Jian Chen, Ph.D.

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Ph.D. - Earth Science
University of Memphis (2008)

M.S. - Physical Geography
East China Normal University (2003)

B.S. - Geography (CS minor)
East China Normal University (1996)


Jian Chen, Ph.D. joined the University of Louisiana at Lafayette (UL Lafayette) as a GIS Applications Manager for the center for Business Information Technology (CBIT) and the National Incident Management Systems and Advanced Technology (NIMSAT) Institute under the Informatics Research Institute (IRI) at UL Lafayette in May 2011. Before joining UL Lafayette, he was a Research Hydrologist at AIR Worldwide Crop. headquartered in Boston, MA. He received his Ph.D. in Earth Sciences in 2008 from the University of Memphis. He leads the development of geospatial capacity at IRI including software development, analytics services, and data science in domains of emergency management, healthcare, and business intelligence. His research philosophy encompasses turning data into information, knowledge, and actionable insight. His research interests are in the broad area of productive uses of data, information, and knowledge for problem solving and decision-making. He has worked on various funded research projects in the field of geospatial analysis, GIS applications development, spatio-temporal data mining, predictive analytics, data streaming analysis, concept drift detection and adaptive learning, ontology and semantics, water resources, and hazards modeling and risk assessment. By 2017, as PI and Co-PI, he already generated research funding $907 K and research related expenditure in a total of $ 8.27 M from various federal and state agencies. His sponsors include National Science Foundation (NSF), U.S. Department of Energy, U.S. Department of Education, Federal Emergency Management Agency (FEMA), Louisiana Governor’s Office of Homeland Security and Emergency Preparedness (GOHSEP), and private sectors. He received the recognition of 2016 NSF I/UCRC Industry-Nominated Technological Breakthroughs (http://www.iucrc.org/node/mapreduce-based-spatio-temporal-hotspots-detection-and-prediction). He has been invited more than sixty times for peer reviewing for twenty-one premium journals in areas of GIS, remote sensing, water resources, and informatics.


  • Borrok, D. M., Chen, J., Eldardiry, H., and Habib, E. 2018. A Framework for Incorporating the Impact of Water Quality on Water Supply Stress: An Example from Louisiana, USA. Journal of the American Water Resources Association (JAWRA) 54(1)134-147. https://doi.org/10.1111/1752-1688.12597
  • Duggimpudi, M.B., Abbady, S. Chen, J., and Raghavan V.V., 2017. Spatio-Temporal Outlier Detection Algorithms Based on Computing Behavioral Outlierness Factor, Data & Knowledge Engineering (In Press) https://doi.org/10.1016/j.datak.2017.12.001
  • Abbady, S., Ke, C., Lavergne, J., Chen, J., Raghavan V.V., and Benton, R., 2017. Online Mining for Association Rules and Collective Anomalies in Data Streams, Second Workshop on Real-time and Stream Processing in Big Data 2288-2297, in 2017 IEEE International Conference on Big Data (BIGDATA), Boston, MA.
  • Chen, J. Abbady, S, and Duggimpudi, M., 2016, Spatio-Temporal Outlier Detection: Did Buoys Tell Where the Hurricanes Were? Papers in Applied Geography 2-3:298-314. http://dx.doi.org/10.1080/23754931.2016.1149874
  • Chen, J., Hill, A.A., and Urbano, L., 2009, A GIS-based model for urban flood inundation, Journal of Hydrology 373(1-2), 184-192, https://doi.org/10.1016/j.jhydrol.2009.04.021 (168 citations)
  • Chen, and Hill, A.A., 2007, Modeling urban flood hazard: Just how much does DEM resolution matter, Papers of the Applied Geography Conferences (2007) 30: 372-379
  • Chen, & Yu, L-Z., 2003, Analysis of requirements for a small watershed environmental management information system based on SDSS, Ocean Development & Management 20(3): 20-24