Shishen Lin (林仕燊)

(Generated by GPT)

University of Birmingham

Edgbaston

Birmingham, UK

B15 2TT

I joined School of Computer Science, University of Birmingham as a PhD student since Sep. 2021, contributing to UKRI Turing AI Acceleration Fellowship project on ``Rigorous Time-Complexity Analysis of Coevolutionary Algorithms”, led by Professor Per Kristian Lehre. I am fortunate to be supervised by Professor Per Kristian Lehre.

My research mainly focuses on Artificial Intelligence, Optimisation, Evolutionary Algorithm. I am interested in reinforcement learning and the combination with evolutionary computation methods.

Before my PhD, I was a MSc Mathematics student at Imperial College London with a focus on probability theory, Markov processes and random matrix theory. I have completed my BSc Maths degree at Warwick before going to Imperial.

Me? Mathematician? Computer Scientist? Or both?

Potential Collaboration: If you share similar research interests or would like to collaborate with me, feel free to reach out to me via email.

News

Jul 14, 2025	Physically attended GECCO 2025 conference at Malaga, Spain!
Apr 29, 2025	Our paper “Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback” has been accepted in IJCAI 2025
Dec 15, 2024	Physically attended the NeurIPS Conference 2024 and presented our accepted paper “No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation”, in Vancouver!
Dec 09, 2024	Our paper “Towards Runtime Analysis of Population-Based Co-evolutionary Algorithms on Sparse Binary Zero-Sum Game” with Prof. Per Kristian Lehre has been accepted as Oral (top 4.6%) in AAAI 2025!

Selected Publications

IJCAI

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

Shishen Lin

In Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI), 2025

Bib

@inproceedings{lin2025ijcai,
  author = {Lin, Shishen},
  title = {Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback},
  booktitle = {Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI)},
  year = {2025},
  address = {Montreal, Canada},
  is_book = {false},
  is_journal = {false},
  is_conference = {true},
  theory = {true}
}

AAAI

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

Per Kristian Lehre, and Shishen Lin

In Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI), 2025

Bib

@inproceedings{lin2025aaai,
  author = {Lehre, Per Kristian and Lin, Shishen},
  title = {Towards Runtime Analysis of Population-Based Co-evolutionary Algorithms on Sparse Binary Zero-Sum Game},
  booktitle = {Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  address = {Philadelphia, Pennsylvania, USA},
  is_book = {false},
  is_journal = {false},
  is_conference = {true},
  theory = {true}
}

NeurIPS

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

Per Kristian Lehre, and Shishen Lin

In Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS), 2024

Bib

@inproceedings{lin2024neurips,
  author = {Lehre, Per Kristian and Lin, Shishen},
  title = {No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation},
  booktitle = {Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  address = {Vancouver, Canada},
  is_book = {false},
  is_journal = {false},
  is_conference = {true},
  theory = {true}
}

PPSN

Overcoming Binary Adversarial Optimisation with Competitive Coevolution

Per Kristian Lehre, and Shishen Lin

In Proceedings of the 18th International Conference on Parallel Problem Solving From Nature (PPSN), 2024

Bib

@inproceedings{lin2024ppsn,
  author = {Lehre, Per Kristian and Lin, Shishen},
  title = {Overcoming Binary Adversarial Optimisation with Competitive Coevolution},
  booktitle = {Proceedings of the 18th International Conference on Parallel Problem Solving From Nature (PPSN)},
  year = {2024},
  address = {Hagenberg, Austria},
  is_book = {false},
  is_journal = {false},
  is_conference = {true},
  theory = {true}
}