Jan Niklas Böhm
| Surname | Böhm |
| First name | Jan Niklas |
| Present position and title | PhD Student |
Business address
Werner Reichardt Centre for Integrative Neuroscience (CIN)
Institute for Ophthalmic Research
University of Tübingen
Otfried-Müller-Str. 25
D-72076 Tübingen,
Germany
Phone: +49 (0)7071 29-88910
E-mail: jan-niklas.boehm@uni-tuebingen.de
Website: jnboehm.com
Academic Education
| Year | Degree | University | Field of study |
|---|---|---|---|
| 2017-2020 | Msc | University of Tübingen | Computer Science |
| 2019 | Msc | University of Amsterdam | Exchange Semester |
| 2014-2017 | Bsc | RheinMain University of Applied Sciences | Applied Computer Science |
Professional Experience
| Period | Institution | Position | Discipline |
|---|---|---|---|
| 2019 | CERN | Summer student | ML for trigger generation |
| 2018 | Bosch | Student employee | |
| 2018 | University of Tübingen | Teaching assistant | Course «Computer Science 2» |
| 2017 | German Research Center for Artificial Intelligence, Kaiserslautern | Research assistant | Social network analysis |
| 2015-2017 | RheinMain University of Applied Sciences | Teaching assistant | Courses «Algorithms and Data Structure» and «Statistics and Probability Theory» |
Research Interests
I’m interested in dimensionality reduction techniques for high-dimensional data. Learning good and compact representations in an unsupervised setting is a key part of that, some examples include contrastive learning and t-SNE.
As the amount of unlabeled data grows, the performance of the approaches used becomes more important. Optimization techniques are applicable in surprising settings and are of interest as well.