Research Focus
During my Ph.D. studies at USC, I focused on representation learning, knowledge graphs, and machine learning research under the supervision of Prof. C.-C. Jay Kuo (ACM Fellow, IEEE Fellow).
Publications
- Graph-Based Deep-Tree Recursive Neural Network (DTRNN) for Text Classification
- Deepwalk-Assisted Graph PCA (DGPCA) for Language Networks
- K-Covers for Active Learning in Image Classification
- Post-Processing of Word Representations via Variance Normalization and Dynamic Embedding
- Evaluating Word Embedding Models: Methods and Experimental Results — ATSIP 2019
- Graph Representation Learning: A Survey
- Efficient Sentence Embedding via Semantic Subspace Analysis
- SBERT-WK: A Sentence Embedding Method by Dissecting BERT-based Word Models — TASLP 2020
- Dynamic Texture Synthesis by Incorporating Long-range Spatial and Temporal Correlations
- AnomalyHop: An SSL-based Image Anomaly Localization Method
- Inductive Learning on Commonsense Knowledge Graph Completion — KDD 2021
- PEDENet: Image Anomaly Localization via Patch Embedding and Density Estimation
- GraphHop: An Enhanced Label Propagation Method for Node Classification
- Task-Specific Dependency-based Word Embedding Methods
- CORE: A Knowledge Graph Entity Type Prediction Method via Complex Space Regression and Embedding
- KGBoost: A Classification-Based Knowledge Base Completion Method with Negative Sampling
- Just Rank: Rethinking Evaluation with Word and Sentence Similarities — ACL 2022
- SynWMD: Syntax-aware Word Mover's Distance for Sentence Similarity Evaluation
- TypeEA: Type-Associated Embedding for Knowledge Graph Entity Alignment
- An Overview on Language Models: Recent Developments and Outlook
- CompoundE: Compounding Geometric Operations for Knowledge Graph Completion
- GreenKGC: A Lightweight Knowledge Graph Completion Method
- Knowledge Graph Embedding: An Overview
- Knowledge Graph Embedding with 3D Compound Geometric Transformations
- AsyncET: Asynchronous Learning for Knowledge Graph Entity Typing with Auxiliary Relations
Awards
- APSIPA Sadaoki Furui Prize Paper Award, 2024
- APSIPA Sadaoki Furui Prize Paper Award, 2022
- GSG Research Travel Grant, USC, 2019
Teaching Assistantships
- EE 599 — Applied and Cloud Computing for Electrical Engineers. Instructor: Dr. Brandon Franzke. Spring 2021.
- EE 141L — Applied Linear Algebra for Engineers. Instructor: Prof. Antonio Ortega. Fall 2020.
- EE 155L — Introduction to Computer Programming for Electrical Engineers. Instructor: Prof. Sandeep Gupta. Spring 2020.
- EE 141L — Applied Linear Algebra for Engineers. Instructor: Prof. Antonio Ortega. Fall 2019.
- EE 483 — Introduction to Digital Signal Processing. Instructor: Dr. Robert Popoli. Spring 2019.
- EE 483 — Introduction to Digital Signal Processing. Instructor: Prof. Richard Leahy. Fall 2018.