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Assistant Professor at Aalto University | Adversarial & Trustworthy Machine Learning
I’m a tenure-track assistant professor and I lead the Trustworthy & Adversarial Computing Lab at Aalto University (taclab.aalto.fi). I also serve as a deputy director and the head of research development and partnerships at the Helsinki-Aalto Institute for Cybersecurity (haic.fi). I'm interested in trustworthy machine learning and adjacent areas such as confidential computing, differential privacy, and media authenticity. Recently, I've been working on privacy, provenance and ownership, and adversarial robustness in generative ML -- and increasingly on replacing empirical guarantees with formal, verifiable assurances. More broadly, I'm interested in different ways that we can protect the models and data to enable secure and trustworthy analysis -- both in terms of the technical details as well as legislation compliance. You can view my website and publications for more detailed info. Feel free to reach out to me if you'd like to collaborate or have a chat. sebszyller.com bluesky @ sebszyller
Aalto University
Doctor of Science - PhD, Computer Science (Security and Privacy of Machine Learning)
January 1, 2020 – January 1, 2023
Aalto University
Master of Science, Machine Learning and Data Mining
January 1, 2017 – January 1, 2020
Turku University of Applied Sciences
Erasmus+ Exchange, Computer Science
January 1, 2016 – January 1, 2016
Lodz University of Technology
Bachelor of Science (B.Sc.), Computer Science
January 1, 2013 – January 1, 2017
Aalto University
Assistant Professor
September 1, 2025 – Present
Intel Labs
Research Scientist (Security & Privacy of Machine Learning)
June 1, 2023 – August 1, 2025
Portland, Oregon, United States (remote)
University of Waterloo
Visiting Researcher
October 1, 2022 – November 1, 2022
Waterloo, Ontario, Canada
Aalto University School of Science and Technology
Doctoral Researcher, Machine Learning Security & Privacy
March 1, 2020 – June 1, 2023
Huawei Technologies
Machine Learning and Security Research Intern
July 1, 2019 – September 1, 2019
Helsinki, Uusimaa, Finland
Aalto University School of Science and Technology
Machine Learning Research Assistant
September 1, 2017 – March 1, 2020
GFT Group
Big Data & Scala Software Engineer
April 1, 2017 – July 1, 2017
Lodz, Lodz District, Poland
GFT Group
Junior Big Data & Scala Software Enginner
October 1, 2016 – March 1, 2017
Lodz, Lodz District, Poland
GFT Group
Graduate Big Data & Scala Software Engineer
June 1, 2016 – September 1, 2016
Lodz, Lodz District, Poland
Accenture
SAP/ABAP Intern Developer
July 1, 2015 – September 1, 2015
Lodz Metropolitan Area
How to Improve Medical and Health Awareness
March 1, 2015 – July 1, 2015
Project of the International Faculty of Engineering with Design Thinking methodology. The goal of the project was to figure out a way to raise health awareness among people of all ages. In the end, our team created an NFC-enabled Android application in which children would take care of a tamagochii-like creature. The main innovation of the project was that each in-game action performed on the pupil could have been performed by the kid in real life instead and rewarded by scanning the NFC tag associated with the given action resulting in the development of proper hygiene habits via association.
Functional Program Design in Scala
Coursera Course Certificates
June 24, 2026 – Present
Parallel programming
Coursera Course Certificates
June 24, 2026 – Present
Functional Programming Principles in Scala
Coursera Course Certificates
June 24, 2026 – Present
Cambridge English: First (FCE)
Cambridge English
June 24, 2026 – Present
Cambridge English: Advanced (CAE)
Cambridge English
June 24, 2026 – Present
Cambridge English: Proficiency (CPE)
Cambridge English
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards academic research and specialized ML security/privacy roles. While this provides deep expertise, the project diversity is limited to one personal project and the professional experience is primarily research-focused. The target role of 'ML Engineer' typically requires a balance of research and practical engineering/deployment skills. The candidate's experience with Scala, Apache Spark, and Hadoop from earlier roles indicates some engineering foundation, but recent experience is predominantly research. This profile suggests a strong fit for research-oriented ML Engineer roles or those with a heavy emphasis on ML security and privacy, but potentially less for general ML engineering roles focused on product development and deployment without further evidence of those skills.
Soft Skills & Operational Fit
The candidate's extensive academic and research background suggests strong analytical, problem-solving, and independent research skills. Their leadership roles (Assistant Professor, Lab Lead, Deputy Director) indicate capabilities in guiding teams and strategic planning. The project description for 'How to Improve Medical and Health Awareness' demonstrates an ability to apply design thinking and develop innovative solutions, suggesting creativity and user-centric thinking. However, without psychometric test results, specific insights into work attitude, stress handling, and team collaboration are not available.