- Senior Research Fellow:Faculty of Computer Science / Big Data and Information Retrieval School / Samsung-HSE Laboratory
- Alexander Novikov has been at HSE since 2015.
Conducting research in the area of tensor neural networks, convolutional networks acelerating and K-FAC optimization.
Diploma in Applied math and computer science
Lomonosov Moscow State University, computational mathematics and cybernetics
Continuing education / Professional retraining / Internships / Study abroad experience
Google USA, Mountain View, CA July 2014 — October 2014
Software Engineering Intern
Young Faculty Support Program (Group of Young Academic Professionals)
Category "New Researchers" (2017)
- Preprint Novikov A., Trofimov M., Oseledets I. Exponential machines / stat :: arxiv :: Cornell University. Series stat :: arxiv :: Cornell University "stat :: arxiv :: Cornell University". 2017.
- Chapter Khrulkov V., Novikov A., Oseledets I. Expressive power of recurrent neural networks, in: Proceeding of sixth International Conference on Learning Representations (ICLR 2018). , 2017.
- Preprint Izmailov P., Novikov A., Kroptov D. Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition / Cornell University. Series arxive "math". 2017.
Skolkovo Institute of Science and Technology, Junior Research Scientist, October 2014 — September 2015
In this specialization the listeners will complete the courses on deep learning, Bayesian methods, reinforcement learning, natural language processing etc. Alexander Novikov, research fellow of the laboratory, is a lecturer of Bayesian Methods course.
In December 2016, five new international laboratories opened up at the Higher School of Economics, one of which was the International Laboratory of Deep Learning and Bayesian Methods. This lab focuses on combined neural Bayesian models that bring together two of the most successful paradigms in modern-day machine learning – the neural network paradigm and the Bayesian paradigm.