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mipt.ruPage of school
Phystech-school of applied mathematics
and computer science (PSAMCS)
Moscow Institute of Physics and Technology
“Мathematics is beautiful not because of its applications. It is beautiful in and of itself! But this is precisely why it has so many applications” © Andrey Raigorodskii
Director of Phystech-School of Applied Mathematics and Computer Science,Head of Discrete Mathematics Department, Head of the Laboratory of Advanced Combinatorics and Network Applications,Head of the Laboratory of Applied Research MIPT-Sberbank
PSAMCS is a synergy of education, science and industry
Practice-based education
Department of Control and Applied Mathematics
Department of Innovation and High Technology
mipt.ru/diht/
mipt.ru/dcam/
Key research areas: IT и Data Science
Key research areas: Mathematical modelling, programming, data mining, optimization and control
During their 3rd and 4th years, students simultaneously study at the MIPT and at the chosen base department, of which there are two types: • Joint with leading research
institutes of Russian Academy of Science (RAS): ISP RAS, MI-RAS, FRCCSC of RAS, IITP RAS, INM RAS, IAM of RAS nm. Keldysh, ISR RAS, etc.
• Industrial base departments in cooperation with top IT companies: Yandex, SberBank, ABBYY, 1C, Acronis, Tinkoff, RVC, S7, Smart Engines, RUSNANO, GosNIIAS, RANEPA, etc.
PSAMCS
PSAMCS makes it possible for students and graduates to work in its research and industrial laboratories located on campus.
Labs are divided into 4 categories:• Industrial cooperation labs are open
to projects in their research areas from all external partners
• Laboratories of fundamental mathematics are for conducting math-related research and they are also open to scientific and industrial partners.
• Labs of mathematical modelling in physics are used mostly in grant research
• Joint labs with companies carry out their own projects
PSAMCS was created on the basis of two faculties: DCAM and DIHT with their own mathematical and IT subjects.
Now the school consists of five departments:• Department of Discrete Mathematics• Department of Algorithms and
Programming Technologies• Department of Theoretical and
Applied Problems of Innovation• Department of Mathematical
Foundations of Control• Department of Analysis of Systems
and Decisions
These departments lead their own subjects in fundamental mathematics and programming and distinguish PSAMCS from other schools.
Education Research and projects in labs
PSAMCS covers key areas of mathematics, programming, mathematical modelling and data science
Department of Mathematical
Foundations of Control
Department of Theoretical and Applied Problems of Innovation
Department of Algorithms and Programming Technologies
Department of Discrete Mathematics
Department of Analysis of Systems and
Decisions
● Combinatorics● Mathematical logic● Discrete analysis● Introduction to data
science● Computational
complexity● Mathematical
statistics● Geometry in
programming applications
● Dynamic systems● Statistical methods
in econometrics● Graph theory● Random graphs● Combinatorial
geometry● and more
● Abstract algebra and coding theory
● Data bases● Probability theory● Computational
models● Formal systems● Convex and
discrete optimization● Stochastic
processes● Methods of optimal
control● Differential geometry ● Applied statistics● and more
Programming on:● C++● Python● Java
Subjects:● Algorithms and data
structures● Machine learning● Applied data
analysis● Software design● Parallel
programming● Object-oriented
programming practices
● System programming
● and more
● Infrastructure of innovation support
● Mathematics and software of VR-systems
● Neural networks● Basics of data
transfer and storage infrastructure
● Technological projects management
● Patent law● Intellectual property
management● and more
● Mathematical models in economy
● Game theory● Experimental
economy● Decision support
systems● Mathematical control
theory● System analysis in
market economy● Mathematical
models● Ergodic theory● and more
PSAMCS laboratories1) Machine intelligence laboratory 2) Cognitive Modeling Center:
a) Cognitive dynamic systemsb) Intellectual transport laboratory
3) Neural networks and deep learning4) Laboratory of numerical methods of applied structural optimization5) Hybrid intellectual systems 6) Laboratory of applied research MIPT-Sberbank7) Innovation lab (additional professional education for companies)8) Laboratory of advanced combinatorics and network applications9) Laboratory of combinatorial and geometric structures
10) Experimental economy lab11) Modelling of nonlinear processes laboratory12) Laboratory of applied and computational geophysics13) Mechatronics and robotics laboratory14) Fluid dynamics and seismo-acoustics laboratory 15) Laboratory of Artificial Intelligence of VK16) Laboratory of fundamental research MIPT-Yandex17) Computer vision and natural language processing laboratory (ABBYY)18) Financial technologies laboratory (Tinkoff)19) Digital business laboratory (1C)20) Data analysis and recommendation systems development lab (Russian Agricultural Bank)
Joint labs with companies
Laboratories of fundamental mathematics
Labs of mathematical modelling in physics
Industrial cooperation labs
Head: Konstantin Vorontsov Professor of RAS, Doctor of physical and mathematical Sciences, head of Intelligent Systems department.
Deputy Head: Alexey GoncharovHead of research teams, postgraduate MIPT.
Site: http://machine-intelligence.ru
The team works on general research-oriented AI projects and carries out client-specific tasks. The research process based on our methodology allows us to achieve results quickly and efficiently.
Research interestso Deep Learning: compression, architecture optimisation
o NLP: Topic Modelling, Knowledge Graphs and Language representation models
o Computer Vision: Image-to-Image tasks, Video processing
o Time series: wearable devices, signal processing
Achievementso Open-source framework TopicNet for automation of TopicModelling
o Open-source framework BigARTM for TopicModelling
o 16 completed projects
o 27 scientific publications and speeches at conferences
Teamo Core team: 4 Scientific consultants, 16 Researchers and 5 Assistants
o Contractor researchers: up to 17 researchers
o Internship program: up to 10 interns
• Contact center dialogues tagging and clustering• News feed rubrication• Internet user activity analysis• Retail bank customer profiling• Documents recognition and classification• Topic replicas in contact center dialogs• Template documents recognition• Biomedical signal analysis• Neural network architectures comparison models• Client profiling• 2D indoor navigation by IMU-sensors• Audio noise reduction
Completed projects
Partners
Machine Intelligence Laboratory
Head of the Center: Aleksandr I. PanovPhD, Associate Professor, Member of the Scientific Council of Russian Association of Artificial Intelligence
Site: https://cogmodel.mipt.ru
Scientific interests
Computer cognitive modelingo Behavior planning for robotic coalitionso New neuromorphic architecture of neural networkso Reinforcement learning
Natural language processingo Semantic and syntactic text analysiso Information extraction from text messageso Cognitive assistant
Intelligent agent auto navigation methodso Simultaneous mapping and localizationo Path planning in space
Computer Visiono Segmentation, classification, detection, tracking of objects on imageso Computer vision for unmanned vehicles mobile robots
Team consists of 35 researchers (5 advisors, 10 PhD students and 30 students)
• Biologically plausible learning algorithms• Cognitive assistants• Hierarchical reinforcement learning• Computer vision for mobile robots• Theory of the sign-based world model• Mapping and localization• Road scene recognition• Re-identification of objects, tracking and
trajectory prediction• Analysis of orthophotoplans and 3D terrain
models• Path planning and behaviour-planning tasking
of mobile robots• Visual Question Answering
Projects
Center for Cognitive Modeling (consists of 2 laboratories:laboratory of cognitive dynamic systems and intelligent transport lab)
Partners
Head: Mikhail BurtsevPhD in Physics and Mathematics, Head of DeepPavlov.ai,Head of Neural Networks and Deep Learning Lab
Project site: deeppavlov.ai
The Neural Networks and Deep Learning Laboratory at MIPT researches deep neural network architectures for working with text in natural language. Since June 2017, the main activity of the laboratory has been implementation of the DeepPavlov (DP) project.
Research and Development
o Research in Machine Learning, Language Model Development
o Development of open-source DP Library for building dialogue systems. It comes with several predefined components for solving NLP problems and a framework to build a modular pipelines
o Development of open-source framework DP Agent for building interactive agents that orchestrate different conversational skills to address a wide spectrum of user tasks
o Development of open-source DP Assistant for a production-ready multi-skill virtual system Assistant combines skills from Library and orchestrate it by Agent.
Achievements
o 2019 Amazon grant “Alexa Prize Socialbot Grand Challenge 3”
o 2019 Best Open-Source Project (ODS community vote)
o 2019 won Google competition “Powered by TF Challenge”
o 2016 won Facebook grant
o 2016 status “NVIDIA GPU Research Center”
o over 60 scientific publications and speeches at conferences
Team - core team: 30 scientists (including 4 masters and 8 PhD students).
• DeepReply – a technology platform for creating interactive agents and services (Sberbank)
• Implementation of a component for creating a Chatbot in the Intersvyaz mobile app
• Documentation Automated Answering System• Customer Feedback Tagging System for Dodo
Pizza• Routing and Fault Classification System• Intellectual Assistant in Legal Support
Completed projects
Neural Networks and Deep Learning Laboratory (DeepPavlov.ai)
Partners
Projects
Head: Yuri G. EvtushenkoProfessor, academician of RAS, Doctor of physical and mathematical Sciences,
Site: https://mipt.ru/education/departments/fpmi/labs/laboratory_NuMASO_eng.pdf
• Traffic distribution problems • Computer networks simulation • Inverse problems of mathematical physics• Optimal management in metallurgy• Robotics: working environment approximation
Partners
Laboratory of Numerical Methods of Applied and Structural Optimization
Mission of the laboratory is solving hard practical optimization problems and carry out state-of-the-art research in optimization theory and methods.
Research interests and research areas:o Structural optimization
o Numerical methods for local and global optimization
o Multicriteria optimization
o Non-convex and non-smooth optimization
o Problems of linear and nonlinear,
semidefinite and equilibrium programming
o Numerical methods of optimal control
o Stochastic optimization
o High-performance optimization techniques
o Distributed optimization
Team consists of 20+ researchers (including 8+ Dr.of Sciences and 5+ PhDs)
Competencies:o Machine Learning
o Traffic assignment problems
o Computer networks modeling
o Inverse problems of mathematical physics
o Optimal Control in the Foundry Industry
o Global Optimization
o Robotics: Approximation of the Robot’s workspace
o Fast Automatic Differentiation
o Non-linear analysis and its applications
o Software Framework
o Software Development
Projects
No-cashiers store:• Goods detection and tracking in the
real-world conditions• Human pose identification, re-identification
and tracking, action detection
Other:• Methods for image normalization and
preprocessing for domain-invariant learning• Development of the production-ready
machine learning systems with automated error correction and online-learning
Partners
Laboratory of Hybrid Intelligent Systems was created to develop complex systems comprising of heterogeneous sub-systems and algorithms to solve applied real-world problems.
Our main project is “No-cashiers store”. The system is being developed in partnership with Neurus Lab for Vkusvill to build stores with new user experience and effective labor costs management.
HIS Lab develops algorithms with a pre-defined cost-to-value for a wide spectrum of tasks: from generating photorealistic speakers from text script to algorithms for active noise suppression and 3D object localization.
Scientific interestso Shallow and deep machine learning
o Edge-computing
o Heuristic methods
Hybrid Intelligent Systems Laboratory
Current teamo 7 permanent engineers/data scientists
o 10 temporary/project-based engineers/data scientists
o 3 invited experts (for individual projects)
Scientific Advisor: Boris GoldengorinDoctor of physical and mathematical Sciences,Professor of Operations Research, visiting professor, University of Baltimore
Head: Samosyuk AlexeyTeam leader, postgraduate MIPT
Site: https://neuruslab.ru
Projects● Analysis of logs of various information
systems for security● Novel biometry and Liveness Detection● Semantic Requirement Management System● Smart-Grid Flexibility Control System● Intelligent IoT routers for monitoring and
control● Researching the possibility of searching for an
insider among employees who have legal access to Big Data
● Fraud detection in credit applications
Partners
Laboratory consists of researchers, engineers and students from different universities. Our main
research area of interest is the analysis of big graph models, including telemetry/time-series data
linked to semantic graphs and different cybersecurity applications including biometry and liveness
detection methods and data analysis for countering cyber threats. With such an integration of
telemetry data streams and semantic graph models we strive to improve the quality of decision
making and the degree of automation in organizations.
We are doing R&D in methods and instruments for the whole data lifecycle: from data collecting,
ingesting, curating and integrating to analysis, anomaly detecting and labeling of time-series and
graph data and to producing recommendations for users and designing complex information systems
with web-interface and big-data storage.
Research Areas:o Biometric authentication and liveness detection with video-stream processing
o IoT and multiagent infrastructure for Smart-Grid flexibility control
o Intelligent systems for recording and analyzing security events with user behavior analytics
o Models of complex graph structures like ‘credit factory’
o Ontological modelling and novel web-interfaces technologies for linked-data systems
o
Laboratory for Applied Research at MIPT-Sberbank
Head: Andrey RaigorodskiiDoctor of physical and mathematical Sciences, Professor
Deputy Head: Sergey TreninLead engineer, project leader
Site: mipt.ru/science/labs/mipt-sberbank-applied-research/
Laboratory provides further education and corporate training in companies. Today, it can offer more than 70 courses at Sberbank University and Bank of Russia.
Corporate training and further education for companies in the following areas:o Data mining and machine learning
o Natural language processing
o Time series analysis
o Deep learning and neural networks
o Advanced combinatorics
o Machine learning for product owners
o Retraining program Reboot: Data Science, Data Analytics and Data Engineering
o Stand-alone courses: Big Data, ETL processes, SQL for Data Science
Organization of Hackathons, including:
o Image Inpainting Online Hackathon (2019) with Huawei - 113 teams and 3 winners
o Birth Hack (2018) with S7 Airlines and 1C
o And other 6 hackathons
Organization of courses and competitions: o Deep Learning School - practical online courses for neural networks (3000 students/year)
o Olympiad of National Technological Initiative
o Math and DS tracks in olympiad “I-Profi”
o
Innovation Laboratory
Partners
• Business Process Management• Optimization of potential customers selection
process (Tinkoff)• Development of a methodology for calculating
coefficients of a credit scoring model (Tinkoff)• Effective search for teams for R&D projects
(Tinkoff)
Projects
Head: Evgeny Blagodarny Laboratory head, postgraduate MIPT.
Site: https://mipt.ru/science/labs/innovation/
Head: Andrey RaigorodskiiDoctor of physical and mathematical Sciences, Professor, head of Discrete Mathematics DepartmentSite: mipt.ru/education/chairs/dm/laboratoriya-prodvinutoy-kombinatoriki-i-setevykh-prilozheniy/
• Random graphs and hypergraphs: models and applications for information search and analysis of complex networks such as the Internet, social networks, interbank interaction networks, other economic networks, and biological networks
• Classification of exchange-traded strategies based on expected returns
• First-and second-order logic of a random Erdös-Renyi graph
• Combinatorics of words, symbolic dynamics and its applications in the theory of rings and semigroups
Projects
Laboratory of Advanced Combinatorics and Network Applications
Research interests and research areaso Probabilistic, algebraic and topological methods in combinatorics
o Graph theory, web graphs, algorithms on graphs
o Discrete optimization
o Algorithms and complexity of calculations
o Fundamental research and practical applications of discrete mathematics
o Discrete functions and optimization
o Combinatorics of words
o Symbolic dynamics
o Random graphs and hypergraphs
o Mathematical modeling and optimization of complex processes and structures
Team consists of 30+ researchers including 6 Dr.of Science and 8 PhD, among those 3 foreign members
Partners
Head: Janos Pach (curriculum vitae)Doctor of physical and mathematical Sciences, professor of Alfréd Rényi Institute of Mathematics, Invited Speaker at the ICM, Seoul(2014), Member of Academia Europaea(2014), AMS Fellow (2015)
Grants
Laboratory of Combinatorial and Geometric Structures
Team consists of 30 researchers including 6 Dr.of Science and 10 PhD, among those 7 foreign members
Partners
MegaGrant “Combinatorics, discrete and computational geometry, and analysis of complex data structures”.
Funded by Russian Foundation for Basic Research, Presidential Grant programs, etc.
o J. Fox, J. Pach, A. Sheffer, A. Suk, J. Zahl, A semi-algebraic version of Zarankiewicz's problem, J. Eur. Math. Soc., 19 (2017), 1785-1810.
o M. Csikós, N. H. Mustafa, A. Kupavskii. "Tight Lower Bounds on the VC-dimension of Geometric Set Systems." Journal of Machine Learning Research 20, no. 81 (2019): 1-8.
o M.E. Zhukovskii, A.M. Raigorodskii, Random graphs: models and asymptotic characteristics. Rus. Math. Surveys, (2015) 70(1), p.33.
o Z. Jiang, A. Polyanskii, Proof of László Fejes Tóth’s zone conjecture. Geometric and Functional Analysis, (2017) 27(6), pp.1367-1377.
o Random Graphs and Hypergraphs
o Theoretical Сomputer Science
o Discrete Geometry
o Extremal Combinatorics
o Algebraic, Topological, and Probabilistic Methods
o Additive Combinatorics
o Computational Geometry and Topology
o Convex Geometry
Recent selected articles:
Research interests:
Our aim is to initiate collaboration between foreign and Russian researchers to study various problems in computational geometry and combinatorics as well as their applications.
See more: http://combgeo.org, Youtube, Facebook, Vk
• Analysis of the impact of socialization on decision-making in small groups
• Comparative analysis of behavioral concepts of equilibrium by methods of experimental Economics
• Research on the influence of gender and psychological characteristics on decision-making in the course of socio-economic interactions
• Research of the functional state of interaction participants in the decision-making process
Grants
Partners
Laboratory of Experimental Economics
The laboratory participates in scientific research and supports research done by masters and graduate students in game theory and decision making, experimental economics, neuroeconomics, as well as the psychophysiological aspects of decision making.
Research areas:
o Developing and conducting a course of experimental Economics based on active teaching methods
o Involvement of MIPT students and postgraduates in the creation and analysis of new laboratory games
o Behavioral Economics and the study of human interaction in the decision-making process using experimental Economics methods
o Neuroeconomics
o Psychophysiology of decision making
o Game theory and decision making
Hardware and software:
o Laboratory experiment support systems: zTree, oTree, FTS
o Hardware-software complex of 10 stabilographic seats
o Cardiac Sensors and Neuro Hoops
o Three computer labs equipped for laboratory games
Head: Alexander ChabanHead of laboratory
Laboratory website: labee.ru
Partners
History: the laboratory was created at MIPT in 2011 as part of the work in the framework of the Russian government grant “Measures to Attract Leading Scientists to Russian Educational Institutions” (contract No. 11.G34.31.0072).
Research interests:o Computational fluid dynamics and parallel computing
o Hypersonic aerodynamics and heat transfer, simulation of laminar-turbulent transition
o Numerical methods for hyperbolic conservation laws in general
o Hybrid methods for numerical simulation of turbulent flows based on domain decomposition
In-house software:
o Several fully parallel codes for modelling compressible gas flows taking into account real non-equilibrium physics, turbulence and transition;
o Codes are applicable to real-life geometries, such as full spacecraft with superstructures, and flow regimes at various altitudes
Resources:
o Two HPC clusters based on Intel 8-,12- and 26 core processors (in total more than 1300 cores)
o Academic versions of Intel Parallel Studio, ANSYS, Tecplot, Pointwise
Publications:
Results are published in top international journals, including Journal of Computational Physics, Computers & fluids, Journal of Fluid Mechanics, AIAA Journal, Journal of Computational and Applied Mathematics, Computer Physics Communications and others
Team consists of approximately 20 researchers
o ws which is used for industrial computations of real-life vehicle geometries taking into account non-equilibrium physical and chemical processes
Team consists of 15+ researchers (including 1+ Dr.of Sciences and 5+ PhDs)
Laboratory for Modelling of Nonlinear Processes
PartnersHead: Sergey V. Utyuzhnikov Doctor of physical and mathematical Sciences, Professor
Site: https://mipt.ru/science/labs/modeling_of_nonlinear_processes_lab/
• Fundamental research projects funded by Russian Science Foundation, Russian Foundation for Basic Research, Presidential Grant programs, etc
• Industrial cooperation with NPO Lavochkin and Russian Space corporation “Energia”, including long-term contract (years 2016-2023) on the study of “Orel” reusable crewed spacecraft.
Projects
Director: Michael S. ZhdanovDoctor of physical and mathematical Sciences, Professor
Site: mipt.ru/science/labs/applied_computational_geophysics_lab/
• Development of new methods for three-dimensional numerical modeling of harmonic fields in problems of exploration geophysics
• Development of a software package for supercomputers for solving problems of seismics taking into account the dynamics of destroyed material
Projects
Laboratory of Applied Computational Geophysics
The main task of the laboratory is to conduct advanced research and develop methods of geophysical research based on innovative methods of numerical modeling and solving inverse problems of geophysics and high-performance computing systems.
Research direction:
o Development of methods for large-scale numerical modeling of geophysical fields in complex heterogeneous geological environments
o Development and improvement of elastic migration methods
o Development of new computer technologies for solving inverse geophysical problems for geological structures with clear boundaries (for example, an oilfield)
o Solving problems to improve the accuracy of seismic and electromagnetic modeling of seismic and electrical exploration tasks
o Development of innovative integrated methods of geophysical exploration
Team consists of 15+ researchers (including 3+ Dr.of Sciences and 7+ PhDs)
Partners
Head: Alexey BorisovDoctor of physical and mathematical Sciences
Deputy Head: Sergei SokolovDoctor of Physical and Mathematical Sciences, head of Theoretical Mechanics Department
Website of the laboratory: mipt.ru/science/labs/mechatronics-and-robotics
• Development of optimal control algorithms for a highly maneuverable omni-wheel mobile robot and their experimental verification
• Development of pendulum-like actuated spherical robot.
Projects
Mechatronics and robotics laboratory
Research areas:
o Theoretical robotics (mobile robotics)
o Optimal control theory and sub-Riemannian geometry (including experimental studies of rolling bodies as an example of model task for constructing a dynamic friction model that is most suitable for describing the movement of systems in real conditions)
o Nonholonomic mechanics
o Integrable Systems
o Highly maneuverable robotic platforms with rolling elements: spherical robot, omni-wheel mobile robot, multi-link wheeled robot
Achievements:
o RFBR grant for Interdisciplinary Complex Investigations
o More than 20 scientific publications and conference talks
Hardware and software of laboratory includes robotic complex and the motion-capture system
Team consists of 15+ researchers (including 3+ Dr.of Sciences and 7+ PhDs)
Partners
Head: Koldoba Alexander VasilyevichDoctor of physical and mathematical Sciences, Professor
Site: mipt.ru/science/labs/fluid_dynamics_and_seismo_acoustics_lab/
● Adaptive electro-hydraulic servo system with modulated oscillation
● The two-dimensional thermohydrodynamic simulation of multiphase multicomponent flows
Projects
Laboratory of fluid dynamics and Seismo-Acoustics
The laboratory team is engaged in modern computational tasks of oil exploration and development of hydrocarbon deposits. Currently, the efforts of the laboratory are concentrated in two main areas: vibration and thermal gas effect on oil-bearing strata.
Research areas:
o Seismics: the problem of calculating the propagation of acoustic waves in a solid medium under external mechanical influence
o Filtration: modeling of hydrodynamic processes inside the reservoir, numerical integration of equations of hydrodynamics of porous media, taking into account heat transfer, phase transformations and chemical reactions
o Mathematical modeling of heavy oil production intensification technologies using thermal and chemical methods of impact on the reservoir
Partners
Laboratory of Artificial Intelligence of VK
Joint lab with VK.com was founded in 2019. Projects are tailored to business needs of VK. Research interestso Natural Language Processing
○ Text generation and repetition removal
○ Natural Language understanding
○ Curriculum learning
o Neural networks compression
o Recommendation models in neural networks
o Computer vision
o Graph embeddings
o Curriculum and progressive learning• Multi-representation approach to text regression
of financial risks• Self-attentive model for headline generation• BERT Compressing• Iterative graph embedding construction
Projects
CompanyHead: Pavel KalaidinHead of Applied Research Team at VK.com
Website mipt.ru/science/labs/machine-intelligence/
CompanyHead: Artem BabenkoHead of Yandex Research division, PhD
The Yandex research laboratory was created in cooperation with the Yandex Research department. Yandex Research and the Yandex laboratory at MIPT focus on fundamental scientific challenges in core areas of computer science and AI including:
o Natural Language Processing and Machine Translation
o Web Mining, Search and Recommendations
o Speech Technologies
o Computer Vision
o Machine Learning
o Crowdsourcing
Being constantly presented at the top conferences (such as NIPS, ICML, SIGIR, WWW, WSDM, KDD, ACL, CVPR, ICCV, ECCV etc), members of Yandex Research also frequently join their efforts with other teams helping to significantly improve Yandex products and services. It also has tight collaborations with leading research groups worldwide, including universities of Oxford, Amsterdam, and Edinburgh.
Laboratory of Fundamental Research of MIPT-Yandex
• Unsupervised visual understanding
• Interpretability of image generative models
• Distributed learning of huge-scale ML models
• Uncertainty estimation in large-scale NLP systems
• Representation Learning
Projects
Computer Vision and Natural Language Processing Laboratory (ABBYY Lab)
The laboratory was founded at the end of 2019 together with ABBYY.
ABBYY Lab conducts research aiming to solve a wide range of tasks of computer vision and
natural language processing with possible application for document understanding.
Ongoing research includes the following areas:
o Comprehensive recognition (handwritten/scene text)
o Color physics and its application
o Video generation
o Topic-agnostic text classification
o Social media language understanding
o Text landmarks detection
o Multi-modal interaction
o Differentiable algorithms
o Neural architecture search
o Semi-supervised, unsupervised, few-shot learning
Team:
The laboratory has 10 employees, including one Doctor of Science and two PhDs.
Head: Alexandr ZhukovskiHead of Computer Vision Research Group in ABBYY Lecturer at MIPT
Website of the laboratory: mipt.ru/science/labs/abbyy-lab
Company
● webcorpora.ru – The General Internet-Corpus of Russian (2e10+ words)
● Social media language understanding● Neural architecture search for end-to-end
text recognition● Hierarchical neural networks for many-class
classification● Style vector-controlled data augmentation for
handwritten text recognition● Synthesis of realistic text-based video agent
with fixed style
Projects
Financial technologies laboratory (Tinkoff)
Joint lab with Tinkoff Bank is engaged in research of Artificial Intelligence for company needs.
Research Areas:
o Data Analysis
o Recommender systems
o Natural Language Processing
o Computer Vision
o Voice Recognition
Head: Anna AndreevaTinkoff Head of ML-products
Site: fintech.tinkoff.ru/study/academy/mipt_lab/VKontakte group: https://vk.com/fintech.tinkoff
Company
● Speech-to-video● Lip reading● Voice activity detection● Voice conversion● Experiments with the language model● Randomized language models● OCR through segmentation● Delivery market analysis● Geography of deliveries
Projects
1C Digital Business LaboratoryHead: Nikita StarichkovDeputy head of Corporate Informations Systems Department, developer in 1С
Site: https://mipt.ru/science/labs/1c-digital-business/
The main objective of the lab is to design and develop advanced technologies in the sphere of business automation.
Current laboratory projects are related to the topics of data visualization, modeling of complex processes in economics, development of augmented reality technologies and etc.
Laboratory is closely connected with Corporate Informations Systems Department - bachelors and masters base department of PSAMCS.
Research areaso Data science in applied problems
o Forecasting in economy
o Computer Vision
o Time Series analysis
o Natural Language Processing
o AI for business needs
o Traffic modelling
o Virtual Reality and Augmented Reality
Company
• Anomaly and outliers detection• Time Series Analysis in corporate systems• Augmented reality on the production line• Automatic selection of data visualization tools• Finding data dependencies
Projects
Data Analysis and Recommendation Systems Development Lab
Head: Alexey GoncharovHead of research teams, postgraduate MIPT.
Joint laboratory organized in 2020 with Russian Agricultural Bank to solve problems in the agricultural marketplace platform. All work is about building prototypes and Natural Language Processing models.
Research areaso Search in text descriptions with domain specific vocabulary
o Customer and operator speech interaction automation
o Insult detection
o News aggregation
o Financial adviser
Company
IndustryPSAMCS Partners
Science
Opening a base department or joint laboratory
To become part of MIPT ecosystem, company should open a subdivision in MIPT based in PSAMCS. Two different possible forms are available: base department (education) and joint laboratory (research work).
Common features
Base Department“Phystech-system” lean on education on base departments - when industrial companies or research institutes are heavily involved in educational process of MIPT and sharpen students for their requests.Organizations with base departments: Yandex, Tinkoff, Sberbank, 1C, ISP RAS, S7 Group, ABBYY, Acronis, IITP RAS, FRCCSC RAS and etc.
● Centralized project and student coordination through this unit● Faster and easier contract signing process, no problems with negotiations with MIPT ● Easy access to all MIPT students and alumni● Possibility to organize and PR own events on the MIPT campus like a base department● Free participation in huge events like Career Day, PSAMCS Day and etc
Features● Organization of the educational process through the creation of a
curriculum (masters only or bachelors + masters)● Teaching 15+ students every year on that curriculum with 3-5
subjects per semester● Students have “base days” - when they study and work in company● Student diplomas are based on research work in your department
(which is connected with your company)
Features● Joint lab is more flexible unit than big R&D department in company
and it takes less time for it to test hypotheses and write articles● Possibility to form a research group from MIPT students and
alumni ● Students works 20+ hours per week in labs● Lab is located on the MIPT campus (convenient for students)
Joint LaboratoryLaboratory is an edge that connects science and industry in bipartite graph of PSAMCS. It is an R&D subunit of MIPT which allows to carry out projects of your company by MIPT students. Organizations with laboratories: Yandex, Tinkoff, Sberbank, 1C, VK, Gazprom Neft, VkusVill, ABBYY, Russian Agricultural Bank and etc.
