News

Two articles accepted to domestic journals, 12/2017: Two articles have been accepted to domestic journals: The Korean Society for Geo-Spatial Information Sicence, and Korean Society of Hazard Mitigation.

Presentation at two conferences in Korean, 11/2017: I presented two conference articles at KSCE 2018 convention, and KSIS fall conference.

2017 Spring Semester ACE Best Teacher Award, 10/2017: I am delighted to have received ACE Best Teacher Award in recognition of my work during last semester.

KOICA Global Training, 09/2017: I participated in a workshop as an instructor for Capacity Building For Surveying and Geographic Information Institute. Twenty representatives from eight countries (e.g., Nepal, Mozambique, Mongolia, Uzbekistan, Vietnam, Nicaragua, Philippines, and Rwanda) joined this worksop.

Spring semester ends, 06/2017: I taught three courses -- Fundamentals of GIS, Surveying I, and Capstone Design -- in the spring at Chosun University. The figure shows the final test for Fundamentals of GIS. Well done everyone.

New position as an Assistant Professor, 03/2017: I embark on a new journey of my life as an Assistant Professor in the Department of Civil Engineering, Chosun University, Korea.

Instructor, GEOG 489 (Programming for GIS), 01/2017: I led GEOG 489 (Programming for GIS) course, Spring 2017 in the Illinois at Urbana-Champaign Department of Geography and Geographic Information Science. Topics include the principles of programming, advanced function and tools coding, visualization, fundamental spatial data structures, and spatial algorithms

Android app with AWS Kinesis, 12/2016: I am developing an android app with AWS Kinesis. The aim of this work is for streaming data analysis of radiation levels.

Teaching at CyberGIS Fall Training Workshops, 11/2016: I taught how to use R on ROGER, CyberGIS Fall Training Workshops. This workshop provided how to use parallel processing for R in geospatial applications by using Jupyter Notebook.

Presentation at ACM SIGSPATIAL, 10/2016: I presented a paper "Data depth based clustering analysis" at ACM SIGSPATIAL 2016 [ppt]. The accept rate was 18% (40 out of 217) this year.

ACM GIS paper is accepted, 09/2016: Data depth based clustering analysis was accepted as a full paper to ACM SIGSPATIAL 2016. This paper proposes a new data depth based clustering method which can preserve clusters under affine transformations.

  • M.-H. Jeong, Y. Cai, C. J. Sullivan, and S. Wang. Data depth based clustering analysis. In Proc. of 24th ACM SIGSPATIAL International Conference on Geographic Information Systems, California, USA, accepted 2016.

Presentation at CyberGIS 2016, 08/2016: This work proposes a hypothesis testing of two spatiotemporal patterns using data depth. Data depth based inference takes into account the overall structure of the data to detect differences in the amount of scale and shifts in location.

Teaching at CyberGIS Summer School, 07/2016: I taught how to use R for big spatial data analysis on ROGER, CyberGIS Summer School. This workshop provides how to leverage parallel processing in R, and how to connect R up to Hadoop.

Three short peer-reviewed papers are accepted, 06/2016: I have had three short peer-reviewed conference papers accepted in quick succession.

  • M.-H. Jeong, J. Yin, C. J. Sullivan, and S. Wang. Robust statistical approaches to enhance spatial autocorrelation. In Proc. of 9th International Conference on Geographic Information Science, Canada, accepted 2016.
  • M.-H. Jeong, C. J. Sullivan, and S. Wang. Minimization of the impact of sensor velocity on the probability of source detection using geographically weighted methods. In Proc. IEEE Nuclear Science Symposium & Medical Imaging Conference, France, accepted 2016.
  • M.-H. Jeong, S. Wang, and C. J. Sullivan. Density maps based on data depth. In Proc. of 3rd International Conference on CyberGIS and Geospatial Data Science, USA, accepted 2016.

Android app development for streaming data analysis, 05/2016: I made an android app with AWS kinesis to load and analyze streaming data. This app will be used for radiation data analysis in real time.

Presentation at AAG 2016, 04/2016: I gave a short presentation at Association of American Geographers Annual Meeting: Robust cluster analysis using data depth. This approach is affine equivalence and robust to noises.

Teaching at Advanced Topics in GIS (GEOG 479), 03/2016: I taught big data analysis with R in the course of Advanced Topics in GIS (GEOG 479). This sub-course deals with the fundamentals of parallel R computation as well as Hadoop with R to have a better undersanding of big spatial data sets.

A full peer-reviewed conference paper submission, 02/2016: This paper describes spatial analyses as a manner that includes new insights and advances that are often ignored in a standard geospatial analysis. The approach is based on the robust statistics methods. This study presents how and why conventional geospatial analysis can be unsatisfactory under non-normal distributions with practical and simulated data. Further, the revised approaches show insensitivity against deviations from the assumptions.

  • M.-H. Jeong, J. Yin, C. J. Sullivan and S. Wang. Robust statistical approaches to enhance spatial autorcorrelation and density estimation. in review

A short conference paper submission, 01/2016: This article presents a broad range of geospatial methods for radioactive source detection.

  • M.-H. Jeong, C. J. Sullivan and S. Wang. Urban search of radioactive materials enhanced by mobile sensor networks and geospatial methods. in review

Experiments for anomaly detection of radiation levels, 12/2015: The aim of this work is higher probability of detection with lower false alarm rate with mobile sensors. I am currently using local spatial association to identify radiation abnormality.

Teaching at CyberGIS Fall Workshops, 11/2015: I lead two workshops: Data Parallelism for GIS Analysis, and Data Science with Pig on Hadoop. These workshops provide hands-on training with cutting-edge CyberGIS applications with a focus on big data handing and analysis.

Journal article accepted, 10/2015: This research investigates the graphical representation of uncertain numerical data (such as the outputs from predictive epidemiological models) that makes relative (qualitative) judgments as effortless as possible, while making absolute (quantitative) estimation as effortful as possible.

  • Jeong M-H, Duckham M, Bleisch S (2015) Graphical Aids to the Estimation and Discrimination of Uncertain Numerical Data. PLoS ONE 10(10): e0141271.

Presentation at 2015 CyberGIS All Hands Meeting, 09/2015: I introduced my current project "Detection of the Illicit Movement of Nuclear Materials with Big Data" at CyberGIS AHM'15.

Journal article accepted, 08/2015: This paper describes an efficient, decentralized algorithm in a geosensor network to monitor qualitative spatial events in a dynamic scalar field. The events of interest involve changes to the critical points (i.e., peak, pits and passes) and edges of the surface network derived from the field.

  • Jeong, M.-H. and Duckham, M. Decentralized Detection of Qualitative Spatial Events in a Dynamic Scalar Field. Sensors, 15:21350-21376, 2015

Teaching at CyberGIS Summer School on Big Data Landscapes, 07/2015: I led Data Science with Python on Hadoop workshop. This workshop is primarily designed for researchers who need to understand how to apply data science to large datasets with Hadoop.

Presentation at Vespucci 2015, 06/2015: I presented my paper [presentation file] at GIScience 2015 Vespucci Institute. It was a good oppoortunity to meet big and young stars at GIScience discipline.

Conference article accepted, 05/2015: This article provides an alternative to understand radiation level changes using surface networks.

  • M.-H. Jeong, S. Wang and C. J. Sullivan (2015) Analysis of dynamic radiation level changes using surface networks. Accepted for Advancing Geographic Information Science: The Past and Next Twenty Years, 2015, Maine, USA.

Presentation at AAG 2015, 04/2015: I gave a short presentation at Association of American Geographers Annual Meeting. I explained the detection of radiation level changes using geovisualization and geographic information systems.

Nuclear forensics with GIS, 02/2015: I have involded in a new project, Nuclear forensics driven by geographic information system and big data analytics. I visualized radiation measurements in July 2013, Koriyama Japan. The data was acquired from Safecast (http://blog.safecast.org).

New position as a postdoctoral research associate, 10/2014: I have joined in CyberGIS center as a postdoctoral research associate. I will mainly work on spatial algorithm to deal with unprecedented large data sets.

Presentation at ARC Linkage Project update meeting: 08/2014: "Networks, neighborhoods and newborns: defining household and local area influences on social connectedness, to understand pathways to health"
I presented preliminary findings at this meeting. People trajectories are generated based on CATI data. Frequent patterns of location use (e.g., house - work - house) are discovered using people trajectories. The discovered frequent sequences revealed how the individual trajectories differ across advantaged and disadvantaged areas. The linked image visualizes the frequent sequences of advantaged areas by using hierarchical layered graphs.

Pilot experiment for communicating complexity and uncertainty, 07/2014: The pilot experiment was conducted with volunteer students in Spatial Visualization class. The aim of this experiment is to enable policy makers to make informed and effective decisions using visualization. Mathematical models are increasingly used to help policy makers to decide alternative strategies in terms of infectious disease health policy. However, modelling approaches are challenging to communicate accurately and comprehensibly. This experiment provided non-numeric displays to the participants in order to avoid communicating with uncertain explicit quantities.

PhD degree award, 06/2014: I have sucessfully completed all the requirements for the PhD degree. My thesis examiners were Associate Professor Nittel Silvia at University of Maine and Professor Monika Sester at University Hannover. The citation is "Who studied the foundations of spatial computing in highly distributed environmental sensor systems, like wireless geosensor networks. His results show how decentralized algorithms can be used efficiently to monitor the qualitative characteristics of spatiotemporal fields. His work will help us to make sense of big data from environmental sensor systems."

  • M.-H. Jeong. Qualitative characteristics of fields monitored by a resource-constrained geosensor network. Ph.D. dissertation, University of Melbourne, 2014.

New position as a research fellow (PostDoc), 02/2014: I have joined Sense+Know project as a postdoctoral research fellow after I submitted my thesis ("Qualitative characteristics of fields monitored by a resource-constrained geosensor network").

Journal article accepted, 04/2013: This paper provides a decentralized and coordinate-free algorithm, called DGraF (decentralized gradient field) to identify critical points (peaks, pits, and passes) and the topological structure of the surface network connecting those critical points.

  • Jeong, M.-H., Duckham, M., Kealy, A., Miller, H., and Peisker, A. (Accepted) Decentralized and coordinate-free computation of critical points and surface networks in a discretized scalar field. International Journal of Geographical Information Science

Journal article accepted, 12/2012: This paper explores the design and evalutation of a family of new algorithms for determining the topological relations between regions monitored by such a resoruce-constrained geosensor network. The algorithms are based on efficient decentralized (in-network) variants of conventional 4-intersection and intersection and difference models, with in-network data aggregation.

  • Jeong, M.-H. and Duckham, M. (Accepted) Decentralized querying of topological relations between regions monitored by a coordinate-free geosensor network. Geoinformatica

Conference article accepted, 12/2012: This article proposes a decentralized and coordinate-free algorithm to monitor spatial events in a dynamic scalar field. The events that are the focus of this article are the appearance, disappearance and movement of "peaks" (local maxima).

  • Jeong, M.-H. and Duckham, M. (2013) A coordinate-free, decentralized algorithm for monitoring events occurring to peaks in a dynamic scalar field. Accepted for ISSNIP 2013, Melbourne, Australia.