Ji Meng Loh is associate professor in the department of mathematical sciences at New Jersey Institute of Technology. He is also the coordinator of the department’s statistical consulting service. His primary research interests are in the area of spatial statistics, especially the development of statistical methodology for the analysis of spatial point patterns. Ji Meng has made contributions to bootstrap methods for spatial data, anomaly detection of spatial point patterns and understanding the effects of data quality issues on statistical inference.
In his research, Ji Meng strikes a balance between theory and applications. His statistical work has included applications in fields such astronomy, fMRI studies, public health, disease surveillance, and telecommunications.
Prior to coming to NJIT, Ji Meng served on the faculty at Columbia University and also as Principal Member of Technical Staff at AT&T Labs-Research.
2001 PhD Statistics, University of Chicago
1994 Postgraduate diploma in Education, National Institute of Education, Singapore
1991 Bsc (Hons) Mathematics and Physics, Victoria University of Wellington, New Zealand
Ji Meng’s research interest is in spatial statistics. This involves working with data that contains information about the locations from which the data are collected. Statistical analyses make use of the correlation inherent in the spatial data to improve statistical inference.
Ji Meng’s particular area of expertise is in the analysis of spatial point patterns. His work has included analyzing the degree of clustering of astronomical gas clouds, examining the relation between locations of fast food restaurants and schools in New York City, using cellular data for urban planning, residual analysis of models fit to fMRI data to identify mismodeling, and anomaly detection of spatial point patterns in order to identify unusual clusters of data points.
Ji Meng is also working on quantifying and displaying differences between two sets of mapped data, understanding the effect of data quality issues on statistical inference.
Loh (2013) - Comparing spatial densities characterizing human mobility using ratio maps - Statistics and Its Interface (accepted).
Becker, Caceres, Hanson, Isaacman, Loh, Martonosi, Rowland, Urbanek, Varshavsky and Volinksy (2013) - Human mobility characterization from cellular network data - Communications of the ACM, 56, 74-82.
Dasu and Loh (2012) - Statistical distortion: consequences of data cleaning - 38th International Conference on Very Large Data Bases (VLDB), 5(11), 1674-1683.
Yau and Loh (2012) - A Generalization of the Neyman-Scott Process - Statistica Sinica, 22, 1717-1736.
Becker, Caceres, Hanson, Loh, Urbanek, Varshavsky and
Volinsky (2011) - A tale of one city: using cellular network data for urban planning - IEEE Pervasive Computing, 10, 18-26 (also at NetMob 2011).
Yue and Loh (2011) - Bayesian Nonparametric Intensity Estimation for Inhomogeneous Spatial Point processes - Biometrics, 67, 937-946.
Loh (2011) - K-scan for Anomaly Detection in Disease Surveillance - Environmetrics, 22, 179-191.
Hariharan, Loh, Shanahan and Yamada (2010) - Spatial Probabilistic Modeling of Calls to Businesses - ACM SIGSPATIAL 2010.
Kwate and Loh (2010) - Separate and Unequal: The Influence of Neighborhood and School Characteristics on Spatial Proximity between Fast Foods and Schools - Preventive Medicine, 51, 153-156.
Loh and Jang (2010) - Estimating a Cosmological Mass Bias Parameter with Semi-Parametric Bootstrap Bandwidth Selection - Journal of the Royal Statistical Society, Series C, 59, 761-779.
Loh (2010) - Bootstrapping an Inhomogeneous Point Process - Journal of Statistical Planning and Inference, 140, 734-749.
Kwate, Yip, Loh and Williams (2009) - Inequality in Obesigenic Environments: Fast Food Density in New York City - Health and Place, 15, 364-373
Loh, Lindquist and Wager (2008) - Residual Analysis for Detecting Mismodeling in fMRI Images - Statistica Sinica, 18, 1421-1448.
Loh (2008) - Estimating Third-Order Moments for an Absorber Catalog - Astrophysical Journal, 674, 636-643.
Loh and Stein (2008) - Spatial Bootstrap with Increasing Observations in a Fixed Domain - Statistica Sinica, 18, 667-688
Guan and Loh (2007) - A thinned block Bootstrap Procedure for Modeling Inhomegeneous Spatial Point Patterns - Journal of the American Statistical Association, 102, 1377-1386.