MCML at CAiSE 2024

One Accepted Paper

We are happy to announce that MCML researchers have contributed a total of 1 paper to CAiSE 2024. Congrats to our researchers!

R. S. Oyamada • G. M. Tavares • S. B. Junior • P. Ceravolo
Enhancing Predictive Process Monitoring with Time-Related Feature Engineering.
CAiSE 2024 - 36th International Conference on Advanced Information Systems Engineering. Limassol, Cyprus, Jun 03-07, 2024. DOI

05.02.2026

Needle in a Haystack: Finding Exact Moments in Long Videos

ECCV 2024 research introduces RGNet, an AI model that finds exact moments in long videos using unified retrieval and grounding.

04.02.2026

Benjamin Busam Leads Design of Bavarian Earth Observation Satellite Network “CuBy”

Benjamin Busam leads the scientific design of the “CuBy” satellite network, delivering AI-ready Earth observation data for Bavaria.

©Florian Generotzky / LMU

30.01.2026

Cracks in the Foundations of Cosmology

Daniel Grün examines cosmological tensions that challenge the Standard Model and may point toward new physics.

29.01.2026

How Machines Can Discover Hidden Rules Without Supervision

ICLR 2025 research shows how self-supervised learning uncovers hidden system dynamics from unlabeled, high-dimensional data.

28.01.2026

Matthias Nießner Co-Founds AI Startup Synthesia

Julien Gagneur comments on DeepMind’s AlphaGenome, highlighting its precision and remaining challenges in genome prediction.