Research Group for Neuromorphic Computing
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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
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ZHAW School of Life Sciences and Facility Management
FS Cognitive Computing in Life Sciences
Schloss
8820 Wädenswil -
ZHAW School of Life Sciences and Facility Management
FG Neuromorphic Computing Group
Schloss 1
8820 Wädenswil -
ZHAW School of Life Sciences and Facility Management
FG Neuromorphic Computing Group
-
ZHAW School of Life Sciences and Facility Management
FG Neuromorphic Computing Group
-
ZHAW School of Life Sciences and Facility Management
FS Cognitive Computing in Life Sciences
-
ZHAW School of Life Sciences and Facility Management
FG Neuromorphic Computing Group
Current projects
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Multi-Asset Investment Process using Bayes Ensembles of Trading Models
Since 2009, low interest rates and asset purchases by central banks are severely distorting investment opportunities and trends in financial markets. The performance of active investment strategies decreased substantially since then. This project aims to provide an investment process that finds the optimal ...
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Design of an online expert system based on Bayes’ian Networks and its first market implementation
On a scientific basis, an online expert system for the B2B business is being developed, which enables significant cost savings in the sales process and an increase in the quality of processing. Using the example of a highly fragmented niche market (promotional items), the new approach will be tested by taking into ...