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Target audience
Engineers, technicians, CTOs, R&D consultants, and scientists who use imaging (in engineering, life sciences, manufacturing, etc.), and are seeking to gain skills in image analysis algorithms and AI-based approaches.
Prerequisites
Basic programming knowledge is recommended. Participants should bring their own laptop and be able to install open-source software.
overview
From real-time inspection to quantification, imaging is omnipresent in R&D, engineering, manufacturing, and life sciences — spanning scales, processes, and applications. Driven by advances in high-resolution, high-dimensional imaging technologies and by the implementation of machine learning, image data has become significantly more powerful. Building on the core principles of image processing, how to combine imaging, engineering, and deep learning to design more efficient image analysis workflows that support higher quality control and more effective automation? How can we unlock new opportunities for AI-powered imaging, while addressing related risks and challenges?
Objectives
- Gain insights into cutting-edge imaging techniques and into the latest trends shaping the imaging industry
- Develop the visual expertise required to capture, process, enhance, and interpret image data
- Acquire hands-on skills in open-source software and AI models for effective image analysis
- Explore the opportunities and risks of AI-powered image analysis workflows in industry
- Learn the best practices in image analysis for industrial and scientific applications
Certification
Upon completing the course and passing the related exam, participants will receive a Microcredential (MC) Certificate of 2 ECTS.
Programme
DAY 1 – Working with Image Data
- Integrative imaging, image quality, and visual expertise development
- Image processing: from operators to convolutional neural network (CNN)
- Workshop: handling and visualization of multidimensional images (3D/Time) with open-source software (e.g.: ImageJ/FIJI/Napari)
- Industry expert presentation: trends in imaging, project management, and system deployment
DAY 2 – Mastering Image Analysis
- Image quantification, extraction of visual features, and object detection
- Strategies to solve image analysis problems
- Workshop: building an image analysis pipeline
- Discussion: evaluation and critical thinking on system design and performance
DAY 3 – Shifting to AI for Image Segmentation
- Model-based and data-driven approaches
- Image segmentation and deep learning
- Workshop: applying segmentation, algorithmic, pre-trained models, customized deep learning models
- Industry expert presentation: transitioning to AI — risks, challenges, and opportunities
DAY 4 – Understanding Computational Imaging
- Cutting-edge imaging techniques and correlative imaging
- Image reconstruction, motion, 3D, and inverse problems
- Workshop: coding a complete image analysis workflow from A to Z
Assessment format: Multiple-choice questions and short application-based questions.
Organisation
Organisation
- Center for Imaging, EPFL
The EPFL Center for Imaging promotes and facilitates cross-disciplinary research in imaging at EPFL. It actively supports the EPFL community with the use of imaging technology, particularly by addressing its ever-growing needs in image analysis and reconstruction. The Center for Imaging’s goal is to nurture a global imaging network at EPFL and to provide common solutions to shared problems.
Program Director
- Prof. Michael Unser, Academic Director, Center for Imaging, EPFL
Program Committee
- Dr. Daniel Sage, Head of Software Development, Biomedical Imaging Group and Center for Imaging, EPFL
- Dr. Edward Andò, Head of the Image Analysis Hub, Center for Imaging, EPFL
Intructors
- Dr. Daniel Sage, EPFL lecturer
- Dr. Edward Andò, EPFL lecturer
Additional experts from EPFL and industry will teach and give presentations.
practical information
Dates and schedule
Format: 4-day course on campus, from 9:00 am to 5:00 pm
- Thursday, March 26, 2026
- Friday, March 27, 2026
- Wednesday, April 22, 2026
- Thursday, April 23, 2026
Course venue
EPFL, Lausanne, Switzerland and online
Material
Participants should bring their own laptop and be able to install open-source software.
Price
CHF 2’900.-*
* 10% special discount for contributing members of EPFL Alumni and EPFL partners
Registration deadline
January 12, 2026
Number of participants is limited
