Research Assistant Professor Department of Computer Science and Engineering   Research Group

Research Areas: Evolutionary Computation, AI and Games, Optimisation in uncertain contexts

Personal Webpage: www.liujialin.tech

Experience

2017.8 - 2018.5: Postdoctoral Research Associate, Queen Mary University of London (QMUL), UK

2016.3 - 2017.7: Postdoc, University of Essex (UoE), UK

Education

2016.3: Ph.D in Computer Science, Team TAO, INRIA Saclay-CNRS-LRI, Université Paris-Saclay, Paris Saclay, France

2013.1 - Master's degree in Bioinformatics and Biostatistics, Université Paris-Sud & École Polytechnique, Orsay, France.

2012.9 - Engineer's degree in Computer Science (Network, Artificial Intelligence), Polytech'Paris-Sud, Orsay, France

2010.7 - Bachelor's degree in Optical & Electronic Information, Huazhong University of Science and Technology (HUST), Wuhan, China

Personal Profile

Research

Evolutionary Computation, AI and Games, Optimisation in uncertain contexts


Publications Read More

Jialin Liu, Sam Snodgrass, Ahmed Khalifa, Sebastian Risi, Georgios N. Yannakakis, Julian Togelius, “Deep Learning for Procedural Content Generation,” Neural Computing and Applications (NCAA), 2020. (Early Access)

Jialin Liu, Ke Tang, Xin Yao, “Robust Optimisation in Uncertain Capacitated Arc Routing Problems: Progresses and Perspectives,” IEEE Computational Intelligence Magazine (IEEE CIM), 2020. (Accepted)

Jialin Liu, Antoine Moreau, Mike Preuss, Jeremy Rapin, Baptiste Roziere, Fabien Teytaud, Olivier Teytaud, “Versatile Black-Box Optimization,” Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO 2020), Association for Computing Machinery, New York, NY, USA, 620–628.

Tianye Shu, Ziqi Wang, Jialin Liu*, Xin Yao, “A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros,” 2020 IEEE Congress on Evolutionary Computation (CEC 2020). IEEE. (Tianye Shu and Ziqi Wang were 3rd year UG students)

Qingquan Zhang, Feng Wu, Yang Tao, Jiyuan Pei, Jialin Liu*, Xin Yao, “D-MAENS2: A Self- adaptive D-MAENS Algorithm with Better Decision Diversity”, The 2020 IEEE Symposium Series on Computational Intelligence. (Accepted) (Qingquan Zhang was 2nd year Master student)

Diego Perez-Liebana, Jialin Liu*, Ahmed Khalifa, Raluca D. Gaina, Julian Togelius, Simon M. Lucas, “General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms,” in IEEE Transactions on Games, vol. 11, no. 3, pp. 195-214, Sept. 2019.

Jialin Liu and Xin Yao, “Self-adaptive Decomposition and Incremental Hyperparameter Tun- ing Across Multiple Problems,” Proceedings of the IEEE Symposium Series on Computational Intelligence, Xiamen, China, 2019, pp. 1590–1597. IEEE.

Jialin Liu and Olivier Teytaud, “A Simple Yet Effective Resampling Rule in Noisy Evolution- ary Optimization,” Proceedings of the IEEE Symposium Series on Computational Intelligence, Xiamen, China, 2019, pp. 689-696. IEEE.

Jialin Liu and Olivier Teytaud, “Efficient Decision Making under Uncertainty in a Power System Investment Problem,” Proceedings of the IEEE Symposium Series on Computational Intelligence, Xiamen, China, 2019, pp. 697–704. IEEE.

Vanessa Volz, Jacob Schrum, Jialin Liu, Simon M Lucas, Adam Smith, Sebastian Risi, “Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Network,” Proceedings of 2018 Annual Conference on Genetic and Evolutionary Computation (GECCO 2018), Kyoto, pp. 221228, ACM Press. (Best Paper Award)

Jialin Liu, Julian Togelius, Diego Perez-Liebana and Simon M. Lucas, “Evolving Game Skill-Depth using General Video Game AI Agents,” Proceedings of the IEEE Congress on Evolutionary Computation (CEC’17), San Sebastian, 2017, pp. 2299–2307.

Jialin Liu, Diego Perez-Liebana and Simon M. Lucas, “Bandit-Based Random Mutation Hill-Climbing,” Proceedings of the IEEE Congress on Evolutionary Computation (CEC’17), San Sebastian, 2017, pp. 2145–2151.

Marie-Liesse Cauwet, Jialin Liu*, Baptiste Rozi`ere, Olivier Teytaud, “Algorithm Portfolios for Noisy Optimization,” Annals of Mathematics and Artificial Intelligence (AMAI), vol. 76, no 1-2, p. 143-172, 2016.

Jialin Liu, Oliver Teytaud, Tristan Cazenave, “Fast Seed-Learning Algorithms for Games,” Proceedings of the 9th International Conference on Computers and Games (CG 2016), Lecture Notes in Computer Science, vol 10068. Springer, Cham.

Jialin Liu, Diego P ́erez-Li ́ebana and Simon M. Lucas, “Rolling Horizon Coevolutionary Planning for Two-Player Video Games,” Proceedings of the 8th Computer Science and Electronic Engineering (CEEC 2016), Colchester, 2016, pp. 174–179.

Jialin Liu, David L. St-Pierre and Olivier Teytaud, “A Mathematically Derived Number of Resamplings for Noisy Optimization,” Proceedings of the 16th Annual Conference on Genetic and Evolutionary Computation (GECCO 2014), Vancouver, pp. 6162, ACM Press.

Jialin Liu and Olivier Teytaud, “Meta Online Learning: Experiments on a Unit Commitment Problem,” Proceedings of European Symposium on Artificial Neural Networks (ESANN 2014), Computational Intelligence and Machine Learning, Bruges (Belgium), 23–25 April 2014.

Jialin Liu, Tom Schaul, Pieter Spronck and Julian Togelius, “Artificial and Computational Intelligence in Games: Revolutions in Computational Game AI (Dagstuhl Seminar 19511)”, Dagstuhl Reports, Volume 9, Issue 12. 3.

News More

  • Second Prize in the 2020 Competition of Advanced Computer Science Experiment

    2020-11-01
  • Two student papers accepted by IEEE SSCI

    2020-10-01
  • 本科生蓝文兴、叶梓元和阮沛钧获综合设计二等奖

    2020-08-01

Lab members Read More

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Graduate students, research assistants and postdoc position opened. 

课题组常年招收博士后、研究助理、博士生、硕士生、访问学者/学生。待遇从优。

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liujl(at)sustech.edu.cn

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