Pavlo Molchanov

I am a Distinguished Research Scientist and Team Manager at NVIDIA Research. I work in the LPR team led by Jan Kautz, focusing on efficient deep learning and human-centric computer vision. Since 2023, I have been leading a research team dedicated to efficient deep learning, specifically in the areas of model compression, NAS-like acceleration, novel architectures, and adaptive/conditional inference. Currently we are primary focused on LLM and vision-language models.

I earned my PhD from Tampere University of Technology, Finland in 2014, specializing in signal processing under the supervision of Karen Eguiazarian. Prior to that, I obtained my master’s degree from the National Aerospace University in Kharkiv, Ukraine. My master’s research centered around radio systems, with a focus on high-order spectrum techniques for signal processing, mentored by Alexander Totsky.

We are always on the lookout for promising interns and full-time positions in the area of LLM and VLM efficiency. Feel free to reach out to me for more details. I am also interested in connecting with individuals who share similar research interests.

Publications

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AM-RADIO: Reduce All Domains Into One. Mike Ranzinger, Greg Heinrich, Jan Kautz, Pavlo Molchanov (2023). In Arxiv.

PDF Cite Code CVPR2024

VILA: On Pre-training for Visual Language Models. Ji Lin, Hongxu Yin, Wei Ping, Yao Lu, Pavlo Molchanov, Andrew Tao, Huizi Mao, Jan Kautz, Mohammad Shoeybi, Song Han (2023). In Arxiv.

PDF Cite CVPR2024

FasterViT: Fast Vision Transformers with Hierarchical Attention. A. Hatamizadeh, G. Heinrich, H. Yin, A. Tao, J. Alvarez, J. Kautz, P. Molchanov (2023). In Arxiv.

PDF Cite Code ICLR2024

Heterogeneous Continual Learning. D. Madaan, H. Yin, W. Byeon, J. Kautz, P. Molchanov (2023). In CVPR 2023.

PDF Cite Code Video CVPR2023 Highlight

Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models. P. Micaelli, A. Vahdat, H. Yin, J. Kautz, P. Molchanov (2023). In CVPR 2023.

PDF Cite Code Video CVPR2023

Global context vision transformers. A. Hatamizadeh, H. Yin, J. Kautz, P. Molchanov (2023). In ICML 2023.

PDF Cite Code ICML2023

LANA: Latency Aware Network Acceleration. P. Molchanov, J. Hall, H. Yin, J. Kautz, N. Fusi, A. Vahdat (2022). In CVPR 2022.

PDF Cite Video ECCV2022

Structural pruning via latency-saliency knapsack. M. Shen, H. Yin, P. Molchanov, L. Mao, J. Liu, J. Alvarez (2022). In NeurIPS2022.

PDF Cite Code Video NeurIPS2022

Gradvit: Gradient inversion of vision transformers. Ali Hatamizadeh, Hongxu Yin, Holger Roth, Wenqi Li, Jan Kautz, Daguang Xu, Pavlo Molchanov (2022). In CVPR 2022.

PDF Cite Code CVPR2022

Do Gradient Inversion Attacks Make Federated Learning Unsafe?. Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona G Flores, Jan Kautz, Daguang Xu, others (2022). arXiv preprint arXiv:2202.06924.

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