Research Interests
My research interests include, but not limited to: Evolutionary Computation, Noisy Optimisation (derivation-free algorithms, dynamic resampling strategies), Game AI (AI for playing games, AI for designing games), and Algorithm Portfolio methods.
Publications
Peer-reviewed Publications
You can also check my publications on Google Scholar.
(* indicates that I'm the corresponding author; ♦ indicates that the authors are listed in alphabetical order.)
Not updated since 2023. Please check Google Scholar for recent publications.
- Qingquan Zhang, Jialin Liu*, Zeqi Zhang, Junyi Wen, Bifei Mao, Xin Yao, ``Mitigating Unfairness via Evolutionary Multi-objective Ensemble Learning,'' in IEEE Transactions on Evolutionary Computation, 2022. (Early Access)
- Jiyuan Pei, Yi Mei, Jialin Liu, Xin Yao, ``An Investigation of Adaptive Operator Selection in Solving Complex Vehicle Routing Problem,'' in The 19th Pacific Rim International Conference on Artificial Intelligence. (Accepted)
- Ziqi Wang, Jialin Liu, ``Online Game Level Generation from Music,'' in The 2022 IEEE Conference on Games. 2022. (Accepted) (EI)
- Keyuan Zhang, Jiayu Bai, Jialin Liu, ``Generating Game Levels of Diverse Behaviour Engagement,'' in The 2022 IEEE Conference on Games. 2022. (Accepted) (EI) [pdf]
- Chengpeng Hu, Ziqi Wang, Tianye Shu, Hao Tong, Julian Togelius, Xin Yao, Jialin Liu*, ``Reinforcement Learning with Dual-Observation for General Video Game Playing,'' in IEEE Transactions on Games, 2022. (Accepted) (SCI)
- Hao Tong, Qingquan Zhang, Chengpeng Hu, Xudong Feng, Feng Wu, Jialin Liu. ``Simpler is Sometimes Better: A Dynamic Aero-Engine Calibration Study,'' In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2022. Lecture Notes in Computer Science, vol 13345. Springer, Cham. https://doi.org/10.1007/978-3-031-09726-3_31
- Wenxing Lan, Ziyuan Ye, Peijun Ruan, Jialin Liu*, Peng Yang, Xin Yao, ``Region-focused Memetic Algorithms with Smart Initialisation for Real-world Large-scale Waste Collection Problems,'' in IEEE Transactions on Evolutionary Computation, 2021. (Early Access) (SCI)
- Jialin Liu, Ke Tang, Xin Yao, ``Robust Optimisation in Uncertain Capacitated Arc Routing Problems: Progresses and Perspectives,'' in IEEE Computational Intelligence Magazine, vol. 16, no. 1, pp. 63-82, Feb. 2021, doi: 10.1109/MCI.2020.3039069. (SCI) [pdf] or [pdf]
- Jialin Liu, Sam Snodgrass, Ahmed Khalifa, Sebastian Risi, Georgios N. Yannakakis, Julian Togelius, ``Deep Learning for Procedural Content Generation,'' Neural Computing and Applications (NCAA), vol. 33, pp. 19-37, 2021. (SCI) [pdf]
- Jialin Liu, Qingquan Zhang, Jiyuan Pei, Hao Tong, Xudong Feng, Feng Wu, ``fSDEA: Efficient Evolutionary Optimisation for Many-objective Aero-engine Calibration,'' in Complex & Intelligent Systems, 2021. DOI: 10.1007/s40747-021-00374-1 (Early Access) (SCI)
- Qingquan Zhang, Jialin Liu, Zeqi Zhang, Junyi Wen, Bifei Mao, Xin Yao, ``Fairer Machine Learning Through Multi-objective Evolutionary Learning,'' in: Farkaš I., Masulli P., Otte S., Wermter S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2021. Lecture Notes in Computer Science, vol 12894, pp 111-123. Springer, Cham. https://doi.org/10.1007/978-3-030-86380-7_10 (EI)
- Ziqi Wang, Jialin Liu, Georgios N. Yannakakis, ``Keiki: Towards Realistic Danmaku Generation via Sequential GANs,'' in The 2021 IEEE Conference on Games. 2021. (Accepted) (EI) [pdf]
- Tianye Shu, Jialin Liu, Georgios N. Yannakakis, ``Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study,'' in The 2021 IEEE Conference on Games. 2021. (Accepted) (EI) [pdf]
- Jiyuan Pei, Chengpeng Hu, Jialin Liu, Yi Mei and Xin Yao, ``Bi-Objective Splitting Delivery VRP with Loading Constraints and Restricted Access,'' in The 2021 IEEE Symposium Series on Computational Intelligence (SSCI2021). (Accepted) (EI)
- Hao Tong, Jiyuan Pei, Qingquan Zhang, Jialin Liu, Xudong Feng and Feng Wu, ``Learning Boosts Optimisation: Surrogate-Assisted Real Engine Calibration,'' in The 2021 IEEE Symposium Series on Computational Intelligence (SSCI2021). (Accepted) (EI)
- 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. DOI:https://doi.org/10.1145/3377930.3389838. (EI) [pdf] (♦)
- Jacob Schrum, Jake Gutierrez, Vanessa Volz, Jialin Liu, Simon Lucas, Sebastian Risi, ``Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networks,'' Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO 2020), Association for Computing Machinery, New York, NY, USA, 148–156, DOI:https://doi.org/10.1145/3377930.3389821. (EI) [pdf]
- Han Zhang, Jialin Liu, Xin Yao, ``A Hybrid Evolutionary Algorithm for Reliable Facility Location Problem,'' Proceedings of the Sixteenth International Conference on Parallel Problem Solving from Nature (PPSN XVI), LNCS 12270, pp. 454–467, 2020. (EI) [pdf] or [pdf]
- Tianye Shu, Ziqi Wang, Jialin Liu, Xin Yao, ``A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros,'' Proceedings of the 2020 IEEE Congress on Evolutionary Computation (CEC 2020), Glasgow, United Kingdom, 2020, pp. 1-10, doi: 10.1109/CEC48606.2020.9185538. IEEE. (EI) [pdf]
- 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 (SSCI 2020), Canberra, Australia, 2020, pp. 2754-2761. (EI)
- Chenhao Li, Jiyuan Pei, Qingquan Zhang, Jialin Liu, Xin Yao, ``An Extendable Platform for Routing Problem: Optimisation, Evaluation and Solution Visualisation'', The 2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020), Canberra, Australia, 2020, pp. 2391-2398. (EI)
- 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. doi: 10.1109/TG.2019.2901021. [pdf] (SCI)
- Jialin Liu and Xin Yao, ``Self-adaptive Decomposition and Incremental Hyperparameter Tuning Across Multiple Problems,'' Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), Xiamen, China, 2019, pp. 1590-1597, doi: 10.1109/SSCI44817.2019.9002966. [pdf] (EI)
- Jialin Liu and Olivier Teytaud, ``A Simple Yet Effective Resampling Rule in Noisy Evolutionary Optimization,'' Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), Xiamen, China, 2019, pp. 689-696, doi: 10.1109/SSCI44817.2019.9003078. [pdf] (EI)
- Jialin Liu and Olivier Teytaud, ``Efficient Decision Making under Uncertainty in a Power System Investment Problem,'' Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), Xiamen, China, 2019, pp. 697-704, doi: 10.1109/SSCI44817.2019.9003075. [pdf] (EI)
- Hao Tong, Jialin Liu and Xin Yao, ``Algorithm Portfolio for Individual-based Surrogate-assisted Evolutionary Algorithms,'' Proceedings of 2019 Genetic and Evolutionary Computation Conference (GECCO 2019), Kyoto, pp. 943-950, ACM Press, doi: 10.1145/3321707.3321715. [pdf] (EI)
- Hao Tong, Changwu Huang, Jialin Liu and Xin Yao, ``Voronoi-based Efficient Surrogate-assisted Evolutionary Algorithm for Very Expensive Problems,'' Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2019), Wellington, New Zealand, 2019, pp. 1996-2003, doi: 10.1109/CEC.2019.8789910. [pdf] (EI)
- Ivan Bravi, Simon M. Lucas, Diego Perez-Liebana and Jialin Liu, ``Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor,'' Proceedings of the IEEE Conference on Games (CoG 2019), London, United Kingdom, 2019, pp. 1-8, doi: 10.1109/CIG.2019.8848028. [pdf] (EI)
- Simon M. Lucas, Jialin Liu, Ivan Bravi, Raluca D. Gaina, John Woodward, Vanessa Volz and Diego Perez-Liebana, ``Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is the Best,'' AAAI-2019 Workshop on Games and Simulations for Artificial Intelligence, 2019. [pdf]
- Chiara Sironi, Jialin Liu and Mark Winands, ``Self-Adaptive Monte-Carlo Tree Search in General Game Playing,'' in IEEE Transactions on Games, vol. 12, no. 2, pp. 132-144, June 2020, doi: 10.1109/TG.2018.2884768. [pdf] (SCI)
- Chang-Shing Lee, Mei-Hui Wang, Chi-Shiang Wang, Olivier Teytaud, Jialin Liu, Su-Wei Lin, Pi-Hsia Hung, ``PSO-Based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application,'' in IEEE Transactions on Fuzzy Systems, vol. 26, no. 5, pp. 2618-2633, Oct. 2018. [pdf] (SCI)
- 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. 221–228, ACM Press. [pdf] (EI) (Best Paper Award of DETA+THEORY+GECH tracks)
- Ruben Rodriguez Torrado, Philip Bontrager, Julian Togelius, Jialin Liu and Diego Perez Liebana, ``Deep reinforcement learning for General Video Game AI,'' Proceedings of the IEEE Computational Intelligence and Games Conference (CIG 2018), Maastricht, 2018, pp. 1-8. [pdf] (EI)
- Ivan Bravi, Diego Perez, Simon Lucas and Jialin Liu, ``Shallow decision-making analysis in General Video Game Playing,'' Proceedings of the IEEE Computational Intelligence and Games Conference (CIG 2018), Maastricht, 2018, pp. 1-8. [pdf] (EI)
- Chiara F. Sironi, Jialin Liu, Diego Perez-Liebana, Raluca D. Gaina, Ivan Bravi, Simon M. Lucas, Mark H.M. Winands, ``Self-Adaptive MCTS for General Video Game Playing,'' Applications of Evolutionary Computation (EvoApplications 2018), Lecture Notes in Computer Science, vol 10784. Springer, Cham. [pdf] (EI)
- Simon M. Lucas, Jialin Liu, Diego Perez-Liebana, ``The N-tuple Bandit Evolutionary Algorithm for Game Agent Optimisation,'' Proceedings of the IEEE Congress on Evolutionary Computation (CEC'18), Rio de Janeiro, 2018, pp. 1-9. [pdf] (EI) (shortlisted for Best Paper Award from 347 accepted papers)
- Marie-Liesse Cauwet, Jeremie Decock, Jialin Liu, Olivier Teytaud, ``Direct Model Predictive Control: A Theoretical and Numerical Analysis,'' Proceedings of the 20th Power Systems Computation Conference (PSCC 2018), Dublin, 2018, pp. 1-7. [pdf] (EI)
- Philipp Rohlfshagen, Jialin Liu, Diego Perez-Liebana and Simon M. Lucas, ``Pac-Man Conquers Academia: Two Decades of Research Using a Classic Arcade Game,'' in IEEE Transactions on Games, vol. 10, no. 3, pp. 233-256, Sept. 2018. [pdf] (SCI)
- Raluca D. Gaina, Adrien Couëtoux, Dennis JNJ Soemers, Mark HM Winands, Tom Vodopivec, Florian Kirchgeßner, Jialin Liu, Simon M. Lucas, and Diego Perez-Liebana, ``The 2016 Two-Player GVGAI Competition,'' in IEEE Transactions on Games, vol. 10, no. 2, pp. 209-220, June 2018. [pdf] (SCI)
- 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. [pdf] (EI)
- 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. [pdf] (EI)
- Kamolwan Kunanusont, Raluca D. Gaina, Jialin Liu, Diego Perez-Liebana and Simon M. Lucas, ``The N-Tuple Bandit Evolutionary Algorithm for Automatic Game Improvement,'' Proceedings of the IEEE Congress on Evolutionary Computation (CEC'17), San Sebastian, 2017, pp. 2201-2208. [pdf] (EI)
- Raluca D. Gaina, Jialin Liu, Simon M. Lucas, Diego Perez-Liebana, ``Analysis of Vanilla Rolling Horizon Evolution Parameters in General Video Game Playing,'' Proceedings of Applications of Evolutionary Computation (EvoApplications 2017), Lecture Notes in Computer Science, vol 10199. Springer, Cham. [pdf] (EI)
- Simon M. Lucas, Jialin Liu and Diego Perez-Liebana, ``Efficient Noisy Optimisation with the Multi-sample and Sliding Window Compact Genetic Algorithms,'' 2017 IEEE Symposium Series on Computational Intelligence (SSCI), Honolulu, 2017, pp. 1-8. [pdf] (EI)
- Marie-Liesse Cauwet, Jialin Liu (*), Baptiste Rozière, Olivier Teytaud, ``Algorithm Portfolios for Noisy Optimization,'' Annals of Mathematics and Artificial Intelligence (AMAI), vol. 76, no 1-2, p. 143-172. [pdf] (SCI) (♦)
- Sandra Astete-Morales, Marie-Liesse Cauwet, Jialin Liu, Olivier Teytaud, ``Simple and Cumulative Regret for Continuous Noisy Optimization,'' Theoretical Computer Science (TCS), vol. 617, p. 12-27. [pdf] (SCI) (♦)
- 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. [pdf] (EI)
- Tristan Cazenave, Jialin Liu, Fabien Teytaud, Olivier Teytaud, ``Learning Opening Books in Partially Observable Games: Using Random Seeds in Phantom Go,'' Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG 2016), Santorini, 2016, pp. 1-7. [pdf] (EI) (♦)
- Jialin Liu, Diego Pérez-Liébana 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. [pdf] (EI)
- Jérémie Decock, Jialin Liu and Olivier Teytaud, ``Variance Reduction in Population-Based Optimization: Application to Unit Commitment,'' Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (GECCO 2015), Madrid, pp. 61–62, ACM Press. [pdf] (EI) (♦)
- Tristan Cazenave, Jialin Liu, Olivier Teytaud, ``The Rectangular Seeds of Domineering,'' 2015 IEEE Computational Intelligence and Games Conference (CIG 2015), Tainan, 2015, pp. 530-531. [pdf] (EI) (♦)
- Mei-Hui Wang, Chi-Shiang Wang, Chang-Shing Lee, Olivier Teytaud, Jialin Liu, Su-Wei Lin and Pi-Hsia Hung, ``Item Response Theory with Fuzzy Markup Language for Parameter Estimation and Validation,'' Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015), Istanbul, 2015, pp. 1-7. (EI)
- Shih-Yuan Chiu, Ching-Nung Lin, Jialin Liu, Tsan-Cheng Su, Fabian Teytaud, Olivier Teytaud and Shi-Jim Yen, ``Differential Evolution for Strongly Noisy Optimization: Use 1.01^n Resamplings at Iteration n and Reach the −1 Slope,'' Proceedings of IEEE Congress on Evolutionary Computation (CEC'15), Sendai, 2015, pp. 338-345. [pdf] (EI) (♦)
- David L. St-Pierre, Jialin Liu and Olivier Teytaud, ``Nash Reweighting of Monte Carlo Simulations: Tsumego,'' Proceedings of IEEE Congress on Evolutionary Computation (CEC'15), Sendai, 2015, pp. 1458-1465. [pdf] and [slides] (EI)
- Jean-Joseph Christophe, Jérémie Decock, Jialin Liu and Olivier Teytaud, ``Variance Reduction in Population-Based Optimization: Application to Unit Commitment,'' Proceedings of Biennial International Conference on Artificial Evolution (EA 2015), Lecture Notes in Computer Science, vol 9554. Springer, Cham. [pdf] (EI) (♦)
- Cheng-Wei Chou, Ping-Chiang Chou, Jean-Joseph Christophe, Adrien Couetoux, Pierre De Freminville, Nicolas Galichet, Chang-Shing Lee, Jialin Liu, David Lupien Saint-Pierre, Michele Sebag, Olivier Teytaud, Mei-Hui Wang, Li-Wen Wu and Shi-Jim Yen, ``Strategic Choices in Optimization,'' Journal of Computing and Information Science in Engineering (JCISE), vol. 30, no 3, p. 727-747, 2014. [pdf] (SCI) (♦)
- 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. 61–62, ACM Press. [pdf] (EI)
- 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. [pdf] or [pdf] (EI)
- David Auger, Jialin Liu, Sylvie Ruette, David L. St-Pierre and Olivier Teytaud, ``Sparse Binary Zero-sum Games,'' Proceedings of the Sixth Asian Conference on Machine Learning (ACML 2014), PMLR 39:173-188, 2015. [pdf] (EI) (♦)
- Marie-Liesse Cauwet, Jialin Liu and Olivier Teytaud, ``Algorithm Portfolios for Noisy Optimization: Compare Solvers Early,'' Proceedings of the International Conference on Learning and Intelligent Optimization (LION 2014), Lecture Notes in Computer Science, vol 8426. Springer, Cham. [pdf] (EI) (♦)
- David L. St-Pierre and Jialin Liu, ``Differential Evolution Algorithm Applied to Non-stationary Bandit Problem,'' Proceedings of IEEE Congress on Evolutionary Computation (CEC'14), Beijing, China, pp. 2397-2403, IEEE. [pdf] (EI)
- Sandra Astete-Morales, Jialin Liu and Olivier Teytaud, ``Noisy Optimization Convergence Rates,'' Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation (GECCO 2013), Amsterdam, The Netherlands, pp. 223–224, ACM Press. [pdf] (EI) (♦)
- Sandra Astete-Morales, Jialin Liu and Olivier Teytaud, ``Log-log Convergence for Noisy Optimization,'' Proceedings of Biennial International Conference on Artificial Evolution (EA 2013). Lecture Notes in Computer Science, vol 8752. Springer, Cham. [pdf] (EI) (♦)
Technical Reports and Book
- [Book] Diego Perez-Liebana, Simon M. Lucas, Raluca D. Gaina, Julian Togelius, Ahmed Khalifa and Jialin Liu, ``General Video Game Artificial Intelligence,'' Morgan and Claypool, 2020. [pdf]
- 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. [Full report]
- Vanessa Volz, Dan Ashlock, Simon Colton, Steve Dahlskog, Jialin Liu, Simon M. Lucas, Diego Perez Liebana and Tommy Thompson, ``4.18 Gameplay Evaluation Measures,'' Report of Dagstuhl Seminar Artificial and Computational Intelligence in Games: AI-Driven Game Design, Volume 7, Issue 11, pp. 105-107, 2018. [Full report]
- Dan Ashlock, Cameron Browne, Simon Colton, Amy K Hoover, Jialin Liu, Simon M Lucas, Mark J Nelson, Diego Perez Liebana, Sebastian Risi, Jacob Schrum, Adam M Smith, Julian Togelius and Vanessa Volz, ``4.1 Game Search Space Design and Representation,'' Report of Dagstuhl Seminar Artificial and Computational Intelligence in Games: AI-Driven Game Design, Volume 7, Issue 11, pp. 93-95, 2018. [Full report]
- David L. St-Pierre, Jean-Baptiste Hoock, Jialin Liu, Fabien Teytaud and Olivier Teytaud, ``Automatically Reinforcing a Game AI,'' Arxiv (2016). [pdf]
Students
PhD student
- Ivan Bravi (4th year, Queen Mary University of London, UK), co-supervised with Prof. Simon M. Lucas and Dr. Diego Perez-Liebana
Master students
- Siyu Chen (will start in Sept 2022)
- Ziqi Wang (started in Sept 2021)
- Chengpeng Hu, co-supervised with Prof. Xin Yao (started in Sept 2021)
- Jiyuan Pei (started in Sept 2020)
- Qingquan Zhang, co-supervised with Prof. Xin Yao (started in Sept 2019, graduated in 2022; will join University of Birmingham as a PhD candidate with fulled funded scholarship, co-supervised with Dr. Shuo Wang)
Undergraduate students
- Haocheng Du (intern at NetEase)
- Yunlong Zhao (intern at Parametrix.ai)
- keyuan Zhang (graduated in 2022; will join Virginia Polytechnic Institute and State University as a PhD candidate with fulled funded scholarship)
- Jiayu Bai (graduated in 2022; currently at NetEase)
- Tianye Shu (graduated in 2021; intern at Tencent Lightspeed Studios in 2020; currently a master student at SUSTech)
- Ziqi Wang (graduated in 2021, currently a master student at SUSTech, intern at Huawei in 2020)
- Chengpeng Hu (graduated in 2021; intern at UBTECH in 2020; currently a master student at SUSTech)
- Yu Zhao (graduated in 2021; intern at Wiqun in 2019; intern at Tencent Lightspeed Studios in 2020; currently at Yotta Games)
- Jiyuan Pei (graduated in 2020; intern at Tencent Lightspeed Studios in 2020; currently a master student at SUSTech)
- Wenxing Lan (graduated in 2020; currently a master student at SUSTech)
- Ziyuan Ye (graduated in 2020; currently a master student at SUSTech)
- Haozhi Dong (graduated in 2020; currently a master student at Shenzhen University)
- Chenhao Li (graduated in 2020; currently at Huawei)
- Peijun Ruan (graduated in 2020; currently at Shopee)
Visiting students
- Hao Tong (PhD student at University of Birmingham)
- Kongming Cao (Undergraduate student from Rensselaer Polytechnic Institute, USA): Oct-Dec, 2021
- Yishuang Wang (Master student from University of Nottingham, UK): Jul-Aug, 2020