🔈 About Me

Currently I am a PhD student in the Information Systems Technology and Design (ISTD) pillar at the Singapore University of Technology and Design (SUTD), where I joined in September 2024. I am fortunate to be supervised by Professor Wenxuan Zhang and to be a member of the iNLP Lab at SUTD. My research focuses on Natural Language Processing (NLP), with interests spanning large language model reasoning and efficiency.

Before joining SUTD, I received my Master of Library & Information Science from East China Normal University (2022–2024). Prior to that, I completed dual bachelor’s degrees — in Business Administration from East China Normal University and in Global BBA from Emlyon Business School (2018–2022).

📧 chen_huang[at]mymail[dot]sutd[dot]edu[dot]sg

🔥 News and Events

• 2026.04:  🌟 I will be attending ICLR 2026 in Rio de Janeiro, Brazil. If you are around, feel free to reach out — always happy to connect!
• 2026.02:  🎉 New project MoltNet — understanding social behavior of AI agents in the agent-native MoltBook — is now available on arXiv.
• 2026:  🎉 Paper “PEAR: Phase Entropy Aware Reward for Efficient Reasoning” accepted at ICLR 2026.
• 2025:  🎉 Paper “Text Clustering as Classification with LLMs” accepted at SIGIR-AP 2025.
• 2025:  🎉 Paper “Through the Valley: Path to Effective Long CoT Training for Small Language Models” accepted at EMNLP 2025.

📝 Publications

• MoltNet: Understanding Social Behavior of AI Agents in the Agent-Native MoltBook, Y. Feng, C. Huang, Z. Man, R. Tan, L.P. Hoang, S. Xu, W. Zhang, arXiv preprint arXiv:2602.13458, 2026 | [Project Page]

• PEAR: Phase Entropy Aware Reward for Efficient Reasoning, C. Huang, W. Lu, W. Zhang, ICLR 2026 | [Code]

• Text Clustering as Classification with LLMs, C. Huang, G. He, Proceedings of SIGIR-AP 2025 | [Code]

• Through the Valley: Path to Effective Long CoT Training for Small Language Models, R. Luo, J. Li, C. Huang, W. Lu, Proceedings of EMNLP 2025

• Few-Shot Medical Relation Extraction via Prompt Tuning Enhanced Pre-trained Language Model, G. He, C. Huang, Neurocomputing 633, 129752, 2025

📖 Educations

• 2024.09 - 2029.06 (expected), Doctor of Philosophy (PhD), Information Systems Technology and Design (ISTD), Singapore University of Technology and Design (SUTD), Singapore.
• 2022.09 - 2024.06, Master of Library & Information Science (MLIS), East China Normal University, Shanghai, China. Main research focus: Natural Language Processing.
• 2020.09 - 2022.06, Bachelor, Global Bachelor Business Administration, Emlyon Business School, France.
• 2018.09 - 2020.06, Bachelor, Business Administration, East China Normal University, Shanghai, China.

💻 Internships

• 2023.05 - 2023.11, NLP Intern, China Pacific Insurance (Group) Co Ltd (CPIC), Shanghai, China.
  • Deployed large language models (ChatGLM2-6b) from scratch with API serving via FastAPI and OpenAI-compatible format.
  • Explored quantization-based low-cost deployment, achieving local inference under 7 GB GPU memory.
  • Fine-tuned LLMs using P-Tuning v2 and full-parameter fine-tuning with DeepSpeed-Chat.
  • Designed a task-oriented dialogue (TOD) workflow for CPIC’s intelligent voice customer service, covering intent recognition, entity slot extraction, and multi-turn dialogue management.
  • Constructed a multi-domain TOD training dataset (100K+ dialogue turns across 30 domains) by combining open-source datasets (CrossWOZ, MultiWOZ 2.2, RiSAWOZ) with proprietary data.