Stochastic Partial Differential Equations

Stochastic partial differential equations arise naturally in several models of random phoenomena, in such fields as biology, physics and engineering. In particular, while deterministic models represent an efficient tool to describe time-evolution of real-world systems, they fail in rendering the presence of possible microscopic uncertainty of the model. Such randomness components may be related to several factors and are usually tracked through the introduction of a stochastic source of randomness in the equations involved. One of the most challenging goal of the mathematics of stochastic partial differential equations is the understanding of quantitative and qualitative properties of solutions and their dependence on the coefficients.

The aim of the workshop is to bring together leading experts, as well as a number of talented young researchers and to share fresh information on new results and future perspectives. The stay at the Institute will promote informal interaction progress in collaborations.

Feb. 12, 2024
09:00 — 09:20
Registration
09:20 — 09:30
Opening
10:15 — 10:45
Coffee Break
11:30 — 12:10
12:15 — 14:00
Lunch Break
14:00 — 14:40
15:30 — 16:00
Coffee Break
Feb. 13, 2024
09:00 — 09:40
István Gyöngy (U Edinburgh)
On parabolic SPDEs with singular coefficients
09:45 — 10:25
10:30 — 11:00
Coffee Break
11:00 — 11:40
12:30 — 14:00
Lunch Break
14:45 — 15:25
15:30 — 16:00
Coffee Break
19:00 — 22:00
Social Dinner

Heuriger Schübel-Auer, https://www.schuebel-auer.at/

Feb. 14, 2024
10:30 — 11:00
Coffee Break
11:00 — 11:40
Martin Ondreját (Czech Academy of Sciences, Prague)
Numerical approximation of the stochastic total variation flow
Feb. 15, 2024
09:00 — 09:40
09:45 — 10:25
10:30 — 11:00
Coffee Break
11:00 — 11:40
12:30 — 14:00
Lunch Break
14:00 — 14:40
15:30 — 16:00
Coffee Break
16:00 — 16:40

unfortunatly chancelled!

Feb. 16, 2024
09:00 — 09:40
10:30 — 11:00
Coffee Break
11:00 — 11:40
11:45 — 12:25
12:30 — 12:35
Closing

Organizers

Name Affiliation
Sandra Cerrai University of Maryland
Martin Hairer Imperial College London
Carlo Marinelli University College London
Eulalia Nualart University of Barcelona
Luca Scarpa Politecnico di Milano
Ulisse Stefanelli University of Vienna

Attendees

Name Affiliation
Antonio Agresti Technical University Delft
Lukas Anzeletti TU Wien
Marco Bagnara Scuola Normale Superiore
Yuri Bakhtin New York University
Viorel Barbu University Al.I.Cuza
Timo Bertolini University of Vienna
Ajay Chandra Imperial College London
Federico Cornalba University of Bath
Sonja Cox University of Amsterdam
Kostantinos Dareiotis University of Leeds
Arnaud Debussche École normale supérieure de Rennes
Benedetta Ferrario University of Pavia
Mohammud Foondun University of Strathclyde
Peter K. Friz Technical University Berlin
Paul Gassiat Paris Dauphine University
Benjamin Gess Universität Bielefeld
Giuseppina Guatteri Politecnico di Milano
István Gyöngy University of Edinburgh
Erika Hausenblas Montanuniversität Leoben
Ansgar Jüngel Technical University of Vienna
Helena Kremp TU Wien
Tijana Levajkovic TU Wien
Chengcheng Ling University Augsburg
Jan Maas Institute of Science and Technology Austria
Federica Masiero University of Milano-Bicocca
Annie Millet University Paris Sorbonnes
Katerina Nik University of Vienna
Martin Ondreját Czech Academy of Sciences
Carlo Orrieri University of Pavia
Chiara Rigoni University of Vienna
Benjamin Robinson University of Vienna
Michael Röckner Universität Bielefeld
Christian Schmeiser University of Vienna
Stefan Schrott University of Vienna
Katharina Schuh Technical University of Vienna
Eduard Stefanescu Technische Universität Graz
Fabio Toninelli Technical University of Vienna
Jan van Neerven Technical University Delft
Hendrik Weber University of Münster
Ivan Yaroslavtsev University of Hamburg
Immanuel Zachhuber Freie Universität Berlin
Margherita Zanella Politecnico di Milano
Tusheng Zhang University of Manchester
Aleksandra Zimmermann Clausthal University of Technology
Preview of Erika Hausenblas - A stochastic Schauder Theorem and biochemical nonlinear systems of SPDEs
Erika Hausenblas (Montanuniversität Leoben): A stochastic Schauder Theorem and biochemical nonlinear systems of SPDEs
Feb. 12, 2024 14:00 — 14:40
Preview of Paul Gassiat - Gradient flow on control space with rough initial condition
Paul Gassiat (Dauphine U, Paris): Gradient flow on control space with rough initial condition
Feb. 13, 2024 14:45 — 15:25
Preview of Martin Ondreját - Numerical approximation of the stochastic total variation flow
Martin Ondreját (Czech Academy of Sciences, Prague): Numerical approximation of the stochastic total variation flow
Feb. 14, 2024 11:00 — 11:40
Preview of Peter K. Friz - Analyzing classes of SPDEs via RSDEs
Peter K. Friz (TU Berlin): Analyzing classes of SPDEs via RSDEs
Feb. 16, 2024 09:00 — 09:40
Preview of Ajay Chandra - A priori bounds for the generalised parabolic Anderson model
Ajay Chandra (Imperial College London): A priori bounds for the generalised parabolic Anderson model
Feb. 16, 2024 11:00 — 11:40
At a glance
Type:
Workshop
When:
Feb. 12, 2024 — Feb. 16, 2024
Where:
ESI Boltzmann Lecture Hall
Organizer(s):
Sandra Cerrai (U of Maryland)
Martin Hairer (Imperial College London)
Carlo Marinelli (University College London)
Eulalia Nualart (U Barcelona)
Luca Scarpa (Politecnico Milano)
Ulisse Stefanelli (U of Vienna)