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Tag "students"

HSE Students Win Hackathon Held by McKinsey and Gett

HSE Students Win Hackathon Held by McKinsey and Gett
The MacDacHack team, which includes HSE students and one alumna, recently won a Big Data hackathon held by McKinsey and Gett.

Two Teams of Top Programmers to Represent HSE at the International Collegiate Programming Contest

HSE student team: Alexander Zimin (Faculty of Mathematics), Timur Iskhakov and Igor Kraskevich (both from the Faculty of Computer Science)
One of the teams successfully qualified for the world finals at the recent Northern Eurasia heat. The other will be attending the finals by special invitation.

Faculty of Computer Science Students Take Gold at BPI Challenge 2017

Faculty of Computer Science Students Take Gold at BPI Challenge 2017
Elizaveta Povalyaeva, Artem Fomenko and Ismail Khamitov, fourth-year students of Software Engineering, took first place in the student category at the BPI Challenge 2017, a business process analysis competition. They presented their solution at the 13th International Workshop on Business Process Intelligence 2017 and are the first students from Russia to participate in the event and win, with the highest-ever number of projects participating in the competition.

Research Paper Competition Winners Can Get a Headstart on Their Academic Careers

The application period for HSE’s Student Research Paper Competition has started. The winners will have an opportunity to take part in workshops on academic skills development, while those in state-financed studies will improve their chances of seeing their academic scholarships increased. Also, in addition in HSE students, learners from other academic institutions are eligible for this competition.

Bayesian Methods in Deep Learning Summer School in Moscow

Bayesian Methods in Deep Learning Summer School in Moscow
Bayesian Methods in Deep Learning Summer School was held in Moscow fron 26 to 30 August. During these five days 96 participants from 8 countries listened to lectures about Bayesian methods in deep learning and trained neural networks.

Students from HSE Computer Science Faculty Win BlockchainHack Hackathon

Students from HSE Computer Science Faculty Win BlockchainHack Hackathon
BlockchainHack, Russia's largest hackathon focusing on the development of block chain projects, took place in Moscow on the 1st and 2nd of July. Seniors from the HSE Faculty of Computer Science took home the grand prize of $50,000.

Faculty of Computer Science Organized Event for Radboud University Students

Faculty of Computer Science Organized Event for Radboud University Students
From April 20 – 30, 2017, students from Radboud University Nijmegen took part in a cultural and educational programme organized by the Faculty of Computer Science as part of the ‘Information and Computer Technology in Different Cultures’ course.

HSE Students Win International Competition in Computer Security

HSE Students Win International Competition in Computer Security
Team HSE has taken second place at RuCTF - a leading information security competition. The championship was held in Ekaterinburg on April 14-17, 2017. RuCTF (‘Capture the Flag’) is an annual open all-Russian interuniversity competition and conference on information security. The event has been held annually since 2008.

HSE Team Made it to Imagine Cup, International Student Project Competition, Finals

An  app developed by the Faculty of Computer Science student team has made it to the finals of the Imagine Cup 2017, an international student project technology competition. Together with the other two finalists from Russia, the HSE team will represent their country at the international finals in Seattle this summer, where they will compete for the $100,000 main prize.

Third summer school on "Machine learning in high energy physics"

From 17 to 23 July the third international school "Machine Learning in High Energy Physics 2017" (MLHEP 2017) will be held in the city of Reading, Great Britain. Within the framework of the summer school there will be lectures and seminars, which will demonstrate real examples of how modern technologies of machine learning allow us to give more precise answers to questions about the structure of our universe.