Mikhail Burtsev Email and Phone Number
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I am currently a Landau AI Fellow at the London Institute for Mathematical Sciences (LIMS). Prior to moving to the UK through the Global Talent Visa program, I served as the Scientific Director of the Artificial Intelligence Research Institute (AIRI), which is one of the largest AI research organizations in the CIS, employing over 120 researchers across more than 20 projects. At Moscow Institute of Physics and Technology (MIPT), I also lead the Neural Networks and Deep Learning Laboratory.In 2017, I founded the DeepPavlov project with the aim of creating an all-in-one conversational AI framework. This project has since become one of the most popular open-source libraries in its category, boasting over 6,000 stars on GitHub. I have also proposed and co-organized a series of academic Conversational AI Challenges (at NIPS 2017, NeurIPS 2018, EMNLP 2020, NeurIPS 2021, NeurIPS 2022), as well as eight summer schools since 2015.As a leader of a research group, I have co-authored over 100 scientific papers in the fields of artificial intelligence and machine learning, with a focus on natural language processing, reinforcement learning, and conversational agents. These papers have been published in well-recognized venues. Additionally, I have been invited multiple times to review research proposals for the European Research Executive Agency.At LIMS, I work on three research topics. The first topic is to build a theory and develop models for the open-ended emergence of more and more complex systems. The second topic focuses on modular representation to enable rapid learning and efficient search for solutions. The third topic involves training large DNA language models to understand the language of life and the patterns in DNA sequences.
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Landau Ai FellowLondon Institute For Mathematical Sciences Apr 2023 - PresentLondon, England, Gb -
Chief Science OfficerSentius Jul 2023 - PresentBelmont, Ca, Us -
Founder And LeaderDeeppavlov.Ai Jul 2017 - PresentDeepPavlov (DP) is an open-source framework to develop and deploy conversational assistants in production.Who are users of DeepPavlov?* Developers of multi-skill conversational agents and stand alone skills. Use DP to build and deploy production ready systems. Reuse and finetune existing components, skill templates and reference conversational agents. Contribute new skills and industry related features to the DP.* Researchers working in the area of Conversational AI. Use DP to experiment with new ideas for Conversational AI. Reuse referent agents to save time on implementation of infrastructure for dialogue task, and reuse basic models to create new architectures. Contribute new models for conversational functions.
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Scientific DirectorAiri Jun 2021 - Dec 2022Москва, Москва, RuPrior to foundation of the AIRI designed core organizational principles, after establishment of the institute worked on a mission and key goals. Set up internal science board. Designed and implemented research procedures for internal scientific projects including proposal structure, submission and evaluation by internal science board. Interviewing key employees out of total 90 research staff. Review of more than 25 research project proposals. Development of AIRI’s basic research strategy which was successfully approved by external science advisory board. -
Head Of Neural Nets And Deep Learning LabMoscow Institute Of Physics And Technology (Mipt) Dec 2015 - Dec 2022Dolgoprudniy, Moscow Region, RuSet up and run lab currently including of 3 postdocs, 10 PhD students, 5 MS students, 3 BS students, 5 software engineers, 4 administrative staff. Started development of open-source conversational AI framework DeepPavlov. DeepPavlov has about 360 000 pip installs over 4 years with current monthly download rate of 15 000. DeepPavlov was recognized as one of the winners of Google’s “Powered by TF challenge” and selected as organization included in the Google Summer of Code 2021 program. Lab was selected as NVIDA and Facebook academic partner in 2016-2017. Supervised team of PhD and MS students who participated in Amazon Alexa 3 and 4 Challenges (supported by $500K funding from Amazon). In 2021 lab won the Read//able UpGreat Prize (about $1 mln.) for the human level teacher like proof-reading and commenting of high school essays. -
Remote EvaluatorEuropean Research Executive Agency (Rea) Jun 2021 - Jul 2021Brussels, BeReview of three research projects for European Innovation Council and Small and Medium-sized Enterprises Executive Agency (EISMEA). -
Lead OrganizerThe Conversational Intelligence Challenge Apr 2018 - Dec 2018ConvAI2 NeurIPS competition that aims to further the state-of-the-art in open-domain chatbots. Some key takeaways from the competition are:(i) pretrained Transformer variants are currently the best performing models on this task,(ii) but to improve performance on multi-turn conversations with humans, future systems must go beyond single word metrics like perplexity to measure the performance across sequences of utterances (conversations)--in terms of repetition, consistency and balance of dialogue acts (eg how many questions asked vs. answered).
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Lead Organizer1St Nips Conversational Intelligence Challenge (Convai.Io) Apr 2017 - Dec 2017The first Conversational Intelligence Challenge ( convai.io/2017 ) was conducted over 2017 with finals at NIPS conference. The challenge aimed at evaluating the state-of-the-art in non-goal-driven dialogue systems (chatbots) and collecting a large dataset of human-to-machine and human-to-human conversations manually labelled for quality. We established a task for formal human evaluation of chatbots that allows to test capabilities of chatbot in topic-oriented dialogue. Instead of traditional chit-chat, participating systems and humans were given a task to discuss a short text. Ten dialogue systems participated in the competition. The majority of them combined multiple conversational models such as question answering and chit-chat systems to make conversations more natural. The evaluation of chatbots was performed by human assessors. More than 1,500 volunteers were attracted and over 4,000 dialogues were collected during competition. Final score of the dialogue quality for the best bot was 2.746 compared to 3.8 for human. This demonstrates that current technology allows supporting dialogue on a given topic but with quality significantly lower than that of human. To close this gap we plan to continue the experiments by organising the next conversational intelligence competition. This future work will benefit from the data we collected and dialogue systems that we made available after the competition.
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Author Of Idea And Chief Organizer Of Ai School-HackathonRl.Deephack.Me Feb 2017 - Feb 2017The school-hackathon http://RL.DeepHack.me had the task of improving performance of DNN RL algorithms on those Atari games where deep learning approaches still demonstrate subhuman performance. Leading scientists working in the field of reinforcement learning including Andrew Barto and Doina Precup gave talks to eight teams totaling 47 hackers participated in the event.Video of the final match - https://youtu.be/Hq2dVKviowILeaderboard http://deeprl.tilda.ws/page95443.htmlDeepHack.RL is distinguished from similar events which set practical goals by its emphasis on scientifically useful results applicable to AI algorithm development. Side by side with the coding challenge, a science school offered lectures by leading specialists in the field of machine learning, which were attended by over 300 people.
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Senior Research ScientistKurchatov Nbic-Centre Jan 2011 - Jan 2017Department of Neuroscience, Kurchatov NBIC Centre, Moscow, RussiaDesigned and launched cell culture laboratory equipped with multi-electrode system for recording and stimulating activity of neurons in vitro. Supervised experiments to study learning in networks developed from primary hippocampal cultures of mice neurons. Simulation of biologically plausible neural networks to model learning in vitro. Proposed novel neuroevolutionary methods.
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Author Of Idea And Chief Organizer Of Ai School-HackathonQa.Deephack.Me Feb 2016 - Feb 2016Winter deep learning school-hackathon Deephack Q&A ( http://qa.deephack.me/ , talks areavailable at https://goo.gl/nQ49MS ). People from DeepMind (Phil Blunsom), OpenAI, FAIR, Google, NYU, and Stanford University gave talks to more than 50 participants who have been hacking the Kagglechallenge on the 8th grade test questions answering.
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Vice Chair Of Expert PanelEuropean Commission Nov 2015 - Jan 2016Vice Chair of ICT Panel for the Horizon 2020 Future and Emerging Technologies (FET) projects.Remote work consisting of cross-reading FET Open proposals and Individual Evaluation Reports (IERs) resulting from the remote evaluation. Meeting in Brussels for the final panel review. Acting as Rapporteur for a set of about 10 FET OPEN RIA proposals and as Crossreader in the panel discussion for another set of about 30 proposals.
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Senior ResearcherAnokhin Institute Of Normal Physiology Rams 2006 - 2013
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ResearcherKeldysh Institute Of Applied Mathematics Dec 2000 - Dec 2011
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Senior Academic VisitorWolfson College Cambridge Mar 2008 - May 2008Host prof. Patrick Bateson
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Senior Academic VisitorWolfson College Cambridge Mar 2007 - May 2007Cambridge, GbHost prof. Patrick Bateson
Mikhail Burtsev Skills
Mikhail Burtsev Education Details
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Keldysh Institute Of Applied MathematicsComputer Science -
Santa Fe InstituteComplex Systems -
Moscow Power Engineering Institute (Technical University)Microelectronics
Frequently Asked Questions about Mikhail Burtsev
What company does Mikhail Burtsev work for?
Mikhail Burtsev works for London Institute For Mathematical Sciences
What is Mikhail Burtsev's role at the current company?
Mikhail Burtsev's current role is Landau AI Fellow.
What is Mikhail Burtsev's email address?
Mikhail Burtsev's email address is mbur@ya.ru
What schools did Mikhail Burtsev attend?
Mikhail Burtsev attended Keldysh Institute Of Applied Mathematics, Santa Fe Institute, Moscow Power Engineering Institute (Technical University).
What are some of Mikhail Burtsev's interests?
Mikhail Burtsev has interest in Science And Technology.
What skills is Mikhail Burtsev known for?
Mikhail Burtsev has skills like Machine Learning, Computer Science, Algorithms, Mathematical Modeling, Artificial Intelligence, Neural Networks, Science, Research, Programming, Artificial Neural Networks, Data Mining, Reinforcement Learning.
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