PeopleofSuperintelligence

Researcher

Ke Tang

Also known as 唐珂, Tang Ke

Ke Tang is a computer scientist at Southern University of Science and Technology (SUSTech) whose research covers evolutionary computation and machine learning. After a PhD at Nanyang Technological University in 2007, he worked at the University of Science and Technology of China from 2007 to 2017 and became a professor there in 2011. He coauthored Frequency Fitness Assignment in 2014 and Negatively Correlated Search in 2016, and he received the IEEE Computational Intelligence Society Outstanding Early Career Award for 2018. Papers he coauthored in 2023 and 2024 cover large language models as evolutionary optimizers, evolutionary reinforcement learning and a mixture-of-experts neural optimizer. At SUSTech, he is a Chair Professor of Computer Science and Engineering.

Timeline

  1. 2002–2007

    A PhD at Nanyang Technological University

    He completes an undergraduate degree in control science and engineering at Huazhong University of Science and Technology in 2002. A PhD from the School of Electrical and Electronic Engineering at Nanyang Technological University follows in 2007.

  2. 2007–2017

    Professor at USTC

    In 2007, he joins the School of Computer Science and Technology at the University of Science and Technology of China (USTC) as an associate professor. He becomes a professor there in 2011 and stays until 2017.

  3. 2014

    Frequency fitness assignment

    IEEE Transactions on Evolutionary Computation publishes Frequency Fitness Assignment in 2014, coauthored with Thomas Weise, Mingxu Wan, Pu Wang, Alexandre Devert and Xin Yao. The paper introduces a frequency fitness that rates how often solutions with the same objective value have been discovered so far.

  4. 2015

    A Royal Society Newton fellowship

    In 2015, he receives a Royal Society Newton Advanced Fellowship, which runs from 2016 to 2018.

  5. 2016

    Negatively correlated search

    Negatively Correlated Search, coauthored with Peng Yang and Xin Yao, appears in IEEE Journal on Selected Areas in Communications in 2016. The evolutionary algorithm runs several search processes in parallel and promotes differences among their search behaviors, and it achieves the best overall performance on 20 multimodal continuous optimization problems.

  6. 2018

    An IEEE early career award

    In 2018, he receives the IEEE Computational Intelligence Society Outstanding Early Career Award in Rio de Janeiro, at the IEEE World Congress on Computational Intelligence. He is a SUSTech professor who studies evolutionary computation and machine learning.

  7. 2023–2024

    Language models and evolutionary search

    In 2023, he coauthors Large Language Models as Evolutionary Optimizers with Shengcai Liu, Caishun Chen, Xinghua Qu and Yew-Soon Ong; the LMEA method asks a language model to select parents and to perform crossover and mutation on traveling salesman problems. In 2024, he coauthors a survey of Evolutionary Reinforcement Learning, which combines evolutionary algorithms with reinforcement learning, and MEGO, a mixture-of-experts neural optimizer for binary optimization.

  8. Since 2025

    Chair professor at SUSTech

    In 2025, he becomes Chair Professor of Computer Science and Engineering at Southern University of Science and Technology, after working as a professor in the same department.

Career

  1. Since 2025Southern University of Science and TechnologyChair Professor of Computer Science and Engineering
  2. 2007–2017University of Science and Technology of ChinaAssociate professor, Professor

Education

  1. 2007Nanyang Technological UniversityPhD
  2. 2002Huazhong University of Science and TechnologyUndergraduate degree

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Southern University of Science and Technology. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Southern University of Science and Technology. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes University of Science and Technology of China. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.
  4. 44% of AI career moves go from one university to anotherIncludes University of Science and Technology of China. We estimate how 26,439 AI career moves link universities, companies, labs, nonprofits and government research centers, with decade counts, net flows and the top paths.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Ke Tang yet. Send us a free-licensed photo.

  1. Ke Tang cse.sustech.edu.cn. Checked 21 October 2026.
  2. Frequency fitness assignment - University of Birmingham research.birmingham.ac.uk. Checked 21 October 2026.
  3. [1504.04914] Negatively Correlated Search arxiv.org. Checked 21 October 2026.
  4. SUSTech Computer Science Professor wins IEEE Outstanding Early Career Award newshub.sustech.edu.cn. Checked 21 October 2026.
  5. [2310.19046] Large Language Models as Evolutionary Optimizers arxiv.org. Checked 21 October 2026.
  6. [2401.11963] Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey on Hybrid Algorithms arxiv.org. Checked 21 October 2026.
  7. [2405.18884] MEGO: Learning Mixture-of-Experts for General-Purpose Binary Optimization arxiv.org. Checked 21 October 2026.
  8. TANG Ke - Faculty - SUSTech sustech.edu.cn. Checked 21 October 2026.