Anke Schmeink
Anke Schmeink is an RWTH Aachen professor whose machine-learning research spans wireless communications and personalized medicine. She studied mathematics with a minor in medicine, earned a doctorate in electrical engineering, and worked in medical signal processing at Philips Research. She received the Vodafone Foundation research prize in 2007 and the Helene-Lange Prize in 2009. With Guido Dartmann and Houbing Herbert Song, she co-edited a 2019 book on machine learning for the Internet of Things and co-authored a 2021 reinforcement-learning paper on critical-care ventilation. As of October 2026, she leads the Chair of Information Theory and Data Analytics at RWTH Aachen.
- Now at
- RWTH Aachen University
- Works
- 421
- Citations
- 4,425
- h-index
- 34
- Badges
Publication numbers from OpenAlex, as of 18 October 2026.
Timeline
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2002–2006
A doctorate in engineering
At RWTH Aachen, she earns a mathematics diploma with a minor in medicine in 2002, then completes a doctorate in electrical engineering and information technology in 2006.
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2006
Medical signal processing at Philips
From late 2006, she works at Philips Research in Medical Signal Processing.
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2007–2009
Vodafone and Helene-Lange prizes
The Vodafone Foundation awards her its 2007 natural and engineering sciences prize for her dissertation on capacity analysis and resource allocation in wireless communications. She receives the Helene-Lange Prize in 2009.
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2012
Professor at RWTH Aachen
In October 2012, she becomes a professor at RWTH Aachen's Information Theory and Design of Communication Systems laboratory.
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2019
Machine learning for IoT
With Guido Dartmann and Houbing Herbert Song, she co-edits the 2019 book Big Data Analytics for Cyber-Physical Systems: Machine Learning for the Internet of Things.
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2021
A reinforcement-learning paper
She co-authors the 2021 paper ‘Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care.’
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2021
VentAI in critical care
In 2021, the paper develops and evaluates VentAI, a reinforcement-learning algorithm that suggests a dynamically optimized mechanical-ventilation regimen for critically ill patients.
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As of October 2026
Information Theory Chair
As of October 2026, she leads RWTH Aachen's Chair of Information Theory and Data Analytics. Her research includes machine learning and data analytics for wireless communications and personalized medicine.
Career
- Since 2012RWTH Aachen UniversityProfessor
- 2021–2025Wuhan University
- From 2006Philips
Education
- 2006RWTH Aachen UniversityDoctorate in electrical engineering and information technology
- 2002RWTH Aachen UniversityMathematics diploma with a minor in medicine
Most-cited works
- Robust and Secure Resource Allocation for ISAC Systems: A Novel Optimization Framework for Variable-Length Snapshots
- Deep Reinforcement Learning based Resource Allocation in Low Latency Edge Computing Networks
- Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care
- SWIPT-Enabled Relaying in IoT Networks Operating With Finite Blocklength Codes
- Optimal 1D Trajectory Design for UAV-Enabled Multiuser Wireless Power Transfer
Sources and credits
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- Preisträger: Förderpreis 2007
- About us | 6GEM+
- Ausschreibung: Helene-Lange-Preis für Nachwuchswissenschaftlerinnen
- Anke Schmeink - HiPEAC
- Big Data Analytics for Cyber-Physical Systems - 1st Edition | Elsevier Shop
- Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care | npj Digital Medicine
- Prof. Dr.-Ing. Anke Schmeink | RWTHcontacts


