AI Research & Technology Leader | Foundation Models | Agentic AI | Enterprise AI
My work connects advanced AI research with real-world systems, spanning foundation models, agentic systems, research strategy, reinforcement learning, simulation, and the translation of emerging capabilities into practical products. At SAP, my work included leading machine learning research for complex, structured environments.
I have authored 50+ peer-reviewed publications, including five first-author ACL papers, and am a co-inventor on 30+ patents. My research has received more than 5,500 citations.
Website · LinkedIn · Google Scholar · ORCID
- Foundation models for structured and relational data
- Agentic AI and autonomous systems for complex workflows
- application world models, reinforcement learning, and simulation
- Representation learning across language, vision, and structured data
- Model adaptation, post-training, evaluation, and responsible deployment
My research spans foundation models, natural language processing, privacy-preserving machine learning, continual learning, reinforcement learning, and multimodal representation learning.
It includes highly cited work on client-level federated learning, continual learning, medical image analysis, and self-supervised representation learning, alongside more recent work on controllable language models, agentic AI, and enterprise systems.
Selected publications and research projects are available on my website and Google Scholar.
My academic background includes postdoctoral research at MIT CSAIL and Harvard Medical School and a Ph.D. summa cum laude from the Technical University of Munich.
I have built and led research teams, developed international academic collaborations, advised early-stage companies on applied AI, and mentored researchers working across academia and industry.