Iaroslav V. Ponomarenko

Hi, I'm Iaroslav! I'm a PhD student in Robotics at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), supervised by Professor Yoshihiko Nakamura.

Before starting my doctorate, I completed a Master of Science in Computer Applied Technology at Peking University, where I conducted research at the Center on Frontiers of Computing Studies (CFCS) under the supervision of Professor Hao Dong. I first joined MBZUAI in April 2025 as a visiting student researcher, working with Professor Nakamura until February 2026.

Earlier, I earned an Engineer (Specialist) degree in Information Systems and Technologies from the Voronezh Institute of High Technologies and a Technician Diploma in Automated Information Processing and Control Systems from the Borisoglebsk College of Informatics and Computer Engineering.

Portrait of Iaroslav V. Ponomarenko

News

Publications

(*) Equal contribution. (†) Corresponding author. Highlighted entries denote papers selected for special recognition.

  1. ManipGPT graphical abstract

    Kim, T., Bae, H., Li, Z., Li, X., Ponomarenko, I., Wu, R. & Dong, H.†.

    ManipGPT – is affordance segmentation by large vision models enough for articulated object manipulation?

    Proc. IROS (2025).

  2. CrayonRobo graphical abstract

    Li, X., Xu, L., Zhang, M., Liu, J., Shen, Y., Ponomarenko, I., Xu, J., Heng, L., Huang, S., Zhang, S. & Dong, H.†.

    CrayonRobo – object-centric prompt-driven vision-language-action model for robotic manipulation.

    Proc. CVPR (2025).

  3. SpatialBot graphical abstract

    Cai, W.*, Ponomarenko, I.*, Yuan, J., Li, X., Yang, W., Dong, H. & Zhao, B.†.

    SpatialBot – precise spatial understanding with vision language models.

    Proc. ICRA (2025).

  4. ManipVQA graphical abstract

    Huang, S.*, Ponomarenko, I.*, Jiang, Z., Li, X., Hu, X., Gao, P., Li, H. & Dong, H.†.

    ManipVQA – injecting robotic affordance and physically grounded information into multi-modal large language models.

    Proc. IROS (2024). Oral Pitch

  5. ImageManip graphical abstract

    Li, X., Wang, Y., Shen, Y., Ponomarenko, I., Lu, H., Wang, Q., An, B., Liu, J. & Dong, H.†.

    ImageManip – image-based robotic manipulation with affordance-guided next view selection.

    Preprint (2023).

  6. LPAVAA3DOM graphical abstract

    Ju, Y., Geng, H., Yang, M., Geng, Y., Ponomarenko, I., Kim, T., Wang, H. & Dong, H.†.

    Learning part-aware visual actionable affordance for 3D articulated object manipulation.

    Proc. CVPR 3DVR (2023). Spotlight

  7. Sukhanov, A. A. & Ponomarenko, I. V..

    Application of block periodization in the design of health-prolonging training cycles.

    Proc. of Interregional Final Scientific Student Conferences: “Student Science” and “Young Scientists” 354, 275–279 (2017).

  8. Sukhanov, A. A., Ponomarenko, I. V. & Rubin, V. S.†.

    The potential of instrumental methods for medical soft tissue diagnostics in physical education and health-improving training.

    Proc. of the All-Russian Scientific Online Conference: Fitness–Aerobics 2016 226, 97–98 (2016).

  9. Sukhanov, A. A., Ponomarenko, I. V. & Rubin, V. S.†.

    The study of methodological approaches to intermuscular coordination and strength development in women of early adulthood engaged in health-improving training.

    Proc. of the All-Russian Scientific Online Conference: Fitness–Aerobics 2016 226, 98–100 (2016).

  10. Sukhanov, A. A. & Ponomarenko, I. V..

    Assessment of the muscle condition as one of the physical health indicators in the framework of physical education and health-improving training.

    Proc. of Students and Young Scientists of the Russian State University of Physical Education, Sport, Youth and Tourism 279, 78–80 (2016).

Service

Conference Reviewer: RSS (2025), ICRA (2025, 2026), IROS (2026)
Membership: IEEE (2024–present), CAAI (2024–2029)
Teaching Assistant: Fundamentals of Artificial Intelligence, Peking University (Spring 2024)