Ji Meng Loh
BIG DATA: Healthcare Analytics
Associate Professor of Mathematical Sciences
The work of Associate Professor Ji Meng Loh, a statistician who will join the Department of Mathematical Sciences, has implications for advances in fields ranging from functional magnetic resonance imaging and epidemiology to telecommunications and astronomy. The background that is the foundation for this work spans industrial research and academia, as well as the globe. Before coming to NJIT, Loh was a member of technical staff at AT&T Labs. He has taught at Victoria University in New Zealand, at Anderson Junior College in Singapore, and at the University of Chicago and Columbia University.
Loh has also been a research fellow at SAMSI — the Statistical and Applied Mathematical Sciences Institute. SAMSI is a partnership of Duke University, North Carolina State University, the University of North Carolina at Chapel Hill and the National Institute of Statistical Sciences, in collaboration with the William R. Kenan, Jr. Institute for Engineering, Technology and Science. The partnership is part of the Mathematical Sciences Institutes program of the Division of Mathematical Sciences at the NSF. Loh completed his PhD in statistics at the University of Chicago. He added this credential to a postgraduate diploma in education from the National Institute of Education in Singapore and a bachelor’s in mathematics and physics from New Zealand’s Victoria University.
The research that Loh pursues can be broadly classified into three types: applied spatial data analysis and visualization that helps to answer questions raised by the work of collaborators, the development of statistical methodology to make better inferences from spatial data, and the working out the theory to support methodology. Many datasets are inherently spatial and/or temporal, and in a growing range of applications investigators are finding that it's important to incorporate spatial and temporal correlations into their models.
The significance of Loh’s work is indicated by the breadth of his publications. Titles include “Retail Redlining in New York City: Racialized Access to Dayto- Day Retail Resources,” “A Tale of One City: Using Cellular Network Data for Urban Planning,” “Separate and Unequal: The Influence of Neighborhood and School Characteristics on Spatial Proximity between Fast Foods and School,” “Adaptive Spatial Smoothing of fMRI Images,” “Estimating the Large-Scale Structure of the Universe Using Quasi-Stellar Object Carbon IV Absorbers.”
Support for Loh’s research as a principal and co-investigator has come from the Robert Wood Johnson Foundation and the NSF. As co-investigator for a Robert Wood Johnson Healthy Eating Research Grant, Loh looked into “Inequality in New York City’s Food Environment: Determinants of Fast Food Density, Spatial Distribution, and Store Operation.” Two NSF projects were “DHB: Decentralization and Local Public Goods: How Does Allocation of Decision-Making Authority Affect Provision?” and “Spatial Inference with Application to Astronomy.”