Dillon Ze Chen 


        E: dillon dot chen 1 at gmail dot com
        T: +33 05 61 33 63 48
        W: https://dillonzchen.github.io

I am a PhD student in automated planning and machine learning supervised by Sylvie Thiébaux in the RIS team.

For research, keep reading below. To play the dog gacha, refresh the page (rates and rarities coming soon!).

Links 

[dblp] [Google Scholar] [🧦 GitHub] [CV]
[ICAPS Visualisations]
[PhD Travel Photos]

News

[2024.10]One year milestone!
[2024.09]Paper accepted to NeurIPS-24.
[2024.09]I am giving a talk at the Aachen RLeap Symposium. Thanks Hector for the invitation!
[expand]

Research Interests

I work in the union of machine learning and sequential decision making, with a particular focus in the field of automated planning. My starry-eyed thesis goal is to scale up planning technology to real-world scenarios involving humongous numbers of objects.

So far I have worked on various delicious flavours of planning, including numeric, multi-objective, stochastic, non-deterministic, and hierarchical planning.

I can also keep up to date with machine learning research, with publications in graph neural networks, foundation models, graph kernels, and applications.

Publications

ICAPS, AAAI, NeurIPS and ICLR are A* conferences.

Conference papers

[C8] Dillon Ze Chen and Sylvie Thiébaux. Graph Learning for Numeric Planning. In 38th Conference on Neural Information Processing Systems (NeurIPS), 2024. 
[ pdf | poster | slides | code ]
[C7] Dillon Ze Chen and Sylvie Thiébaux. Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning. In 17th International Symposium on Combinatorial Search (SoCS), 2024. 
[ pdf | poster | slides | code ]
[C6] Dillon Ze Chen, Felipe Trevizan, and Sylvie Thiébaux. Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning. In 34th International Conference on Automated Planning and Scheduling (ICAPS), 2024. 
[ pdf | poster | slides | code | plots ]
[C5] Dillon Ze Chen, Sylvie Thiébaux, and Felipe Trevizan. Learning Domain-Independent Heuristics for Grounded and Lifted Planning. In 38th AAAI Conference on Artificial Intelligence, 2024. 
[ pdf | poster | slides | code ]
[C4] Qing Wang, Dillon Ze Chen, Asiri Wijesinghe, Shouheng Li, and Muhammad Farhan. N-WL: A New Hierarchy of Expressivity for Graph Neural Networks. In 11th International Conference on Learning Representations (ICLR), 2023. 
[ pdf | poster | slides | code ]
[C3] Dillon Ze Chen, Felipe Trevizan, and Sylvie Thiébaux. Heuristic Search for Multi-Objective Probabilistic Planning. In 37th AAAI Conference on Artificial Intelligence, 2023. 
[ pdf | poster | slides | code ]
[C2] Dillon Ze Chen and Pascal Bercher. The Complexity of Flexible FOND HTN Planning. In 32nd International Conference on Automated Planning and Scheduling (ICAPS), 2022. Best Undergraduate Student Paper Award. 
[ pdf | poster | slides ]
[C1] Dillon Ze Chen and Pascal Bercher. Fully Observable Nondeterministic HTN Planning – Formalisation and Complexity Results. In 31st International Conference on Automated Planning and Scheduling (ICAPS), 2021. Best Undergraduate Student Paper Award. 
[ pdf | poster | slides ]

Workshop papers

[W3] Dillon Ze Chen, Sylvie Thiébaux, and Felipe Trevizan. GOOSE: Learning Domain-Independent Heuristics. In 7th Workshop on Generalization in Planning (GenPlan), 2023. «Subsumed by [C5]». 
[ pdf | poster | slides ]
[W2] Dillon Ze Chen, Felipe Trevizan, and Sylvie Thiébaux. Graph Neural Networks and Graph Kernels For Learning Heuristics: Is there a difference?. In 7th Workshop on Generalization in Planning (GenPlan), 2023. «Subsumed by [C6]». 
[ pdf | poster ]
[W1] Dillon Ze Chen and Pascal Bercher. The Complexity of Flexible FOND HTN Planning. In 4th ICAPS Workshop on Hierarchical Planning (HPlan), 2021. «Subsumed by [C2]». 
[ pdf ]

Reviewing

I have reviewed for the following conferences and workshops, listed in alphabetical order.

Conferences

Workshops

Clocks

Time zone map


        

        
        

        

        

        

        

        

        

        

        

        
        
        

        
            
        

        

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