Ilya Makarov

Senior Lecturer:Faculty of Computer Science / School of Data Analysis and Artificial Intelligence

Ilya Makarov has been at HSE University since 2011.

Education

2015
Doctoral programme
Lomonosov Moscow State University, Mechanics and Mathematics
2011
Degree in Mathematics
Lomonosov Moscow State University, Mechanics and Mathematics

Continuing education / Professional retraining / Internships / Study abroad experience

2018 Department of Computer Science, UCL

2015 Istanbul University, 5th Universal Logic School

2012 Technologies of Blended and Online Learning

Professional Interests

functions of three-valued logic Klein polyhedron Game Artificial Intelligence

Research interests

Artificial Intelligence:

Network Science: graph embeddings for machine learning problems on graphs; large-scale recommender systems
Computer Vision: image and video super-resolution (including multi-frame and HDR), semantic segmentation, pose estimation, action recognition, etc.
Augmented Reality: depth reconstruction from low-resolution depth sensor and/or RGB; virtual fashion; video games in AR
Virtual Reality: solving the problem of infinite locomotion in limited physical area
Computer Animation: improving graphics in old video games by image-to-image translation; synchronization of two-dimensional face animation for video live news
Autonomous vehicles: path planning, machine vision, three-dimensional scene reconstruction
Game Artificial Intelligence: game-design and game development of video-games in Unreal Engine 4

Other areas:

Discrete Mathematics and Logic: finding finite total equivalence system for closed classes of many-valued logic; ontology-based data access and temporl logics
Number Theory: multi-dimensional integer geometry, multidimensional generalizations of continued fractions
Quantum Mechanics
Applied programming in physics equations

Awards and Accomplishments

Best Teacher – 2018, 2017

Young Faculty Support Program (Group of Young Academic Professionals)
Category "New Lecturers" (2013-2014)
Category "Future Lecturers" (2012)

Grants

Grant of Russian President MK-5016.2012.1 "Multim-dimensional Diophantine Approximations"

Grant of Russian Science Foundation 17-11-01294 "Knowledge Representation, Discovery and Processing: a Logic-based Approach"

Publications⁶³

Article Makarov I., Kiselev D., Nikitinsky N., Subelj L. Survey on graph embeddings and their applications to machine learning problems on graphs // PeerJ Computer Science. 2021. Vol. 4. P. 1-40. doi
Chapter Anna Averchenkova, Alina Akhmetzyanova, Sudarikov K., Stanislav Petrov, Makarov I., Pendiukhov M., Zhukov L. E. Collaborator Recommender System, in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics. Springer, 2020. doi P. 101-119. doi
Chapter Boris Tseytlin, Makarov I. Content Based Video Retrieval System for Distorted Video Queries, in: Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2020 (MACSPro 2020) / Ed. by Alexander Shapoval, V. Popov, I. Makarov. Vol. 2795. CEUR Workshop Proceedings, 2020. P. 99-107.
Chapter Ananyeva M., Makarov I., Pendiukhov M. GSM: Inductive Learning on Dynamic Graph Embeddings, in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics. Springer, 2020. doi P. 85-99. doi
Chapter Daniil Tikhomirov, Nikitinsky N., Makarov I. Named Entity Recognition from Chernobyl Documentaries, in: Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2020 (MACSPro 2020) / Ed. by Alexander Shapoval, V. Popov, I. Makarov. Vol. 2795. CEUR Workshop Proceedings, 2020. P. 133-139.
Article Dmitrii Maslov, Makarov I. Online supervised attention-based recurrent depth estimation from monocular video // PeerJ Computer Science. 2020. Vol. 6. No. e317. P. 1-22. doi
Chapter Kiselev D., Makarov I. Prediction of New Itinerary Markets for Airlines via Network Embedding, in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Kazan, Russia, July 17–19, 2019, Revised Selected Papers. Communications in Computer and Information Science Vol. 1086. Springer, 2020. doi P. 315-325. doi
Book Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2020 (MACSPro 2020) / Ed. by Alexander Shapoval, V. Popov, I. Makarov. Vol. 2795. CEUR Workshop Proceedings, 2020.
Chapter Makarov I., Daniil Chernyshev. Real-Time 3D Model Reconstruction and Mapping for Fashion, in: 2020 43rd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2020. doi P. 133-138. doi
Chapter Denis Zuenko, Makarov I. Real-Time Vehicle Type Detection and Counting from Road Camera Video, in: Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2020 (MACSPro 2020) / Ed. by Alexander Shapoval, V. Popov, I. Makarov. Vol. 2795. CEUR Workshop Proceedings, 2020. P. 92-98.
Article Makarov I., Kiselev D., Gerasimova O., Sulimov P., Zhukov L. E. Recommending Collaborators via Co-authorship Network Embedding // Network Science. 2020. P. 1-13. (in press)
Chapter Makarov I., Veldyaykin N., Maxim Chertkov, Alexei Pokoev. American and Russian Sign Language Dactyl Recognition and Text2Sign Translation, in: Analysis of Images, Social Networks and Texts. 8th International Conference AIST 2019. Springer, 2019. P. 309-320. doi
Chapter Makarov I., Veldyaykin N., Maxim Chertkov, Aleksei Pokoev. American and russian sign language dactyl recognition, in: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '19). NY : ACM, 2019. P. 204-210. doi
Chapter Зайнутдинова А. Р., Писаревская Д. Б., Zubov M., Makarov I. Deception Detection in Online Media, in: Proceedings of the Fifth Workshop on Experimental Economics and Machine Learning at the National Research University Higher School of Economics co-located with the Seventh International Conference on Applied Research in Economics (iCare7) / Ed. by D. I. Ignatov. Aachen : CEUR Workshop Proceedings, 2019. P. 121-127.
Chapter Ildar Kamaldinov, Makarov I. Deep Reinforcement Learning Methods in Match-3 Game, in: Analysis of Images, Social Networks and Texts. 8th International Conference AIST 2019. Springer, 2019. P. 51-62. doi
Chapter Ildar Kamaldinov, Makarov I. Deep Reinforcement Learning in Match-3 Game, in: Procedings of IEEE Conference on Games (COG'19). NY : IEEE, 2019. P. 1-4. doi
Chapter Dmitry Akimov, Makarov I. Deep Reinforcement Learning in VizDoom First-Person Shooter for Health Gathering Scenario, in: Proceedings of 11th International Conference on Advances in Multimedia (MMEDIA'19). Lansing : ThinkMind, 2019. P. 59-64.
Chapter Dmitry Akimov, Makarov I. Deep Reinforcement Learning with VizDoom First-Person Shooter, in: Proceedings of the Fifth Workshop on Experimental Economics and Machine Learning at the National Research University Higher School of Economics co-located with the Seventh International Conference on Applied Research in Economics (iCare7) / Ed. by D. I. Ignatov. Aachen : CEUR Workshop Proceedings, 2019. P. 3-17.
Article Makarov I., Gerasimova O., Sulimov P., Zhukov L. E. Dual network embedding for representing research interests in the link prediction problem on co-authorship networks // PeerJ Computer Science. 2019. P. 1-20. doi
Chapter Pavel Zolnikov, Zubov M., Nikitinsky N., Makarov I. Efficient Algorithms for Constructing Multiplex Networks Embedding, in: Proceedings of the Fifth Workshop on Experimental Economics and Machine Learning at the National Research University Higher School of Economics co-located with the Seventh International Conference on Applied Research in Economics (iCare7) / Ed. by D. I. Ignatov. Aachen : CEUR Workshop Proceedings, 2019. P. 57-67.
Chapter Alisa Korinevskaya, Makarov I. Fast Depth Map Super-Resolution Using Deep Neural Network, in: Proceedings of IEEE International Symposium on Mixed and Augmented Reality (ISMAR'18). NY : IEEE, 2019. P. 117-122. doi
Chapter Ildar Lomov, Makarov I. Generative Models for Fashion Industry using Deep Neural Networks, in: Proceedings of 2nd International Conference on Computer Applications & Information Security (ICCAIS). NY : IEEE, 2019. P. 1-6. doi
Chapter Gerasimova O., Makarov I. Higher School of Economics Co-Authorship Network Study, in: Proceedings of 2nd International Conference on Computer Applications & Information Security (ICCAIS). NY : IEEE, 2019. P. 1-4. doi
Chapter Gerasimova O., Makarov I. Link Prediction Regression for Weighted Co-authorship Networks, in: Advances in Computational Intelligence. IWANN 2019. Berlin : Springer, 2019. doi P. 667-677. doi
Chapter Makarov I., Dmitrii Maslov, Gerasimova O., Vladimir Aliev, Alisa Korinevskaya, Sharma U., Wang H. On Reproducing Semi-dense Depth Map Reconstruction using Deep Convolutional Neural Networks with Perceptual Loss, in: Proceedings of 27th ACM International Conference on Multimedia. NY : ACM, 2019. P. 1080-1084. doi
Chapter Makarov I., Gerasimova O. Predicting Collaborations in Co-authorship Network, in: Proceedings of the 14th International Workshop on Semantic and Social Media Adaptation and Personalization. NY : IEEE, 2019. P. 1-6. doi
Chapter Makarov I. Russian Freight Flights Time Prediction, in: Proceedings of 2nd International Conference on Computer Applications & Information Security (ICCAIS). NY : IEEE, 2019. P. 1-5. doi
Chapter Makarov I., Veldyaykin N., Maxim Chertkov, Aleksei Pokoev. Russian Sign Language Dactyl Recognition, in: 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). NY : IEEE, 2019. P. 726-729. doi
Chapter Rajput N. S., Deogune M., Mishra A., Kumar A., Makarov I. A Novel Autonomous Taxi Model for Smart Cities, in: Proceedings of 4th IEEE World Forum on Internet of Things WF-IoT 2018. NY : IEEE Computer Society, 2018. P. 625-628. doi
Chapter Makarov I., Gerasimova O., Sulimov P., Zhukov L. E. Application of Graph Embedding to Constructing Graph-based Recommender System, in: Proceedings of WebSci’18 Main Conference Poster Session. Aachen : CEUR Workshop Proceedings, 2018. Ch. 1. P. 1-2. (in press)
Chapter Makarov I., Gerasimova O., Sulimov P., Zhukov L. E. Co-authorship Network Embedding and Recommending Collaborators via Network Embedding, in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science / Ed. by W. M. van der Aalst, V. Batagelj, G. Glavaš,, D. I. Ignatov, M. Khachay, O. Koltsova, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch,, A. Napoli,, A. Savchenko, A. Panchenko,, P. M. Pardalos, M. Pelillo,. Vol. 11179. Berlin : Springer, 2018. doi P. 32-38. doi
Chapter Kostyakova Nadezhda, Karpov I., Makarov I., Zhukov L. E. Commercial Astroturfing Detection in Social Networks, in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics Vol. 247. Springer, 2018. doi P. 309-318. doi
Chapter Makarov I., Alisa Korinevskaya, Vladimir Aliev. Fast Semi-dense Depth Map Estimation, in: Proceedings of the 2018 ACM ICMR Workshop on Multimedia for Real Estate Tech. NY : Association for Computing Machinery (ACM), 2018. P. 18-21. doi
Chapter Makarov I., Diana Polonskaya, Anastasia Feygina. Improving Picture Quality with Photo-Realistic Style Transfer, in: Proceedings of 15th International Conference, ICIAR 2018, Póvoa de Varzim, Portugal, June 27–29, 2018. Berlin : Springer, 2018. doi P. 47-55. doi
Chapter Laptsuev Rodion, Ananyeva Marina, Meinster Dmitry, Karpov I., Makarov I., Zhukov L. E. Information Propagation Strategies in Online Social Networks, in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics Vol. 247. Springer, 2018. doi P. 319-328. doi
Chapter Makarov I., Gerasimova O., Sulimov P., Ksenia Korovina, Zhukov L. E. Joint Node-Edge Network Embedding for Link Prediction, in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science / Ed. by W. M. van der Aalst, V. Batagelj, G. Glavaš,, D. I. Ignatov, M. Khachay, O. Koltsova, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch,, A. Napoli,, A. Savchenko, A. Panchenko,, P. M. Pardalos, M. Pelillo,. Vol. 11179. Berlin : Springer, 2018. doi P. 20-31. doi
Chapter Makarov I., Dmitry Savostyanov, Boris Litvyakov, Ignatov D. I. Predicting Winning Team and Probabilistic Ratings in Dota 2 and Counter-Strike: Global Offensive Video Games, in: Analysis of Images, Social Networks and Texts. 6th International Conference, 2017, Revised Selected Papers / Ed. by W. M. van der Aalst, D. I. Ignatov, M. Khachay, S. Kuznetsov, V. Lempitsky, I. A. Lomazova, A. Napoli, A. Panchenko, P. M. Pardalos, A. V. Savchenko, S. Wasserman. Vol. 10716. Cham : Springer, 2018. doi P. 183-196. doi
Chapter Anastasia Feygina, Ignatov D. I., Makarov I. Realistic post-processing of rendered 3D scenes, in: Proceedings of ACM SIGGRAPH'18 Posters. NY : Association for Computing Machinery (ACM), 2018. P. 1-2. doi
Chapter Makarov I., Gerasimova O., Sulimov P., Zhukov L. E. Recommending Co-authorship via Network Embeddings and Feature Engineering: The case of National Research University Higher School of Economics, in: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries. NY : Association for Computing Machinery (ACM), 2018. P. 365-366. doi
Chapter Makarov I., Bulanov O., Olga Gerasimova, Natalia Meshcheryakova, Karpov I., Zhukov L. E. Scientific Matchmaker: Collaborator Recommender System, in: Analysis of Images, Social Networks and Texts. 6th International Conference, 2017, Revised Selected Papers / Ed. by W. M. van der Aalst, D. I. Ignatov, M. Khachay, S. Kuznetsov, V. Lempitsky, I. A. Lomazova, A. Napoli, A. Panchenko, P. M. Pardalos, A. V. Savchenko, S. Wasserman. Vol. 10716. Cham : Springer, 2018. doi P. 404-410. doi
Chapter Makarov I., Alisa Korinevskaya, Vladimir Aliev. Sparse Depth Map Interpolation using Deep Convolutional Neural Networks, in: Proceedings of 2018 41st International Conference on Telecommunications and Signal Processing (TSP). NY : IEEE, 2018. P. 1-5. doi
Chapter Makarov I., Alisa Korinevskaya, Vladimir Aliev. Super-resolution of interpolated downsampled semi-dense depth map, in: Proceedings of the 23rd International ACM Conference on 3D Web Technology. NY : Association for Computing Machinery (ACM), 2018. P. 1-2. doi
Chapter Makarov I., Pavel Polyakov, Roman Karpichev. Voronoi-based Path Planning based on Visibility and Kill/Death Ratio Tactical Component, in: Supplementary Proceedings of the 7th International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2018), Moscow, Russia, July 5-7, 2018 / Ed. by W. van der Aalst,, V. Batagelj, G. Glavaš,, D. I. Ignatov, M. Khachay,, O. Koltsova,, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch,, A. Napoli,, A. Savchenko, A. Panchenko,, P. M. Pardalos, M. Pelillo,. Aachen : CEUR Workshop Proceedings, 2018. P. 129-140.
Article Краснов Ф. В., Макаров Илья Андреевич Прогнозирование развития соавторства в написании научных статей научно-технического центра Газпромнефть на основе модели // Интернет-журнал Науковедение. 2018. Т. 10. № 1. С. 1-11.
Chapter Makarov I., Konoplya O., Pavel Polyakov, Maxim Martynov, Zyuzin P., Gerasimova O., Bodishtianu Valeria. Adapting First-Person Shooter Video Game for Playing with Virtual Reality Headsets, in: Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2017, Marco Island, Florida, USA, May 22-24, 2017. AAAI Press 2017, ISBN 978-1-57735-787-2. Palo Alto : AAAI Press, 2017. P. 412-415.
Chapter Makarov I., Bulanov O., Zhukov L. E. Co-author Recommender System, in: Models, Algorithms, and Technologies for Network Analysis. Springer Proceedings in Mathematics & Statistics / Ed. by V. A. Kalyagin, A. I. Nikolaev, P. M. Pardalos, O. Prokopyev. Vol. 197. Springer, 2017. doi P. 251-257. doi
Chapter Makarov I., Vladimir Aliev, Gerasimova Olga, Pavel Polyakov. Depth Map Interpolation using Perceptual Loss, in: Adjunct Proceedings of 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct). NY : IEEE, 2017. P. 93-94. doi
Chapter Makarov I., Andrej Kashin, Alice Korinevskaya. Learning to Play Pong Video Game via Deep Reinforcement Learning: Tweaking Deep Q-Networks versus Episodic Control, in: Supplementary Proceedings of the Sixth International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2017), Moscow, Russia, July 27-29, 2017 / Ed. by W. van der Aalst, M. Y. Khachay, S. Kuznetsov, V. Lempitsky, I. A. Lomazova, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, A. V. Savchencko, S. Wasserman, D. I. Ignatov. Vol. 1975. Aachen : CEUR-WS.org, 2017. P. 236-241.
Chapter Makarov I., Valeria Bodishtyanu. Logic of Existentialism in Fiction, in: Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2017, Marco Island, Florida, USA, May 22-24, 2017. AAAI Press 2017, ISBN 978-1-57735-787-2. Palo Alto : AAAI Press, 2017. P. 632-637.
Chapter Rustem M. Khayrullin, Makarov I., Zhukov L. E. Predicting Psychology Attributes of a Social Network User, in: Proceedings of the Fourth Workshop on Experimental Economics and Machine Learning (EEML 2017), Dresden, Germany, September 17-18, 2017 / Ed. by R. Tagiew, D. I. Ignatov, A. Hilbert, K. Heinrich, R. Delhibabu. Vol. 1968. Aachen : CEUR Workshop Proceedings, 2017. P. 2-8.
Chapter Makarov I., Anastasia Frolenkova, Ivan Belov. Quantum Logic and Natural Language Processing, in: CLLS 2016. Computational Linguistics and Language Science. Proceedings of the Workshop on Computational Linguistics and Language Science. Moscow, Russia, April 26, 2016 / Ed. by E. Artemova, D. Ilvovsky, D. Skorinkin, A. Vybornova. Vol. 1886. Aachen : CEUR Workshop Proceedings, 2017. P. 135-140.
Chapter Makarov I., Vladimir Aliev, Olga Gerasimova. Semi-Dense Depth Interpolation using Deep Convolutional Neural Networks, in: Proceedings of the 25th ACM international conference on Multimedia (ACM MM'17), Mountain View, CA USA, 23-27 October 2017.. NY : Association for Computing Machinery (ACM), 2017. P. 1407-1415. doi
Chapter Makarov I., Mikhail Tokmakov, Pavel Polyakov, Peter Zyuzin, Maxim Martynov, Oleg Konoplya, George Kusnetsov, Ivan Guschenko-Cheverda, Maxim Uriev, Ivan Mokeev, Olga Gerasimova, Lada Tokmakova, Alexey Kosmachev. First-Person Shooter Game for Virtual Reality Headset with Advanced Multi-Agent Intelligent System, in: Proceedings of the 24th ACM international conference on Multimedia (ACM MM'16), Amsterdam, Netherlands, 15-19 October 2016.. NY : Association for Computing Machinery (ACM), 2016. P. 735-736. doi
Chapter Makarov I., Peter Zyuzin, Pavel Polyakov, Mikhail Tokmakov, Olga Gerasimova, Ivan Guschenko-Cheverda, Maxim Uriev. Modelling Human-like Behavior through Reward-based Approach in a First-Person Shooter Game, in: Proceedings of the Third Workshop on Experimental Economics and Machine Learning (EEML 2016), Moscow, Russia, July 18, 2016 / Ed. by R. Tagiew, D. I. Ignatov, A. Hilbert, R. Delhibabu. Vol. 1627. Aachen : CEUR Workshop Proceedings, 2016. Ch. 3. P. 24-33.
Chapter Makarov I., Pavel Polyakov. Smoothing Voronoi-based Path with Minimized Length and Visibility using Composite Bezier Curves, in: Supplementary Proceedings of the 5th International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2016), Yekaterinburg, Russia, April 7-9, 2016. / Ed. by D. I. Ignatov. Vol. 1710. Aachen : CEUR Workshop Proceedings, 2016. Ch. 19. P. 191-202.
Article Makarov I. Existence of Finite Total Equivalence Systems for Certain Closed Classes of 3-Valued Logic Functions // Logica Universalis. 2015. Vol. 9. No. 1. P. 1-26. doi
Chapter Makarov I., Mikhail Tokmakov, Lada Tokmakova. Imitation of Human Behavior in 3D-Shooter Game, in: Supplementary Proceedings of the 4th International Conference on Analysis of Images, Social Networks and Texts (AIST'2015) Issue 1452. Aachen : CEUR Workshop Proceedings, 2015. Ch. 9. P. 64-77.
Chapter Makarov I. Logical Generalized Continued Fractions, in: Proceedings of the 10th Panhelleic Logic Symposium. Samos Island : University of Aegean, 2015. Ch. 31. P. 121-121.
Chapter Olga Gerasimova, Makarov I. Separator Method for Constructing Canonical Types of Formulas, in: Handbook of the 5th World Congress and School on Universal Logic. Istanbul : University of Istanbul, 2015. P. 372-373.
Chapter Olga Gerasimova, Makarov I. Total Equivalence Systems for Classes of 3-valued Projection Logic whose Projections Equal to the Class of Linear Boolean Functions, in: Proceedings of the 10th Panhelleic Logic Symposium. Samos Island : University of Aegean, 2015. Ch. 23. P. 82-86.
Book Макаров И. А., Токмакова Л. Р. Учебно-методический комплекс дисциплины "Дискретная математика". М. : Издательский дом НИУ ВШЭ, 2015.
Article Makarov I. Interior Klein Polyhedra / Пер. с рус. // Mathematical notes. 2014. Vol. 95. No. 6. P. 795-805. doi
Preprint Макаров И. А. Внутренние полиэдры Клейна / Математические заметки. 2012. № -.

Conferences

2016
The 5th international conference on Analysis of Images, Social Networks, and Texts (AIST) (Екатеринбург). Presentation: Smoothing Voronoi-based Path with Minimized Length and Visibility using Composite Bezier Curves
Third International Workshop on Experimental Economics and Machine Learning (EEML 2016) (Москва). Presentation: Modelling Human-like Behavior through Reward-based Approach in a First-Person Shooter Game
The 6th International Conference on Network Analysis (Nizhny Novgorod). Presentation: Co-author Recommender System
ACM Multimedia 2016 (Амстердам). Presentation: First-Person Shooter Game for Virtual Reality Headset with Advanced Multi-Agent Intelligent System
2015
The 4th international conference on Analysis of Images, Social Networks, and Texts (AIST) (Екатеринбург). Presentation: Imitation of human behavior in 3D-shooter game
10th Panhellenic Logic Symposium (Karlovasi, Samos). Presentation: Total Equivalence Systems for Classes of 3-valued Projection Logic whose Projections Equal to the Class of Linear Boolean Functions
10th Panhellenic Logic Symposium (Karlovasi, Samos). Presentation: Logical Generalized Continued Fractions
5th World Congress on Universal Logic (Istanbul). Presentation: Separator Method for Constructing Canonical Types of Formulas
2014
Конференция научно-педагогических работников Национального исследовательского университета «Высшая школа экономики» (Москва). Presentation: Выборы Ученого Совета НИУ ВШЭ
2012
Ломоносовские чтения - 2012 (Москва). Presentation: О некоторых свойствах внутренних полиэдров Клейна

Supervising Course/Diploma/Research Projects

Complete list including group projects: http://cs.hse.ru/ai/research

- Graph Embeddings (graph representation and ML tasks on graphs)
- Convexity in Networks
- VR infinite locomotion (differential geometry and non-convex optimization)
- Computer Vision: image/video segmentation, super-resolution, depth/reflection/lightning reconstruction, video action recognition
- Augmented Reality: methods and applications, deep fashion and virtual mirrors
- Game design: Multiplayer FPS in UE4
- Social Network Analysis (general problems, analysing echo-chambers, opinion and rumour spreading)
- Deep Reinforcement Learning in VizDoom
- Translation and Generation of Sign Languages
- Many-value logics

Student Term / Thesis Papers

Bachelor
S. Pilipchuk, Computer Music Generation via Deep Neural Networks. HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE), 2020
P. Kuznetsov, 3D-Scene Reconstruction for Monocular Vision. Faculty of Computer Science, 2019
K. Pankov, Computer Modelling for Fashion E-Commerce. HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE), 2019
M. Chertkov, Translating Sign Language to Natural Language Text using Deep Learning. HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE), 2019
M. Shulgin, Scalable Deep Learning Algorithm for Brand Logo Detection in Images. Faculty of Computer Science, 2019
S. Korovin, Application of Graph Embeddings to Network Convexity Problems. Faculty of Computer Science, 2019
D. Chernyshev, Real-Time 3D Model Reconstruction and Mapping for Fashion. Faculty of Computer Science, 2019
A. Smirnov, Conditional Unpaired Image-to-Image Translation for Postprocessing Rendered 3D Scene. Faculty of Computer Science, 2019
N. Veld, Translation Between Sign Language and Symbolic Recording. Faculty of Computer Science, 2019
F. Kondrashov, User Behavior Analysis for the Credit Scoring Problem. Faculty of Computer Science, 2018
S. Zamylin, Forecasting Financial Indicators of Public Joint-Stock Companies Using Machine Learning Algorithms. Faculty of Computer Science, 2018
Y. Karamnova, Human Body Segmentation Using Deep Convolutional Neural Networks. Faculty of Computer Science, 2018
R. Mamtsev, Application for Lighting Reconstruction in Augmented Reality. Faculty of Computer Science, 2018
I. Lomov, GANs and Style Transfer for Fashion. Faculty of Computer Science, 2018
I. Kasyanov, Solving Optimization Problem for Mapping Virtual and Physical Worlds. Faculty of Mathematics, 2018
A. Pokoev, Image Super-Resolution Using Deep Learning Techniques. Faculty of Computer Science, 2018
K. Korovina, Graph Embeddings for Multi-class Classification of Nodes and Edges. Faculty of Mathematics, 2018
R. Bobrov, RGB-D Segmentation Applications in 3D Reconstruction Problem Based on Depth Map Data. Faculty of Computer Science, 2017
A. Shchavrovskii, Local Positioning of Smartphone Holder for AR. Faculty of Computer Science, 2017
P. Zyuzin, Weapon Selection Algorithms Based on Neural Networks for 3D First Person Shooter in Unreal Engine 4. Faculty of Computer Science, 2016
O. Konoplia, Application of Oculus Rift VR DK2 to the Navigation and Sighting for 3D First Person Shooter in Unreal Engine 4. Faculty of Computer Science, 2016
E. Vakulyaka, Analysis of the Scientific and Pedagogical NRU HSE Staff Publication Graph. Faculty of Computer Science, 2016
O. Bulanov, Recomender System Based on the Publication Graph Scientific and Pedagogical NRU HSE Staff. Faculty of Computer Science, 2016
Master
M. Mitrofanova, Leveraging Linguistic Features from Graph-Based Text Representations for Language Clustering. Faculty of Humanities, 2020
I. Gushchenko-cheverda, Learning Loss for Active Learning in Depth Reconstruction Problem. Faculty of Computer Science, 2020
A. Mikheev, Automated Creation of Synchronized Music Video. Faculty of Computer Science, 2020
D. Maslov, Fast Monocular Depth Reconstruction using Deep Neural Networks. Faculty of Computer Science, 2020
M. Makarov, Fusion of Text and Graph Information for Machine Learning Problems on Graphs. Faculty of Computer Science, 2020
B. Pleshakov, Industrial Machine Learning for Fault Detection on Aircraft Engines Sensor Data. Faculty of Computer Science, 2020
H. Alhaddad, Development of Deep Learning Based Agent in Procedurally Generated Game. Faculty of Computer Science, 2020
M. Lyubimov, Fault Detection in Tennessee Eastman Process. Faculty of Computer Science, 2020
A. Broilovskiy, Human Action Recognition For Boxing Training Simulatior. Faculty of Computer Science, 2020
A. Pokoev, Industrial Machine Learning for Fault Detection on Aircraft Engines Sensor Data. Faculty of Computer Science, 2020
A. Raskevich, Realistic Video Post-Processing of Rendered 3D Scene. Faculty of Computer Science, 2020
D. Zuenko, Style-transfer Autoencoder for Efficient Deep Voice Conversation. Faculty of Computer Science, 2020
A. Beketova, Instagram Hashtag Prediction Using Sequential Analysis with Deep Neural Networks. Faculty of Computer Science, 2020
A. Manuzina, Content-based Media Similarity and Clustering. Faculty of Communications, Media, and Design, 2020
K. Tikhomirova, Telegram Channel Market in Russia: Participants and Communications on the Platform. Faculty of Communications, Media, and Design, 2020
C. Rondonuwu, Rumor Propagation Analysis during COVID-19 Outbreak. Faculty of Communications, Media, and Design, 2020
K. Lomotin, Automated Image and Video Quality Assessment for Computational Video Editing. Faculty of Computer Science, 2020
V. Davydova, Contextualized Word Embeddings for Word Sense Induction for Russian Language. Faculty of Humanities, 2020
B. Tseytlin, Image Based Hotels Recommendation via Latent Image Embedding. Faculty of Computer Science, 2020
I. Vasilev, Optimal Classification Using Latent Space Generated from Autoencoders. Faculty of Computer Science, 2020
E. Luboshnikov, Federated Learning in Named Entity Recognition. Faculty of Computer Science, 2020
V. Ovechkin, Scalable Logo Recognition Using Deep Neural Networks. Faculty of Computer Science, 2020
C. Liang, Voters Network Structure and Social Choice of Presidential Election 2020 in Taiwan. Faculty of Communications, Media, and Design, 2020
M. Pozhidaeva, Information Extraction for Modelling Screenplay Evolution of Star Wars Fiction. Faculty of Humanities, 2020
I. Lomov, Fault Detection in Tennessee Eastman Process. Faculty of Computer Science, 2020
D. Kuvshinova, Video and Image Quality Estimation for Blur and Defocus Removement. Faculty of Computer Science, 2020
L. Tokmakova, Conditional Image Generation from Text. Faculty of Computer Science, 2020
R. Misiutin, Accelerating Modelling of Injection Molding with Geometric Deep Learning. Faculty of Computer Science, 2020
E. Pavlova, Reinforcement Learning algorithms in a Mean field games with a lot of players. Faculty of Computer Science, 2019
K. Kordyukov, Deep Learning of Energy and Nutritional Value in Food Analysis from Video. Faculty of Computer Science, 2019
S. Petrov, Human Pose Estimation for Shadow Boxing. Faculty of Computer Science, 2019
S. Krasnov, Esperanto – English Hybrid Machine Translation System. Faculty of Humanities, 2019
D. Kiselev, Prediction of New Itinerary Markets for Airlines. Faculty of Computer Science, 2019
I. Kamaldinov, Deep reinforcement Learning in Match-3 Game. Faculty of Computer Science, 2019
D. Shvedov, Automated Music Video Editing and Ranking. Faculty of Computer Science, 2019
A. Tolokonnikov, Modelling Influence of Shock Events on Country Trade Networks Using Graph Embeddings. Faculty of Computer Science, 2019
P. Adamenko, Automated Music Video Editing and Ranking. Faculty of Computer Science, 2019
A. Mikhaylov, Deep Reinforcement Learning in VizDoom. Faculty of Computer Science, 2019
K. Sudarikov, ECoG Processing for Motion Kinematics Reconstruction. Faculty of Computer Science, 2019
P. Zolnikov, Effective Algorithms for Constructing Multiplex Networks Embedding. Faculty of Computer Science, 2019
I. Sokolova, Using Word Co-occurrence Networks for Measuring the Complexity of Constructed Languages. Faculty of Humanities, 2019
A. Lapidus, Recommending Relevant Research Papers based on Citation Network Embedding. Faculty of Humanities, 2019
D. Tikhomirov, Knowledge Retrieval and Opinion Mining from Chernobyl Documentaries. Faculty of Humanities, 2019
A. Zaynutdinova, Deception Detection in Online Media. Faculty of Communications, Media, and Design, 2019
N. Semenova, Graph Embedding for Text Attributed Network. Faculty of Humanities, 2019
N. Kostiakova, Train Arrival Time Prediction Using Network Analysis. Faculty of Computer Science, 2018
P. Danilov, Analysis And Determination of Key Events in Dota 2 Matches. Faculty of Computer Science, 2018
D. Akimov, Deep Reinforcement Learning in Vizdoom FPS. Faculty of Computer Science, 2018
E. Tetin, Real-Time Object Tracking for AR. Faculty of Computer Science, 2018
M. Ananyeva, Inductive Learning of Dynamic Graph Embeddings. Faculty of Computer Science, 2018
A. Korinevskaya, Depth Map Reconstruction Using Deep Convolutional Neural Networks. Faculty of Computer Science, 2018
V. Aliev, Depth Map Interpolation via Convolutional Neural Network. Faculty of Computer Science, 2017
T. Grunina, Predictive Modeling in Big Data: Learning Multimodal Enviroment with Deep Reinforcement Learning. Graduate School of Business, 2017
A. Kashin, Application of Deep Neural Networks for Decision Making in First-person Shooter. Faculty of Computer Science, 2017

Full list of of student term / thesis papers

Life inside HSE

Election of the Academic Council

First meeting on EP AMI FCS

Everybody want to know, what was added to the compote in MIEM dining room

7 days after the accreditation

                                  (3 days left till next disaster)

                        My first graduates at HSE
                        Testimonial for Ilya Makarov for 2011-2014

Jul

2020

Senior Lecturer of DADiII Ilya Makarov at the 43rd International Conference on Telecommunications and Signal Processing (TSP), Milan, Italy, July 7-9

I. Makarov made a presentation “Real-Time 3D Model Reconstruction and Mapping for Fashion” at the conference TSP2020 on the topic of virtual fitting rooms based on machine learning models. Due to the restrictions on the pandemic, the conference was held online.

Aug

2018

ANR-Lab hold the Ninth International Summer School "Applied Data Analysis with Python" (TMSA-2018)

The traditional summer school of the International Laboratory for Applied Network Research is over.

Dec

2016

HSE Student Analyses Social Network to Find Runaway Brother

It is a fairly common story for families – a runaway teenager leaves a note saying ‘I’m not coming back, and don’t try looking for me’ and turns off their cell phone. In a recent case, however, a sister was able to find her brother by using the knowledge she acquired as a student in HSE’s Applied Mathematics and Information Science programme. Her story shows what social networks can say about its users to someone who knows how to listen.

Mar

2015

School of Data Analysis and Artificial Intelligence Join the Association for Symbolic Logic

Institutional cooperation between the Association and the Department has been expanded with the participation of three students who wrote their term and graduation papers under the supervision of the Department’s lecturers in the following fields: Boolean and many-valued logics; Functional expressibility in closed classes; Blueprint trees and building a decision-making system in 3D shooters, based on deduction rules.

Ilya Makarov

Education

Continuing education / Professional retraining / Internships / Study abroad experience

Professional Interests

Research interests

Awards and Accomplishments

Grants

Publications63

Conferences

Courses (2020/2021)

Courses (2019/2020)

Courses (2018/2019)

Courses (2017/2018)

Courses (2016/2017)

Courses (2015/2016)

Mentoring Coding Projects