Publications
“Emergent Macroscopic Market Impact Analysis on AI-Generated Limit Order Book Data.” [In preparation for ICAIF 2026].
“Understanding the Inner Workings of HFT Foundation Models.” [In preparation for ICAIF 2026].
“Neural Scaling Laws for Order Flow Generation.” [Submitted to NeurIPS 2026].
Mohl, V, S Frey, R Leyland, K Li, G Nigmatulin, M Cucuringu, S Zohren, J Foerster, and A Calinescu. 2025. “JaxMARL-HFT: GPU-Accelerated Large-Scale Multi-Agent Reinforcement Learning for High-Frequency Trading.” Proceedings of the 6th ACM International Conference on AI in Finance (ICAIF), pp. 18-26. [Honourable Mention]. https://arxiv.org/abs/2511.02136.
Volkova, E, K Pavlov, K Beliaev, A Perchik, V Lychagov, E Nikolaev, A Ayuev, G Nigmatulin, W Lee, H Lee, and Y Kim. 2025. “Electronic Device and Method for Determining a Body Core Temperature.” US Patent No. US20250352075A1, Samsung Electronics Co., Ltd. https://patents.google.com/patent/US20250352075A1/en.
Nigmatulin, G, K Pavlov and A Zaytsev. 2023. “Anomaly detection aided Active Learinng.” Accepted to IEEE Globecom 2023 IoTSN, https://edas.info/showManuscript.php?m=1570902535&ext=pdf&random=211154087&type=stamped.
Pavlov, K., Perchik, A., Tsepulin, V., Megre, G., Nikolaev, E., Volkova, E., Nigmatulin, G., L, HJ., L, WS., and K, YH. 2022. “Sweat loss estimation algorithm for smartwatches.” IEEE Access, vol. 11, pp. 23926-23934, 2023, https://ieeexplore.ieee.org/document/10061707.
Nigmatulin, G, and O Chaganova. 2021. “Research of an Optimization Model for Servicing a Network of ATMs and Information Payment Terminals.” Communications in Computer and Information Science, Springer. https://arxiv.org/abs/2210.09927.
Bolodurina, I, G Nigmatulin, and D Parfenov. 2020. “Intersection of Triangles in Space Based on Cutting Off Segment.” Communications in Computer and Information Science, Springer. https://arxiv.org/abs/2210.15472.
Nigmatulin, G. 2019. “Predicting Study Time in an Online Course System Based on Machine Learning Methods.” In Book of Abstracts for the School-Conference “Invitation to Dynamical Systems, 2020”. Higher School of Economics. https://cupdf.com/document/book-of-abstracts-higher-school-of-economics-according-to-3-4-for-any-gradient-like.html?page=1
Nigmatulin, G, and I Bolodurina. 2019. “Comparative Analysis of the Methods of Training Recurrent Neural Network (Rus.). Step into Science, no. 2: 50-52. https://www.elibrary.ru/item.asp?id=41105398
Nigmatulin, G, D Parfenov, I Bolodurina, and Zaporozhko. V. 2019. “Solving the Problem of Categorical Regression Using Neural Networks and Gradient Boosting to Predict the Academic Performance at MOOCS (Rus.).” In University Complex as a Regional Center of Education, Science and Culture, 1529-33. https://elibrary.ru/item.asp?id=42532268
Parfenov, D, G Nigmatulin, V Zaporozhko, and L Zabrodina. 2019. “Prototype of the Module for the Intelligent Formation of an Individual Educational Trajectory of a Student for a Digital Platform (Rus.).” https://www.elibrary.ru/item.asp?id=42587112
Shchepacheva, N, and G Nigmatulin. 2018. “Analysis of the Company’s Activities Based on Chaos Theory (Rus.).” Step into a Science, no. 3: 35-38. https://www.elibrary.ru/item.asp?id=38564592