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).
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Daedalean AI has been featured in some leading aviation news providers, check that out! Read more
It is a non-trivial (and sometimes an ill-posed) task to define conditional probabilities using straightforward formula like \(P(B \vert A) = P(A \cap B) / P(A)\). Attempt to gather what I learned myself and taught in the classes. Read more