박사 과정 채용(Florida Atlantic University)
- 글쓴이
- 양광수
- 등록일
- 2019-03-02 07:00
- 조회
- 1,677회
- 추천
- 0건
- 댓글
- 0건
관련링크
-
http://faculty.eng.fau.edu/yangk/home/
377회 연결
-
http://www.ceecs.fau.edu/
4609회 연결
1) 웹사이트: http://faculty.eng.fau.edu/yangk/home/
2) 학비, salary, 컨퍼런스 경비 제공
3) 연구 분야: Spatial Database and Data Mining, Graph Algorithms.
4) 지원 시기: 2019-2020
5) 프로젝트: NSF Career 2019 Spatial Network Database approach for Emergency Management Information Systems; Mar. 2019 - Feb. 2024
6) 우대 사항: 알고리즘 분석 능력, 프로그래밍 능력, 수학적인 분석 능력, 데이터 베이스, 데이터 마이닝
7) 전공 백그라운드: 전산과, 수학과, 통계학과, 공간 분석 학과
8) 이메일: yangk@fau.edu
My research is broadly in the area of Spatial Big Data (SBD). Examples of SBD include temporally detailed road maps that provide speeds every minute for every road-segment, GPS trace data from cell-phones, and engine measurements of fuel consumption, greenhouse gas emissions, etc. SBD has the potential to transform society via next-generation routing services, emergency and disaster response, and discovery of potentially useful patterns embedded in these datasets. However, SBD poses significant challenges as the size, variety, and update rate of mobile datasets exceed the capacity of commonly used spatial computing and spatial database technologies to learn, manage, and process the data with reasonable effort. My research has focused on two issues within Spatial Big Data: storage of big spatio-temporal network (STN) data and design of scalable algorithms for big spatial networks.
2) 학비, salary, 컨퍼런스 경비 제공
3) 연구 분야: Spatial Database and Data Mining, Graph Algorithms.
4) 지원 시기: 2019-2020
5) 프로젝트: NSF Career 2019 Spatial Network Database approach for Emergency Management Information Systems; Mar. 2019 - Feb. 2024
6) 우대 사항: 알고리즘 분석 능력, 프로그래밍 능력, 수학적인 분석 능력, 데이터 베이스, 데이터 마이닝
7) 전공 백그라운드: 전산과, 수학과, 통계학과, 공간 분석 학과
8) 이메일: yangk@fau.edu
My research is broadly in the area of Spatial Big Data (SBD). Examples of SBD include temporally detailed road maps that provide speeds every minute for every road-segment, GPS trace data from cell-phones, and engine measurements of fuel consumption, greenhouse gas emissions, etc. SBD has the potential to transform society via next-generation routing services, emergency and disaster response, and discovery of potentially useful patterns embedded in these datasets. However, SBD poses significant challenges as the size, variety, and update rate of mobile datasets exceed the capacity of commonly used spatial computing and spatial database technologies to learn, manage, and process the data with reasonable effort. My research has focused on two issues within Spatial Big Data: storage of big spatio-temporal network (STN) data and design of scalable algorithms for big spatial networks.
