Berens Lab
Data Science for Vision Research
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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[at]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.
Jan Niklas Böhm