基本信息
views: 13
![](https://originalfileserver.aminer.cn/sys/aminer/icon/show-trajectory.png)
Bio
Ashkan Ebadi is a multidisciplinary applied data science researcher with expertise in artificial intelligence (AI), machine learning, deep learning, and graph analytics. He received his Ph.D. in information systems engineering with an emphasis on AI-based decision support systems. He also carried a two-year postdoctoral fellowship in health informatics at the University of Florida (USA). He is currently a senior research officer at the National Research Council Canada (NRC), the government of Canada’s largest research organization, an Adjunct Assistant Professor at the University of Waterloo, an Affiliate Assistant Professor at Concordia University (Canada), and a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) organization. Ashkan has intensive academic and industrial experience in the design and implementation of data-driven solutions. His 12+ years of professional industry experience covers the entire life-cycle of the data science pipeline, from (business) problem definition to scalable big data analytics applications. His research aims to leverage advanced analytics and machine learning to solve complex real-life problems in various domains.
Research Interests
Papers共 60 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
SENSORSno. 5 (2024): 1664
arxiv(2024)
Cited0Views0Bibtex
0
0
arxiv(2024)
Cited0Views0Bibtex
0
0
Archives of Advanced Engineering Science (2023)
Sensors (Basel, Switzerland)no. 19 (2023): 8122-8122
arXiv (Cornell University) (2022)
2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)pp.613-618, (2022)
Load More
Author Statistics
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