Postdoctoral Research Fellow at
NExT++ Research Center and National Cybersecurity R&D Lab
School of Computing
National University of Singapore
Email: yunshan dot ma at u dot nus dot edu dot com or mysbupt at gmail.com
• Google Scholar Page • GitHub Page
Biography
I am a Postdoctoral Research Fellow in National University of Singapore, where I am a member of NExT++ Research Center, supervised by Prof. Chua Tat-Seng. And I am also under National Cybersecurity R&D Lab and work with Prof. Chang Ee-Chien. I have served as the PC member for top-tier conferences including SIGIR, KDD, and the invited reviewer for prestigious journals including TKDE, TOIS, and TMM.
Prospective Ph.D., Master, and Undergraduate Students
I am looking for highly motivated students (PhD, master, undergraduate students) to work together on multimodal event forecating, computational fashion, and recommender system. Please feel free to send me your CV and transcripts, if you have interest. We are also actively looking for opportunities in research, partnership and commercialization in exciting data science projects.
News
Smart Fitting Room: A One-stop Framework for Matching-aware Virtual Try-On. [pdf]
FashionReGen: LLM-Empowered Fashion Report Generation. [pdf]
DiFashion: Towards Personalized Outfit Generation. [pdf]
Filter-based Stance Network for Rumor Verification. [pdf]
Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models. [pdf]
MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation. [pdf]
Enhancing Item-level Bundle Representation for Bundle Recommendation. [pdf]
Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction. [pdf]
Rule-guided Counterfactual Explainable Recommendation. [pdf]
Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction. [pdf]
A Learning-Based Approach for Estimating Inertial Properties of Unknown Objects from Encoder Discrepancies. [pdf]
Personalized Fashion Outfit Generation with User Coordination Preference Learning. [pdf]
Context-aware Event Forecasting via Graph Disentanglement. [pdf]
FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs. [pdf]
Strategy-aware Bundle Recommender System. [pdf]
Causal Disentangled Recommendation Against User Preference Shifts. [pdf]
CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation. [pdf]
Professional Services
- I will be a volunteers co-chair in The Web Conf 2024.
- I chair the session of Recommendations and Ads of SIRIP in SIGIR 2023.
- I serve as an area co-chair of Information Retrieval, Text Classification, and Question Answering in CCL 2023.
- KDD, WWW, SIGIR, IJCAI, ACMMM, WSDM, AAAI, etc.
- TKDE, TOIS, TMM, ToMM, TWeb, TIST, etc.
Honors and Awards
Background
Supervisor: Prof Tat-Seng Chua.
Supervisor: Prof Tat-Seng Chua.