12/2024 I am proud to be selected as one of the fellows for 2025 Teach Access Fellowship cohort! Teach Access is a non-profit, sponsored by Microsoft and other organizations, that collaborates with academic institutions and industry oriented in supporting educators to teach and students to learn about digital accessibility. As a fellow, I am eager to use the resources and support provided to benefit the community. I look forward to collaborating with other program fellows to exchange ideas, and share effective strategies, knowledge, and experience that will enrich my approach to enhancing the accessibility of the courses I am currently teaching and will developing for Spring and Fall 2025 semesters at The University of Texas Rio Grande Valley.

08/2024: I am pleased to announce that on 09/01 I will be joining University of Texas Rio Grande Valley as an Assistant Professor (tenure-track) in the Department of Computer Science. I look forward to contributing to the academic community, continuing my research in AI/ML security and robustness, and working alongside the outstanding faculty team headed by Dr. Emmet Tomai, the Department Chair.

04/2024: On 04/29, my PhD dissertation defense has commenced (successfully) at RIT. This is an important milestone in my life, which has been achieved through the years of hard but truly inspiring, passionate, and rewarding work of solving challenging problems and building my unique knowledge and skill sets. Success is rarely achieved in isolation, and this dissertation would not have been possible without the unwavering support and guidance of a remarkable group of individuals, who significantly contributed to shaping and maturing my research endeavor, including my advisor, Dr. Leon Reznik, and my PhD dissertation committee members: Dr. Ivan De Oliveira Nunes, Dr. Stanislaw Radziszowski, and Dr. Igor Khohklov. I extend my deepest gratitude for the help in maturing myself as a researcher, and for the opportunity to have a collaboration with them to: Dr. Ernest Fokoue, Dr. Richard Zanibbi, Dr. Roman Yampolskiy, Dr. Sergey Lyshevski, Dr. Garegin Grigoryan, Dr. Haibo Yang, Dr. Ilia Viksnin, Dr. Igor Komarov, Raman Zatsarenko, Dmitrii Korobeinikov, Harshil Patel, Anirudh Narayanan, Shivam Mahajan, Chirayu Anil Marathe, Moinuddin Memon, Kartavya Manojbhai Bhatt, Rahul Ganesh, Matthew Hyland, John Flory, Antoun Obeid, Akshaya Nandkishor Satam, Srujan Shetty, Ruslan Gataullin, Iuliia Kim, Egor Marinenkov, Pavel Belyaev, Evgenii Neverov, Nikita Tursukov, Eduard Lazarev, Timofey Melnikov, Maria Usova, Julia Lyakhovenko, Dr. Kseniya Salakhutdinova, and many others. To all of you, my deepest gratitude!

09/2023: I am excited to announce that Dr. Reznik and myself are starting our new (2023-2026) research project funded by NSF: Collaborative research: IDEAS lab: ETAUS: Smarter Microbial Observatories for Realtime ExperimentS (SMORES). This big ($1.5M) project will be performed in collaboration between Harvard University, RIT, Florida International University and University of Georgia. It involves studies and practical work in biology, AI and engineering as well as field underwater experiments in Florida and California. The project will study marine sediments, which play a critical role in natural carbon sequestration. We propose to develop a novel seafloor sensor/sampler array to better understand how tidal pumping and subsurface currents influence seafloor oxygenation and sedimentary carbon cycling. Our team will be responsible for developing smarter control systems that use ML models and techniques to understand how to make intelligent predictions about when and where to best sense/sample based on the historical and real-time data.

06/2023: On 06/14, I had the opportunity to serve as a volunteer judge for the students' science projects presented at the international GENIUS Olympiad held at RIT. With students coming from all over the world, the event was an amazing platform for cultural exchange and development! The opportunity to serve as a judge was extremely beneficial for me in various ways. I was excited and pleased to enhance my knowledge about approaches to sustainable environmental problems in different world regions, as well as improve my skills in project evaluation and grading, which I will definitely leverage in my future career. I had a chance to talk with many students about their projects, and I was astonished by their confidence, knowledge, and the employed efforts on the problems they are working on! I firmly believe that such olympiads and contests are indeed fundamental and advantageous in the early stage to motivate future professionals in their endeavors to make our world better.

06/2023: From 06/05 to 06/06 I had a great opportunity to present our recent research results at the IEEE CAI 2023 conference happened in Santa Clara, CA. I presented two research papers there: Federated Learning for Robust Computer Vision in Intelligent Transportation Systems (Chuprov, S., Bhatt, K.M., & Reznik, L.); and Federated Learning with Trust Evaluation for Industrial Applications (Chuprov, S., Memon, M., & Reznik, L.). The second paper was included into the 10 best conference's papers list based on the reviews, and was selected for the oral presentation during the technical sessions. I want to express the most sincere gratitude to the IEEE CAI'23 organizers and reviewers for this incredible privilege, and to the amazing public for their attention and the chance to obtain useful feedback and aspects for the future work from the Q&A discussion. In addition, I want to congratulate my co-authors and thank them for their valuable contributions: Kartavya, Moinuddin, and Dr. Reznik! Without you, these papers would not be possible.

05/2023: Our paper, ``Robust Autonomous Vehicle Computer-Vision-Based Localization in Challenging Environmental Conditions'' has been finally published in the ``Challenges in the Guidance, Navigation and Control of Autonomous and Transport Vehicles'' Special Issue, MDPI Applied Sciences Journal.

04/2023: From 04/21 to 04/22 I had been privileged to participate in UPSTAT 2023 conference that took place at the Rochester Institute of Technology. At the event, I presented our work ``Enhancing Federated Learning Security with Reputation and Trust-Based Indicators'' authored by myself, Prof. Leon Reznik, and Moinuddin Memon (both affiliated with RIT). I am thrilled to announce that our work won the Gold Medal in the poster session! I want to express our deep gratitude to the UPSTAT'23 Organizing Committee and to all conference's participants!

01/2023: From 01/23 to 01/27 I had an honor to participate in POWDER-RENEW Mobile and Wireless Week 2023 at the University of Utah, Salt Lake City. The event was diligently organized by the POWDER team and was full of novel and useful knowledge and hands-on practical tutorials on how to work with the POWDER platform. POWDER team-members were really friendly and eager to help in case of any questions and issues. During the event, I have developed both my personal skills and knowledge, and also new collaborations with other participants, which will definitely help me to advance my further research. Greatly appreciate POWDER team vigilance and organization, and looking forward to the next year event!

11/2022: From 10/30 to 11/02 I had an amazing time in Dallas, TX, participating in 2022 IEEE Sensors conference. Any conference is about people, and the Sensors community definitely proves this thesis! So many engaging talks and interesting speakers. I also presented our two papers, which you can find below in Conference Proceedings section.

08/2022: I am happy to announce that our paper ``Study on Destructive Informational Impact in Unmanned Aerial Vehicles Intergroup Communication'' has been finally published in the MDPI Symmetry Journal's Special Issue ``Symmetry in Distributed Algorithms and Parallel Algorithms and Their Applications''. I want to thank all the co-authors contributed to this paper: Egor, Nikita, Iuliia, and Ilia - congrats!

07/2022: Congrats to my colleague, Dr. Ilia Viksnin, who have recently published his co-authored book in Russian: ``Unmanned Aerial Vehicles Safety: Informational, Functional and Criminal Law Aspects''! The book discusses issues in understanding the responsibility for unmanned autonomous vehicles safety accidents, and proposes interesting insights related to the topic. I also contributed to the book publishing process by assisting with the editing and proofreading. Please, use this link for the reference.

05/2022: I am happy to announce that I have completed my first Ph.D. year at RIT and successfully passed the Research Potential Assessment. I want to kindly thank all who have been helping me in this journey, especially, my pre-assessment committee members: Dr. De Oliveira Nunes, Dr. Radziszowski, and my advisor Dr. Reznik.

08/2021: I am starting my Ph.D. in Computing and Information Sciences at RIT, under the supervision of Prof. Leon Reznik.

Projects

Refereed Publications (Download as PDF)

Patents

1. Chuprov, S., & Reznik, L. ``Federated Learning with A Compromised Unit Exclusion from Receiving Global Model Updates''. Provisional application filed on January 13, 2023
2. Chuprov, S., & Reznik, L. ``Network Adjustment based on Machine Learning End System Performance Monitoring Feedback''. Provisional application filed on September 14, 2022. Converted to non-provisional

Books & Book Chapters

1. Chuprov, S., Zatsarenko, R., & Reznik, L. (2025) ``mLINK: Machine Learning Integration with Network and Knowledge'' in Metacognitive Artificial Intelligence, eds. Shakarian, P. & Wei, H. Cambridge University Press. URL

Reprints

1. Chuprov, S., Belyaev, P., Gataullin, R., Reznik, L., Neverov, E., & Viksnin, I. (2024) ``Robust Autonomous Vehicle Computer-Vision-Based Localization in Challenging Environmental Conditions'' in Applied Sciences. 2024, pp. 34-48., doi: doi.org/10.3390/books978-3-7258-2184-6. Reprint of the Special Issue ``Challenges in the Guidance, Navigation and Control of Autonomous and Transport Vehicles'' that was published in Applied Sciences in 2023. URL

Journal Publications

1. Korobeinikov, D., Zatsarenko, R., Chuprov, S., Barea, A., & Reznik, L. (2026). ``InteFL Framework: Optimizing Federated Learning with Metacognition for Application Design and Deployment'' in IEEE Intelligent Systems. 2026. doi: 10.1109/MIS.2026.3658072. URL (Published in Special Issue)
2. Chuprov, S., Reznik, L., & Zatsarenko, R. (2025). ``KISS: Knowledge Integration System Service for ML End Attacks Detection and Classification'' in IEEE Transactions on Dependable and Secure Computing. 2025, pp. 1-12. doi: 10.1109/TDSC.2025.3553807. URL
3. Chuprov, S., Zatsarenko, R., Reznik, L., & Khokhlov, I. (2024). ``Data Quality Based Intelligent Instrument Selection with Security Integration'' in ACM Journal of Data and Information Quality. 2024, vol. 16, no. 3, pp. 1-24. doi: 10.1145/3695770. URL
4. Chuprov, S., Belyaev, P., Gataullin, R., Reznik, L., Neverov, E., & Viksnin, I. (2023). ``Robust Autonomous Vehicle Computer-Vision-Based Localization in Challenging Environmental Conditions'' in Applied Sciences. 2023, no. 13(9):5735. doi: 10.3390/app13095735. URL (Published in Special Issue)
5. Berezovskaya, O., Chuprov, S., Neverov, E., & Sadreev, E. (2023). ``Review and Comparison of Lightweight Modifications of the AES Cipher for a Network of Low-Power Devices'' in Automatic Control and Computer Sciences. 2022, no. 56, pp. 994-1006. URL
6. Melnikov, T., Chuprov, S., Lazarev, E., Gataullin, R., & Viksnin, I. (2022). ``Improving Reputation and Trust-Based Approach with Reliability Indicators for Autonomous Vehicles Intergroup Communication'' in Tomsk State University Journal of Control and Computer Science. 2022, no. 61, pp. 108-117. URL
7. Marinenkov, E., Chuprov, S., Tursukov, N., Kim, I., & Viksnin, I. (2022). ``Study on Destructive Informational Impact in Unmanned Aerial Vehicles Intergroup Communication'' in Symmetry. 2022, Vol. 14, no. 8, pp. 1-18. URL (Published in Special Issue)
8. Viksnin, I., Marinenkov, E., & Chuprov, S. (2022). ``A Game Theory approach for communication security and safety assurance in cyber-physical systems with Reputation and Trust-based mechanisms'' in Scientific and Technical Journal of Information Technologies, Mechanics and Optics, vol. 22, no. 1, pp. 47–59. doi: 10.17586/2226-1494-2022-22-1-47-59. URL
9. Khokhlov, I., Reznik, L., & Chuprov, S. (2020). ``Framework for Integral Data Quality and Security Evaluation in Smartphones'' in IEEE Systems Journal, vol. 15, no. 2, pp. 2058-2065, doi: 10.1109/JSYST.2020.2985343. URL
10. Chuprov, S., Viksnin, I., Kim, I., Tursukov, N., & Nedosekin, G. (2020). Empirical Study on Discrete Modeling of Urban Intersection Management System. International Journal of Embedded and Real-Time Communication Systems (IJERTCS), vol. 11(2), pp. 16-38, doi: 10.4018/IJERTCS.2020040102. URL
11. Chuprov, S., Viksnin, I., Kim, I., Marinenkov, E., Usova, M., Lazarev, E., Melnikov, T., & Zakoldaev, D. (2019). Reputation and Trust Approach for Security and Safety Assurance in Intersection Management System. Energies, 12(23), 4527, doi: 10.3390/en12234527. URL

Conference Proceedings

1. Peña, A. & Chuprov, S. (2026). ``Improving PID-Based Aggregation in Federated Learning for Consumer Applications'' in 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC). 2026. doi: 10.1109/CCNC65079.2026.11366291. URL
2. Zatsarenko, R., Chuprov, S., Korobeinikov, D., Reznik, L., & Peña, A. (2026). ``How to Improve Federated Learning in Consumer Applications? Detect and Exclude Bad Clients'' in 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC). 2026. doi: 10.1109/CCNC65079.2026.11366313. URL
3. Peredo, A. & Chuprov, S. (2026). ``Improving Generalization with Harmonic Aggregation in Personalized Federated Learning'' in 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC). 2026. doi: 10.1109/CCNC65079.2026.11366390. URL
4. Fonseca, P., Chuprov, S., Solis, J. P., & Marquez, G. (2025). ``Improving Lean Construction by Integrating ML for Contractor Performance Prediction'' in 2025 38th Conference of Open Innovations Association (FRUCT). 2025. doi: 10.23919/FRUCT67853.2025.11239221. URL
5. Chan, E. E. N. & Chuprov, S. (2025). ``Bayesian Optimization of PID Coefficients for Robust Federated Learning'' in TACCSTER 2025 Proceedings. 2025. doi: 10.26153/tsw/62178. URL
6. Korobeinikov, D., Chuprov, S., & Reznik, L., (2024). ``Towards More Robust Federated Learning with Medical Imaging Model Anomaly Detection'' in 2024 IEEE Western New York Image and Signal Processing Workshop (WNYISPW), 2024, pp. 1-4. URL
7. Narayanan, A., Chuprov, S., Reznik, L., Zatsarenko, R., & Korobeinikov, D. ``Intelligent Soccer Event Detection and Highlights Generation with Broadcast Cues Integration'' in 23rd International Conference on Machine Learning and Applications (ICMLA'24), Miami, FL, USA, 2024, pp. 554-559, doi: 10.1109/ICMLA61862.2024.00081. URL
8. Patel, H., Chuprov, S., Korobeinikov, D., Zatsarenko, R., & Reznik, L. (2024). ``Improving Federated Learning Security with Trust Evaluation to Detect Adversarial Attacks'' in 19th Annual Symposium on Information Assurance (ASIA’ 24), 2024, pp. 37-43. URL
9. Korobeinikov, D., Chuprov, S., Zatsarenko, R., & Reznik, L., (2024). ``Federated Learning Robustness on Real World Data in Intelligent Transportation Systems'' in 19th Annual Symposium on Information Assurance (ASIA’ 24), 2024, pp. 30-36. URL
10. Chuprov, S., Zatsarenko, R., Korobeinikov, D., & Reznik, L. (2024). ``Robust Training on the Edge: Federated vs. Transfer Learning for Computer Vision in Intelligent Transportation Systems'' in 2024 IEEE World AI IoT Congress (AIIoT), Seattle, WA, USA, 2024, pp. 172-178, doi: 10.1109/AIIoT61789.2024.10578970. URL
11. Zatsarenko, R., Chuprov, S., Korobeinikov, D., & Reznik, L. (2024). ``Trust-Based Anomaly Detection in Federated Edge Learning'' in 2024 IEEE World AI IoT Congress (AIIoT), Seattle, WA, USA, 2024, pp. 273-279, doi: 10.1109/AIIoT61789.2024.10578967. URL
12. Kovtun R., Chuprov, S., Gataullin, R., Ruchkan, A., Alhasan, A., & Viksnin, I. (2024). ``A Modern Approach to High Dynamic Range Image Processing with Machine Learning Architectures'' in 2024 XXVII International Conference on Soft Computing and Measurements (SCM), 2024, pp. 207-212, doi: 10.1109/SCM62608.2024.10554097. URL
13. Garifullin M., Turushev, T., Tursukov, N., & Chuprov, S. (2024). ``Extended Formulation of the Problem of Terrain Exploration using a Multi-agent System'' in 2024 XXVII International Conference on Soft Computing and Measurements (SCM), 2024, pp. 207-212, doi: 10.1109/SCM62608.2024.10554236. URL
14. Chuprov, S., Mahajan, S., Zatsarenko, R., Reznik, L., & Ruchkan, A. (2023). ``Are Industrial ML Image Classifiers Robust to Withstand Adversarial Attacks on Videos?'' in 2023 IEEE Western New York Image and Signal Processing Workshop (WNYISPW), 2023, pp. 1-4, doi: 10.1109/WNYISPW60588.2023.10349595. URL
15. Zatsarenko, R., Chuprov, S., Marathe, C.A., Hyland, M., & Reznik, L. (2023). ``Are Industrial ML Image Classifiers Robust to Data Affected by Network QoS Degradation?'' in 2023 IEEE Western New York Image and Signal Processing Workshop (WNYISPW), 2023, pp. 1-4, doi: 10.1109/WNYISPW60588.2023.10349560. URL
16. Neverov, E., Viksnin, I., & Chuprov, S. (2023) ``The Research of AutoML Methods in the Task of Wave Data Classification'' in 2023 XXVI International Conference on Soft Computing and Measurements (SCM), 2023, pp. 156-158, doi: 10.1109/SCM58628.2023.10159058. URL
17. Tursukov N., Viksnin I., Neverov E., Sheinman E., & Chuprov S. (2023) ``Evaluation of the Effectiveness of Neural Networks Based on the Criteria for Completing the Object Classification Task'' in 2023 XXVI International Conference on Soft Computing and Measurements (SCM), 2023, pp. 120-122, doi: 10.1109/SCM58628.2023.10159070. URL
18. Chuprov, S., Bhatt, K.M., & Reznik, L. (2023). ``Federated Learning for Robust Computer Vision in Intelligent Transportation Systems'' in 2023 IEEE Conference on Artificial Intelligence (CAI), Santa Clara, CA, USA, 2023, pp. 26-27, doi: 10.1109/CAI54212.2023.00019. URL
19. Chuprov, S., Memon, M., & Reznik, L. (2023). ``Federated Learning with Trust Evaluation for Industrial Applications'' in 2023 IEEE Conference on Artificial Intelligence (CAI), Santa Clara, CA, USA, 2023, pp. 347-348, doi: 10.1109/CAI54212.2023.00153. URL
20. Chuprov, S., Reznik, L., & Grigoryan, G. (2022). ``Study on Network Importance for ML End Application Robustness'' in ICC 2023 - IEEE International Conference on Communications, 2023, pp. 6627-6632, doi: 10.1109/ICC45041.2023.10279698. URL
21. Chuprov, S., Satam, A. N., & Reznik, L. (2022). ``Are ML Image Classifiers Robust to Medical Image Quality Degradation?'' in 2022 IEEE Western New York Image and Signal Processing Workshop (WNYISPW), 2022, pp. 1-4, doi: 10.1109/WNYISPW57858.2022.9983488. URL
22. Chuprov, S., Khokhlov, I., Reznik, L., & Manghi, K. (2022). ``Multi-Modal Sensor Selection with Genetic Algorithms'' in 2022 IEEE Sensors, 2022, pp. 1-4, doi: 10.1109/SENSORS52175.2022.9967296. URL
23. Khokhlov, I., Chuprov, S., & Reznik, L. (2022). ``Integrating Security with Accuracy Evaluation in Sensors Fusion'' in 2022 IEEE Sensors, 2022, pp. 1-4, doi: 10.1109/SENSORS52175.2022.9967235. URL
24. Chuprov, S., Khokhlov, I., Reznik, L., & Shetty, S. (2022). ``Influence of Transfer Learning on Machine Learning Systems Robustness to Data Quality Degradation'' in 2022 International Joint Conference on Neural Networks (IJCNN), 2022, pp. 1-8, doi: 10.1109/IJCNN55064.2022.9892247. URL
25. Chuprov, S., Reznik, L., Obeid, A., & Shetty, S. (2022). ``How Degrading Network Conditions Influence Machine Learning End Systems Performance?'' in IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2022, pp. 1-6, doi: 10.1109/INFOCOMWKSHPS54753.2022.9798388. URL
26. Chuprov, S., Gataullin, R., Neverov, E., Belyaev, P., Kim, I., & Viksnin, I. (2022). ``Police Office Model Performance and Security Evaluation in a Simulated Group of Mobile Robots'' in The 5th International Conference on Future Networks & Distributed Systems (ICFNDS 2021). Association for Computing Machinery, New York, NY, USA, pp. 606–615, doi: 10.1145/3508072.3508195. URL
27. Chuprov, S., Viksnin, I., Kim, I., Melnikov, T., Reznik, L., & Khokhlov, I. (2021). ``Improving Knowledge Based Detection of Soft Attacks Against Autonomous Vehicles with Reputation, Trust and Data Quality Service Models'' in 2021 IEEE International Conference on Smart Data Services (SMDS), pp. 115-120. URL
28. Domnitsky, E., Mikhailov, V., Zoloedov, E., Alyukov, D., Chuprov, S., Marinenkov, E., & Viksnin, I. (2021). ``Software Module for Unmanned Autonomous Vehicle’s On-board Camera Faults Detection and Correction'' in CEUR Workshop Proceedings, Vol. 2893, pp. 1-10. URL
29. Lyakhovenko, Y., Viksnin, I., & Chuprov, S. (2021). ``Integrating Smart Contracts into Smart Factory Elements’ Informational Interaction Model'' in CEUR Workshop Proceedings, Vol. 2893, pp. 1-6. URL
30. Usova, M., Viksnin, I., & Chuprov, S. (2021). ``Informational Messages and Space Models Application in Smart Factory Concept'' in CEUR Workshop Proceedings, Vol. 2893, pp. 1-8. URL
31. Khanh, T.D., Komarov, I., Don, L.D., Iureva, R., & Chuprov, S. (2020). ``TRA: Effective Authentication Mechanism For Swarms Of Unmanned Aerial Vehicles'' in 2020 IEEE Symposium Series on Computational Intelligence, pp. 1852-1858, doi: 10.1109/SSCI47803.2020.9308140. URL
32. Melnikov, T., Lazarev, E., Berezovskaya, O., Chuprov, S., & Viksnin, I. (2020). ``Empirical Study on Premises Monitoring Algorithm Implementation in Mobile Robotic System'' in The International Conference ``Nonlinearity, Information and Robotics'', pp. 1-6, doi: 10.1109/NIR50484.2020.9290188. URL
33. Usova, M., Chuprov, S., & Viksnin, I. (2020). ``Informational Space and Messages Interaction Models for Smart Factory Concept'' in 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT, pp. 617-621, doi: 10.1109/MetroInd4.0IoT48571.2020.9138292. URL
34. Chuprov, S., Marinenkov, E., Viksnin, I., Reznik, L., & Khokhlov, I (2020). ``Image Processing in Autonomous Vehicle Model Positioning and Movement Control'' in IEEE 6th World Forum on Internet of Things (WF-IoT) Proceedings, pp. 1-6, doi: 10.1109/WF-IoT48130.2020.9221258. URL
35. Chuprov, S., Viksnin, I., Kim, I., Reznik, L., & Khokhlov, I. (2020). ``Reputation and Trust Models with Data Quality Metrics for Improving Autonomous Vehicles Traffic Security and Safety'' in Proc. IEEE/NDIA/INCOSE Syst. Secur. Symp, pp. 1-8, doi: 10.1109/SSS47320.2020.9174269. URL
36. Chuprov, S., Viksnin, I., Kim, I., & Nedosekin, G. (2019) ``Urban Intersection Management with Connected Infrastructure Objects and Autonomous Vehicles'' in 2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE), pp. 1-4, doi: 10.1109/ICCVE45908.2019.8964917. URL
37. Chuprov, S., Viksnin, I., Kim, I., & Usova, M. (2019). ``Intersection Management Tasks in Mobile Robotic System with Decentralized Control'' in CEUR Workshop Proceedings, vol. 2344, pp. 1-12. URL
38. Usova, M., Chuprov, S., Viksnin, I., Gataullin, R., Komarova, A., & Iuganson, A. (2019). ``Model of Smart Manufacturing System'' in International Symposium on Intelligent and Distributed Computing, pp. 356-362, doi: 10.1007/978-3-030-32258-8\_42. URL
39. Marinenkov, E., Chuprov, S., Viksnin, I., & Kim, I. (2019). ``Empirical Study on Trust, Reputation, and Game Theory Approach to Secure Communication in a Group of Unmanned Vehicles'' in CEUR Workshop Proceedings, vol. 2590, pp. 1-12. URL
40. Usova, M., Chuprov, S., Viksnin, I., & Baranova, O. (2019). ``Model of Secure Informational Messages for Ensuring Informational Interaction in Smart Factory'' in CEUR Workshop Proceedings, vol. 2590, pp. 1-8. URL
41. Viksnin, I., Lyakhovenko, J., Tursukov, N., Chuprov, S., & Sozinova, E. (2019). ``Empirical Study on Modeling of People Behavior in Emergency'' in CEUR Workshop Proceedings, vol. 2590, pp. 1-8. URL
42. Kim, I., Matos-Carvalho, J. P., Viksnin, I., Campos, L. M., Fonseca, J. M., Mora, A., & Chuprov, S. (2019). ``Use of Particle Swarm Optimization in Terrain Classification based on UAV Downwash'' in 2019 IEEE Congress on Evolutionary Computation (CEC), pp. 604-610, doi: 10.1109/CEC.2019.8790031. URL
43. Viksnin, I., Chuprov, S., Usova, M., & Zakoldaev, D. (2019). ``Police Office Model for Multi-agent Robotic Systems'' in IOP Conference Series: Materials Science and Engineering, vol. 497, no. 1, p. 012036, doi: 10.1088/1757-899X/497/1/012036. URL