Sebastian Stammler

Sebastian Stammler

Sebastian obtained his Master’s degree in Mathematics from the University of Cambridge in 2010 and Diploma in Mathematics from TU Darmstadt in 2012. He then went on to work as a Quantitative Finance analyst at Ernst & Young and then as a software developer at nterra. In late 2015, he decided to go back into academics, pursuing his PhD in the field of Genomic Privacy at TU Darmstadt, where he studies privacy-preserving techniques for the analysis of genomic data. Secure Multi-Party Computation is the main focus of his PhD studies. He was also involved as CTO in a Blockchain-Startup in Tel Aviv, Israel in 2017/18. Since late 2018, he joined the Applied Cryptography research group at TU Darmstadt to lead the implementation of the Perun Protocols.

Curriculum Vitae

2006 – 2013 Diploma Mathematics, TU Darmstadt
2009 – 2010 Master of Advanced Studies (Mathematics), University of Cambridge
2013 – 2014 Quantitative Finance Analyst, Ernst & Young, Eschborn
2015 Software Developer, nterra, Darmstadt
2015 – present PhD in Genomic Privacy, TU Darmstadt
2017 – 2018 Co-Founder/CTO Blocksource, Frankfurt a.M./Tel Aviv
2019 – present Lead Perun Implementation, TU Darmstadt

Lectures

2016 + 2017 Lecture: Bioinformatics

Publications

Sebastian Stammler, Stefan Katzenbeisser, Kay Hamacher: Correcting Finite Sampling Issues in Entropy l-diversity. Privacy in Statistical Databases 2016, Dubrovnik, Croatia. https://doi.org/10.1007/978-3-319-45381-1_11

Daniel Demmler, Kay Hamacher, Thomas Schneider, Sebastian Stammler: Privacy-Preserving Whole-Genome Variant Queries. Cryptology And Network Security 2017, Hong Kong. https://doi.org/10.1007/978-3-030-02641-7_4

Johannes Buchmann, Matthias Geihs, Kay Hamacher, Stefan Katzenbeisser,Sebastian Stammler: Long-Term Integrity Protection of Genomic Data. GenoPri‘17, Orlando, FL, USA. http://2017.genopri.org/program.html

Maximilian J. Dombrowsky, Sven Jager, Benjamin Schiller, Benjamin E. Mayer, Sebastian Stammler, Kay Hamacher: StreaMD: Advanced Analysis of Molecular Dynamics Using R. Journal of Computational Chemistry 39, no. 21 (2018): 1666–74. https://doi.org/10.1002/jcc.25197