Welcome! Long story short:
- Currently, I work as a machine learning engineer at Daedalean AI, making a self-flying car that uses certifiable (acc. to EASA regulations) avionics/autopilot.
- In 2018, I completed my PhD at the ETH Zurich, in Information Science and Engineering Group. I was an associate fellow of Max Planck ETH Center for Learning Systems.
- In 2017, I did an internship at Google Research and Machine Intelligence working on deep learning for Question Answering. See blog post by Google AI.
- In 2010-2012, I worked at ABBYY as a part of NLP Compreno Project in the role of C++ SWE. There I developed an SDK for morphological and lexical analyzer subsystems.
- In 2011, I graduated from Moscow State University, dept. of Mathematics and Mechanics. I specialized in discrete mathematics (see Projects).
Highlights:
- Daedalean featured (among others) in Avionics International and eVtol publications! Check it out.
- Check out the latest video on the joint Daedalean-Volocopter flight tests (YouTube link). Press-release is available here.
Recent posts:
(go to all for tag/language filters)
Daedalean’s autonomous flight tech featured in news
18 Aug 2019
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news
aviation
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1 min read
Daedalean AI has been featured in some leading aviation news providers, check that out! Read more
Subtle pitfalls of conditional probabilities and the Borel-Kolmogorov paradox
06 Jan 2019
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science
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16 min read
It is a non-trivial (and sometimes an ill-posed) task to define conditional probabilities using straightforward formula like . Attempt to gather what I learned myself and taught in the classes. Read more
Our paper in Journal of Theoretical Computer Science
28 Dec 2018
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news
science
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1 min read
Our long paper on posterior agreement was published in J. of TCS Read more