Research Group
Machine Learning
and Security
View from our building over Berlin.

Research Team

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.

photo of team

Professor

Prof. Dr. Konrad Rieck
BIFOLD  •  TU Berlin  •  Homepage

Team Assistant

Sarah Hashmi
BIFOLD  •  TU Berlin

Postdocs

Dr. Thorsten Eisenhofer
BIFOLD  •  TU Berlin  •  Homepage

Dr. Anne Josiane Kouam
BIFOLD  •  TU Berlin  •  Homepage

PhD Students

Stefan Czybik
BIFOLD  •  TU Berlin  •  Homepage

Mohammad Ebrahimi
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

Student Staff

Elena Bank
BIFOLD  •  TU Berlin

Ekin Boke
BIFOLD  •  TU Berlin

Hristo Boyadzhiev
BIFOLD  •  TU Berlin

Elias Burggräfe
BIFOLD  •  TU Berlin

Past Members

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

Past Guests

Alejandro Calleja
University Carlos III of Madrid

Dr. Marco Melis
University of Cagliari

Dr. Michele Scalas
University of Cagliari

Job Applications

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.