Humboldt-Universität zu Berlin - School of Business and Economics

Short-Bio

Vincent Gurgul is currently pursuing his PhD at the Chair of Information Systems. He completed his studies in Business Economics at the Humboldt University Berlin and the University of Warsaw, specializing in programming, data analysis, data visualization, and deep learning. Vincent has gained professional experience in the field of data analytics both in academia and in industry. He has presented his research on Natural Language Processing and Time Series Analysis at international conferences and is proficient in programming languages such as Python, R, and C.

Research Interests

Vincent’s research interests lie at the intersection of data analytics, deep learning, and information systems. His focus lies on applying advanced neural network architectures to solve complex problems in the realm of linguistic analysis and financial forecasting. His work aims to harness the power of data for insightful decision-making, with an emphasis on real-world applications and industry relevance.

Areas of interest include:

- Natural Language Processing
- Time Series Analysis
- Non-Euclidian Machine Learning
- Quantum Machine Learning
- Reinforcement Learning

Publications

V. Gurgul, S. Lessmann, W. K. Härdle (2025). Deep learning and NLP in cryptocurrency forecasting: Integrating financial, blockchain, and social media data. International Journal of Forecasting. https://doi.org/10.1016/j.ijforecast.2025.02.007

L. Vöge, V. Gurgul, S. Lessmann (2024). Leveraging zero-shot prompting for efficient language model distillation. ArXiv. https://doi.org/10.48550/arXiv.2403.15886

E. Bremer, T. Ermakova, B. Fabian, V. Gurgul, N. Martin (2022). Ethics of AI-Supported Autonomous Driving. Pacific Asia Conference on Information Systems (PACIS) 2022 - Proceedings. https://aisel.aisnet.org/pacis2022/289/

Grants

Individual Strategic Partnership Grant for a research stay at the National University of Singapore (NUS), "Quantum Algorithms for Reinforcement Learning", funded by the Berlin University Alliance (BUA) within the Strategic Partnerships Program (2024).

Reviewing

Peer-reviewing service for various leading international journals and conferences:

- International Journal of Forecasting (IJF)
- Intelligent Systems with Applications (ISWA)
- Knowledge and Information Systems (KAIS)
- International Conference on Business Informatics (WI)

Teaching

Tutorial sessions and exam preparation/grading for various graduate and postgraduate courses:

- Deep Learning for Text Analytics (DeLTA): SS 24, SS 25
- Seminar Applied Predictive Analytics (APA): SS 24
- Introduction to Python Programming for Machine Learning and AI (IPML): WS 23/24, WS 24/25
- Seminar Information Systems (IS): WS 23/24
- Strategy, Organization and IT (SOIT): SS 23, SS 24
- Advanced Data Analytics for Management Support (ADAMS): SS 22
- Business Analytics and Data Science (BADS): WS 21/22, WS 22/23