Research Group
Machine Learning
and Security
and Security
View from our building over Berlin.
Our research group is part of the Berlin Institute for the Foundations of Learning and Data (BIFOLD) at Technische Universität Berlin. We advance research at the intersection of machine learning and security with a dedicated team. Explore the team members and their homepages below.
Prof. Dr. Konrad Rieck
BIFOLD • TU Berlin • Homepage
Sarah Hashmi
BIFOLD • TU Berlin
Dr. Thorsten Eisenhofer
BIFOLD • TU Berlin • Homepage
Dr. Anne Josiane Kouam
BIFOLD • TU Berlin • Homepage
Stefan Czybik
BIFOLD • TU Berlin • Homepage
Mohammad Ebrahimi
BIFOLD • TU Berlin
Pia Hanfeld
BIFOLD • TU Berlin
Micha Horlboge
BIFOLD • TU Berlin • Homepage
Erik Imgrund
BIFOLD • TU Berlin
Jonas Möller
BIFOLD • TU Berlin • Homepage
Lukas Pirch
BIFOLD • TU Berlin • Homepage
Felix Weißberg
BIFOLD • TU Berlin • Homepage
Lukas Seidel
Binarly • Homepage
Elena Bank
BIFOLD • TU Berlin
Hristo Boyadzhiev
BIFOLD • TU Berlin
Elias Burggräfe
BIFOLD • TU Berlin
Prof. Dr. Hugo Gascon
GEC • Comillas Pontifical Uni.
Prof. Dr. Christian Wressnegger
Karlsruhe Institute of Technology
Prof. Dr. Fabian Yamaguchi
ShiftLeft • Stellenbosch University
Prof. Dr. Daniel Arp
TU Wien
Dr. Tom Ganz
Amazon
Dr. Ansgar Kellner
Volkswagen
Dr. Marius Musch
1&1 Telecommunication
Dr. Erwin Quiring
Ruhr-University Bochum
Dr. Alexander Warnecke
Databricks
Dr. Guido Schwenk
Vattenfall
Robert Michael
TU Braunschweig
Michael Reimsbach
SAP
Alwin Maier
MPI Solar System Research
Alejandro Calleja
University Carlos III of Madrid
Dr. Marco Melis
University of Cagliari
Dr. Michele Scalas
University of Cagliari
We are always looking for motivated and skilled PhD students and postdocs to join our team. Please check our open positions. If no positions are currently open, you may contact us directly at jobs@mlsec.org.
Before submitting your application, however, take the time to write a concise, well-focused cover letter. In this letter, explain specifically why you would be a strong fit for our team, avoiding general praise. Please include reference letters. Additionally, add the result of (0x62df**215)%0xf0e5 in the subject line of your email.