22.04.22

Google Researcher presents Computer Vision Highlights at CAI Colloquium

On March 30, 2022, we welcomed a special guest at our CAI colloquium. Dr. Lucas Beyer, senior research engineer at Google Brain, presented the most recent breakthroughs in applying transformer architectures to computer vision.

14.02.22

Initiative for Large-Scale Development & Testing of Autonomous Systems launched in the Canton of Zurich

ZHAW, UZH and ZHdK developed a concept for the safe development and testing of drones and robots together with renowned partners.

14.02.22

CAI focuses on autonomous systems as demonstrators for AI in teaching

A current bachelor thesis transfers our AI research to four-legged walking robots. These will serve as demonstrators and training objects for teaching.

07.01.22

Video Analysis for Data-Driven Intensive Care of Patients

In a newly-funded DIZH Rapid Action project, CAI and University Hospital Zurich team up to improve automatic data quality monitoring for intensive care interventions

17.12.21

The CAI joins AI4Media as Associate Member

The ZHAW Centre for Artificial Intelligence has become Associate Member of the EU-funded Network for Excellence AI4Media: Artificial Intelligence for the Media and Society. Tha aim of AI4Media is to become a Centre of Excellence engaging a wide…

16.12.21

First successfully completed Ph.D. at the CAI

Jan Deriu, researcher in the Natural Language Processing Group at the CAI, successfully completed his Ph.D. at the University of Zurich in October 2021. The Ph.D. was co-supervised by Prof. Dr. Mark Cieliebak, head of the NLP Group, within the PhD…

13.12.21

ZHAW President Jean-Marc Piveteau and the board of the School of Engineering visiting the CAI

On Friday December 10, ZHAW president Jean-Marc Piveteau and board members of the ZHAW School of Engineering visited the campus Eulachpassage. Mark Cieliebak presented the results of the Innosuisse-funded project Interscriber (link and pix),…

03.12.21

New paper introduces a method to robustly homogenize data targeting COVID detection from CT images

The PrepNet neural network architecture homogenizes the appearance of CT images from different source datasets and hospitals so that more robust and trustworthy classifiers can be trained based on larger datasets.

23.11.21

How can kids learn so much faster than transformers?

Christoph von der Malsburg guest speaker at the CAI colloquium in Winterthur on November 17, 2021.

12.11.21

Bias, awareness, and ignorance in deep-learning-based face recognition

Humanity has developed successful approaches to overcome human biases. Our recent study shows why we need different approaches to reduce bias in machines.