معرفی
Mannes Poel is a researcher specializing in Datamanagement & Biometrics with a focus on applied machine learning. His work spans healthcare analytics, sensor technology optimization, and meta-learning frameworks for missing data. ORCID: 0000-0002-3813-9732
- Active Domains: Artificial Intelligence, Medical Predictive Modeling, Industrial Sensor Analytics
- Collaboration Network: Interdisciplinary work with institutions in healthcare (e.g., Diagnostics journal) and engineering (e.g., IEEE MEMS conference)
Scientific Achievements:
- Best paper award at Intetain 2107 (2017)
Research Trends: His recent publications (2024-2025) emphasize explainable AI for missing data in clinical contexts and machine learning-enhanced sensor systems for industrial fluid dynamics. These works combine traditional ML with real-time data processing and cross-domain model adaptation.
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