and work on designing sample efficient RL fine tuning algorithms for pre-trained diffusion policy.

ANU Summer Research Scholarships

Online Attention in Social Media

Nov 2021 - Feb 2022

I worked with Prof. Lexing Xie on online attention markets and the effects of filter bubbles and echo chamber effects in social media. We investigated in different stochastic models to simulate the online interaction process and used the T-Recs simulator to perform experiments.

CSIRO Student Internships

Nov 2022 - Mar 2023

During the last year of my undergraduate, I worked with Dr Tirthankar Bandyopadhyay at CSIRO and built a simulation environment for robotic arms to interact with cluttered objects. Specifically, I used the Mujoco physics engine and OMPL library to achieve the goal.

More About Me

RDL Lab Climbing Photos