Scholar
Hongyi Ling
Google Scholar ID: ei8O1BEAAAAJ
Texas A&M University
Graph Neural Networks
Trustworthy AI
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Citations & Impact
All-time
Citations
359
H-index
6
i10-index
6
Publications
12
Co-authors
10
list available
Contact
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Publications
9 items
Sound State Encodings in Translational Separation Logic Verifiers (Extended Version)
2026
Cited
0
Balancing Fine-tuning and RAG: A Hybrid Strategy for Dynamic LLM Recommendation Updates
2025
Cited
0
Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics
2025
Cited
0
Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
2025
Cited
0
Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists
2025
Cited
0
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation
Neural Information Processing Systems · 2025
Cited
0
Complex LLM Planning via Automated Heuristics Discovery
2025
Cited
0
Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights
2025
Cited
0
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Resume (English only)
Academic Achievements
- Paper 'Graph Mixup with Soft Alignments' accepted to ICML 2023
- Paper 'Learning Fair Graph Representations via Automated Data Augmentations' accepted to ICLR 2023 as a Spotlight (top 8.0%)
- Program Committee Member & Reviewer for conferences including ICLR 2024, ICML 2023, NeurIPS 2023, LoG 2023, ACM TIST, etc.
Research Experience
- Software Development Engineer Intern, Amazon Web Services, Summer 2020
Education
- Ph.D. Student, Department of Computer Science & Engineering, Texas A&M University, Advisor: Prof. Shuiwang Ji, August 2019 - present
- M.S. Student, Department of Computer Science & Engineering, University of California San Diego, September 2019 - June 2021
- B.S. Student, Department of Computer Science and Technology, Nanjing University, Advisor: Prof. Limin Wang, September 2015 - June 2019
Background
Research Interests: Deep learning and machine learning, specifically in graph deep learning, trustworthy AI, fairness, and causal machine learning.
Miscellany
Résumé link provided
Co-authors
10 total
Shuiwang Ji, Professor and Truchard Family Chair
Department of Computer Science & Engineering, Texas A&M University
Zhimeng Jiang
Google, TAMU
Na Zou
Assistant Professor, University of Houston
Meng Liu
Research Scientist, NVIDIA
Xuan Zhang
PhD student, Department of Computer Science & Engineering, Texas A&M University
Cong Fu
Texas A&M University, Computer Science
Co-author 7
Henrik Iskov Christensen
Director / Professor @ UCSD
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