Resume
Academic Achievements
- Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding, ACM WWW 2024
- LLM-Ensemble: Optimal Large Language Models Ensemble Method for E-commerce Product Attribute Value Extraction, SIGIR 2024 industry track
- Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation, IEEE BigData 2023
- A Counterfactual Fair Model for Longitudinal Electronic Health Records via Deconfounder, IEEE ICDM 2023
- Relation labeling in product knowledge graphs with large language models for e-commerce, International Journal of Machine Learning and Cybernetics (JMLC)
- Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation, IEEE BigData 2022
- Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders, IEEE BigData 2022
- Mitigating Health Disparities in EHR via Deconfounder, ACM BCB 2022
- Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network, IEEE BigData 2021
- Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network, ACM SIGIR 2021
- Basket Recommendation with Multi-Intent Translation Graph Neural Network, IEEE BigData 2020
- Heterogeneous Similarity Graph Neural Network on Electronic Health Record, IEEE BigData 2020
- Dynamic Graph Collaborative Filtering, IEEE ICDM 2020
- Blood Pressure Prediction via Recurrent Models with Contextual Layer, WWW 2017
Research Experience
- Working as a Senior Data Scientist at Walmart Global Tech, involved in Generative AI applications related to e-commerce and recommender systems.
Education
- Received a Ph.D. in Computer Science from the University of Illinois at Chicago (UIC), under the supervision of Prof. Philip S. Yu.
Background
- Research interests include large language models, multi-modal language models, diffusion models, and recommender systems. Currently working as a Senior Data Scientist at Walmart Global Tech, focusing on Generative AI applications in e-commerce and recommender systems.
Miscellany
- No specific personal interests or hobbies mentioned.