Clemens Heitzinger
Associate Prof. Dr.techn. Dipl.-Ing.
Research Areas
- Partial Differential Equations, Stochastic Differential Equations, Stochastic finite element methods, Multi-body problems, Machine Learning
About
Reinforcement learning; Bayesian methods for ordinary- and partial-differential-equation models; large language models.
Role
-
Associate Professor
Machine Learning, E194-06
Courses
2024W
- Bachelor Thesis in Computer Science / 194.112 / PR
- CAIML seminar / 192.138 / SE
- Generative AI / 194.154 / VU
- Interdisciplinary Project in Data Science / 194.147 / PR
- Introduction to Machine Learning / 194.025 / VU
- Project in Computer Science 1 / 194.145 / PR
- Scientific Research and Writing / 193.052 / SE
- Seminar for PhD Students / 194.110 / SE
2025S
- Bachelor Thesis in Computer Science / 194.112 / PR
- Privatissimum for Doctor's Thesis / 194.028 / PV
- Seminar for PhD Students / 194.110 / SE
Projects
-
Reliable reinforcement learning for sustainable enery systems
2023 – 2025 / Austrian Research Promotion Agency (FFG)
Publications
- A Short Introduction to Artificial Intelligence: Methods, Success Stories, and Current Limitations / Clemens Heitzinger, & Stefan Woltran. (2024). A Short Introduction to Artificial Intelligence: Methods, Success Stories, and Current Limitations. In H. Werthner, C. Ghezzi, & J. Kramer (Eds.), Introduction to Digital Humanism : A Textbook (pp. 135–149). Springer. https://doi.org/10.1007/978-3-031-45304-5_9
- Improving sensor interoperability between contactless and contact-based fingerprints using pose correction and unwarping / Ruzicka, L., Dominik Söllinger, Kohn, B., Heitzinger, C., Uhl, A., & Strobl, B. (2023). Improving sensor interoperability between contactless and contact-based fingerprints using pose correction and unwarping. IET Biometrics, 2023, Article 7519499. https://doi.org/10.1049/2023/7519499
- Development of a reinforcement learning algorithm to optimize corticosteroid therapy in critically ill patients with sepsis / Bologheanu, R., Kapral, L., Laxar, D., Maleczek, M., Dibiasi, C., Zeiner, S., Agibetov, A., Ercole, A., Thoral, P., Elbers, P., Clemens Heitzinger, & Kimberger, O. (2023). Development of a reinforcement learning algorithm to optimize corticosteroid therapy in critically ill patients with sepsis. Journal of Clinical Medicine, 12(4), Article 1513. https://doi.org/10.3390/jcm12041513
- Bayesian estimation of physical and geometrical parameters for nanocapacitor array biosensors / Stadlbauer, B., Cossettini, A., Morales Escalante, J. A., Pasterk, D., Scarbolo, P., Taghizadeh, L., Heitzinger, C., & Selmi, L. (2019). Bayesian estimation of physical and geometrical parameters for nanocapacitor array biosensors. Journal of Computational Physics, 397, Article 108874. https://doi.org/10.1016/j.jcp.2019.108874
Awards
-
PDE Models for Nanotechnology
2013 / START Prize / Austria / Website -
START-Preis
2013 / START-Programm / Austria -
Erwin Schrödinger Fellowship (FWF)
2003 / Schrödinger-Stipendium / Austria
And more…
Soon, this page will include additional information such as reference projects, activities as journal reviewer and editor, memberships in councils and committees, and other research activities.
Until then, please visit Clemens Heitzinger’s research profile in TISS .