PUBLICATIONS  (* Equal Contribution)

2026 

• Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami: Birds of a Feather Reason Together: Gestalt Grouping Meets Neuro-Symbolic Inference, Conference on Uncertainty in Artificial Intelligence (UAI 2026)

• Yu Deng*, Teng Cao*, Hikaru Shindo, Jiahong Xue, Quentin Delfosse, Kristian Kersting: STORM: Segment, Track, and Object Re-Localization from a Single Image,  International Conference on Machine Learning (ICML 2026) [paper]

• Antonia Wüst, Wolfgang Stammer, Hikaru Shindo, Lukas Helff, Devendra Singh Dhami, Kristian Kersting: Learning Visual Concepts via Vision Language Programs. The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2026) [paper]

• Lukas Helff, Ruben Härle, Wolfgang Stammer, Felix Friedrich, Manuel Brack, Antonia Wüst, Hikaru Shindo, Patrick Schramowski, Kristian Kersting: ActivationReasoning: Logical Reasoning in Latent Activation Spaces.  International Conference on Learning Representations (ICLR 2026) [paper]

• Lukas Helff, Ahmad Omar, Felix Friedrich, Antonia Wüst, Hikaru Shindo, Rupert Mitchell, Tim Woydt, Patrick Schramowski, Wolfgang Stammer, Kristian Kersting: SLR: Automated Synthesis for Scalable Logical Reasoning, The 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026)  [paper]

Preprint

• Hikaru Shindo*, Hanzhao Lin*, Lukas Helff, Patrick Schramowski, Kristian Kersting: SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systems, arXiv Preprint, arXiv:2604.16022 [paper]

• Hikaru Shindo, Henri Rößler, Quentin Delfosse, Kristian Kersting: GRAIL: Autonomous Concept Grounding for Neuro-Symbolic Reinforcement Learning,  arXiv Preprint, arXiv:2604.16871 [paper]

2025  

• Hikaru Shindo, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting: BlendRL: A Framework for Merging Symbolic and Neural Policy Learning. 13th International Conference on Learning Representations (ICLR 2025, Spotlight). [paper] [code]

• Gopika Sudhakaran, Hikaru Shindo, Patrick Schramowski, Simone Schaub-Meyer, Kristian Kersting, Stefan Roth: ART: Adaptive Relation Tuning for Generalized Relation Detection. (ICCV 2025)

• Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami: Gestalt Vision: A Dataset for Evaluating Gestalt Principles in Visual Perception. 19th International Conference on Neurosymbolic Learning and Reasoning. (NeSy 2025, in PMLR) 

• Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting: NeST: The Neuro-Symbolic Transpiler., 2025. International Journal of Approximate Reasoning (IJAR). [paper] 

• Fateme Golivand Darvishvand, Hikaru Shindo*, Sahil Sidheekh*, Kristian Kersting, Sriraam Natarajan: Human-Allied Relational Reinforcement Learning. 25th Annual Conference on Advances in Cognitive Systems (ACS 2025, Oral) [paper]

Workshops

• Antonia Wüst, Hikaru Shindo, Wolfgang Stammer, Devendra Singh Dhami, Kristian Kersting: Learning Visual Concepts via Vision Language Programs. WiML Workshop@NeurIPS 2025. [paper]

• Lukas Helff, Ahmad Omar, Felix Friedrich, Antonia Wüst, Hikaru Shindo, Rupert Mitchell, Tim Woydt, Patrick Schramowski, Wolfgang Stammer, Kristian Kersting: SLR: Automated Synthesis for Scalable Logical Reasoning, FoRLM Workshop@NeurIPS 2025 [paper]

• Lukas Helff, Ruben Härle, Wolfgang Stammer, Felix Friedrich, Manuel Brack, Antonia Wüst, Hikaru Shindo, Patrick Schramowski, Kristian Kersting: ActivationReasoning: Logical Reasoning in Latent Activation Spaces. FoRLM Workshop@NeurIPS 2025 [paper]

2024

• Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting: DeiSAM: Segment Anything with Deictic Prompting. 38th Conference on Neural Information Processing Systems (NeurIPS 2024) [preprint] [code] 

• Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting: Learning Differentiable Logic Programs for Abstract Visual Reasoning.  Machine Learning (MLJ), 2024. [paper] [code] [web]

• Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami: Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes, Neurosymbolic Artificial Intelligence Journal (NAIJ) 2024.[paper]

• Wolfgang Stammer, Felix Friedlich, David Steinmann, Manuel Brack, Hikaru Shindo, Kristian Kersting: Learning by Self-Explaining. Transactions on Machine Learning Research (TMLR),  2024. [paper]

• Lukas Helff*, Wolfgang Stammer*, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting: V-LoL: A Diagnostic Dataset for Visual Logical Learning. Journal of Data-centric Machine Learning Research (DMLR) . 2024. [paper] [code] [web]

2023

• Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting: alphaILP: Thinking Visual Scenes as Differentiable Logic Programs.  Machine Learning (MLJ),  vol. 112, pp. 1465–1497, 2023. [paper] [code] [doc]

• Quentin Delfosse*, Hikaru Shindo*, Devendra Singh Dhami, Kristian Kersting: Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction. 37th Conference on Neural Information Processing Systems (NeurIPS 2023). [paper] [code]

• Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami: Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes, 17th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2023) [paper]

Workshops

• Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting: DeiSAM: Segment Anything with Deictic Prompting. AAAI Workshop on Neuro-Symbolic Learning and Reasoning in the era of Large Language Models (NuCLeaR@AAAI) [openreview] [slides] [extended_preprint] [code] 

~2022

• Viktor Pfanschilling, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting: Sum-Product Loop Programming: From Probabilistic Circuits to Loop Programming. 19th International Conference on Principles of Knowledge Representation and Reasoning (KR 2022). [paper].

• Hikaru Shindo, Masaaki Nishino, Akihiro Yamamoto: Differentiable Inductive Logic Programming for Structured Examples.  35th AAAI Conference on Artificial Intelligence (AAAI 2021, Focus Area on Neuro-Symbolic AI), February 2021. [paper] [slides] [poster] [code] [bibtex]

• Hikaru Shindo, Masaaki Nishino, Yasuaki Kobayashi, Akihiro Yamamoto: Metric Learning for Ordered Labeled Trees with pq-grams.  24th European Conference on Artificial Intelligence (ECAI 2020 ), Santiago, Spain, June 2020. [paper] [code] [bibtex]

• Hikaru Shindo, Masaaki Nishino, Akihiro Yamamoto: Using Binary Decision Diagrams to Enumerate Inductive Logic Programming Solutions. 28th International Conference on Inductive Logic Programming (ILP 2018, Up-and-Coming paper), Ferrara, Italy, September 2-4, 2018. [paper]  [slides]  [poster] [bibtex]

• Zihan Ye, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:  Differentiable Meta Logical Programming. Preprint. 2022. [paper]

• Björn Deiseroth, Patrick Schramowski, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting:  LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems. Preprint. 2022. [paper]

• Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting: Neuro-Symbolic Forward Reasoning. Preprint. 2021. [paper] [code]

Others

• Kaneko M., Tsuji K., Masuda K., Ueno K., Henmi K., Nakagawa S., Fujita R., Suzuki K., Inoue Y., Shindo H., Konishi E., Takamatsu T., Ukimura O.: Automated urine cell image analysis with a convolutional neural network. European Urology Open Science, 19, e1357. 2020.

Service

Serving as a reviewer at: Artificial Intelligence Review (Springer), NeurIPS 2022, nCSI Workshop@NeurIPS 2022, ICML 2023, NeurIPS 2023, ICLR 2024, ICML 2024, ICLR 2025, IJCLR 2025, NeurIPS 2025, AAAI 2025

EDUCATION

Ph.D. candidate Nov 2020 -

Artificial Intelligence and Machine Learning Lab, Department of Computer Science, TU Darmstadt, Germany.

Supervised by Prof. Dr. Kristian Kersting 

M.S.   April 2018 - March 2020 

Computational Intelligence Lab, Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Japan.  

Supervised by Prof. Dr. Akihiro Yamamoto 

B.S.  April 2014 - March 2018

Department of Informatics and Mathematical Science, Faculty of Engineering, Kyoto University, Japan. 

Supervised by Prof. Dr. Akihiro Yamamoto 

EXPERIENCES

Employment

• Hessen Research Associate  Oct 2023-

• Research Associate (Wissenschaftlicher Mitarbeiter) in SPAICER project Nov 2020 - Sep 2023

• JSPS Research Fellow  (日本学術振興会特別研究員DC1)  April 2020 - Oct 2020 

INTERNSHIPS

• NTT Communication Science Laboratories, Kyoto, Japan.  Research Intern  (May 2019 - March 2020)

• Rist Inc., Kyoto, Japan.  Machine Learning Engineer (January 2018 - March 2020)

• M3 Inc., Tokyo, Japan. Machine Learning Engineer (September 2018)

OTHER ACTIVITIES

Teaching Assistant.  Data Science Spring School, Kyoto University, Japan.  (March 2019)