SAMM 2020: Learning Models from Data

from Monday, 27 July 2020 (13:30) to Friday, 31 July 2020 (19:45)
Virtual event

        : Sessions
    /     : Talks
        : Breaks
27 Jul 2020
28 Jul 2020
29 Jul 2020
30 Jul 2020
31 Jul 2020
AM
PM
13:40 --- Opening ---
14:00 Lecture/exercises 1 - Feliks Nüske (Paderborn University)   ()
16:00 Lecture/exercises 1 - Benjamin Peherstorfer (New York University)   ()
18:00 Lecture/exercises 1 - J. Nathan Kutz (University of Washington)   ()
19:30
Posters 1 (until 20:30) ()
19:30 A function space random feature model for PDE solution maps - Nicholas H. Nelsen (Caltech)   ()
19:30 An optimization-based approach for the reduction of parametrized conservation laws with discontinuities - Mrs Marzieh Alireza Mirhoseini (University of Notre Dame)   ()
19:30 Analysis of bubble dynamics using data-driven dynamical systems and machine learning - Mr Andrew J. Gibson (Department of Mechanical and Aerospace Engineering, University of Colorado Colorado Springs)   ()
19:30 Analytical and Data-driven Models to Predict Algae Biofilm Growth in Water Treatment - Gerald Jones (Utah State University)   ()
19:30 Analytical and Learning Model of a Hybrid-Fluidic Elastomer Actuator for Reliable Control and Perturbation Detection - Uksang Yoo (The University of Texas at Austin)   ()
19:30 Analytical Modeling and Evaluation of Curvature-Dependent Distributed Friction Force in Tendon-Driven Continuum Manipulators - Mr Yang Liu (The University of Texas at Austin)   ()
19:30 Analyzing the Transition to Buffeting of a 2D Airfoil using the Dynamic Mode Decomposition - Mr Sathsara Dias (Clarkson University)   ()
19:30 Discovering the governing PDE of an active nematic system from video data - Connor Robertson (New Jersey Institute of Technology)   ()
19:30 Extrapolating Nuclear Masses using Bayesian Gaussian Process Regression - Mr Rahul Jain (Michigan State University )   ()
19:30 Learning age-related chronic disease progression from cognitive measurements - Cindy Catherine Orozco Bohorquez (Stanford University)   ()
19:30 Learning Constitutive Relations using Symmetric Positive Definite Neural Networks - Kailai Xu (Stanford University)   ()
19:30 Learning the Interfacial Area Equation from Data - Stephen Chen (University of California San Diego)   ()
19:30 Machine learning for parameters identification in structural joints models - Simone Gallas (KU Leuven, Department of Mechanical Engineering, Division LMSD; Core Lab DMMS-D, Flanders Make)   ()
19:30 Modulus-based iterative methods for constrained $\ell_p$-$\ell_q$ minimization - Dr Mirjeta Pasha (Arizona State University)   ()
19:30 MUQ-hIPPYlib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty - Ki-Tae Kim (University of California, Merced)   ()
19:30 Nonlinear model reduction for one-dimensional solidification process in additive manufacturing - Parisa Khodabakhshi (Oden Institute for Computational Engineering and Sciences, UT Austin)   ()
19:30 Optimizing Intense Laser-Plasma Interactions with Evolutionary Algorithms and Machine Learning - Joseph Smith (The Ohio State University)   ()
19:30 PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain - Han Gao (University Of Notre Dame)   ()
19:30 Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks - Mr Colby Wight (PNNL)   ()
19:30 System Identification by Sparse Bayesian Learning - Luning Sun (University of Notre Dame)   ()
19:30 Weak SINDy: Galerkin-Based Data-Driven Model Selection - Daniel Messenger (University of Colorado Boulder)   ()
14:00 Lecture/exercises 2 - Feliks Nüske (Paderborn University)   ()
16:00 Lecture/exercises 2 - Benjamin Peherstorfer (New York University)   ()
18:00 Lecture/exercises 2 - J. Nathan Kutz (University of Washington)   ()
19:30 --- Social event ---
14:00 Lecture/exercises 3 - Feliks Nüske (Paderborn University)   ()
16:00 Lecture/exercises 3 - Benjamin Peherstorfer (New York University)   ()
18:00 Lecture/exercises 3 - J. Nathan Kutz (University of Washington)   ()
19:30
Posters 2 (until 20:30) ()
19:30 A Hamiltonian Monte Carlo Bayesian Inference Approach Using Deep Learning for Modeling Metabolism - Christina Schenk (Basque Center for Applied Mathematics)   ()
19:30 Adaptive Interpolatory MOR by Learning the Error Estimator in the Parameter Domain - Mr Sridhar Chellappa (Max Planck Institute for Dynamics of Complex Technical Systems)   ()
19:30 Artificial neural network for bifurcating phenomena modelled by nonlinear parametrized PDEs - Federico Pichi (SISSA, International School for Advanced Studies)   ()
19:30 Convolutional Neural Networks for object detection in professional appliances - Laura Meneghetti (SISSA)   ()
19:30 Data-Driven Identification and Reduction of Dynamical Systems with the Loewner Framework - Dimitrios S. Karachalios (MPI-DRI)   ()
19:30 Data-driven metamodelling in Global Sensitivity Analysis - Mr Panagiotis Demis (Department of Chemical and Process Engineering, University of Surrey)   ()
19:30 Data-driven reduced-order modeling from noisy measurements: new results and future perspectives - Dr Ion Victor Gosea (MPI Magdeburg)   ()
19:30 Deep learning of multibody minimal coordinates for estimation - Andrea Angeli (KU Leuven, Flanders Make)   ()
19:30 Deep Neural Networks for Hyperbolic Conservation laws with Non-convex Flux - Dr Hadi Minbashian (Technical University of Darmstadt)   ()
19:30 Fusing Online Gaussian Process-Based Learning and Control for Scanning Quantum Dot Microscopy - Mr Maik Pfefferkorn (Otto-von-Guericke University Magdeburg)   ()
19:30 Kernel-based Active Subspaces with application to CFD problems using Discontinuous Galerkin method - Mr Francesco Romor (SISSA)   ()
19:30 Learning from Data for Traffic Control - Mr Urs Baumgart (Fraunhofer ITWM)   ()
19:30 Machine learning for parameter identification and model reduction of gradient-enhanced damage models for metal forming processes - Mr Robin Schulte (Institute of Mechanics, TU Dortmund University)   ()
19:30 Model adaptation for hyperbolic balance laws employing constraint aware neural networks - Mr Hrishikesh Joshi (Technical University of Darmstadt)   ()
19:30 Multipopulation mortality rates modelling and forecasting: The multivariate functional principal component analysis approach - Mr Ka Kin Lam (University of Leicester)   ()
19:30 One size does not fit all: Parameterized biomechanical models for crashworthiness simulations - Göktürk Kuru (Siemens Digital Industries Software)   ()
19:30 Prediction-Based Nature-Inspired Dynamic Optimization - Almuth Meier (SCHOTT AG)   ()
19:30 Real-time virtual acoustics using physics-informed data-driven techniques - Finnur Pind (Technical University of Denmark)   ()
19:30 Reduced order modelling for data assimilation in parametrized optimal control framework - Maria Strazzullo (SISSA, mathLab)   ()
19:30 Sensor selection for hyper-parameterized linear Bayesian inverse problems - Ms Nicole Aretz-Nellesen (RWTH Aachen)   ()
19:30 Towards Deep Learning Based Controllers with Nominal Closed Loop Stability Guarantees - Mr Hoang Hai Nguyen (Otto-von-Guericke University Magdeburg, Magdeburg, Germany)   ()
19:30 Wavelet based dynamic mode decomposition - Mr Manu Krishnan (PhD Candidate, Department of Aerospace and Ocean Engineering, Virginia Tech)   ()
13:00
Posters 3 (until 14:00) ()
13:00 A data-driven physics-informed finite-volume scheme for nonclassical undercompressive shocks - Mr Deniz A Bezgin (Technical University of Munich)   ()
13:00 Basis Generation Techniques for Symplectic Model Order Reduction - Patrick Buchfink (University of Stuttgart)   ()
13:00 Can machine learning methods be used to create parametrized reduced models of vibro-acoustic systems? - Quirin Aumann (Technical University of Munich, Chair of Structural Mechanics)   ()
13:00 Chance-constrained optimal control of hyperbolic supply systems - Kerstin Lux (Technical University of Munich)   ()
13:00 Data-based Approach for Fault Diagnosis of Hydropower Rotors - Mr Christian Sperber (Voith Hydro Holding GmbH & Co. KG)   ()
13:00 Data-based soil-tool interaction force prediction based on measurements and the Discrete Element Method - Mr Jonathan Jahnke (Fraunhofer ITWM)   ()
13:00 Data-driven computational continuum mechanics - Mr Vu Chau (University of Luxembourg )   ()
13:00 Data-Driven Learning of Reduced-Order Dynamics for a Parametrized Shallow Water Equation - Süleyman Yildiz (Institute of Applied Mathematics, Middle East Technical University, Ankara, Turkey)   ()
13:00 Data-driven Reduced Order Model of Flow-Induced Piezoelectric Energy Harvesters - Ms Lan Shang (University of Luxembourg)   ()
13:00 Deep Kernel approaches with a Neural-Network-like structure - Tizian Wenzel (University of Stuttgart)   ()
13:00 Deep learning based model reduction approaches in flow models - Yiran Wang (The Chinese University of Hong Kong)   ()
13:00 Deep learning of superstructures in turbulence - Manuel Schaller (TU Ilmenau) Friedrich Philipp (TU Ilmenau) Mitsuru Wilson (TU Ilmenau)   ()
13:00 Enhancing battery recharge performance by combined Machine Learning and PDE modelling - Mrs Angela Monti (University of Salento)   ()
13:00 Insights into squealing disk brakes through explainable machine learning for time series data - Merten Stender (Hamburg University of Technology)   ()
13:00 Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics - Mr Jonas Kneifl (Institute of Engineering and Computational Mechanics)   ()
13:00 Model Reduction for Advection Dominated Problems - Davide Torlo (University of Zurich)   ()
13:00 Physics Guided Deep-Learning Based Nonlinear Reduced Order Model for Aeroelastic Applications - Dr Rahul Halder (National University of Singapore)   ()
13:00 Quantifying incompressible two-phase flow fields from the interface movement using physics-informed neural networks - Mr Aaron Buhendwa (Technical University Munich, Chair of Aerodynamics and Fluid mechanics)   ()
13:00 Stochastic frequency domain surrogate models for linear structural dynamics - Felix Schneider (Technical University of Munich)   ()
13:00 Stochastic Grey-box Model of the Flow-Front Dynamics - Dr Rishi Relan (Siemens Energy, Technical University of Denmark, BML Munjal University)   ()
13:00 The Construction and Application of Surrogate Models for Sensitivity Analysis - Xifu Sun (Australian National University)   ()
13:00 The use of machine learning in Computational Fluid Dynamics for an economic approach to flow optimization problems. - Mr Georg Schatzdorfer (TU Graz)   ()
14:00 Lecture/exercises 4 - Feliks Nüske (Paderborn University)   ()
16:00 Lecture/exercises 4 - Benjamin Peherstorfer (New York University)   ()
17:30 --- Virtual group photo ---
18:00 Lecture/exercises 4 - J. Nathan Kutz (University of Washington)   ()
14:00 Lecture/exercises 5 - Feliks Nüske (Paderborn University)   ()
16:00 Lecture/exercises 5 - Benjamin Peherstorfer (New York University)   ()
18:00 Lecture/exercises 5 - J. Nathan Kutz (University of Washington)   ()
19:30 --- Closing ---