معرفی
Professor Ji Meng Loh is a faculty member in the Department of Mathematical Sciences at New Jersey Institute of Technology (NJIT). His research focuses on spatial statistics, quantile regression, healthcare data analysis, and software testing methodologies. He has led multiple federally funded projects including 'Scalable Inference of Quantile Regression for Large-Scale Health Care Data' (2019-2022) and 'Spatial Inference with Application to Astronomy' (2005-2010). His work bridges theoretical statistics with applications in astronomy, biomedicine, and software engineering.
Research Interests:
- Spatial point processes and bootstrap methods
- Statistical computing and machine learning
- Healthcare policy and data analysis
- Formal software testing and mutation analysis
- Astronomy data modeling
Recent Research Trends: His 2020-2025 publications emphasize methodological advancements in:
- Mortality modeling with neural networks
- Biostatistical analysis of EEG data
- Formal verification of software loops
- Mutation testing metrics
Grants & Collaboration: Co-PI on NSF-funded projects investigating local public goods allocation (2006-2012) and aerospace engineering cost modeling (2005-2013). Active collaborations span NJIT's departments of Computer Science, Public Health, and Biomedical Engineering.
Professional Contributions: Developed novel statistical methods for analyzing spatial data in astronomy and public health contexts. His work on 'equivalent mutants' in software testing has influenced industry standards. Currently oversees statistical consulting initiatives for NJIT researchers.
