Pavlo Molchanov

I am a distinguished research scientist and team manager at NVIDIA Research since 2015. 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.

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

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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.

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

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

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

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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

DRaCoN--Differentiable Rasterization Conditioned Neural Radiance Fields for Articulated Avatars. Amit Raj, Umar Iqbal, Koki Nagano, Sameh Khamis, Pavlo Molchanov, James Hays, Jan Kautz (2022). arXiv preprint arXiv:2203.15798.

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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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AViT: Adaptive Tokens for Efficient Vision Transformer. H. Yin, A. Vahdat, J. Alvarez, A. Mallya, J. Kautz, P. Molchanov (2021). In CVPR 2022.

PDF Cite Code CVPR2022 (Oral)

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