Artificial Intelligence is one of the fastest-evolving scientific disciplines. Staying relevant requires more than following trends — it demands continuous engagement with fundamental research.
At AI-Sunrise, we were born in the academy, and we never left it behind.
Research as a Discipline, Not a Buzzword
Conducting basic research and teaching AI courses forces us to stay permanently connected to the state of the art. New algorithms, modeling techniques, and theoretical advances emerge constantly — and engaging with them firsthand is the only way to truly understand their scope and limitations.
This ongoing process of learning directly feeds into the applications and tools we develop for real-world problems.
From Theory to Practice
Academic research sharpens:
- Mathematical intuition
- Model interpretability
- Understanding of uncertainty and limitations
- Awareness of failure modes in AI systems
These are exactly the qualities required to build robust, reliable AI solutions, especially in high-stakes environments such as public policy, health, and finance.
Teaching as a Catalyst for Learning
Teaching advanced AI courses and organizing specialized workshops pushes us to constantly refine our understanding. Explaining complex ideas clearly is often the best test of whether they are truly understood.
Workshops also allow us to explore emerging topics deeply, expanding our internal knowledge before they reach mainstream adoption.
Published Scientific Work
Our academic activity is not abstract — it is reflected in peer-reviewed publications and open research projects, including work on:
- Bayesian inference and uncertainty quantification
- Topic modeling and unsupervised learning
- Applications of AI to fundamental physics
- Advanced data-driven modeling techniques
Some selected publications and research projects:
- https://scipost.org/SciPostPhysCore.6.2.046
- https://arxiv.org/abs/2210.07358
- https://doi.org/10.3389/frai.2022.852970
- https://doi.org/10.1103/PhysRevD.105.092001
- https://arxiv.org/abs/2002.02460
- https://github.com/ManuelSzewc/Topic-Model-for-four-top-at-the-LHC/
Research as a Competitive Advantage
Basic research is not separate from applied AI — it is its foundation.
By remaining active in academia, we ensure that our solutions are not only innovative, but also scientifically grounded, explainable, and built to last in a rapidly changing technological landscape.