Biography
I am enthusiastic about applying mathematical ideas to solve real-world problems, by developing interpretable statistical methods, accompanied by robust software implementations. From a statistical perspective, this interest encompasses high-dimensional data, selective inference, and supervised learning.
Download my resumé.
Interests
- Statistics
- Applied Mathematics
- Bioinformatics
Education
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Msc in Mathematics, 2023
University of Heidelberg
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BSc in Mathematics, 2020
University of Heidelberg
Experience
Research assistant - Public Health
Continuing research project in collaboration with Pascal Geldsetzer. We are analysing the health disparities attributable to particulate matter exposure between different socio-demographic groups in the United States.
Non-graduating exchange student
Advised by Prof. Dr. Smita Krishnaswamy and Prof. Dr. Yuval Kluger. Graduate-level courses in Theory and Application of Deep Learning, Statistical Methods in Human Genetics, Molecular and Biochemical Principles of Gene Function, Geometric and Topological Methods in Machine Learning, Differential Topology, Stochastic Models and Inference for the Biomedical and Social Sciences
Master of Science, Mathematics
Research assistant - Biostatistics
I worked with Wolfgang Huber and Nikos Ignatiadis. I extended a multiple testing procedure (IHW) to multi-dimensional input data through the use of random forests.
Research assistant - Public Health
Research project in collaboration with Pascal Geldsetzer. We are analysing the health disparities attributable to particulate matter exposure between different socio-demographic groups in the United States.
Non-graduating exchange student
Graduate-level courses in Functional Analysis, Algebraic Combinatorics, and Quantitative Models.
Bachelor of Science, Mathematics
Recent & Upcoming Talks
Publications
Contact
- daniel.fridljand [at] embl.de
- Meyerhofstraße 1, Heidelberg, 69117
- DM Me