Evelyne Knapp

Evelyne Knapp is a Researcher at the ZHAW School of Engineering, Zurich University of Applied Sciences, within the Organic Electronics & Photovoltaics research focus area. Her work centers on advanced materials science, semiconductor physics, and machine learning applications in energy systems. She has led major projects such as 'Uncertainty quantification in ML Prediction for PV Quality Assurance' and contributed to innovations in perovskite solar cell optimization, organic semiconductor characterization, and device simulation models.

Her research interests span photovoltaic technologies, charge transport phenomena, and optoelectronic device development. Key areas include:

• Perovskite solar cell performance analysis and degradation mechanisms
• Machine learning-driven parameter extraction for semiconductor materials
• Electro-thermal modeling of organic light-emitting devices
• Frequency-domain analysis of large-area solar cells

Knapp's publications (over 30 peer-reviewed articles) demonstrate expertise in device simulation, material characterization, and interdisciplinary approaches merging computational methods with experimental data. Recent work highlights include:

• Advancing ML techniques to identify limiting parameters in perovskite solar cells
• Developing inverse models for solar cell parameter estimation
• Quantifying charge transport dynamics in organic semiconductors

Her contributions have been presented at leading conferences including the IEEE Photovoltaic Specialists Conference and the Society for Information Display Symposium.