All Blogposts

Here you’ll find all blog posts from the Lamarr Institute – across all topics and categories. Our authors share how AI is researched, applied, and discussed. Enjoy exploring and learning!

BlogArticle FranceRose AnimalBehavior Image - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

BlogBasics

Why do we Need AI to Quantify Animal Behavior?

Dr. France Rose,

10. June 2026

Why quantifying behavior is a fundamental step to understand the brain and the living animals? How can AI help us in this endeavor? Let's review the latest developments and their impacts....

Digital illustration. Showing a glowing human brain in blue and purple tones connected to a stylized walking human figure. Bright data and network structures flow between the brain and body, symbolizing neurological processes, movement, and AI-supported Parkinson’s disease research.

BlogBasics

Artificial Intelligence in Parkinson’s Research

Prof. Dr. Holger Fröhlich,

13. May 2026

Could Artificial Intelligence transform the future of Parkinson’s care? This article explores how trustworthy AI methods may enable earlier diagnosis, more personalized treatments, and improved prediction of disease progression....

Hard labels in healthcare michael kamp lamarr institute - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

BlogResearch

Little Is Enough: Hard Labels for Stronger Federated Learning in Healthcare

Prof. Dr. Michael Kamp,

15. April 2026

Can hospitals collaboratively train diagnostic AI without exposing patient data? Hard-label federated co-training strengthens federated learning in healthcare while preserving diagnostic performance. ...

00 Beitragsbild c Illustration generated using ChatGPT By OpenAI kateract - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

BlogApplication

Seeing More, Caring Better: AI-based Ophthalmic Video Analysis for Global Ophthalmology

Prof. Dr. Thomas Schultz, Dr. Maximilian Wintergerst, Simon Müller,

19. March 2026

AI-powered video analysis enables scalable eye screening and improves cataract surgery – using simple smartphone technology....

BlogApplication

CapyMOA: Efficient Machine Learning for Evolving Data Streams

Dr. Heitor Murilo Gomes,

25. February 2026

Real-time data keeps changing – your models should too. CapyMOA brings high-performance stream learning and concept drift handling to Python, bridging MOA efficiency with practical usability....

Illustration in a Van-Gogh-inspired style showing a calm humanoid robot observing a flowing stream of data that transforms into adaptive decision trees. Swirling blue and yellow brushstrokes depict real-time data streams, changing graphs, and evolving tree structures, symbolizing Streaming Gradient Boosting and online learning under concept drift.

BlogResearch

Streaming Gradient Boosting: Pushing Online Learning Beyond its Limits

Dr. Nuwan Gunasekara,

04. February 2026

Streaming Gradient Boosting (SGB) brings gradient boosting to evolving data streams—adapting models to concept drift in real time with strong accuracy and efficiency across classification and regression tasks....

00 Blog Beitragsbild HEROS - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

BlogResearch

Green Online Learning with Heterogeneous Ensembles

Kirsten Köbschall,

29. January 2026

What if greener AI could also be more accurate? Discover how heterogeneous online ensembles like HEROS boost performance, cut resource costs, and adapt instantly to evolving data streams....

Generated by ChatGPT via the prompt “A digital scene captures a humanoid robot, with a smooth white body and dark accents, operating a wooden waterwheel at a quaint watermill beside a flowing river under a clear sky. The landscape around it is painted in bold, swirling strokes reminiscent of Van Gogh's Post-Impressionist style, featuring lush greenery, rolling hills, and a winding path, with the robot and the rotating waterwheel as the focal points.”

BlogBasics

Learning From Data Streams: Foundations of Stream Learning

Dr. Sebastian Buschjäger,

21. January 2026

Data never stops — so how do models keep up? This opening post introduces stream learning, concept drift, and real-time adaptation for continuously evolving data streams....

BlogApplication

Fine-Tuning a Low-Resource Language: Training the Whisper Model on Marathi

Dr. Rishikesh Pandit,

12. November 2025

A wide gap still separates how well an English or German ASR model would transcribe especially on heavy accented or non-native speech and similar in case of Marathi or other low resource languages. Can we overcome this shortcoming? If yes, how?...