Peter Andersson is a researcher (PhD) and project manager at RISE’s Materials and Production division, specializing in digitalization, data analytics, and applied artificial intelligence. He develops methods and solutions that strengthen industry’s ability to collect, structure, and utilize data to improve quality, efficiency, and innovation.
As a researcher, I work with the digitalization of industrial processes, data management, and applied artificial intelligence. My work focuses on how organizations can create value by structuring, analyzing, and utilizing data from production systems and business operations. I have a background in physics and measurement technology, with particular expertise in medical physics, digital measurement systems, and data management. This enables me to work at the intersection of experiments, modeling, and digital solutions.
I lead and contribute to projects involving:
- Project management and research funding
- Data cataloging and structuring of industrial data flows
- AI and analytics methods for quality assurance and decision support
- Simulations and computational physics for radiation interaction and radiation dosimetry
- Integration of data from multiple sources (sensors, information systems, manual processes)
- Visualization and accessibility of data for operational and strategic decision making
A central theme of my work is making data practically useful, from data acquisition and management to actionable insights and measurable business improvements.
Collaboration and Application
I work closely with industrial partners, often in multidisciplinary projects, with a focus on:
- Identifying needs and opportunities related to data and AI
- Developing and validating solutions in real-world environments
- Creating scalable methods, workflows, and practices
I have particular experience in translating research-based methods into practical applications for small and medium-sized enterprises (SMEs).
- Portal dose image prediction using Monte Carlo generated transmission energy fl…
- Monte Carlo and machine learning approach to in-vivo transmission dosi metry fo…
- Cylindrical ionization chamber response in static and dynamic 6 and 15 MV photo…
- Effects of lung tissue characterization in radiotherapy of breast cancer under …