Ryo Kuroiwa

<ryo.kuroiwa [at] mail [dot] utoronto [dot] ca>

Research Interest

Artificial Intelligence, AI Planning, Heuristic Search, Parallel Search.

Publications

• Kuroiwa R, Beck, J.C. 2021. A Branch-and-Cut Approach for a Mixed Integer Linear Programming Compilation of Optimal Numeric Planning. Proc. of ICAPS 2021 Workshop on Heuristic Search for Domain-independent Planning (HSDIP) paper
• Kuroiwa R., Shleyfman A., Piacentini C., Castro M.P., and Beck, J.C. 2021. LM-cut and Operator Counting Heuristics for Optimal Numeric Planning with Simple Conditions. Proc. the 31th International Conference on Automated Planning and Scheduling. (ICAPS 2021) paper supplement code benchmarks
• Yu L, Kuroiwa R, Fukunaga, A. 2020. Learning Search-Space Specific Heuristics Using Neural Network. Proc. of ICAPS 2020 Workshop on Heuristic Search for Domain-independent Planning (HSDIP) paper
• Kuroiwa R., Fukunaga A. 2020. Front-to-Front Heuristic Search for Satisficing Classical Planning. Proc. the 29th International Joint Conference on Artificial Intelligence. (IJCAI-PRICAI 2020) paper code
• Kuroiwa R., Fukunaga A. 2020. Analyzing and Avoiding Pathological Behavior of Parallel Best-First Search. Proc. the 30th International Conference on Automated Planning and Scheduling. (ICAPS 2020) paper code
• Kuroiwa R., Fukunaga A. 2019. A Case Study on the Importance of Low-Level Algorithmic Details in Domain-Indpendent Heuristics. the 12th Symposium on Combinatorial Search. (SOCS 2019) paper
• Kuroiwa R., Fukunaga A. 2019. On the Pathological Search Behavior of Distributed Greedy Best-First Search. Proc. the 29th International Conference on Automated Planning and Scheduling. (ICAPS 2019) paper
• Kuroiwa R., Fukunaga A. 2018. Batch Random Walk for GPU-Based Classical Planning. Proc. the 28th International Conference on Automated Planning and Scheduling. (ICAPS 2018) paper

Education

• 09/2020-present: Ph.D. student, Department of Mechanical and Industrial Engineering, University of Toronto
• 03/2020: M.S., Department of General Systems Studies, Graduate School of Arts and Sciences, University of Tokyo
  • Thesis: Analyzing and Avoiding Pathological Behavior of Parallel Best-First Search
  • Advisor: Alex Fukunaga
  • Ichiko Memorial Award (Best thesis award)
• 03/2018: B.A. in Informatics, Department of Interdisciplinary Sciences, College of Arts and Sciences, University of Tokyo
  • Thesis: A GPU-Based Classical Planner
  • Advisor: Alex Fukunaga

Teaching

• 04/2018 - 08/2019: Assisted students with electric circuits in laboratory experiments.
• 09/2018 - 11/2018: Tutored Python programming to first year undergraduate students.

Grants and Scholorship

• 2018: Division of Multi-Disciplinary Sciences：International Conference Travel Grant (ICAPS 2018)

Community Service

• Reviewer for AAAI 2021

Work Experience

• 04/2020 - 08/2020: Data scientist at CyberAgent, Inc
• 10/2020 - 11/2020: NLP developer internship at AI Shift, Inc
• 08/2016 - 09/2016: Network engineer internship at CyberAgent, Inc
• 12/2015 - 03/2020: Part-time machine learning developer at Usagee, Inc

Other Activities

• 04/2019 - 03/2020: Leader of the Studnet Steering Comnittee of ICT Trouble Shooting Contest 2019
• 10/2016 - 03/2019: Member of the Student Steering Committee of ICT Trouble Shooting Contest 7, 8, 9, and 2018