Portrait of Dmytro Kuzmenko

Dmytro Kuzmenko

Head of AI @ OnlyMonster · PhD Candidate @ NaUKMA · Visiting PhD Student @ AIRlab, UniTo
Torino, Italy
Scholar GitHub LinkedIn X

I am a research engineer working at the intersection of reinforcement learning, robotics, foundation models, and human-robot interaction, with a focus on building efficient and reliable intelligent systems.

I am a founding AI engineer and senior individual contributor at OnlyMonster, where I work on production language and agentic systems for real-time assistance, multilingual translation, safety, and AI-driven product features.

I am also pursuing a PhD in Computer Science at NaUKMA and currently visiting AIRlab in UniTo to collaborate on assistive HRI. My research focuses on efficient perception, control, and HRI, with particular interest in data- and compute-efficient methods and the role of trust and safety in deployed systems.

Outside of work, I enjoy playing shogi, collecting vinyl records, and cooking :)

Interests: HRI, embodied AI, efficient RL, multi-task control, world foundation models.

News

Publications

MoIRA preprint thumbnail
MoIRA: Modular Instruction Routing Architecture for Multi-Task Robotics
D. Kuzmenko, N. Shvai
Neurocomputing, 2026
Full Paper arXiv Bib 
@article{KUZMENKO2026132962,
title = {MoIRA: Modular instruction routing architecture for multi-task robotics},
journal = {Neurocomputing},
volume = {674},
pages = {132962},
year = {2026},
issn = {0925-2312},
doi = {https://doi.org/10.1016/j.neucom.2026.132962},
url = {https://www.sciencedirect.com/science/article/pii/S0925231226003590},
author = {Dmytro Kuzmenko and Nadiya Shvai},
}
EED Gym thumbnail
When Robots Say No: The Empathic Ethical Disobedience Benchmark
D. Kuzmenko, N. Shvai
ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2026 (accepted)
arXiv Code Website Bib 
@article{kuzmenko2025eedgym,
          title   = {When Robots Say No: The Empathic Ethical Disobedience Benchmark},
          author  = {Kuzmenko, Dmytro and Shvai, Nadiya},
          year    = {2025},
          note    = {Accepted at the ACM/IEEE International Conference on Human-Robot Interaction (HRI 2026). Preprint: arXiv:2512.18474},
          doi     = {10.48550/arXiv.2512.18474},
        }
Energy conservation thumbnail
Energy Conservation for Autonomous Agents Using Reinforcement Learning
V. Beimuk, D. Kuzmenko
NaUKMA Research Papers: Computer Science, 2025
DOI Bib 
@article{beimuk2025energy,
                  title={Energy conservation for autonomous agents using reinforcement learning},
                  author={Beimuk, V. and Kuzmenko, D.},
                  journal={NaUKMA Research Papers. Computer Science},
                  volume={8},
                  pages={68--75},
                  year={2025},
                  doi={10.18523/2617-3808.2025.8.68-75}
                }
TD-MPC-Opt preprint thumbnail
TD-MPC-Opt — Distillation & Quantization for Efficient Multi-Task Model-Based RL
D. Kuzmenko, N. Shvai
Preprint (under review), 2025
arXiv GitHub Bib 
@misc{kuzmenko2025tdmpcoptdistillingmodelbasedmultitask,
                      title={TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents}, 
                      author={Dmytro Kuzmenko and Nadiya Shvai},
                      year={2025},
                      eprint={2507.01823},
                      archivePrefix={arXiv},
                      primaryClass={cs.LG},
                      url={https://arxiv.org/abs/2507.01823}, 
                }
AAMAS 2025 thumbnail
Knowledge Transfer in Model-Based Reinforcement Learning Agents for Efficient Multi-Task Learning
D. Kuzmenko, N. Shvai
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2025
ACM DL arXiv Bib 
@inproceedings{10.5555/3709347.3743949,
                  author = {Kuzmenko, Dmytro and Shvai, Nadiya},
                  title = {Knowledge Transfer in Model-Based Reinforcement Learning Agents for Efficient Multi-Task Learning},
                  year = {2025},
                  isbn = {9798400714269},
                  publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
                  address = {Richland, SC},
                  booktitle = {Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems},
                  pages = {2597-2599},
                  numpages = {3},
                  keywords = {efficient rl agents, knowledge distillation, model compression, model-based reinforcement learning, multi-task learning},
                  location = {Detroit, MI, USA},
                  series = {AAMAS '25}
                }
ICTERI 2024 thumbnail
Balancing Performance and Efficiency in Zero-Shot Robotic Navigation
D. Kuzmenko, N. Shvai
ICTERI 2024, Communications in Computer and Information Science (Springer), 2025
DOI arXiv Bib 
@incollection{KuzmenkoShvai2025ZeroShotNavigation,
                title     = {Balancing Performance and Efficiency in Zero-Shot Robotic Navigation},
                author    = {Kuzmenko, Dmytro and Shvai, Nadiya},
                booktitle = {Information and Communication Technologies in Education, Research, and Industrial Applications},
                series    = {Communications in Computer and Information Science},
                volume    = {2359},
                pages     = {370--381},
                year      = {2025},
                publisher = {Springer, Cham},
                doi       = {10.1007/978-3-031-81372-6\_28},
                url       = {https://doi.org/10.1007/978-3-031-81372-6_28}
              }
StairNet thumbnail
StairNet: Visual Recognition of Stairs for Human-Robot Locomotion
A. G. Kurbis, D. Kuzmenko, B. Ivanyuk-Skulskiy, A. Mihailidis, B. Laschowski
BioMedical Engineering OnLine, 2024
DOI arXiv Bib 
@article{Kurbis2024StairNet,
                    title   = {StairNet: Visual Recognition of Stairs for Human-Robot Locomotion},
                    author  = {Kurbis, Andrew Garrett and Kuzmenko, Dmytro and Ivanyuk-Skulskiy, Bogdan and Mihailidis, Alex and Laschowski, Brokoslaw},
                    journal = {BioMedical Engineering OnLine},
                    volume  = {23},
                    number  = {20},
                    year    = {2024},
                    doi     = {10.1186/s12938-024-01216-0},
                    url     = {https://doi.org/10.1186/s12938-024-01216-0}
                  }
IROS 2023 thumbnail
Efficient Visual Perception of Human–Robot Walking Environments Using Semi-Supervised Learning
D. Kuzmenko, O. Tsepa, A. G. Kurbis, A. Mihailidis, B. Laschowski
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
DOI biorXiv Bib 
@INPROCEEDINGS{10341654,
                  author={Kuzmenko, Dmytro and Tsepa, Oleksii and Kurbis, Andrew Garrett and Mihailidis, Alex and Laschowski, Brokoslaw},
                  booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, 
                  title={Efficient Visual Perception of Human-Robot Walking Environments Using Semi-Supervised Learning}, 
                  year={2023},
                  volume={},
                  number={},
                  pages={6544-6549},
                  keywords={Legged locomotion;Training;Supervised learning;Semisupervised learning;Transformers;Real-time systems;Standards},
                  doi={10.1109/IROS55552.2023.10341654}}

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