Speakers

Vadim Markovtsev

source{d}

Currently Vadim is a Lead Machine Learning Engineer at source{d} where he works on deep neural networks that aim to understand all of the world’s developers through their code. Vadim is one of the creators of the distributed deep learning platform Veles (https://velesnet.ml) while working at Samsung. Afterwards Vadim was responsible for the machine learning efforts to fight email spam at Mail.Ru. In the past Vadim was also a visiting associate professor at Moscow Institute of Physics and Technology, teaching about new technologies and conducting ACM-like internal coding competitions. Vadim is also a big fan of GitHub (vmarkovtsev) and HackerRank (markhor), as well as likes to write technical articles on a number of websites including blog.sourced.tech.

Egor Bulychev

source{d}

Currently Egor is a Data Scientist at source{d} where he works on deep neural networks that aim to understand all of the world’s developers through their code. Egor is one of the developers of the distributed deep learning platform Veles (https://velesnet.ml) while working at Samsung Research Russia. Afterwards Egor was responsible for the machine learning efforts to predict customer demography and preferences at Samsung Headquarters. In the past Egor was a robotics engineer whose responsibility was to develop the computer vision system for an unmanned air vehicle while studying at Bauman Moscow State Technical University. He used to be an active participant of international robotics competition Eurobot.

Charles Sutton

University of Edinburgh

Charles Sutton is a Reader (equivalent to Associate Professor: http://bit.ly/1W9UhqT) in Machine Learning at the University of Edinburgh. He has published over 40 papers in a broad range of applications of probabilistic machine learning and deep learning, including natural language processing (NLP), analysis of computer systems, software engineering, sustainable energy, and exploratory data analysis. His work in software engineering has won an ACM Distinguished Paper Award. His PhD is from the University of Massachusetts Amherst, and he has done postdoctoral work at the University of California Berkeley. He is currently Director of the EPSRC Centre for Doctoral Training in Data Science at the University of Edinburgh, and a Faculty Fellow of the Alan Turing Institute.

Pascal van Kooten

Jibes Data Analytics

Pascal van Kooten is fascinated by Human Machine interaction. He has been applying AI (such as bots, machine/deep learning) in open-source projects, competitions and enterprises alike. Among his projects: computer vision to determine car damage, lead generation by scanning and interpreting the whole internet, and generative chatbots to converse intelligently.

Grigory Sapunov

Inten.to

Software engineer with more than 20 years programming experience. Interested in data science and life sciences. Currently CTO and Co-founder of Intento, which benchmarks Cognitive Services and provides a single API to use all of them. Ph.D. in Artificial Intelligence, previously a consultant at IBM Watson, deep learning expert at RoadAR, data science expert & product manager at Stepik, and Tech Lead at Yandex News.

Vitaly Khudobakhshov

Одноклассники

I graduated from St.-Petersburg State University in Computational Physics. I used to do some research in mathematics but my favourite subject is functional programming. Right now I am a senior analyst and data scientist in a social network ok.ru. I am also an experienced Apache Spark user. 4 years ago I encountered a probabilistic programming for the first time. The main goal of my talk is to give a review of this facinating subject for the wider audience.