| 2025 | ESOP | On the Relationship between Dijkstra Monads and Higher-Order Fixpoint Logic. | Risa Yamada, Naoki Kobayashi, Ken Sakayori, Ryosuke Sato |
| 2025 | SAS | Automated Catamorphism Synthesis for Solving Constrained Horn Clauses over Algebraic Data Types. | Hiroyuki Katsura, Naoki Kobayashi, Ken Sakayori, Ryosuke Sato |
| 2024 | APLAS | Mode-based Reduction from Validity Checking of Fixpoint Logic Formulas to Test-Friendly Reachability Problem. | Hiroyuki Katsura, Naoki Kobayashi, Ken Sakayori, Ryosuke Sato |
| 2024 | PEPM | Productivity Verification for Functional Programs by Reduction to Termination Verification. | Ren Fukaishi, Naoki Kobayashi, Ryosuke Sato |
| 2024 | VMCAI | Borrowable Fractional Ownership Types for Verification. | Takashi Nakayama, Yusuke Matsushita, Ken Sakayori, Ryosuke Sato, Naoki Kobayashi |
| 2023 | APLAS | Argument Reduction of Constrained Horn Clauses Using Equality Constraints. | Ryo Ikeda, Ryosuke Sato, Naoki Kobayashi |
| 2023 | ESOP | Gradual Tensor Shape Checking. | Momoko Hattori, Naoki Kobayashi, Ryosuke Sato |
| 2022 | APNOMS | Method for Extracting Suspected Faulty Equipment Through Recursive Use of GNN Model. | Seiji Sakuma, Ryosuke Sato, Mizuto Nakamura, Kyoko Yamagoe |
| 2022 | APNOMS | Methods for Providing Resilience from Electric Power Side to Communications Network Side. | Ryosuke Sato, Yoshikazu Nakamura, Tomonari Fujimoto, Yuji Shinozaki, Motomu Nakajima |
| 2022 | APNOMS | Vectorization Method for Device Alarms Achieving High General Ability for AI Application to Network Operations. | Ryosuke Sato, Mizuto Nakamura, Chiriro Sato, Seiji Sakuma, Motomu Nakajima |
| 2022 | FLOPS | Asynchronous Unfold/Fold Transformation for Fixpoint Logic. | Mahmudul Faisal Al Ameen, Naoki Kobayashi, Ryosuke Sato |
| 2022 | SAS | Parameterized Recursive Refinement Types for Automated Program Verification. | Ryoya Mukai, Naoki Kobayashi, Ryosuke Sato |
| 2021 | APLAS | Termination Analysis for the $$\pi $$-Calculus by Reduction to Sequential Program Termination. | Tsubasa Shoshi, Takuma Ishikawa, Naoki Kobayashi, Ken Sakayori, Ryosuke Sato, Takeshi Tsukada |
| 2021 | APNOMS | Bayesian network equipped workflow engine to coordinate Artificial Intelligence for automating network operation. | Ryosuke Sato, Mizuto Nakamura, Atsushi Takada, Kyoko Yamagoe |
| 2021 | APNOMS | Orchestrator for Automating Failure Response in Telecom Carriers. | Yuichi Suto, Ryosuke Sato, Yuichiro Ishizuka, Kosuke Sakata, Yoshikazu Hagiwara, Tsuyoshi Furukawa |
| 2021 | SAS | Symbolic Automatic Relations and Their Applications to SMT and CHC Solving. | Takumi Shimoda, Naoki Kobayashi, Ken Sakayori, Ryosuke Sato |
| 2020 | APNOMS | A Study on Automation of Network Maintenance in Telecom Carriers for Zero-Touch Operations. | Aiko Oi, Ryosuke Sato, Yuichi Suto, Kosuke Sakata, Motomu Nakajima, Tsuyoshi Furukawa |
| 2020 | QRS | How Fast and Effectively Can Code Change History Enrich Stack Overflow? | Ryujiro Nishinaka, Naoyasu Ubayashi, Yasutaka Kamei, Ryosuke Sato |
| 2019 | ICSE | Git-based integrated uncertainty manager. | Naoyasu Ubayashi, Takuya Watanabe, Yasutaka Kamei, Ryosuke Sato |
| 2019 | PEPM | Combining higher-order model checking with refinement type inference. | Ryosuke Sato, Naoki Iwayama, Naoki Kobayashi |
| 2019 | QRS | When and Why Do Software Developers Face Uncertainty? | Naoyasu Ubayashi, Yasutaka Kamei, Ryosuke Sato |
| 2018 | APLAS | HoIce: An ICE-Based Non-linear Horn Clause Solver. | Adrien Champion, Naoki Kobayashi, Ryosuke Sato |
| 2018 | HCI | Proposal for an Affective Skateboard Using Various Lighting Patterns. | Namgyu Kang, Ryosuke Sato |
| 2018 | ICSE | Exploring uncertainty in GitHub OSS projects: when and how do developers face uncertainty? | Naoyasu Ubayashi, Hokuto Muraoka, Daiki Muramoto, Yasutaka Kamei, Ryosuke Sato |
| 2018 | ICSoft | iArch-U/MC: An Uncertainty-Aware Model Checker for Embracing Known Unknowns. | Naoyasu Ubayashi, Yasutaka Kamei, Ryosuke Sato |
| 2018 | ICSoft | Modular Programming and Reasoning for Living with Uncertainty. | Naoyasu Ubayashi, Yasutaka Kamei, Ryosuke Sato |
| 2018 | MODELSWARD | Can Abstraction Be Taught? Refactoring-based Abstraction Learning. | Naoyasu Ubayashi, Yasutaka Kamei, Ryosuke Sato |
| 2018 | TACAS | ICE-Based Refinement Type Discovery for Higher-Order Functional Programs. | Adrien Champion, Tomoya Chiba, Naoki Kobayashi, Ryosuke Sato |
| 2017 | ESOP | Modular Verification of Higher-Order Functional Programs. | Ryosuke Sato, Naoki Kobayashi |
| 2016 | ICFP | Automatically disproving fair termination of higher-order functional programs. | Keiichi Watanabe, Ryosuke Sato, Takeshi Tsukada, Naoki Kobayashi |
| 2016 | POPL | Temporal verification of higher-order functional programs. | Akihiro Murase, Tachio Terauchi, Naoki Kobayashi, Ryosuke Sato, Hiroshi Unno |
| 2015 | CAV | Predicate Abstraction and CEGAR for Disproving Termination of Higher-Order Functional Programs. | Takuya Kuwahara, Ryosuke Sato, Hiroshi Unno, Naoki Kobayashi |
| 2015 | PEPM | Verifying Relational Properties of Functional Programs by First-Order Refinement. | Kazuyuki Asada, Ryosuke Sato, Naoki Kobayashi |
| 2013 | PEPM | Towards a scalable software model checker for higher-order programs. | Ryosuke Sato, Hiroshi Unno, Naoki Kobayashi |
| 2011 | PLDI | Predicate abstraction and CEGAR for higher-order model checking. | Naoki Kobayashi, Ryosuke Sato, Hiroshi Unno |