About Me

Here is Hanyang Zhong (Hanyang, 钟翰扬).

I am a second-year PhD candidate in the School of Electronic Engineering at the University of York in the UK. My research interests encompass Large Language Models, Multi-modality, 3D Reconstruction, SLAM and Embodied AI. I am currently conducting doctoral research under the supervision of Professor Mark Post, investigating the integration of large language models with robots and Multi-agent SLAM system.

My background includes experience as a researcher in Professor Post’s lab at York, where my focus has been on advancing the state-of-the-art in language model capabilities for robotic platforms. I have a passion for interdisciplinary research that bridges LLM, Embodied AI, and 3D Reconstruction.

I would be delighted to discuss potential collaborations or my research in more detail. Please feel free to email me if you would like to connect further (hanyang.zhong@york.ac.uk).

Academic Background

[Highlight] I am looking for postdoctoral research to start in 2025 Fall. Contact me if you have any leads!

Sep 2021 - June 2022: University of York (MSc)
Sep 2022 - Now: University of York (Phd)

I am currently pursuing a PhD. Upon successful PhD completion, I hope to obtain postdoctoral research opportunities in academia or industry. My goal is to excel in my doctoral studies to be competitive for quality postdoc positions related to my expertise.

Research Interests

Large language models (LLM)
Multi-modality
3D Reconstruction
SLAM
AI Agent
Robotics
Embodied AI

My research centers on advancing Embodied AI by integrating large language models with Robotic platforms, investigating how a robot’s grounded Multi-modality experiences may enrich and enhance the knowledge and inferences of a language model.

News and Updates

July 2024： The ICME 2024 was perfectly held, and our papers (Camera Ready Version of LLM-SAP and FENet) were perfectly exhibited at the conference. Welcome to continue following our work.
April 2024： Our work LLM-SAP: Large Language Models Situational Awareness Based Planning has been accepted to ICMEW 2024 . See you in Canada! Preprint version download🔗
March 2024： Our work FENet: Focusing Enhanced Network for Lane Detection has been accepted to ICME 2024 as an Oral paper. See you in Canada! Preprint version download🔗
Jan 2024: Becoming an ICME reviewer!
Dec 2023: I posted a preprint on arXiv titled “LLM-SAP: Large Language Model Situational Awareness Based Planning” exploring the use of LLMs to enable context-aware robot planning. I welcome constructive feedback, related perspectives, and relevant citations from the community as I continue developing these ideas at the intersection of language models, robotics, and embodied intelligence. Please reach out if you see potential connections to your own research - I believe open collaboration can advance this emerging field.
Dec 2023: I posted the preprint “FENet: Focusing Enhanced Network for Lane Detection” on arXiv. This paper proposes a novel neural network approach to improve lane detection capabilities in autonomous driving. I welcome constructive feedback, relevant perspectives, and citations from the community as I continue refining this method. Please reach out if you see potential connections to your own work at the intersection of computer vision and autonomous systems - open collaboration can advance this important field.