Ilya Makarov
- Associate Professor, Senior Research Fellow:Faculty of Computer Science / School of Data Analysis and Artificial Intelligence
- Senior Research Fellow:HSE Campus in Nizhny Novgorod / Laboratory of Algorithms and Technologies for Networks Analysis (Nizhny Novgorod)
- Visiting Specialist:HSE Campus in Nizhny Novgorod / Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)
- Ilya Makarov has been at HSE University since 2011.
Education and Degrees
- 2021PhD
- 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
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

Young Faculty Support Program (Group of Young Academic Professionals)
Category "New Lecturers" (2013-2014)
Category "Future Lecturers" (2012)
Employment history
HSE University, School of Data Analysis and Artificial Intelligence – Senior Lecturer, Researcher (2011 – current, full-time), Deputy Head (2012-2017)
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"
Publications86
- Book Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2021 (MACSPro 2021) / Отв. ред.: S. Shapoval, T. Khamdamov, I. Makarov. Aachen : CEUR Workshop Proceedings, 2022.
- Chapter Gerasimova O., Makarov I., Лапидус А. А. Research Papers Recommendation, in: Analysis of Images, Social Networks and Texts. 10th International Conference, AIST 2021, Tbilisi, Georgia, December 16–18, 2021, Revised Selected Papers / Ed. by E. Burnaev, D. I. Ignatov, S. Ivanov, M. Khachay, O. Koltsova, A. Kutuzov, Sergei O. Kuznetsov, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, J. Saramäki, A. Savchenko, E. Tsymbalov, E. Tutubalina. Cham : Springer, 2022. doi P. 1-14.
- Article Makarov I., Bakhanova M., Nikolenko S., Gerasimova O. Self-supervised recurrent depth estimation with attention mechanisms // PeerJ Computer Science. 2022. Vol. 8. Article e865. doi
- Article Makarov I., Savchenko A., Arseny Korovko, Leonid Sherstyuk, Severin N., Kiselev D., Mikheev Aleksandr, Babaev D. Temporal network embedding framework with causal anonymous walks representations // PeerJ Computer Science. 2022. Vol. 8. Article e858. doi
- Chapter Davydova V., Gerasimova O., Makarov I. Сontext-dependent Word Embeddings for Word Sense Induction in Russian Language, in: Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2021 (MACSPro 2021) / Отв. ред.: S. Shapoval, T. Khamdamov, I. Makarov. Aachen : CEUR Workshop Proceedings, 2022. P. 1-18. (in press)
- Chapter Konstantin Lomotin, Makarov I. Automated Image and Video Quality Assessment for Computational Video Editing, in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers / Ed. by W. M. van der Aalst, V. Batagelj, D. I. Ignatov, M. Khachay, O. Koltsova, A. Kutuzov, Sergei O. Kuznetsov, I. A. Lomazova, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Cham: Springer, 2021. doi P. 243-256. doi
- Chapter Tikhomirova K., Makarov I. Community Detection Based on the Nodes Role in a Network: The Telegram Platform Case, in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers / Ed. by W. M. van der Aalst, V. Batagelj, D. I. Ignatov, M. Khachay, O. Koltsova, A. Kutuzov, Sergei O. Kuznetsov, I. A. Lomazova, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Cham: Springer, 2021. doi P. 294-302. doi
- Chapter Maria Bakhanova, Ilya Makarov. Deep Reinforcement Learning in VizDoom via DQN and Actor-Critic Agents, in: Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I Vol. 12861. Part 1. Springer, 2021. doi Ch. 12. P. 138-150. doi
- Chapter Anton Zakharenkov, Makarov I. Deep Reinforcement Learning with DQN vs. PPO in VizDoom, in: Proceedings of IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI'21), 18-20 Nov. 2021. NY : IEEE, 2021. doi P. 000131-000136. doi
- Chapter Makarov I., Borisenko G. Depth Inpainting via Vision Transformer, in: Adjunct Proceedings of IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). NY : IEEE, 2021. P. 286-291. doi
- Chapter Dmitrii Maslov, Makarov I. Fast Depth Reconstruction Using Deep Convolutional Neural Networks, in: Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I Vol. 12861. Part 1. Springer, 2021. doi Ch. 38. P. 456-467. doi
- Article Lomov I., Lyubimov M., Makarov I., Zhukov L. E. Fault detection in Tennessee Eastman process with temporal deep learning models // Journal of Industrial Information Integration. 2021. Vol. 23. Article 100216. doi
- Chapter Efim Luboshnikov, Makarov I. Federated Learning in Named Entity Recognition, in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary Proceedings / Ed. by W. M. van der Aalst, V. Batagelj, A. V. Buzmakov, D. I. Ignatov, A. A. Kalenkova, M. Khachay, O. Koltsova, A. Kutuzov, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch, I. Makarov, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Springer, 2021. doi Ch. 8. P. 90-101. doi
- Article Makarov I., Makarov M., Kiselev D. Fusion of text and graph information for machine learning problems on networks // PeerJ Computer Science. 2021. Vol. 7. Article e526. doi
- Chapter Boris Tseytlin, Makarov I. Hotel Recognition via Latent Image Embeddings, in: Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part II. Cham : Springer, 2021. Ch. 24. P. 293-305. doi
- Chapter Anton Broilovskiy, Makarov I. Human Action Recognition for Boxing Training Simulator, in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers / Ed. by W. M. van der Aalst, V. Batagelj, D. I. Ignatov, M. Khachay, O. Koltsova, A. Kutuzov, Sergei O. Kuznetsov, I. A. Lomazova, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Cham: Springer, 2021. doi P. 331-343. doi
- Chapter Anna Beketova, Makarov I. Instagram Hashtag Prediction Using Deep Neural Networks, in: Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part II. Cham : Springer, 2021. Ch. 3. P. 28-42. doi
- Article Makarov I., Korovina K., Kiselev D. JONNEE: Joint Network Nodes and Edges Embedding // IEEE Access. 2021. Vol. 9. P. 144646-144659. doi
- Chapter Makarov I., Guschenko-Cheverda I. Learning Loss for Active Learning in Depth Reconstruction Problem, in: Proceedings of IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI'21), 18-20 Nov. 2021. NY : IEEE, 2021. doi P. 000115-000120. doi
- Chapter Makarov I., Oborevich A. Network Embedding for Cluster Analysis, in: Proceedings of IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI'21), 18-20 Nov. 2021. NY : IEEE, 2021. doi P. 000127-000130. doi
- Chapter Alexander Pugachev, Voronov A., Makarov I. Prediction of News Popularity via Keywords Extraction and Trends Tracking, in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary Proceedings / Ed. by W. M. van der Aalst, V. Batagelj, A. V. Buzmakov, D. I. Ignatov, A. A. Kalenkova, M. Khachay, O. Koltsova, A. Kutuzov, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch, I. Makarov, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Springer, 2021. doi Ch. 4. P. 37-51. doi
- Book Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary Proceedings / Ed. by W. M. van der Aalst, V. Batagelj, A. V. Buzmakov, D. I. Ignatov, A. A. Kalenkova, M. Khachay, O. Koltsova, A. Kutuzov, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch, I. Makarov, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Springer, 2021. doi
- Chapter Maksim Golyadkin, Makarov I. Semi-automatic Manga Colorization Using Conditional Adversarial Networks, in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected Papers / Ed. by W. M. van der Aalst, V. Batagelj, D. I. Ignatov, M. Khachay, O. Koltsova, A. Kutuzov, Sergei O. Kuznetsov, I. A. Lomazova, N. Loukachevitch, A. Napoli, A. Panchenko, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 12602. Cham: Springer, 2021. doi P. 230-242. doi
- Chapter Makarov I., Zuenko D. Style-transfer Autoencoder for Efficient Deep Voice Conversion, in: Proceedings of IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI'21), 18-20 Nov. 2021. NY : IEEE, 2021. doi P. 000121-000126. doi
- 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. 7. P. 1-62. 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.
- Chapter Makarov I., Nikolay Veldyaykin, 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 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 Alsu Zaynutdinova, Dina Pisarevskaya, 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
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
- 2014Конференция научно-педагогических работников Национального исследовательского университета «Высшая школа экономики» (Москва). Presentation: Выборы Ученого Совета НИУ ВШЭ
- 2012Ломоносовские чтения - 2012 (Москва). Presentation: О некоторых свойствах внутренних полиэдров Клейна
Courses (2022/2023)
- Visual geometry and 3D image processing (Master’s programme; Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod); 2 year, 2 module)Eng
- Past Courses
Courses (2021/2022)
- Network Science (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
- Project Seminar ''Intelligent Systems and Structural Analysis'' (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
- Social Networks (Master’s programme; Faculty of Humanities; 2 year, 1, 2 module)Eng
- Structural Analysis and Visualization of Networks (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
Courses (2020/2021)
- Network Science (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
- Project Seminar ''Intelligent Systems and Structural Analysis'' (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
- Social Networks (Master’s programme; Faculty of Humanities; 2 year, 1, 2 module)Eng
- Structural Analysis and Visualization of Networks (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
Courses (2019/2020)
- Applied Network Analysis (Master’s programme; Faculty of Creative Industries; 2 year, 1, 2 module)Rus
- Network Science (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
- Project Seminar ''Intelligent Systems and Structural Analysis'' (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
- Research Seminar (Master’s programme; Faculty of Creative Industries; 2 year, 1-3 module)Rus
- Research Seminar ''Intelligent Systems and Structural Analysis'' (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
- Social Networks (Master’s programme; Faculty of Humanities; 2 year, 1, 2 module)Eng
- Structural Analysis and Visualization of Networks (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
Courses (2018/2019)
- Combinatorics, Graphs and Computational Logic (Bachelor’s programme; Faculty of Computer Science; 3 year, 3, 4 module)Eng
- Introductory Research Seminar (Bachelor’s programme; Faculty of Computer Science; 2 year, 3 module)Eng
- Network Science (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
- Project Seminar (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
- Research Seminar "Data Analysis and Artificial Intelligence 1" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Eng
- Social Network Analysis (Mago-Lego; 4 module)Eng
- Social Networks (Master’s programme; Faculty of Humanities; 2 year, 1, 2 module)Eng
Courses (2017/2018)
- Design Technology (Optional course (faculty); Faculty of Creative Industries; 1-4 module)Rus
- Introductory Research Seminar (Bachelor’s programme; Faculty of Computer Science; 2 year, 3 module)Eng
- Social Network Analysis (Mago-Lego; 4 module)Eng
- Special Project. Game Design and Virtual Reality (Bachelor’s programme; Faculty of Creative Industries; 2 year, 1-4 module)Rus
Mentoring Coding Projects
Project from 1st year challenge: Cinematic Movie of Space Station Docking in Unreal Engine 4
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
Life inside HSE

Election of the Academic Council

First meeting on EP AMI FCS

7 days after the accreditation
(3 days left till next disaster)
My first graduates at HSE
Testimonial for Ilya Makarov for 2011-2014
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.
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.
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.
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.