Juliane Sigl PhD candidate applied mathematics Curriculum vitae “ “ The important thing is not to stop questioning. - Albert Einstein Current positions May. 2017–present Technische Universität München (TUM) Munich TUM Data Innovation Lab (TUM-DI-LAB) Project mentor ‚ personal role: organization, project mentoring, data science ‚ current project with Celonis SE: ’Machine learning powered process mining’ Jun. 2013–present Technische Universität München (TUM) Munich Department of Mathematics, Applied Numerical Analysis, Data Analysis and Optimization PhD candidate ‚ supervisor: Prof. Dr. Massimo Fornasier ‚ project: ’Iteratively reweighted least squares - nonlinear reg- ression and low-dimensional structure learning for Big Data’ Research ‚ general : modeling, solution conception and algorithm devel- opment for data analysis and machine learning ‚ theoretical : algorithm derivation, analysis and proofs ‚ practical : algorithm implementation in MATLAB, numerical ex- periments and performance comparison with state-of-the-art Publication presentation ‚ publication in internationally recognized peer-review journals ‚ conference attendance, presentation of research results Teaching supervision ‚ MSc thesis supervision ‚ exercise conception and tutorial organization ‚ teaching for students in mathematics, IT and engineering Publications and preprints Apr. 2017 Harmonic-mean IRLS for low-rank matrix recovery Sigl, Kümmerle (under review, Journal on Machine Learning Research) Febr. 2016 Nonlinear residual minimization via iteratively reweighted least squares Sigl (Computational Optimization and Applications, 64(3):755-792, 2016) Mar. 2014 Quasilinear compressed sensing Sigl, Ehler, Fornasier (SIAM Multiscale Modeling & Simulation,12(2):725-754, 2014) 1 of 2 Contact address Juliane Sigl Ernest-Thun-Str. 11a 5020 Salzburg phone: +49 (0) 176 – 84740724 mail: [email protected]born: 04.11.1988 nationality: German
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Juliane SiglPhD candidate applied mathematics
Curriculum vitae
“ “
“
The important thing is not to stop questioning. - Albert Einstein
...Juliane showed exceptional motivation and talents by learning very quickly the new research topic and starting immediately to contribute with original results.[...] I do not hesitate to very positively evaluate the large scope of her scientific achievements [...].
- Prof. Dr. Massimo Fornasier, TUM, PhD and MSc thesis supervisor
Although the task was very ambitious to our great surprise Juliane Sigl was able not only to understand the background but come up with a working Matlab code within two months.
- Dr. Frank Filbir, Helmholtz-Zentrum Munich, BSc thesis supervisor and internship mentor
Current positionsMay. 2017–present Technische Universität München (TUM) Munich
TUM Data Innovation Lab (TUM-DI-LAB)Project mentor
‚ personal role: organization, project mentoring, data science‚ current project with Celonis SE: ’Machine learning powered
process mining’
Jun. 2013–present Technische Universität München (TUM) Munich
Department of Mathematics,Applied Numerical Analysis, Data Analysis and OptimizationPhD candidate
‚ supervisor: Prof. Dr. Massimo Fornasier‚ project: ’Iteratively reweighted least squares - nonlinear reg-
ression and low-dimensional structure learning for Big Data’
Research ‚ general: modeling, solution conception and algorithm devel-opment for data analysis and machine learning
‚ theoretical: algorithm derivation, analysis and proofs‚ practical: algorithm implementation in MATLAB, numerical ex-
periments and performance comparison with state-of-the-art
Publicationpresentation
‚ publication in internationally recognized peer-review journals‚ conference attendance, presentation of research results
Teachingsupervision
‚ MSc thesis supervision‚ exercise conception and tutorial organization‚ teaching for students in mathematics, IT and engineering
Publications and preprintsApr. 2017 Harmonic-mean IRLS for low-rank matrix recovery
Sigl, Kümmerle(under review, Journal on Machine Learning Research)
Febr. 2016 Nonlinear residual minimization via iteratively reweightedleast squaresSigl(Computational Optimization and Applications, 64(3):755-792, 2016)