基本信息
views: 154
![](https://originalfileserver.aminer.cn/sys/aminer/icon/show-trajectory.png)
Bio
Prof. Demiris' research interests include Artificial Intelligence, Machine Learning, and Intelligent Robotics, as they pertain to interactive, or 'human-in-the-loop' systems. Of particular interest are fundamental algorithms for intelligent perception, multi-scale user modelling, and adaptive cognitive control architectures in order to determine how intelligent robots can generate personalised assistance to humans in order to improve their physical, cognitive and social well being. He participates in multiple national and international research projects at the interface between the theory and application of interactive learning systems. A major current line of research is centred around the Royal Academy of Engineering Chair in Emerging Technologies (Personal Assistive Robotics, 2019-2029), where he researches AI and machine learning methods for long-term modelling of combined human physical, physiological and cognitive states to allow smart robots to assist humans to achieve their full potential. With multiple international partners (Berkeley, CSHL, Duke, Harvard, NYU and USC in the USA, and UCL & Essex in the UK) within the MURI USA/UK research project "Multimodal Brain Machine Interfaces for Enhancing Decision Accuracy", he is researching the use of human-centred information processing from cameras and wearable sensors to detect human states during driving, in order to intelligent control the visualisation of contextual information to assist the human driver. With multiple European partners (Aalto (Finland), CTU (Czech Republic), UPC (Catalunya), U Bordeaux (France)), he is also researching the use of multimodal information (visual, tactile, and text) to build rich representations of complex (e.g. articulated) objects to assist their intelligent manipulation by robots. With multiple UK collaborators (Herriot-Watt University and University of Manchester) he collaborates through the "UKRI Trustworthy Autonomous Systems Node on Trust" project on machine learning algorithms for acquiring, maintaining and repairing human trust to robotic assistive systems. Finally, within the InnovateUK "D-RISK" project, he collaborates with colleagues from Imperial's Transport Systems Laboratory, DRISK.AI, Claytex Services, Transport for London, and DG Cities, to research how computer vision and machine learning can be used to enhance the perception and handling of "edge-cases" in autonomous driving. In addition to the above, he collaborates widely with academic, clinical and commercial partners to bring AI and Intelligent Robotics to impactful applications.
Research Interests
Papers共 276 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Yijun Gu,Yiannis Demiris
IEEE ROBOTICS AND AUTOMATION LETTERSno. 6 (2024): 5751-5758
arxiv(2024)
Cited0Views0Bibtex
0
0
HRI '24 Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interactionpp.1290-1292, (2024)
COMMUNICATIONS OF THE ACMno. 1 (2024): 98-109
CoRR (2024)
Cited0Views0EIBibtex
0
0
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERINGno. 99 (2024): 1-12
Autonomous Agents and Multi-Agent Systemsno. 1 (2024): 1-22
Yun Zhong,Yiannis Demiris
AAAI 2024no. 9 (2024): 10270-10278
IEEE Journal of Translational Engineering in Health and Medicine (2024): 488-498
Scientific reportsno. 1 (2024): 15698-15698
Load More
Author Statistics
#Papers: 263
#Citation: 8304
H-Index: 41
G-Index: 82
Sociability: 6
Diversity: 3
Activity: 69
Co-Author
Co-Institution
D-Core
- 合作者
- 学生
- 导师
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn