Affiliation: My name is Daniel Bartl and I am currently an
Presidential Young Professor
National University of Singapore
Department of Mathematics, jointly with
Department of Statistics & Data Science
Contact: bartld at nus dot edu dot sg; Office 07.09, S17 Science Drive
Research interests:
Data Science: High-Dimensional Probability & Statistics, robust Optimization
Optimal Transport
Mathematical Finance
Funding:
Sole PI of PYP grant ``Robust Statistical Learning from Complex Data", 500.000 SGD
Sole PI of FWF project P34743 (terminated early due to relocation), ca 400.000 Euro
Sole PI of FWF project ESP31, ca 300.000 Euro
Awards:
Elected member of European Mathematical Society - Young Academy, 2024-2027
Prize for best PhD thesis (German Math. Society - probability group)
Bruti-Liberaty prize (Bachelier Finance society)
Prize for best PhD thesis (Math. and Stat. department, Univ. Konstanz) Excellence Award (VFVH)
Papers (see also google scholar):
Robust, sub-Gaussian mean estimators in metric spaces with G. Lugosi, R. Oliveira, Z. Rico
preprint
Do we really need the Rademacher complexities? with S. Mendelson
preprint
Uniform mean estimation via generic chaining with S. Mendelson
preprint
The Wasserstein Space of Stochastic Processes in Continuous Time with M. Beiglboeck, G. Pammer, S. Schrott, X. Zhang
preprint
Optimal nonparametric estimation of the expected shortfall risk with S. Eckstein
preprint
Numerical method for nonlinear Kolmogorov PDEs via sensitivity analysis with A. Neufeld, K. Park
preprint
A uniform Dvoretzky-Kiefer-Wolfowitz inequality with S. Mendelson
Probability Theory and Related Fields, in press
Sensitivity of robust optimization problems under drift and volatility uncertainty with A. Neufeld, K. Park
Finance and Stochastics, in press
Structure preservation via the Wasserstein distance with S. Mendelson
Journal of Functional Analysis, in press
Empirical approximation of the gaussian distribution in R^d with S. Mendelson
Advances in Mathematics, in press
The Wasserstein space of stochastic processes with M. Beiglboeck, G. Pammer
Journal of the European Mathematical Society, in press
Optimal non-gaussian Dvoretzky-Milman embeddings with S. Mendelson
International Mathematics Research Notices, (10):8459-8480, 2024
Sensitivity of multiperiod optimization problems with respect to the adapted Wasserstein distance with J. Wiesel
Siam Journal on Financial Mathematics, 14(2):704-720, 2023
Random embeddings with an almost Gaussian distortion with S. Mendelson
Advances in Mathematics, 400:108261, 2022
On Monte-Carlo methods in convex stochastic optimization with S. Mendelson
Annals of Applied Probability, 32(4):3146-3198, 2022
Limits of random walks with distributionally robust transition probabilities with S. Eckstein, M. Kupper
Electronic Communications in Probability, 26(28):1-13, 2021
Duality theory for robust utility maximization with M. Kupper, A. Neufeld
Finance and Stochastics, 25(3):469-503, 2021
Sensitivity analysis of Wasserstein distributionally robust optimization problems with S. Drapeau, J. Obloj, J. Wiesel
Proceedings of the Royal Society A, 477:2256, 2021
Mathematics of Operations Research, 48(4):2129-2155, 2023
Estimating processes in adapted Wasserstein distance with J. Backhoff, M. Beiglboeck, J. Wiesel
Annals of Applied Probability, 32(1):529-550, 2022
Functional inequalities for forward and backward diffusions with L. Tangpi
Electronic Journal of Probability, 25(94):1-22, 2020
All adapted topologies are equal with J. Backhoff, M. Beiglboeck, M. Eder
Probability Theory and Related Fields, 78(3):1125–1172, 2020
Adapted Wasserstein distances and stability in mathematical finance with J. Backhoff, M. Beiglboeck, M. Eder
Finance and Stochastics, 24(3):601-632, 2020
Stochastic integration and differential equations for typical paths with M. Kupper, A. Neufeld
Electronic Journal of Probability, 24(97):1-21, 2019
Robust expected utility maximization with medial limits with P. Cheridito, M. Kupper
Journal of Mathematical Analysis and Applications, 471(1-2):752-775, 2019
Pathwise superhedging on prediction sets with M. Kupper, A. Neufeld
Finance and Stochastics, 24(1):215-248, 2020
Marginal and dependence uncertainty: bounds, optimal transport, and sharpness with M. Kupper, T. Lux, A. Papapantoleon
Siam Journal on Control and Optimization, 60(1), 410-434, 2022
Computational aspects of robust optimized certainty equivalents and option pricing with S. Drapeau, L. Tangpi
Mathematical Finance, 30(1):287-309, 2020
Duality for pathwise superhedging in continuous time with M. Kupper, D. Prömel, L. Tangpi
Finance and Stochastics, 23(3):697-728, 2019
A pointwise bipolar theorem with M. Kupper
Proceedings of the American Mathematical Society, 147(4):1483-1495, 2019
Stochastic Processes and their Applications,130(2):785-805, 2020
Annals of Applied Probability, 29(1):577-612, 2019
Recent teaching:
Lecturer "Financial Derivatives: Modelling and Computation", QF5209
Lecturer Seminar "High-dimensional probability theory for Data Science", Uni. Vienna 2024/25
Guest lecturer for tutorials "Stochastics for Engineers", Uni. Klagenfurt 2023/24
Minicourse "Introduction to mathematics of statistical learning theory" at Vienna school of mathematics, 2023
Minicourse "Introduction to geometric aspects of statistical learning theory" at NTU Singapore 5 weeks, 2023
Recent / future activities:
Co-organizer of workshop "Annual Summer School on Mathematical Aspects of Data Science" 2026
Co-organizer of workshop "Quantitative Finance Conference + summerschool" 2026
Co-organizer of workshop "Probabilistic Mass Transport - from Schrödinger to Stochastic Analysis" 2026
Co-organizer of workshop "Optimal Transport for Complex Data" 2025
Recent talks + travel:
AI Theory Seminar (talk) 2026
QMF conference Sydney (talk) 2025
SUTD research seminar (talk) 2025
WU Vienna Statistics Reserach Seminar(talk) 2025
BANFF workshop Bridging Theory and Practice in Finance (talk) 2025
Eighteenth Annual Risk Management Conference (talk) 2025
NUS QF conference (talk) 2025
TU Graz, Colloquium in Data Science (talk) 2025
UC Irvine, Combinatorics and Probability seminar (talk) 2025
Research stay UC Irvine (1 week) 2025
Research stay Stanford (2 weeks) 2025
Research stay UC Berkeley (2 weeks) 2025
Oxford, Stochastic analysis and mathematical finance seminar (talk) 2025
BANFF workshop Modeling, Learning and Understanding (talk) 2024
Research stay ETH (1 week) 2024
Habilitation faculty research presentation at Uni Vienna (talk) 2024
Mathematical aspects of Learning Theory - 20 years later (participant) 2024
Austrian Stochastic Days (talk) 2024
Soft methods in Probability and Statistics (talk) 2024
National University of Singapore (talk) 2024
Machine Learning and Data Science Uni Vienna (talk) 2024
Mathematics for Data Science, Uni Vienna (talk) 2024
Statistics Colloquium at TU Graz (talk) 2024
Mathematical and Statistical Methods for Actuarial Sciences and Finance (talk) 2024
Research stay ETH (1 week) 2024
Austrian Statistics days (talk) 2024
Research stay ETH (2 weeks) 2024
HIM Bonn, High dimensional phenomena: geometric and probabilistic aspects (participant) 2024
Research stay UPF Barcelona (2 weeks) 2024
Foundations of Machine Learning in Finance, ISOR Vienna (talk) 2024
Co-authors: Julio Backhoff, Mathias Beiglboeck, Patrick Cheridito, Samuel Drapeau, Stephan Eckstein, Manu Eder, Michael Kupper, Thibaut Lux, Gabor Lugosi, Shahar Mendelson, Ariel Neufeld, Jan Obloj, Roberto Imbuzeiro Oliveira, Gudmund Pammer, Antonis Papapantoleon, Kyunghyun Park, David Proemel, Zoraida Rico, Stefan Schrott, Ludovic Tangpi, Johannes Wiesel, Xin Zhang