Short Bio

Hi everyone. I’m currently a PhD student at Responsible AI (RAI) Lab, Department of Computer Science, Florida State University. I feel very much fortunate to be advised by Dr. Yushun Dong. My research interests include Spatial-Temporal Data Mining, Graph Neural Networks, AI+X, LLMs & Foundation Models. In general, I’m always highly interested in broad machine-learning fields, application of heterogeneous data mining, and AI+X technologies.

You can find my Google Scholar here: Lincan Li
Github Site here: Lincan Li

Email Contact: ll24bb@fsu.edu

Background

• Researcher at University of New South Wales (Nov 2023 - Dec 2024)
• MPhil at Zhejiang University & Exchange Student at The University of Sydney
• Bachelor at Northeastern University

2024 Latest👍

(Dec/10/2024)🫶🫶 Our Latest “AI+X” Study–“Political-LLM: Large Language Models in Political Science”, the First & Systematic Large Language Model’s guidebook on Political Science Domain, collaborated with 30+ Top Universities and our industrial parterns from NVIDIA and Adobe, is now available online. It is again reported by several major medias, see the Redbook media reports, X posts, AI literature digest, and Wechat recommendation.

See Political-LLM paper here: paper

See Political-LLM online resource library here: website

(Dec/06/2024) ✈️ Touching down Orlando, FL. New journey starts here.

(Nov 2024) Act as the Organization Committee of FSU Student Seminar. Welcome everyone to participate in our inspiring seminar! If you’re currently affiliated with FSU and wish to give a talk at the seminar, please fill in the Google Form. If you are outside FSU and wish to give a talk, please contact me at this email or Dr. Yushun Dong at this email. Thank you.

(Oct/03/2024) Invited reviewer for AISTATS & ICASSP 2025.

(Sep/28/2024) Invited reviewer for ICRL 2025.

(Jun/20/2024) Invited reviewer for NeurIPS 2025.

(June/01/2024) A first-authored paper entitled “Di-GraphGAN: An Enhanced Adversarial Learning Framework for Accurate Spatial-Temporal Traffic Forecasting Under Data Missing Scenarios” is accepted by INFORMATION SCIENCES journal.

(May/13/2024) Our new work leveraging Mamba, the latest deep learning-based selective state space model for Spatial-Temporal Graph Learning is now available.

Paper: STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model

Code: https://github.com/LincanLi98/STG-Mamba/

(Jan/30/2024) Our New survey paper:Data-Centric Evolution in Autonomous Driving: A Comprehensive Survey of Big Data System, Data Mining, and Closed-Loop Technologies is available on ArXiV. It was reported by several major social media platforms, see the media report here.

Paper: Data-Centric Evolution in Autonomous Driving: A Comprehensive Survey of Big Data System, Data Mining, and Closed-Loop Technologies

Code: https://github.com/LincanLi98/Awesome-Data-Centric-Autonomous-Driving

Research Publications

1. Lincan Li, Hanchen Wang, Wenjie Zhang. “STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model”. (Arxiv Preprint).
2. Lincan Li, Jichao Bi, Kaixiang Yang, and Fengji Luo. “Di-GraphGAN: An Enhanced Adversarial Learning Framework for Accurate Spatial-Temporal Traffic Forecasting Under Data Missing Scenarios.” Information Sciences, Accepted, pp. 1-18, 2024. (Journal Article, IF: 8.1, JCR Category Quartile: Q1)
3. Lincan Li, Kaixiang Yang, Fengji Luo, and Jichao Bi. “STS-CCL: Spatial-Temporal Synchronous Contextual Contrastive Learning for Urban Traffic Forecasting.” in the 48th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024, CCF-B).
4. Lincan Li, Jichao Bi, Kaixiang Yang, Fengji Luo and Lu-Xing Yang. “MGC-GAN: Multi-Graph Convolutional Generative Adverserial Networks for Accurate Citywide Traffic Flow Prediction,” in the 52nd IEEE International Conference on Systems, Man, and Cybernetics (SMC 2022), pp. 2557-2562. [Oral]
5. Lincan Li, Jichao Bi, Kaixiang Yang, and Fengji Luo, “Spatial-Temporal Semantic Generative Adversarial Networks for Flexible Multi-step Urban Flow Prediction,” in 31st International Conference on Artificial Neural Networks (ICANN 2022). Springer-Verlag, pp.763–775.
6. Lincan Li, Tong Jia. “Optical Coherence Tomography Vulnerable Plaque Segmentation based on Deep Residual U-Net.” Reviews in Cardiovascular Medicine 20.3 (2019): 171-177. (Journal Article, IF: 4.43, JCR Quartile: Q2)

Academic Awards & Competitions

1. Excellent Master Dissertation Award (Top 1%), “Research on Integrated Urban Traffic Forecasting and Spatiotemporal Data Imputation based on GANs and Graph Representation”.
2. National Scholarship for Undergraduate Student. Awarded by Ministry of Education, Awarded in 2019 and 2020, respectively. (For Top 1% excellent students).
3. Meritorious Winner (First Prize) of the International Interdisciplinary Contest In Mathematical Modeling (ICM). Awarded in April, 2019.

Academic Internship/Exchange at World Leading Institutions

Academic Services

• I’m a long-term reviewer of AAAI/IJCAI/NeurlPS/KDD/ACM MM/ICRL and other top CORE A* conferences in the field of artificial intelligence and deep learning. I’m a graduate student member of ACM and IEEE Society.
• Invited reviewer for IEEE Transactions on Knowledge and Data Engineering.
• Invited reviewer for IEEE Transactions on Intelligent Vehicles.
• Intived reviewer for IEEE Transactions on Industrial Informatics.

More.

• Like other top-tier scholars in academia, I work hard, value time.
• I embrace any kind of challenges in work and life with strong belief, and I always thank life for taking me here.
• I enjoy various kinds of sports in my spare time. I’ve been practicing various kinds of sports since I was 16. I have successfully completed two marathon races. In Sydney and Hangzhou, respectively.
• Love music (R&B, Pop, Hip-Hop, EDM, Afrobeat) and arts (Fashion design, Architecture design, Photography).