Maryan Rizinski

Lecturer

Title Lecturer
Email rizinski@bu.edu
Education Ph.D. University Ss. Cyril and Methodius in Skopje
M.S. University Ss. Cyril and Methodius in Skopje
B.S. University Ss. Cyril and Methodius in Skopje

Maryan Rizinski received his Ph.D. in computer science and engineering and his M.S. and B.S. degrees in electrical engineering and information technologies from the University Ss. Cyril and Methodius in Skopje. He is currently a manager of technology consulting at Bosch, with over ten years of industry experience leading globally-distributed software engineering teams. His expertise spans multiple aspects of the software project lifecycle management, from planning, requirement gathering, and analysis, estimations to driving delivery, rollout, and troubleshooting for international customers. Throughout his professional career, he has managed the implementation of Internet of Things (IoT) and fiber-optics infrastructure projects and has been mentoring and consulting startup IT companies. He is also a part-time lecturer of computer science at Boston University’s Metropolitan College where he is teaching and facilitating networking and data science classes. His research focuses on novel approaches for using machine learning (ML) and natural language processing (NLP) in the financial industry and other related areas. His research aims to enable more accurate decision-making and address fundamental problems of improving the explainability of deep-learning models and addressing ML-related ethical challenges in finance applications. His past research interests focused on computer networking, wireless communications, and new Internet and IoT architectures.

Courses

Research Interests

Scholarly Works

Rizinski, M., Jankov, A., Sankaradas, V., Pinsky, E., Mishkovski, I., & Trajanov, D. (2024). Comparative Analysis of NLP-Based Models for Company Classification. Information, 15(2), 77.

Rizinski, M., Peshov, H., Mishev, K., Jovanovik, M., & Trajanov, D. (2024). Sentiment Analysis in Finance: From Transformers Back to eXplainable Lexicons (XLex). IEEE Access, 10, 7170–7198.

Domazetoski, V., Rizinski, M., Trajanov, D., & Kocarev, L. (2023). Sensitivity analysis of shock distributions in the world economy. Plos one, 18(10), e0293524.

Rizinski, M., Jankov, A., Sankaradas, V., Pinsky, E., Miskovski, I., & Trajanov, D. (2023). Company classification using zero-shot learning. In 20th International Conference on Informatics and Information Technologies (CIIT 2023). Krushevo, North Macedonia, May 4-6, 2023, pp. 67–72. arXiv preprint arXiv:2305.01028.

Rizinski, M., Mishev, K., Chitkushev, L. T., Vodenska, I., & Trajanov, D. (2023). Using NLP transformer models to evaluate the relationship between ethical principles in finance and machine learning. In 13th International Conference on Information Society and Technology (ICIST 2023). Kopaonik, Serbia, March 12-15, 2023, pp. 100–111.

Rizinski, M., Peshov, H., Mishev, K., Chitkushev, L. T., Vodenska, I., & Trajanov, D. (2022). Ethically Responsible Machine Learning in Fintech. IEEE Access, 10, 97531-97554.

Rizinski, M., Day, J., & Chitkushev, L. (2020, February). IoT Architecture Based on RINA. In 2020 23rd Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN) (pp. 41-45). IEEE.

Rizinski, M., & Kafedziski, V. (2013). Ergodic rates of the fast Rayleigh fading relay channel for different cooperative strategies. Serdica Journal of Computing, 7(2), 101-114.

Rizinski, M., & Kafedziski, V. (2013, October). Outage probability of AF, DF and CF cooperative strategies for the slow fading relay channel. In 2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TELSIKS) (Vol. 2, pp. 609-612). IEEE.

Rizinski, M., & Kafedziski, V. (2011, October). Achievable rates of the amplify-and-forward strategy for the Gaussian relay channel. In 2011 10th International Conference on Telecommunication in Modern Satellite Cable and Broadcasting Services (TELSIKS) (Vol. 2, pp. 501-504). IEEE.

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