About Me

Hello! I am currently a Ph.D. student in The Integrated Science and Engineering Project at the National University of Singapore (NUS), honored to be a President's Scholar. I am conducting research under the supervision of Prof. T. H. Lee (Fellow of the Singapore Academy of Engineering) in the Lee Group.

I am driven by a passion for solving foundational challenges at the intersection of artificial intelligence and physical sciences. My work in AI for Science (AI4S) and AI for Engineering (AI4E) focuses on building intelligent systems that can understand, predict, and optimize complex real-world phenomena.

My research experience spans top academic institutions and industry leaders. I have held positions at Huawei, JD.com, and Apple, and served as a CTO for a medical intelligence startup. I graduated Rank 1st from both my Master’s at Tsinghua University and Undergraduate at HIT.

Research Interests:

• Robotic Manipulation: Dexterous hand operation, Visual tactile guidance.
• Embodied AI: World Models, Vision-Language-Action (VLA) models.
• AI for Science: GNNs, Physics-Informed Neural Networks (PINNs) for fluid/structure dynamics.
• Control: Reinforcement learning, Learning-based control.

🔥 News

• [Aug 2025] Began Ph.D. journey as a President’s Scholar at NUS (Singapore's Highest Honor for PhD)!
• [Jun 2025] Graduating from Tsinghua University (Master's), Ranked 1st/1215 (Outstanding Graduate, Top 1%, Highest Honor of Tsinghua University).
• [Apr 2025] Awarded the Hong Kong PhD Fellowship Scheme (HKPFS) at The University of Hong Kong (Hong Kong's Highest Honor for PhD).
• [Feb 2025] Joined Apple as an MQE Intern. Leveraged LLM and Deep Learning to boost efficiency by 400% for 5 Audio/Home vendors. Awarded Outstanding Intern.
• [Nov 2024] Joined JD.com Embodied Intelligence division (VLA models for robotics).
• [Feb 2024] Paper on GNNs for liquid splashing published in Int. J. Numer. Method. HFF (SCI Q1).
• [Dec 2023] Received Outstanding Paper Award at ICCSMT 2023.
• [Jun 2023] Joined Huawei Cloud (Joint Training) as an AI for Simulation Algorithm Architect & Product Manager. Awarded Outstanding Intern and 1st Place in Tsinghua Professional Practice (Ranked 1/1215).
• [Jun 2022] Graduated from Harbin Institute of Technology (Bachelor's), Ranked 1st/151 (Outstanding Graduate, Top 1%, Highest Honor of HIT).
• [Dec 2020] Awarded National Scholarship (Assuming highest honor for undergraduates in China).

📖 Education

National University of Singapore (NUS) 2025 - Present

Ph.D. in Engineering. President's Scholar, ISEP Scholar.

• Research Direction: Dexterous Manipulation & Reinforcement Learning.
• Advisors: Prof. Tong Heng Lee (Former Vice President (Research); Fellow of the Academy of Engineering, Singapore; Past President of Asian Control Association) and Prof. Shuzhi Sam Ge (Fellow of the Academy of Engineering, Singapore; IEEE Fellow; President of Asian Control Association).

Tsinghua University 2022 - 2025

Master of Mechanical Engineering.

• Rank: 1 / 1215 (Top 1%)
• Research Direction: Intelligent Manufacturing (Deep Learning for Physical Simulation Acceleration & Computer Graphics).
• Outstanding Graduate, First Prize in Professional Practice.
• Advisors: Prof. Pingfa Feng (Head of the Department of Intelligent Equipment) and Prof. Feng Feng (Assistant Dean of the Institute for Data and Information).

Harbin Institute of Technology (HIT) 2018 - 2022

Bachelor of Engineering.

• Rank: 1 / 151 (Top 1%)
• Research Direction: Intelligent Equipment CNC Robotics.
• National Scholarship (Highest honor for undergrads).
• Outstanding Graduate, Outstanding Thesis.
• Advisor: Prof. Zhenyu Han (Vice Dean of the School of Mechatronics Engineering).

🛠️ Skills

• Programming: Python, C++, MATLAB (Huawei Certified).
• Simulation & Engineering: ABAQUS, ANSYS, COMSOL, Solidworks, AutoCAD.
• AI & Tools: PyTorch, GNNs, PINNs, OpenCV, Visio.
• Languages: English (IELTS 6.5), Chinese (Native).

💻 Professional Experience

A*STAR (Agency for Science, Technology and Research)

Research Intern

Aug 2025 - Present | Singapore

• Conducted research on robotic manipulation and computer vision.
• Advisors: Dr. Yan Wu and Dr. Wenyu Liang.

Apple

Manufacturing Quality Engineer (MQE) Intern

Feb 2025 - Aug 2025 | Shenzhen & USA

• Enhancing signal testing frameworks for intelligent home systems.
• Applying GNN, CNN, and PINN to predict and detect defects in material processing for high-precision manufacturing.
• Awarded Outstanding Intern.

JD Technology (JD.com)

Algorithm Engineer Intern

Nov 2024 - Feb 2025 | Beijing

• Developing Vision-Language-Action (VLA) models for robotic manipulation in warehousing.
• Building an atomic skill library for robotic arms to enable modular task execution.

Huawei Cloud

Joint Training Researcher (Cloud Architecture Lab)

Jun 2023 - Sep 2024 | Shenzhen & Germany

• AI-driven simulation (AI4E): SPH for fluid dynamics and GNN-based pipeline predictions.
• Integrated PINNs for burr fracture prediction and AI-enhanced chip heat dissipation models.
• Awarded Outstanding Intern.

Shenzhen Institute of Innovation and Entrepreneurship

CTO (Medical Intelligence Startup Team)

Jul 2022 - Present

• Secured seed investment from Prof. Li Zexiang (HKUST).
• Leading development of AI-driven intelligent dental cleaning systems with real-time diagnostics.

📝 Publications

Selected Journals & Conferences

LLM-in-the-loop variable impedance control: Towards safe generalized and personalized robotic interactions

J. Xue, Wenyu Liang, Yilan Xu, J. Nan, Y. Wu, T. H. Lee

AAAI, 2026. (Target/Under Review)

Highlights: Novel framework mapping natural language to controller parameters using LLMs for personalized human-robot interaction.

Efficient modeling of liquid splashing via graph neural networks with adaptive filter and aggregator fusion

J. Nan, P. Feng, J. Xu, F. Feng

International Journal of Numerical Methods for Heat & Fluid Flow, 2024. (SCI Q1)

Highlights: Achieved 30.3% accuracy improvement and 51.6% speed gain over traditional CFD using FEGNS framework.

Advanced Prediction of Microfluidic Flow in Medical Pipelines Using Graph Neural Networks

J. Nan, P. Feng, J. Xu, F. Feng

International Journal of Numerical Methods for Heat & Fluid Flow. (Under Review)

Highlights: Proposed a novel approach using Graph Neural Networks (GNNs) for predicting microfluidic flow behaviors in medical pipelines with complex geometries. Successfully reduced computational time while maintaining high prediction accuracy, outperforming traditional CFD methods.

Working Papers

Physics-Informed Neural Networks for Burr Fracture Prediction in 3D Elastic Structures

(Joint work with German Research Institute)

Highlights: Proposed a Physics-Informed Neural Network (PINN) model to predict burr fracture behavior in 3D elastic structures. Embedded physical constraints directly into the neural network, significantly improving prediction accuracy and reducing inference time to less than 1s (vs 18s for FEM).

Graph Neural Network-Enhanced Chip Heat Dissipation Simulation for PCB Components

(Joint work with Hisilicon)

Highlights: Utilized GNNs to enhance the simulation of conjugate heat transfer in multi-phase solid-fluid systems. Predicts temperature distribution with less than 1.2% error while improving simulation performance for PCB thermal design.

An Atomic Skill Library Construction Method Combined Embodiment VLA

(Joint work with JD.com)

Highlights: Proposed a data-driven Atomic Skill Library construction method based on Vision-Language Models (VLP and VLA). Decomposes complex industrial tasks into reusable atomic skill modules, achieving high success rates and zero-shot sim-to-real transfer.

Patents & Software

• Neural Network-driven SPH Fluid Acceleration System V1.0. China Software Copyright 2024SR0821036.
• A handling robot with an adjustable manipulator. Patent ZL 2019 2 1806945.7.

🏆 Honors & Scholarships

💬 Invited Talks

• NTU CSSA (2026.01): Interview on Embodied AI Development & PhD in Singapore.
• Tsinghua University (2025.05): Interview on First Prize in Professional Practice (Rank 1/1215): Neural Network Accelerated Simulation Software & Joint Training with Huawei.
• Apple (2025.03): Anomaly Detection in Manufacturing using GNNs.
• JD.com (2024.07): Atomic Skill Libraries via Vision-Language Models.
• Harbin Institute of Technology (2022.06): Interview on National Scholarship & Outstanding Graduate: Undergraduate Journey.

🌍 Leadership & Volunteer Work

• Tsinghua: Career Development Mentor (News); International Graduate Practice Team Leader (Singapore & Indonesia); Rural Revitalization Deputy Leader.
• HIT: Secretary of Top Ten Academic Support Organizations.