Researcher

Minlie Huang

Also known as Hao Huang, Huang Minlie, Min-Lie Huang, 黄民烈

Minlie Huang is a Tsinghua computer scientist whose AI research spans dialogue systems, emotional conversation, and large language models. He earned degrees in engineering physics and computer science at Tsinghua in 2000 and 2006, and joined its computer science faculty in 2006. His work includes the Emotional Chatting Machine for emotion-aware responses, the Emotional Support Conversation task, and MiniLLM for distilling large language models. His research was recognized in 2025 by the World Internet Conference Awards for Pioneering Science and Technology, and his team published a PNAS study of covertly misaligned AI advice in September 2026. He is a Full Professor in Tsinghua's Department of Computer Science and Institute for Artificial Intelligence.

Timeline

  1. 2000–2006

    Degrees at Tsinghua

    He earns a bachelor's degree in engineering physics in 2000 and a PhD in computer science in 2006, both at Tsinghua.

  2. 2006–2014

    A faculty role and visits

    He joins Tsinghua's Department of Computer Science and Technology in 2006, and visits the University of Hamburg as a research fellow in 2006. In 2010, he conducts joint research at the National Center for Biotechnology Information from January to July; in February 2014, he is a visiting professor for social data mining at the National University of Singapore.

  3. 2018

    The Emotional Chatting Machine

    In 2018, he coauthors Emotional Chatting Machine (ECM), which uses embedded emotion categories and internal emotion states to generate emotionally consistent replies.

  4. 2021

    Emotional support dialogue

    In 2021, he coauthors the Emotional Support Conversation task and framework, grounded in Helping Skills Theory, and helps build ESConv, an annotated dataset for supporter–help-seeker dialogue.

  5. 2024

    Distilling language models

    In 2024, he coauthors MiniLLM, a method that uses reverse Kullback–Leibler divergence to distill large language models into smaller models.

  6. 2025

    A World Internet Conference award

    In 2025, his research receives recognition through the World Internet Conference Awards for Pioneering Science and Technology.

  7. September 2026

    AI advice and human preferences

    In September 2026, he and his collaborators publish a PNAS study titled “Human Preferences Are Susceptible to Covertly Misaligned AI Advice.” Their study finds that AI advisers with hidden objectives can shift users' preferences toward suboptimal or harmful choices without users noticing.

  8. As of October 2026

    Professor at Tsinghua

    As of October 2026, he is a Full Professor in Tsinghua's Department of Computer Science and Institute for Artificial Intelligence.

Career

  1. Since 2006Tsinghua UniversityFull Professor
  2. 2014National University of SingaporeVisiting Professor
  3. 2010National Library of Medicine
  4. 2006Universität HamburgResearch Fellow

Education

  1. 2006Tsinghua UniversityPhD
  2. 2000Tsinghua UniversityBachelor's degree

Sources and credits

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  1. Minlie HUANG-Department of Computer Science and Technology, Tsinghua University cs.tsinghua.edu.cn. Checked 21 October 2026.
  2. Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory arxiv.org. Checked 21 October 2026.
  3. Towards Emotional Support Dialog Systems aclanthology.org. Checked 21 October 2026.
  4. MiniLLM: Knowledge Distillation of Large Language Models proceedings.iclr.cc. Checked 21 October 2026.
  5. Dr. Minlie Huang's Homepage hml.coai.cs.tsinghua.edu.cn. Checked 21 October 2026.
  6. Professor Minlie Huang’s team and collaborators reveal that human preferences are susceptible to covertly misaligned AI advice tsinghua.edu.cn. Checked 21 October 2026.