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Iโ€™m Nikita Durasov, a PhD student at EPFL IC (๐Ÿ‡จ๐Ÿ‡ญ) where I work under the supervision of Professor Pascal Fua at the Computer Vision Laboratory on problems related to Deep Learning (๐Ÿค–) and Computer Vision (๐Ÿ‘).

Previously, I was a research scientist at Apple, Amazon, and Samsung AI, working on problems related to Computer Vision and Deep Learning. I completed my bachelor's degree at MIPT (๐Ÿ‡ท๐Ÿ‡บ) in Applied Physics and Mathematics while also studying at the Yandex School of Data Analysis.

Until next fall, I'll be with Nvidia's autonomous driving department, focusing on improving perception models.

**UPDATE**: I am finishing my PhD this Fall and will be available for job opportunities starting in December-January. Find my email at the bottom of the page.


I'm broadly interested in enhancing the interpretability and robustness of modern deep learning models through uncertainty quantification and bayesian methods.

Consequently, I'm also curious about new approaches to active learning, bayesian optimization, and other data-efficient techniques for various domains.

Mostly, my research is focused on computer vision and image processing tasks, but it is not limited to them. Occasionally, I delve into natural language processing and reinforcement learning.

I have also contributed as a reviewer for various academic conferences and journals, such as: CVPR NeurIPS ICML ICCV ECCV ICRA IROS ACCV RA-L IJCV TPAMI, and other (full list).

My Stats from Google Scholar:

  • Citations: 179
  • h-index: 6
  • i10-index: 6


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Enabling Uncertainty Estimation in Iterative Neural Networks

Nikita Durasov, Doruk Oner, Jonathan Donier, Hieu Le, Pascal Fua

ICML 2024

pdf | code | page

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ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Nikita Durasov, Nik Dorndorf, Hieu Le, Pascal Fua

TMLR 2024 ICMLW 2024

openreview | pdf | code | page

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How to Boost Face Recognition with StyleGAN?

Artem Sevastopolsky, Yuri Malkov, Nikita Durasov, Luisa Verdoliva, Matthias NieรŸner

ICCV 2023

pdf | code | video | page

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Leveraging Self-Supervision for Cross-Domain Crowd Counting

Weizhe Liu, Nikita Durasov, Pascal Fua

CVPR 2022 (Oral)

pdf | code | video | page

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Masksembles for Uncertainty Estimation

Nikita Durasov, Timur Bagautdinov, Pierre Baque, Pascal Fua

CVPR 2021

pdf | code | media | video | page

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Double refinement network for efficient indoor monocular depth estimation

Nikita Durasov, Mikhail Romanov, Valeriya Bubnova, Pavel Bogomolov, Anton Konushin

IROS 2019

pdf | video

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Learning node embeddings for influence set completion

Sergei Ivanov, Nikita Durasov, Evgeny Burnaev

ICDM 2018

pdf | code


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MirrorCheck: Efficient Adversarial Defense for Vision-Language Models

Samar Fares, Klea Ziu, Toluwani Aremu, Nikita Durasov, Martin Takรกฤ, Pascal Fua, Karthik Nandakumar, Ivan Laptev

ARXIV 2024

pdf | page

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PartAL: Efficient Partial Active Learning in Multi-Task Visual Settings

Nikita Durasov, Nik Dorndorf, Pascal Fua

ARXIV 2022


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DEBOSH: Deep Bayesian Shape Optimization

Nikita Durasov, Artem Lukoyanov, Jonathan Donier, Pascal Fua

ARXIV 2021

pdf | media | page

Invited Talks

  • 10/04/2024: "Deep Uncertainty" was presented at UiT The Arctic University of Norway in Tromsรธ, Norway.
  • 12/02/2024: "Deep Uncertainty" was presented at MBZUAI in Abu Dhabi, UAE.
  • 08/01/2024: "Low-cost Uncertainty Estimation for Deep Learning" at CVLAB Group Meeting in Lausanne, Switzerland.
  • 02/10/2023: "Deep Uncertainty" was presented at Nordic AI Conference in Copenhagen, Sweden.
  • 17/08/2023: "Deep Uncertainty" was presented at Stony Brook University in New York, USA.
  • 16/08/2023: "Deep Uncertainty" was presented at NYU Courant Institute in New York, USA.
  • 09/08/2023: "Deep Uncertainty" was presented at Apple's Park in Cupertino, USA.
  • 08/08/2023: "Deep Uncertainty" was presented at Meta in San Francisco, USA.
  • 13/12/2022: "Masksembles for Uncertainty Estimation" at Uncertainty Reading Group at ETH in Zurich, Switzerland. [video]
  • 30/09/2022: "Enhanced Robustness of Transformer Detectors for Handling Omissions in Ground Truth Data" at Apple Development Center in Zurich, Switzerland.
  • 26/08/2022: "Single-shot Uncertainty Estimation" at CVLAB Group Meeting in Lausanne, Switzerland.
  • 26/04/2022: "Partial Active Learning with Incomplete Annotations" at VILAB Group Meeting in Lausanne, Switzerland.
  • 20/12/2021: "Robust Prediction of Stereo Disparity Under Uncertainty" at Amazon Prime Air in Graz, Austria.
  • 22/06/2021: "Masksembles for Uncertainty Estimation" at CVPR 2021. [video] [paper]