IEEE Symposium on Computer-Augmented Intelligence with Flexible Electronics (IEEE CAIFE)
The 2019 IEEE Symposium on Computer-Augmented Intelligence with Flexible Electronics (CAIFE’19) is part of the 2019 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2019), a flagship annual international conference of the IEEE Computational Intelligence Society (CIS).
As the technology of flexible electronics rapidly advances, a wider range of novel sensors, display, actuators and circuits have been developed and integrated as wearable systems that offer humans with unprecedented capability, flexibility and comfortableness. Up to date, the performance of Artificial Intelligence (AI) already outperforms ordinary human (if not the top experts) in specific domains, such as detection of face and lung cancer. We believe the advantage of computers over human is expected to extend to a larger scope at a faster speed. A systematic solution, based on flexible electronics, is promising in equipping human with the comparable performance as the computer. To augment human intelligence with flexible electronics is what this symposium is mostly interested.
It is our particular focus to integrate technological advances in flexible electronics to improve the human capability and intelligence. These technologies allow long-term monitoring of human activities and intuitive interaction with users. Hardware advances, including the critical studies in material sciences, and software development are both important in this inter-disciplinary domain.
We welcome all submissions (methods, analysis and applications) relevant to our ultimate goal. The manuscripts should be submitted in PDF format. Please refer to the submission page for further guidelines on manuscript preparation.
- Wearable Computing with Flexible Electronics
- Soft and Stretchable Sensor
- Deformable Display
- Soft Actuators
- Bendable Circuits
- Human-Computer Interaction with Flexible Electronics
- Signal Processing for Flexible Electronics
- Computer-Aided Design for Flexible Electronics
- Machine Learning/Artificial Intelligence/Deep Learning for Flexible Electronics
- Applications in Specific Domains, including Health care, Rehabilitation, Training
|Kevin Warwick||Coventry University, UK|
|Nadia Thalmann||Nanyang Technological University, Singapore|
|Peter Kyberd||University of Greenwich, UK|
|Jun Ueda||Georgia Institute of Technology, US|
|David J. Reinkensmeyer||University of California, Irvine, US|
|Yu Haoyong||National University of Singapore, Singapore|
|Pablo Valdivia y Alvarado||Singapore University of Technology and Design, Singapore|
|Jian Chang||Bournemouth University, UK|
|Meili Wang||Northwest A&F University, China|
|Xiangyang Liu||Xiamen University, China|
|Min Jiang||Xiamen University, China|