Iaroslav Shcherbatyi

Position: Research Associate
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Iaroslav Shcherbatyi is a research assistant at the chair in Information and Service Systems (ISS), faculty of Business Administration, Saarland University, Germany.

Short Biography

Iaroslav Shcherbatyi completed a Bachelor’s program at the Chernivtsi National University, Ukraine and a Master’s program in Computer Science program at the University of Saarland. His master thesis topic is “Convexification of Learning From Constraints”, where he developed a novel approach of solving a large class of machine learning problems. During his Master’s program he worked at the Max Planck Institute for Informatics, where he was in charge of a project on human - computer collaboration.

Research Interests

His research interests lie in the areas of mathmematical optimization, artificial intelligence and big data.

All Publications:


Öksüz, N., Shcherbatyi, I., Kowatsch, T., Maaß, W.

A Data-analytical System to Predict Therapy Success for Obese Children, Proceedings of the 39th International Conference on Information Systems (ICIS), 2018.

Shcherbatyi, I. & Maaß, W.

Joint Input and Predictive Model Parameters Selection for Financial Forecasting, European Conference on Data Analysis (ECDA), 2018.

Maaß, W. & Shcherbatyi, I.

Inductive Discovery By Machine Learning for Identification of Structural Models, The 37th International Conference on Conceptual Modeling (ER), 2018.


Maaß, W., Shcherbatyi, I. & Marquardt, S.

Real-time Decision Making with Smart Farming Services, Proc. of 75th International Conference on Agricultural Engineering (AgEng), 2017.
PDF (702 KB) - BibTeX

Öksüz, N., Biswas, R., Shcherbatyi, I., Maaß, W.

Davis, F., Riedl, R., vom Brocke, J., Léger, P. M., Randolph, N. (ed.)
Measuring Biosignals of Overweight and Obese Children for Real-time Feedback and Predicting Performance, Information Systems and Neuroscience - Gmunden Retreat on NeuroIS 2017, Springer, 2017.

Maaß, W. & Shcherbatyi, I.

Data-Driven, Statistical Learning Method for Inductive Confirmation of Structural Models, Hawaii International Conference on System Sciences (HICSS), 2017.


Iaroslav Shcherbatyi & Bjoern Andres

Bodo Rosenhahn & Bjoern Andres (ed.)
Convexification of Learning from Constraints, Lecture Notes in Computer Science, 2016, 9796, pp. 79-90.