Maksim Zhdanov
I'm a Research Scientist focusing on Generative AI for Biology. Currently, I'm pursuing an MSc in Computational Biology at MBZUAI.
I completed my undegraduate degree in CS with Honours at NUST MISIS.
My passion is the AI research. I believe that the state-of-the-art technologies will shape our tomorrow as we continuosly understand the laws of our world better and better. I'm interested in AI4Science, particularly right now I'm focused on:
- Selectivity and kinetics in protein design and equilibirum sampling
- Generative modeling of biomolecular interactions including flexible all-atom docking models and AlphaFold-like co-folding models
- Reward fine-tuning of generative models and test-time steering
I'm also generally interested in the topic of self-supervised learning.
My past experience includes conducting general machine learning research mostly in the areas of uncertainty estimation and out-of-distribution detection. Previously, I worked on image/video generative models at a local startup.
In the past, I participated in numerous machine learning competitions.
From Altai mountains in cold Siberia
Links
[GitHub, Google Scholar, CV, LinkedIn]
Selected Papers
Harmonic Torsional Diffusion for Protein-Ligand Flexible Docking
M. Zhdanov, P. Strashnov, V. Kurenkov
Neural Information Processing Systems (NeurIPS), 2026
(previosuly ICML 2026 GenBio Workshop)
[PDF,
Code]
Vintix II: Decision Pre-Trained Transformer is a Scalable In-Context Reinforcement Learner
*full list of authors in the paper*
International Conference on Learning Representations (ICLR), 2026
[PDF, ArXiv]
Electrostatics from Laplacian Eigenbasis for Neural Network Interatomic Potentials
M. Zhdanov, V. Kurenkov
International Conference on Machine Learning (ICML) GenBio Workshop, 2025
[PDF, ArXiv,
Code]
Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection
M. Zhdanov, S. Dereka, S. Kolesnikov
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025 (previosuly AAAI 2024 Deployable AI Workshop)
[PDF, ArXiv, Poster,
Code]
Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy
S. Dereka, I. Karpukhin, M. Zhdanov, S. Kolesnikov
IEEE International Conference on Image Processing (ICIP), 2024
[PDF, ArXiv,
Code]
Invited Talks
2026, MBZUAI BioLunch
2024, Research4Kids CIS Trip (7 citites)
2023, MISIS
2023, Tinkoff STEM University
News
10/2026: Harmony is accepted at NeurIPS 2026! See you in Paris!
08/2026: I'm starting my MSc in Computational Biology at MBZUAI in Abu Dhabi!
06/2026: Harmony was accepted at 2026 workshop on Generative and Agentic AI for Biology (ICML 2026). See you in Seoul!
06/2026: I've finished my undegraduate degree with Honours in CS from NUST MISIS. Thanks for that chapter of my life!
06/2025: Phi-Module was accepted at The 2nd Workshop on Generative AI and Biology (ICML 2025)!
04/2025: I'm attending ICLR 2025 in Singapore!
11/2024: Our new paper on identity curvature Laplace approximation is accepted to WACV 2024!
09/2024: I'm joining dunnolab to work on multidisciplinary problems of AI for Science!
06/2024: Our paper on the diversification of deep ensembles is accepted to IEEE ICIP 2024!
Meet us in Adu Dhabi in October!
04/2024: I've just deadlifted 200 KG!
04/2024: We've visited 7 cities of CIS with our research talks.
02/2024: I'm joining Tinkoff Research as a Research Scientist!
12/2023: Our paper on Laplace approximation is accepted to AAAI 2024 DAI Workshop. Stay tuned for updates!
03/2023: Our paper on machine learning for X-Ray diffraction is accepted to ICLR 2023
ML4Materials workshop.
01/2023: I'm starting my research internship at Tinkoff AI Lab.
09/2022: I'm starting my undegraduate studies at MISIS university!
