- Founder at DatenVorsprung and PhD student at TU Wien
- Cyber-Physical Systems Group | Institute of Computer Engineering
- TU Wien, Austria
- www.DatenVorsprung.at
- Emails: sophie [at] datenvorsprung.at | sophie.neubauer [at] tuwien.ac.at
Research Interests
My vision: a future with safe and trustworthy AI in safety-critical environments
- Reachability Analysis of cyber-physical systems with neural network controllers
- Stochastic Reachability Analysis
- Stochastic Global Optimization
- Deep Learning based recommender systems
- Machine Learning
- Artificial Intelligence
Current Position
- Founder at DatenVorsprung and PhD student in the Doctoral College Logical Methods in Computer Science, within Cyber-Physical Systems Group.
Education
- MSc: Statistics and Mathematics in Economics, TU Wien
- BSc: Statistics and Mathematics in Economics, TU Wien
Work Experience
- Since 2020: Founder & CTO at DatenVorsprung GmbH
- Since 2017: Advisor at Absolut Ticket GmbH
- 2009-2017: Technical Manager and then CEO at Wiener Mozart Orchester Konzertveranstaltungs GmbH
Awards and Honors
- IEEE Paper Prize: TC Outstanding Student Paper Prize for the CDC-20 paper "Lagrangian Reachtubes: The Next Generation"
- INiTS: Invited as a Keynote Speaker at „Women in Health IT Breakfast“ (organized by INiTS) about "The strength of vision: a future with safe and trustworthy AI in safety- critical environments".
- Degree with honors: TU Wien - Master and Bachelor title with honors
- TUtheTOP: Participated in the high potential program “TUtheTOP” of TU Wien
Press and media
- Factory magazine: How to provide safe AI for industry
- FWF Scilog magazine: Project of the week and first page article in FWF Scilog magazine: „Leading edge with secure data“
- FWF annual report: Article on „Intelligent Contact Tracing“
- DerStandard: Newspaper article on „Contact-Tracing with data privacy“
First and Last Author Publications
- J. Lemmel, Z. Babaiee, M. Kleinlehner, I. Majic, P. Neubauer, J. Scholz, R. Grosu, and S.A. Neubauer (née Gruenbacher) (2022) "Deep-Learning vs Regression: Prediction of Tourism Flow with Limited Data", Accepted for publication at the IJJCAI'22 Workshop AI for Time Series Analysis.
- S.A. Neubauer (née Gruenbacher), R. Grosu (2022) "Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques", Accepted for publication at Henzinger-60 (Thomas Henzinger Festschrift - Conference celebrating his 60th birthday).
- S.A. Gruenbacher, M. Lechner, R. Hasani, D. Rus, T.A. Henzinger, S.A. Smolka, and R. Grosu (2022) "GoTube: Scalable Stochastic Verification of Continuous-Depth Models", Accepted for publication at the Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22).
- S. Gruenbacher, R. Hasani, M. Lechner, J. Cyranka, S.A. Smolka, and R. Grosu (2021) "On the Verification of Neural ODEs with Stochastic Guarantees", Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 2021, pages 11525-11535.
- S. Gruenbacher, J. Cyranka, M. Lechner, M. A. Islam, S. A. Smolka and R. Grosu, "Lagrangian Reachtubes: The Next Generation," 2020 59th IEEE Conference on Decision and Control (CDC), Jeju, Korea (South), 2020, pp. 1556-1563, doi: 10.1109/CDC42340.2020.9304042.
- S. Gruenbacher, J. Cyranka, M.A. Islam, M. Tschaikowski, S.A. Smolka, and R. Grosu (2019) "Under the Hood of a Stand-Alone Lagrangian Reachability Tool". In G. Frehse and M. Althoff, editors, ARCH19. 6th International Workshop on Applied Verification of Continuous and Hybrid Systems, part of CPS-IoT Week 2019, Montreal, QC, Canada, April 15, 2019, volume 61 of EPiC Series in Computing, pages 211–219. EasyChair, 2019