Daniel Wälchli
PhD Student
Research and Interests
- (Multi Agent) Reinforcement Learning
- Inverse Reinforcement Learning
- Uncertainty Quantification
- Stochastic Optimization
- High Performance Computing and General Purpose GPU Computing
- Software Engineering
- Entrepreneurship
Current Project
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Korali A High-Performance Framework for Uncertainty Quantification, Optimization, and Reinforcement Learning
Practical Experience
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Financial Products Application Development & Trading IT, Bank Vontobel Zurich, 2016-2018
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Project Management, Bank Vontobel Zurich, 2018
Education
- M.Sc. Computational Science and Engineering, ETHZ, 2016
- B.Sc. Electrical Engineering & Information Technology, ETHZ, 2013
Publications
2020
- M. Chatzimanolakis, P. Weber, G. Arampatzis, D. Wälchli, I. Kičić, P. Karnakov, C. Papadimitriou, and P. Koumoutsakos, “Optimal allocation of limited test resources for the quantification of COVID-19 infections,” Swiss Med. Wkly., 2020.
[BibTeX] [PDF] [DOI]@article{chatzimanolakis2020a, author = {Michail Chatzimanolakis and Pascal Weber and Georgios Arampatzis and Daniel W{\"a}lchli and Ivica Ki\v{c}i\'{c} and Petr Karnakov and Costas Papadimitriou and Petros Koumoutsakos}, doi = {10.4414/smw.2020.20445}, journal = {{Swiss Med. Wkly.}}, month = {dec}, publisher = {{EMH} Swiss Medical Publishers, Ltd.}, title = {Optimal allocation of limited test resources for the quantification of {COVID}-19 infections}, url = {http://www.cse-lab.ethz.ch/wp-content/papercite-data/pdf/chatzimanolakis2020a.pdf}, year = {2020} }
- P. Karnakov, G. Arampatzis, I. Kičić, F. Wermelinger, D. Wälchli, C. Papadimitriou, and P. Koumoutsakos, “Data-driven inference of the reproduction number for covid-19 before and after interventions for 51 european countries,” Swiss Med. Wkly., iss. 150:w20313, 2020.
[BibTeX] [PDF] [DOI]@article{karnakov2020b, author = {Karnakov, Petr and Arampatzis, Georgios and Ki\v{c}i\'{c}, Ivica and Wermelinger, Fabian and W{\"a}lchli, Daniel and Papadimitriou, Costas and Koumoutsakos, Petros}, doi = {https://doi.org/10.4414/smw.2020.20313}, journal = {{Swiss Med. Wkly.}}, number = {150:w20313}, publisher = {FMH}, title = {Data-driven inference of the reproduction number for COVID-19 before and after interventions for 51 European countries}, url = {http://www.cse-lab.ethz.ch/wp-content/papercite-data/pdf/karnakov2020b.pdf}, year = {2020} }
- D. Wälchli, S. M. Martin, A. Economides, L. Amoudruz, G. Arampatzis, X. Bian, and P. Koumoutsakos, “Load balancing in large scale bayesian inference,” in Proceedings of the platform for advanced scientific computing conference – PASC ’20, 2020.
[BibTeX] [PDF] [DOI]@inproceedings{walchli2020a, author = {Daniel W\"{a}lchli and Sergio M. Martin and Athena Economides and Lucas Amoudruz and George Arampatzis and Xin Bian and Petros Koumoutsakos}, booktitle = {Proceedings of the Platform for Advanced Scientific Computing Conference – {PASC} {\textquotesingle}20}, doi = {10.1145/3394277.3401849}, month = {jun}, publisher = {{ACM}}, title = {Load Balancing in Large Scale Bayesian Inference}, url = {http://www.cse-lab.ethz.ch/wp-content/papercite-data/pdf/walchli2020a.pdf}, year = {2020} }
2019
- G. Arampatzis, D. Wälchli, P. Weber, H. Rästas, and P. Koumoutsakos, “(μ,Λ)-ccma-es for constrained optimization with an application in pharmacodynamics,” in Proceedings of the platform for advanced scientific computing conference – PASC ’19, 2019.
[BibTeX] [PDF] [DOI]@inproceedings{arampatzis2019a, author = {Arampatzis, Georgios and W\"{a}lchli, Daniel and Weber, Pascal and R\"{a}stas, Henri and Koumoutsakos, Petros}, booktitle = {Proceedings of the Platform for Advanced Scientific Computing Conference - {PASC} {\textquotesingle}19}, doi = {10.1145/3324989.3325725}, keywords = {Stochastic optimization, constraint handling, covariance matrix adaptation, evolution strategy, pharmacodynamics, viability evolution}, publisher = {{ACM} Press}, title = {(\Μ,{
})-CCMA-ES for Constrained Optimization with an Application in Pharmacodynamics}, url = {http://www.cse-lab.ethz.ch/wp-content/papercite-data/pdf/arampatzis2019a.pdf}, year = {2019} }
2018
- G. Arampatzis, D. Wälchli, P. Angelikopoulos, S. Wu, P. Hadjidoukas, and P. Koumoutsakos, “Langevin diffusion for population based sampling with an application in bayesian inference for pharmacodynamics,” SIAM J. Sci. Comput., vol. 40, iss. 3, p. B788–B811, 2018.
[BibTeX] [PDF] [DOI]@article{arampatzis2018a, author = {Georgios Arampatzis and Daniel W\"alchli and Panagiotis Angelikopoulos and Stephen Wu and Panagiotis Hadjidoukas and Petros Koumoutsakos}, doi = {10.1137/16m1107401}, journal = {{SIAM J. Sci. Comput.}}, month = {jan}, number = {3}, pages = {B788--B811}, publisher = {Society for Industrial {\&} Applied Mathematics ({SIAM})}, title = {Langevin Diffusion for Population Based Sampling with an Application in Bayesian Inference for Pharmacodynamics}, url = {http://www.cse-lab.ethz.ch/wp-content/papercite-data/pdf/arampatzis2018a.pdf}, volume = {40}, year = {2018} }