CV

Education

• B.S. in Mathematics, University of Warwick, 2017-2020
• M.S. in Pure Mathematics, Imperial College London, 2020-2021
  • Master Thesis: An Overview on Random Matrix Theory
• Ph.D in Computer Science, University of Birmingham, 2021-2025 (expected)
  • Supervisor: Professor Per Kristian Lehre, Dr Rajesh Chitnis
  • PhD Thesis: Learning in Games via Competitive Coevolution: A Rigorous Theoretical Perspective

Work experience

• Summer 2021: Data Analyst Intern
  • Tencent Technology, Shenzhen, China
  • Duties: A 10-weeks summer intern on data analysis. A business and data analyst internship on supporting Tencent Advertising Market Services in particular IAA ( In-App Advertising) division. Analyse data from Ads in Games by using Excel and Python and update data for weekly reports of IAA. Also use Pandas and Numpy to simplify Excel computation.
• Summer 2020: Research Assistant
  • University of Warwick, Coventry, United Kingdom
  • Duties: A 10-weeks funded summer project on number theory, which is supervised by Dr. Chris Williams. The project mainly focuses on rational points on elliptic curves, which is an important object in number theory. It is also important in some modern encryption. During the project, I learn the theory of elliptic curves and use some elementary algebraic geometry to solve number theoretic questions. Meanwhile, I am trying to learn Sage software to do some complicated calculation, which is based on Python Programmimg.
  • Supervisor: Dr. Chris Williams.
• Summer 2019: Research Assistant
  • University of Warwick, Coventry, United Kingdom
  • Duties: A 10-week funded research program on stability and sound in ducted flow, supervised by Dr Ed Brambley. The project mainly studied the instability problem by using mathematical analysis.
  • Supervisor: Dr Ed Brambley

Publications (authors are listed in alphabetical order in theory papers, following the tradition of theory community)

Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback

Shishen Lin. (2025). " Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback." Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI). 7 pages, Montreal, Canada, 2025. to appear.

Towards Runtime Analysis of Population-Based Co-evolutionary Algorithms on Sparse Binary Zero-Sum Game

Per Kristian Lehre and Shishen Lin. (2025). "Towards Runtime Analysis of Population-Based Co-evolutionary Algorithms on Sparse Binary Zero-Sum Game." The 39th Annual AAAI Conference on Artificial Intelligence (AAAI). 7 pages, Philadelphia, Pennsylvania, USA, 2025. to appear (Oral presentation).

No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation

Per Kristian Lehre, and Shishen Lin. (2024). " No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation." 38th Annual Conference on Neural Information Processing Systems (NeurIPS). 9 pages, Vancouver, Canada, 2024.

Overcoming Binary Adversarial Optimisation with Competitive Coevolution

Per Kristian Lehre, and Shishen Lin. (2024). " Overcoming Binary Adversarial Optimisation with Competitive Coevolution." 18th International Conference on Parallel Problem Solving From Nature (PPSN). 14 pages, Hagenberg, Austria, 2024.

Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms

Per Kristian Lehre, and Shishen Lin. (2024). "Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms." Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI). 7 pages, Jeju, South Korea, 2024.

Runtime Analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation

Mario Alejandro Hevia Fajardo, Per Kristian Lehre, and Shishen Lin. (2023). "Runtime analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation." Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA). 11 pages, Potsdam, Germany, 2023.

Runtime Analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation

Mario Alejandro Hevia Fajardo, Per Kristian Lehre, and Shishen Lin. (2023). "Runtime analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation." Proceedings of the Companion Conference on Genetic and Evolutionary Computation (GECCO Companion). 4 pages, Lisbon, Portugal, 2023.

Is CC-(1+1) EA more efficient than (1+1) EA on either separable or inseparable problems?

Per Kristian Lehre, Shishen Lin. (2023). "Is CC-(1+1) EA more efficient than (1+1) EA on either separable or inseparable problems?" IEEE Congress on Evolutionary Computation (CEC). 8 pages, Chicago, USA, 2023.

Talks

How does Problem Separability Impact the Co-operative Co-evolutionary (1+1) EA?

December 01, 2022

Talk at University of Birmingham, UK, Online