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J.M. Suk MSc (Julian)

PhD Candidate

About Me

I am a PhD student from Munich, Germany, working on deep learning for 3D medical data in the form of finite-element meshes and point clouds. I employ graph-convolutional neural networks (GCN) and use symmetry (geometric deep learning) and physics-informed deep learning to boost their performance.

Additionally, I am interested in the mathematical foundations of deep learning through the application of functional analysis and identification of the interplay with dynamical systems and partial differential equations.

I am excited about (super)computers, especially Linux-based systems and clusters. Consequently, I wrote my master's thesis on Hessian-based optimisation of deep neural networks in the context of high performance computing (HPC).

Expertise

Engineering & Materials Science
Computational Fluid Dynamics
Computer Simulation
Convolutional Neural Networks
Deep Learning
Hemodynamics
Network Architecture
Parameter Estimation
Shear Stress

Publications

Recent
Suk, J. M., de Haan, P., Lippe, P. , Brune, C. , & Wolterink, J. M. (2022). Mesh convolutional neural networks for wall shear stress estimation in 3D artery models. In E. Puyol Antón, A. Young, A. Suinesiaputra, M. Pop, C. Martín-Isla, M. Sermesant, O. Camara, & K. Lekadir (Eds.), Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge: 12th International Workshop, STACOM 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Revised Selected Papers (pp. 93-102) https://doi.org/10.1007/978-3-030-93722-5_11

Google Scholar Link

Courses Academic Year  2021/2022

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
 

Contact Details

Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11), room 3006
Hallenweg 19
7522NH  Enschede
The Netherlands

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University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11)
Hallenweg 19
7522NH  Enschede
The Netherlands

Navigate to location

Mailing Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
P.O. Box 217
7500 AE Enschede
The Netherlands