Portrait of Dmytro Kuzmenko

Dmytro Kuzmenko

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

My name is Dmytro Kuzmenko, and I am a machine learning researcher working on human-compatible embodied intelligence at the intersection of reinforcement learning, robotics, foundation models, and human-robot interaction. I am particularly interested in intelligent systems that can continuously learn, adapt, and make decisions in complex, real-world environments that people share.

I am an Assistant Professor at the National University of Kyiv-Mohyla Academy, where I teach across machine learning, reinforcement learning, computer vision, and NLP. Alongside teaching, I am building an independent student research program: I develop research directions, work with students to turn them into tractable projects, and mentor undergraduate and graduate researchers through experimentation, writing, rebuttals, and publication. The first two student-led papers from this work were accepted to ECCV workshops in 2026.

I am pursuing a PhD in Computer Science and am currently a visiting PhD researcher at AIRLab, University of Turin, working on assistive and socially intelligent human-robot interaction.

In parallel, I have over nine years of industry experience in software engineering and applied AI. I currently serve as Head of AI at OnlyMonster, where I work on production language and agentic systems for real-time assistance, multilingual translation, safety, and AI-driven product features.

If you would like to discuss research, collaboration, or related opportunities, feel free to reach out by email.

News

Selected Publications

Proxemic risk assessment results thumbnail
Can Vision-Language Models Assess Proxemic Risk from Egocentric Robot Images?
V. Rudas, D. Kuzmenko
EMR Workshop at the European Conference on Computer Vision (ECCV), 2026
arXiv 
@misc{rudas2026proxemic,
                      title={Can Vision-Language Models Assess Proxemic Risk from Egocentric Robot Images?},
                      author={Vladyslava Rudas and Dmytro Kuzmenko},
                      year={2026},
                      eprint={2608.12515},
                      archivePrefix={arXiv},
                      primaryClass={cs.CV},
                      note={Accepted at the EMR 2026 workshop at ECCV 2026 (non-archival)},
                      url={https://arxiv.org/abs/2608.12515},
                }
Digital twin calibration pipeline thumbnail
Trajectory Design and Budgeted Querying for Digital Twin Calibration
V. Spitkovska, D. Kuzmenko
CDEL Workshop at the European Conference on Computer Vision (ECCV), 2026
arXiv 
@misc{spitkovska2026trajectory,
                      title={Trajectory Design and Budgeted Querying for Digital Twin Calibration},
                      author={Vladyslava Spitkovska and Dmytro Kuzmenko},
                      year={2026},
                      eprint={2608.08631},
                      archivePrefix={arXiv},
                      primaryClass={cs.LG},
                      note={Accepted at the CDEL 2026 workshop at ECCV 2026 (non-archival)},
                      url={https://arxiv.org/abs/2608.08631},
                }
MoIRA preprint thumbnail
MoIRA: Modular Instruction Routing Architecture for Multi-Task Robotics
D. Kuzmenko, N. Shvai
Neurocomputing, 2026
Full paper arXiv 
@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
arXiv Code Website 
@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},
        }
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 Code 
@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},
                }
View all publications (10)

Academic Service

Teaching

Senior Lecturer, NaUKMA
13 undergraduate theses supervised

Courses: