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Personal profile

Research interests

Ivan Oseledets graduated from Moscow Institute of Physics and Technology in 2006, got Candidate of Sciences degree in 2007, and Doctor of Sciences in 2012, both from Marchuk Institute of Numerical Mathematics of Russian Academy of Sciences. He joined Skoltech CDISE in 2013.
Ivan’s research covers a broad range of topics. He proposed a new decomposition of high-dimensional arrays (tensors) – tensor-train decomposition, and developed many efficient algorithms for solving high-dimensional problems. These algorithms are used in different areas of chemistry, biology, data analysis and machine learning. His current research focuses on development of new algorithms in machine learning and artificial intelligence such as construction of adversarial examples, theory of generative adversarial networks and compression of neural networks. It resulted in publications in top computer science conferences such as ICML, NIPS, ICLR, CVPR, RecSys, ACL and ICDM.
Professor Oseledets is an Associate Editor of SIAM Journal on Mathematics in Data Science, SIAM Journal on Scientific Computing, Advances in Computational Mathematics (Springer). He is also an area chair of ICLR 2020 conference.
Ivan Oseledets got several awards for his research and industrial cooperation, including two gold medals of Russian academy of Sciences (for students in 2005 and young researchers in 2009), Dynasty Foundation award (2012), SIAM Outstanding Paper Prize (2018), Russian President Award for young researchers in science and innovation (2018), Ilya Segalovich award for Best PhD thesis supervisor (2019), Best Professor award from Skoltech (2019), the best cooperation project leader award from Huawei (2015, 2017). He also has been a Pi and Co-Pi of several grants and industrial projects (230 million of rubles since 2017).
Professor Oseledets is actively involved in education and research supervision: he introduced and is teaching three courses of Skoltech curriculum, and five of his PhD students have successfully defended their theses, including two PhD students at Skoltech.

Academic Reputation and Societal Impact

The research of my group is visible internationally. This is confirmed by my membership in the editorial boards of top journals in the field (first with Russian affilation), by the visibility of the research. The results on tensor decompositions are included in classical textbooks. The results on deep neural networks were presented at top conferences. Regionally, I have been invited to many committees and expert panels with the funding agencies, governmental bodies, etc. I regularly give open lectures for broad audience, give interviews to national media, and also there was even a film on “Kultura” channel.

We work on broadly applicable algorithms. Many problems come from industry, for example, from wireless communication. In 2019 a lot of effort was put into establishing new partnerships, including large oil&gas companies and the largest Russian Bank.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 2 - Zero Hunger
  • SDG 3 - Good Health and Well-being
  • SDG 6 - Clean Water and Sanitation
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 13 - Climate Action


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