About Me

Hello! I am currently a Ph.D. student at Thrust of Artificial Intelligence at HKUST-GZ, under the supervision of Prof. Menglin Yang. I obtained a Master’s degree in Computer Science and Technology from the School of Artificial Intelligence at JLU, and a Bachelor’s degree in Electronic Engineering from NUDT.

My research interests include Machine Learning (ML) and Deep Learning (DL), with a focus on:

• Large Language Models (LLMs)
  • LLM Agent, Multi-Agent
  • Retrieval-Augmented Generation(RAG), GraphRAG
  • Code Generation
  • LLM Editing
  • others
• Multimodal Learning (MM), Vision-Language model (VLM)
• Electronic Design Assistant (EDA)
• AI-Generated Content (AIGC)
• Geometric Learning with LLM, Geometric Foundation Model, Geometric Alignment
• Graph Learning (GNNs)
• Anomaly Detection (AD)
• Recommender System (RecSys)
• Domain Generalization (DG) and Domain Adaptation (DA)
• Unsupervised Learning, Few-Shot Learning
• Continual Learning (Incremental Learning)

INFORMATION

• E-mail: jli839@connect.hkust-gz.edu.cn
• WeChat: alwaysbeakindperson   (means: always be a kind person)
• Google Scholar: 96
• GitHub:

TECHNICAL ACCOUNTS

EDUCATION

Hong Kong University of Science and Technology (HKUST-GZ)

• Ph.D. in Artificial Intelligence
• Supervisor: Assistant Prof. Menglin Yang

Jilin University (JLU)    985

• M.E. in Computer Science and Technology
• Supervisor: Associate Prof. Qi Wang
• Research Topic: Graph Data Mining, Unsupervised Learning, LLMs
• Academic performance: avg. score: 85.02

The Nc Army College

• B.E. in Commmand
• Academic performance: avg. score: 86.8   rank: 3/98

National University of Defense Technology (NUDT)    985

• B.E. in Electronic Engineering
• Academic performance: avg. score: 82.4   rank: 2/115
• (I have a valid passport and successfully traveled to Europe in 2023, with no issues obtaining a visa)

PAPERS

(+: co-first author, *: corresponding author)

Published

[1] CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection
Jindong Li, Qianli Xing, Qi Wang*, Yi Chang.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD, CCF-B), 2023.
PDF | CODE

[2] ScreenAgent: A Vision Language Model-driven Computer Control Agent
Runliang Niu, Jindong Li, Shiqi Wang, Yali Fu, Xiyu Hu, Xueyuan Leng, He Kong, Yi Chang, Qi Wang*.
International Joint Conference on Artificial Intelligence (IJCAI, CCF-A), 2024.
PDF | CODE | 机器之心

[3] LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism
Wenyu Liu, Jindong Li, Haoji Wang, Run Tan, Yali Fu, Qichuan Tian*
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (J-STARS, JCR Q1), 2025.
PDF | CODE

[4] GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model
Yali Fu+, Jindong Li+, Qi Wang*, Qianli Xing.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD, CCF-B), 2025.
PDF | CODE

arXiv Preprint

[1] Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond
Qi Wang+*, Jindong Li+, Shiqi Wang, Qianli Xing, Runliang Niu, He Kong, Rui Li, Guodong Long, Yi Chang, Chengqi Zhang.
arXiv Preprint.
PDF | GitHub | 机器学习与推荐算法 |

[2] CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey
Jindong Li, Yongguang Li, Yali Fu, Jiahong Liu, Yixin Liu, Menglin Yang*, Irwin King.
arXiv Preprint.
PDF | GitHub | 机器之心 |

[3] Cogito, ergo sum: A Neurobiologically-Inspired Cognition-Memory-Growth System for Code Generation
Yanlong Li, Jindong Li, Qi Wang*, Menglin Yang, He Kong, Shengsheng Wang.
arXiv Preprint.
PDF | CODE | TechXplore

[4] No Fear of Representation Bias: Graph Contrastive Learning with Calibration and Fusion
Jindong Li, Yixin Liu, Qianli Xing, Qi Wang*.
arXiv Preprint.
PDF | CODE

[5] HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly Detection
Yali Fu+, Jindong Li+, Jiahong Liu, Qianli Xing, Qi Wang*, Irwin King.
arXiv Preprint.
PDF | CODE

[6] FANFOLD: Graph Normalization Flows-driven Asymmetric Network for Unsupervised Graph-Level Anomaly Detection
Rui Cao+, Shijie Xue+, Jindong Li+, Qianli Xing, Qi Wang*, Yi Chang.
arXiv Preprint.
PDF | CODE

[7] Revisiting CLIP for SF-OSDA: Unleashing Zero-Shot Potential with Adaptive Threshold and Training-Free Feature Filtering.
Yongguang Li, Jindong Li, Qi Wang*, Qianli Xing, Runliang Niu, Shengsheng Wang, Menglin Yang.
arXiv Preprint.
PDF

[8] Data-Efficient CLIP-Powered Dual-Branch Networks for Source-Free Unsupervised Domain Adaptation
Yongguang Li+, Yueqi Cao+, Jindong Li, Qi Wang, Shengsheng Wang*.
arXiv Preprint.
PDF | CODE

[9] DIRP: Efficient Point Cloud Registration via Dynamic Iteration
Yang Ai, Jindong Li, Qiang Bai, Xi Yang*.
arXiv Preprint.
PDF | CODE

[10] DiffRSG: Rules-based Skip-GCN in Neural Latent Information Diffusion Network for Social Recommendation.
Rui Cao, Jindong Li*, He Kong, Qi Wang, Yi Chang.
[CODE]

In Preparation

[1] Discrete Tokenization for Multimodal LLMs: A Comprehensive Survey.
Jindong Li+, Yali Fu+, Jiahong Liu, Linxiao Cao, Wei Ji, Irwin King, Ming-Hsuan Yang, Mengling Yang*. [GITHUB]

[2] A Survey on LLM Implicit Reasoning.
Jindong Li+, Yali Fu+, Mengling Yang*. [GITHUB]

[3] A Multimodal Benchmark for PCB Placement and Routing.
Jindong Li, Mengling Yang*.

WORK EXPERIENCE

1. Shanghai Artificial Intelligence Laboratory (Shanghai AI Lab)        2023.09-2023.12

• Research Intern
• Mentor: Bin Wang and Linke Ouyang
• Topic: Multimodal Large Language Models (MLLMs), Data Engine
• Responsibilities:
  • Evaluation of MLLMs
  • Multimodal (OCR mainly) models/approaches

2. Jilin University        2024.07-2024.11

• Research Assistant
• Mentor: Yi Chang and Qi Wang

COMPETITION EXPERIENCE

HONORS AND AWARDS

SKILLS

• Language: IELTS Overall Band Score 6.5 (Listening: 6.0, Reading: 7.0, Writing: 6.0, Speaking: 6.5)     2023.11
• Programming Languages: Proficient in Python, C++, Java. Also experienced with C, Go, MySQL.
• Deep Learning Tools: PyTorch, TensorFlow