基本信息
浏览量:372
职业迁徙
个人简介
I am interested in human optimization problems, which we solve by developing software tools to improve how people learn, remember, and make decisions.
I am interested in cognitively informed machine learning, which involves the development of machine learning algorithms that leverage insights from human perception and cognition.
I build computer simulation models of human cognition that allow us to predict and understand behavior. I have worked in the areas of selective attention, awareness, memory, learning, executive control, decision making, and neuropsychological disorders.
Using these models, we can determine the most effective means of teaching and the manner in which to best present information for human consumption. We're just starting a project to instrument smart digital textbooks to boost student learning. We also developed the Colorado Optimized Language Tutor, which helps students learn facts (e.g., foreign language vocabulary) by scheduling study to promote long-term retention. Here's a link to a recent talk on this project.
I use artificial intelligence and machine learning methods to make computer systems smarter and easier to use. A past project that got some notoriety was the adaptive house, a control system that learns to manage energy resources (air heat, water heat, lighting, and ventilation) in an actual residence to maximize the satisfaction of the inhabitants and minimize energy consumption.
I serve on advisory boards for companies that apply machine learning and pattern recognition methods to challenging real-world problems (AnswerOn, Cognilytics, Exelis Visual Information Solutions, Imagen Technologies, Open Table, Sensory)
研究兴趣
论文共 171 篇作者统计合作学者相似作者
按年份排序按引用量排序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
CoRR (2023)
引用0浏览0EI引用
0
0
ICLR 2023 (2023)
引用0浏览0EI引用
0
0
AAAIno. 7 (2023): 8825-8833
引用0浏览0EI引用
0
0
ICML 2023 (2023): 23536-23557
引用6浏览0EI引用
6
0
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn