On August 23rd, 2024, Frederik Boe Hüttel successfully defended his Ph.D. thesis entitled “Deep Bayesian Modelling for Uncertainty Estimation in Transportation Systems“.

Congratulations, Frederik!

He was supervised by Professor Francisco Camara Pereira and Associate Professor  Filipe Rodrigues.

Examiners were Associate Professor Michael Riis Andersen (DTU Compute), Professor Constantinos Antoniou (Technical University of Munich) and Professor Latifa Oukhellou (Gustave Eiffel University).

The defense session was chaired by Associate Professor Jesper Bláfoss Ingvardson.

List of Papers:

• Paper 1: Hüttel, F. B., Peled, I., Rodrigues, F., & Pereira, F. C. (2022). Modeling censored mobility demand through censored quantile regression neural networks. IEEE Transactions on Intelligent Transportation Systems, 23(11), 21753-21765.

• Paper 2: Hüttel, F. B., Rodrigues, F., & Pereira, F. C. (2023). Mind the gap: Modelling difference between censored and uncensored electric vehicle charging demand. Transportation Research Part C: Emerging Technologies, 153, 104189.

• Paper 3: Hüttel, F. B., Rodrigues, F., & Pereira, F. C. (2023). Deep Evidential Learning for Bayesian Quantile Regression. arXiv preprint arXiv:2308.10650.

• Paper 4: Hüttel, F. B., Riis, C., Rodrigues, F., & Pereira, F. C. (2024). Bayesian Active Learning for Censored Regression. arXiv preprint arXiv:2402.11973.

For more information, feel free to contact Frederik via his Linkedin page.