- Evaluating acceleration models and respective stochasticity towards a real-time forecasting model for landslides. Master thesis, 2023 more…
- Physics-Informed Geometric Deep Learning for Molecular Property Prediction. Master thesis, 2023 more…
- Machine Learning in the Context of a Real-Time Education in Gaming. Master thesis, 2023 more…
- Decentralized Mutual Exclusion for Mobile Robots at Shared Resources in Complex. Master thesis, 2023 more…
- Implementing a learning-rate scheduler in a Newton-CG Optimizer for Deep Learning. Bachelor thesis, 2022 more…
- Transfer Learning and Dynamic Loading in TUM-Lens. Master thesis, 2022 more…
- Efficient and Scalable Kernel Matrix Approximation using Hierarchical Decomposition. Master thesis, 2022 more…
- Second-Order Optimization Methods for Bayesian Neural Networks. Master thesis, 2021 more…
- Extending a Newton-CG Second-order Optimizer to Natural Language Processing. Bachelor thesis, 2021 more…
- Training Deep Convolutional Neural Networks on the GPU Using a Second-Order Optimizer. Bachelor thesis, 2020 more…
- Implementing a TensorFlow-Slim based Android app for image classification. Bachelor thesis, 2020 more…
- Application of second-order optimisation for large-scale deep learning. Master thesis, 2020 more…
- Integrated approach of Random Projections and Sparse Grids for Density estimation. Master thesis, 2020 more…
- Python Software Suite of Geometric-Oblivious FMM. IDP-Arbeit, 2020 more…
- Comparison of distance metrics for MDS based NLDR using CNNs. Bachelor thesis, 2020 more…
Severin Reiz
Technical University of Munich
TUM School of CIT
Department of Computer Science
Boltzmannstrasse 3
85748 Garching
Germany
Office: MI 02.05.058
Mail: reiz (at) in.tum.de
Tel: +49-89-289-18603
Office Hours: by arrangement
Background
- Doctoral candidate, TUM Graduate School - IGSSE
- Research Associate (Wissenschaftlicher Mitarbeiter) at TUM SCCS since July 2017
- M.Sc. with Honours in Computational Science and Engineering, Technical University of Munich, 2017
- M. Sc. Thesis at University of Texas at Austin, USA (George Biros)
- Seminar Thesis at Norwegian University of Science and Technology, Trondheim and SINTEF
- B.Sc. Engineering Science, Technical University of Munich, 2014
Open and running student projects
Topics change (frequently) with my ongoing work and depend mostly on the interests and experience of the student. It is best to contact me directly if you are interested in a thesis or student project.
See also the list of Student Projects at our chair.
Do you want to know what other students are working on in our chair? You are warmly encouraged to attend their presentations at the SCCS Colloquium! Come to get ideas, meet your potential supervisor, or to learn from the style of others for your own presentation.
Open student projects
Running student projects
We are working on an android app for live image classification (locally on your device). Feel free to download the Android package (apk)
Past student projects and Theses advised
Teaching
Winter semester 2020/21
- Seminar Computational Aspects of Machine Learning: Link to application page Mooodle
Summer semester 2020
Publications
- Efficient and Scalable Kernel Matrix Approximations Using Hierarchical Decomposition. In: Intelligent Computers, Algorithms, and Applications. Springer Nature Singapore, 2024 more…
- Efficient and Scalable Kernel Matrix Approximations Using Hierarchical Decomposition. In: Intelligent Computers, Algorithms, and Applications. Springer Nature Singapore, 2024 more…
- Neural Nets with a Newton Conjugate Gradient Method on Multiple GPUs. In Proceedings of the 14th International Conference on Parallel Processing and Applied Mathematics, 2022, 13 more…
- Fast Evaluation and Approximation of the Gauss-Newton Hessian Matrix for the Multilayer Perceptron. SIAM Journal on Matrix Analysis and Applications, 2021 more…
- Software for Exascale Computing: Some Remarks on the Priority Program SPPEXA. In: Springer International Publishing, 2020 more…
- Software for Exascale Computing - SPPEXA 2016-2019. Volume LNCSE 136. Lecture Notes in Computational Science and Engineering (LNCSE) 136. Springer, 2020 more…
- H-matrix approximation of the Gauss-Newton Hessian matrix for the multilayer perceptron. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), 2019 more…
- Distributed O(N) Linear Solver for Dense Symmetric Hierarchical Semi-Separable Matrices. Embedded Multicore/Many-core Systems on a chip, IEEE, 2019 more…
- Distributed-Memory Hierarchical Compression of Dense SPD Matrices. SC '18: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2018 more…
- Black Box Hierarchical Approximations for SPD Matrices. Master's thesis, 2017 more…
- CAD-integrated Topology Optimization (BGCE Honours Project). , 2016 more…
- CFD Study of Fuel-air Mixing in a Novel Low-NOx Burner. Projekt thesis, 2015 more…
- Water Injections in Gas Turbines - Kinetic Modeling with Cantera. Bachelor's thesis, 2014 more…
Talks
- SPPEXA and beyond: Perspectives of Exascale Computing in the Context of AI. Human-centric Artificial Intelligence, 20202nd French-German-Japanese Symposium more…
- Some words from SPPEXA. (Talk / Parallel Programming Models - Productivity and Applications for Exascale and Beyond - 4th edition) 2019 more…
- A Fast Multipole Method for Training Neural Networks. PhD Forum: IEEE International Supercomputing Conference, 2019 more…
- Numerical approaches to large-scale machine learning. (Talk / Leogang High Performance Computing Workshop) 2019 more…
- Second-order optimization for AI using HSS Matrices on distributed-memory setup. Convergence of HPC and Data Science for Future Extreme Scale Intelligent Applications, 2019 more…
Posters
- Scalable Hierarchical Approximation of Dense Kernel Matrices. SIAM-PP 2024Baltimore more…
- Training Large-Scale Neural Networks with a Newton Conjugate Gradient Method (Newton-CG). SIAM Conference on Computational Science and Engineering (CSE23), 2023Amsterdam more…
- An Exascale Library for Numerically Inspired Machine Learning (ExaNIML). ISC High Performance, 2020Frankfurt (DIGITAL due corona) more…
- ExaNIML: An Exascale Library for Numerically Inspired Machine Learning. 13th IGSSE Forum, Raitenhaslach, 201913th IGSSE Forum, Raitenhaslach more…
- Nonsymmetric Algebraic Fast Multipole Method. Computational Science at Scale (CoSaS) 2018, 2018 more…