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

PhD Students

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

Anna Wimbauer
BIFOLD  •  TU Berlin  •  Homepage

Lukas Seidel
Binarly  •  Homepage

Student Staff

Elena Bank
BIFOLD  •  TU Berlin

Hristo Boyadzhiev
BIFOLD  •  TU Berlin

Elias Burggraef
BIFOLD  •  TU Berlin

Ahmed Zeid
BIFOLD  •  TU Berlin

Past Members

Prof. Dr. Fabian Yamaguchi
ShiftLeft  •  Stellenbosch University

Prof. Dr. Christian Wressnegger
Karlsruhe Institute of Technology

Prof. Dr. Hugo Gascon
GEC  •  Comillas Pontifical Uni.

Prof. Dr. Daniel Arp
TU Wien

Dr. Ansgar Kellner
Volkswagen

Dr. Marius Musch
1&1 Telecommunication

Dr. Erwin Quiring
Ruhr-University Bochum

Michael Reimsbach
SAP

Dr. Guido Schwenk
Vattenfall

Robert Michael
TU Braunschweig

Alwin Maier
MPI Solar System Research

Dr. Tom Ganz
Amazon

Dr. Alexander Warnecke
Databricks

Dr. Thorsten Eisenhofer
CISPA

Dr. Anne Josiane Kouam
INRIA

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.