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2313D Computer Science, Stony Brook, NY 11794-8330
Email: fusheng  wang  stonybrook edu
Phone: (631)632-2594
- Scalable Big Data Management and Analytics
- Spatial and Temporal Data Management and Analytics
- Medical Imaging Informatics
- Healthcare and Public Health Data Analytics
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I am an Associate Professor at Department of Biomedical Informatics and Department of Computer Science
at Stony Brook University. I received my Ph.D. in Computer Science from University of California, Los Angeles, and M.S. and B.S. in Engineering Physics from Tsinghua University, China.
Prior to joining Stony Brook University, I was an assistant professor at Emory University.
I was a research scientist at Siemens Corporate Research (Princeton, NJ) before joining Emory University.
My research goal on big data management and analytics is to address the research challenges for delivering effective, scalable and high performance software systems for
managing, querying and mining complex big data at multiple dimensions, including 2D and 3D spatial and imaging data, temporal data, spatial-temporal data, and sequencing
data. My research goal on biomedical informatics is to develop novel methods and software systems to optimize the acquisition, extraction, management, and mining of
biomedical data with much improved efficiency, interoperability, accuracy, and usability to support biomedical research and the healthcare enterprise.
I received an NSF CAREER award in 2014.
CV (last updated July 23, 2017).
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Kavya Kopparapu, a summer student in Simons Summer Program of Stony Brook University, mentored by our lab, has been named a top 40 Finalist in the 77th Regeneron Science Talent Search—the nation’s oldest and most prestigious science and mathematics competition for high school seniors. Kavya will travel to Washington, DC in March to participate in the Finals Week competition. Finalists are each awarded at least $25,000, and the top 10 awards range from $40,000 to $250,000. The top 10 Regeneron Science Talent Search 2018 winners will be announced at a black-tie gala awards ceremony at the National Building Museum on March 13, 2018. More information is in the news.
I am teaching a new undergraduate CS course CSE393: Introduction to Biomedical Informatics. cover the basis of biomedical informatics, including biomedical and healthcare data management and standards, medical imaging informatics, medical image analysis, bioinfromatics, and public health informatics and GIS.
iSPEED: an Efficient In-Memory Based Spatial Query System for Large-Scale 3D Data with Complex Structures.
SparkGIS: Resource Aware Efficient In-Memory Spatial Query Processing.
Effective Scalable and Integrative Geocoding for Massive Address Datasets.
We are excited to announce that we started a new program
"Computer Science and Informatics
Research Experience Program for K12 Students" (CSIRE) at Stony Brook University.
The CSIRE program at Stony Brook University is an opportunity for qualified, academically talented and motivated K12 students interested in pursuing a career in Computer Science or Informatics. The program provides the students a unique research experience working with leading researchers in the field.
I am looking for a highly motivated undergraduate student with CS or informatics major to work on an NSF sponsored project on Research Experiences for Undergraduates (REU).
If you are interested, please submit your application at SPIDAL REU at Stony Brook University .
The workshop will bring people cross-cutting the fields of information management and medical informatics,
to discuss innovative data management and analytics technologies highlighting end-to-end applications, systems, and methods to
address problems in healthcare, public health, and everyday wellness, with clinical, physiological, imaging, behavioral,
environmental, and omic- data, and data from social media.
The workshop will be held at Munich, Germany on September 1, 2017.
The workshop is in conjunction with the 43rd Very Large Databases Conference (VLDB 2017).
ACM TechNews
featured our research on GPU accelerated spatial querying methods, which are adopted
by Fixstars Solutions Inc
for their geometry compuation engine.
The work (published in VLDB 2012) is in collaboration with the Ohio State University.
Yanhui's paper "Scalable 3D Spatial Queries for Analytical Pathology Imaging with MapReduce" won the best poster award at SIGSPATIAL 2016.
This course covers recent advances in data management systems. Topics include complex queries and optimizations, XML data management, spatial data management, distributed and parallel databases, NoSQL databases, and MapReduce based data processing systems. We will discuss the foundations of data models, transaction models, storage, indexing and querying methods for these data management systems. We will demonstrate real world databases with biomedical data, geospatial data and/or social media data.
Course Website
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