Research Group for Neuromorphic Computing
![](/storage/_processed_/e/3/csm_NCG_picture_532abe8cdd.webp)
Introduction
The Research Group for Neuromorphic Computing develops advanced neural-network based algorithms, software libraries, and systems with the new generation of computing chips – brain-inspired neuromorphic sensing and computing hardware. We focus on perception, motion planning, and control for robotic actuators with applications in life sciences: healthcare, agriculture, food processing, and smart environments. We follow a human-centered design approach to develop new generation of physical AI systems that are power-efficient, adaptive, and safe.
Expertise
- Neuromorphic computing hardware and algorithms
- Event-based vision
- Robotics: Motion planning, control, SLAM
- Efficient machine learning and AI
- Dynamical systems, cognitive architectures
Areas of application
- Assistive robotics in healthcare, agriculture, food processing, smart environments
- Machine vision in healthcare, agriculture, food processing, smart environments
- Continual learning and adaptive systems
- Robot safety, human-robot interaction
Collaborations and partners
Engagement in teaching
Our research group includes teaching engagements at BSc and MSc level as well as in continuing education.
Our Team
-
ZHAW Life Sciences und Facility Management
FS Cognitive Computing in Life Sciences
Schloss
8820 Wädenswil -
ZHAW Life Sciences und Facility Management
FG Neuromorphic Computing Group
Schloss 1
8820 Wädenswil -
ZHAW Life Sciences und Facility Management
FG Neuromorphic Computing Group
-
ZHAW Life Sciences und Facility Management
FG Neuromorphic Computing Group
-
ZHAW Life Sciences und Facility Management
FS Cognitive Computing in Life Sciences
-
ZHAW Life Sciences und Facility Management
FG Neuromorphic Computing Group
Current projects
- Vorherige Seite
- Seite 01
- …
- Seite 16
- Seite 17
- Seite 18
- Seite 19
- Seite 20
- …
- Seite 25
- Nächste Seite
-
Dayzzi - Next Generation: Empfehlungssystem mit neuronaler Intelligenz
Empfehlungssysteme sind auf digitalen Plattformen allgegenwärtig. Viele Systeme stützen sich allerdings entweder auf die Verfügbarkeit grosser Datenmengen, die ihnen eine datengetriebene Optimierung erlauben (kollaboratives Filtern), oder dann sind sie eher starr und primitiv. Gerade im Umfeld von Life Sciences und ...
-
European government bond dynamics and stability policies: taming contagion risks
From 2004 to 2015, the market perception of the sovereign risks of euro area government bonds experienced several different phases, reflected in a clear time structure of the correlation matrix between the yield changes. “Core” and “peripheral” bonds cluster in a bloc-like structure, but the correlations between the ...