I’m an experimental particle physicist working at the intersection of fundamental science and modern data analysis. From early curiosity to full-time collider research, my path has taken me from Göttingen to Geneva — and now to CERN as a Postdoctoral Fellow with Harvard University. During this journey, I have been motivated by a fascination with the building blocks of matter and by the challenge of developing new methods to study them.

Building a Career in Particle Physics

I began my academic career at the University of Göttingen, where I discovered a lasting interest in experimental research and the teamwork behind large-scale physics. My Ph.D. focused on rare processes involving top quarks and photons, combining fundamental physics questions with methodological innovation. The work earned summa cum laude distinction and was supported by the German Academic Scholarship Foundation. It also gave me first-hand experience in how precision measurements can test the Standard Model at its limits.

In 2021, I moved to the University of Geneva as a Feodor Lynen Fellow of the Humboldt Foundation to pursue new directions in machine learning and collider physics. There I expanded my research toolkit with modern ML techniques, applying them to challenges such as anomaly detection in jets and neutrino reconstruction. This period deepened my conviction that physics and data science enrich one another, and that cross-disciplinary approaches are vital for the next generation of discoveries.

Today, I am a Postdoctoral Fellow at Harvard University, working at CERN on the ATLAS experiment. My research contributes to precision measurements, machine-learning–based data analysis, and searches for new physics. It spans from detailed studies of top-quark production to broader questions of methodology and interpretation, always with the goal of advancing both the science and the tools we use to explore it.

Collaboration, Communication, and Mentoring

Within ATLAS, I have coordinated large-scale analysis efforts and held operational leadership roles during LHC data-taking. I see collaboration not only as a necessity for high-energy physics, but as an opportunity to build systems and communities that leave a lasting scientific impact. My experience as a subgroup convener has taught me the value of balancing technical depth with clear communication and of helping teams stay focused on scientific goals.

Mentoring and teaching are central to that vision. I have supervised students through Ph.D. projects, machine learning research, and short-term training programs. I have also lectured and led practical courses on data analysis and machine learning in physics, aiming to make advanced methods accessible without losing scientific depth. Helping early-career researchers grow into independent contributors — and seeing them take ownership of their projects — remains one of the most rewarding aspects of my work.

Beyond the lab, I started Bridging AI and Society together with Christoph Weisser, an initiative dedicated to fostering critical reflection on how artificial intelligence shapes both research and society. As part of this effort, we co-lead machine learning courses for interdisciplinary audiences at summer schools of the German Academic Scholarship Foundation. These programs bring together students from across the sciences and humanities to explore algorithms, real-world applications, and the societal dimensions of AI.

Outreach and Engagement

I regularly guide visitors through the ATLAS detector and enjoy sharing what we do at CERN with students, teachers, and the public. I also contribute to peer review and editorial work, helping ensure scientific standards across leading journals and collaboration outputs. These activities reflect my belief that science grows stronger when it is open, critically reviewed, and communicated widely.

For current research and leadership details, see the research page. For a closer look at my student supervision and teaching, visit the teaching page.


📬 Want to connect or collaborate? Feel free to get in touch.