Zheye Deng

E-mail: zdengah at cse dot ust dot hk

Hi! I am Zheye Deng (邓哲也). I am a third-year Ph.D. student at The Hong Kong University of Science and Technology advised by Prof. Yangqiu Song. I received my B.Sc. in Computer Science from Peking University, where I was advised by Prof. Ming Zhang.

My research interest mainly focus on the integration of graph structures and natural language in machine learning, including the construction of large-scale knowledge graphs, as well as extracting and integrating structural information from texts to enhance the ability to answer complex queries.

Interests
  • Knowledge Graph
  • Neural Graph Database
  • Information Extraction
Education
  • Ph.D. in Computer Science and Engineering, 2022-Present

    The Hong Kong University of Science and Technology

  • B.Sc. in Computer Science and Technology, 2016-2020

    Peking University

Experience

 
 
 
 
 
Research and Development Engineer
July 2020 – August 2022 Beijing, China
  • Contributed code to MegEngine, a deep learning framework with auto-differentiation.
  • Focused on optimizing the memory usage during model training with SOTA approaches.
  • Improved and implemented a gradient checkpointing algorithm DTR in MegEngine.
 
 
 
 
 
Research Assistant
January 2017 – July 2020 Beijing, China
  • Advisor: Prof. Ming Zhang
  • Focused on natural language processing, recommendation system and data mining:
    • Graph Neural Networks for Table-based Fact Verification
    • Sequential Recommendation with Contrastive Predictive Coding
    • ACM International Conference on Web Search and Data Mining Cup 2018
 
 
 
 
 
Research Assistant
June 2019 – September 2019 Santa Barbara, CA, USA
  • Advisor: Prof. William Wang
  • Published a large and high-quality dataset called AnchorNER using abstracts from Wikipedia and DBpedia
  • Developed a neural correction model for open-domain Named Entity Recognition and obtained SOTA results
 
 
 
 
 
Research and Development Engineer
June 2018 – October 2018 Beijing, China
  • Developed an algorithm based on a decision tree to identify comment baiting videos in TikTok.
  • Collaborated with team members using Kafka and HiveQL to process massive user data.

Publications

(2024). Evaluating and Enhancing LLMs Agent based on Theory of Mind in Guandan: A Multi-Player Cooperative Game under Imperfect Information.

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(2024). Text-Tuple-Table: Towards Information Integration in Text-to-Table Generation via Global Tuple Extraction.

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(2024). NegotiationToM: A Benchmark for Stress-testing Machine Theory of Mind on Negotiation Surrounding.

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(2023). Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise Detection. In Findings of EMNLP 2023.

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Awards

  • HKUST RedBird Academic Excellence Award for Continuing PhD Students (2023 - 2024)
  • Hong Kong PhD Fellowship (2022 - 2026)
  • HKUST RedBird PhD Scholarship (2022)
  • Third-class Scholarship from Peking University (2019)

Teaching

  • COMP4332 Big Data Mining and Management Teaching Assistant (Spring 2023)
  • Learning Python with Data Mining: Experience and Outlook (Spring 2019)
  • Foundations of Computer (Fall 2018)