LynxData – A New Startup in Digital Innovation

LynxData, a new startup founded by members of the iCoSys community, is at the forefront of digital innovation. Specializing in complex IT systems and multi-platform applications, LynxData is based in Grolley, Fribourg, and is dedicated to pushing the boundaries of technology.

PhD Position in Machine Learning (Document Image Analysis)

Large language models (LLMs) have a high potential for analyzing, recognizing, and validating scanned documents. However, they are mainly focused on the OCR text and do not take into account visual aspects, such as layout, illustrations, etc. that are of fundamental importance for document understanding. The successful candidate will perform basic research and develop novel methods for efficient integration of visual aspects into LLMs for document understanding. A particular focus will be to obtain explainable results with respect to both visual and textual contents of the documents.

Artificial Intelligence at HEIA-FR Open Days

The Artificial Intelligence takes the stage at the Open Day event of the Engineering University of Fribourg. A full AI experience, with interactive exhibits, engaging workshops, and insightful presentations.

AI Days 2024: Advancements, Insights, and Collaborations

The AI Days 2024, hosted by CSIA-PME, showcased cutting-edge AI research and applications across industries like Industry 4.0, Healthcare, and Energy. Featuring distinguished speakers and workshops, the event facilitated connections between SMEs, researchers, and AI enterprises, fostering collaboration and understanding of Swiss AI Center activities.

Les Brainstormings d’Alliance | Maintenance prédictive: des données à l’IA

iCoSys is excited to participate in Alliance’s brainstorming event focused on predictive maintenance with AI. Predictive maintenance is crucial for companies across various industries to prevent financial losses caused by equipment breakdowns or premature replacements. This approach relies on data analysis and artificial intelligence can play a pivotal role. The event on September 28 will feature discussions among industry peers and academic institutions on the automatic collection and management of relevant data for effective predictive maintenance. Additionally, Prof. Dr. Jean Hennebert will deliver a talk on the remaining research challenges in this field.