Researchers in CAMS working on problems related to Statistics:

Dhar, Sunil
Dios, Rose
Guo, Wenge
Johnson, Ken
Loh, Ji Meng
Subramanian, Sundar
Wang, Antai

Applied Probability and Statistics/Biostatistics is concerned with the study of processes in which uncertainty plays a significant role. In today's data driven environment, the utility and need for modeling and statistical analysis of uncertainty is assuming increasing importance in virtually every field of human interest. Typical examples are in the comparative study of DNA databases, evaluation of drug safety and effectiveness, design and analysis of modern communication protocols, stochastic models in finance, study of aging and performance analysis of components and complex systems.

While Applied Probability and Statistics/Biostatistics are driven by the need to solve applied problems, their progress and development comes from basic research and from their applications to solve specific problems arising in practice. This interplay of basic and applied research has benefited both. Real life applied problems have often posed new theoretical challenges which had to be solved by developing new methods (e.g., survival analysis and clinical trials). Conversely, theoretical ideas and methods which were developed in a specific applied context were later seen to be of much broader applicability (e.g., nonparametric aging ideas which owe their origins to research in stochastic modeling of reliability of physical systems were later seen as useful constructs in many other areas such as in the study of queuing systems, stochastic scheduling, branching processes as well as in modeling economic inequality).

The Statistical Consulting Laboratory (SCL), which operates under the umbrella of CAMS, provides data analysis and statistical modeling consulting services to the University community, as well as to external clients. Consulting on statistical and biostatistics problems channeled through the SCL, are provided by statistics faculty (e.g., Sunil Dhar, Ari Jain and Kenneth Johnson on statistical consulting – in AY 2008-09). The current coordinator of the SCL is Ari Jain. Examples of recent consulting projects, in which graduate students were involved to gain valuable hands-on experience are: (i) survey design to assess the reliability of electronic voting machines, as part of a study commissioned by the Attorney General of the State of New Jersey, and (ii) a statistical analysis of the data from 3 sources (sediment, water and benthics organisms) in 10 sites in Kearney Marsh to test the effect of AquaBlok on the level of metal and organic contaminates and (iii) statistical modeling of the metal concentration and organic composites in clean wetland soils in Northeast/Southeast marsh in October ’07 and June ’08 as a function of levels of elevation, marshes, depths, and time period: as part of several projects with the Meadowlands Environmental Research Institute. An example of biostatistics consulting is: the determination of optimal number of woodchucks that need to be observed in winter based on a specified significant difference for a given fixed percentage of woodchucks experiencing arrhythmia in summer.

The current research interests of the Statistics faculty are in the following broad and overlapping areas: applied probability models (Bhattacharjee, Dhar), Bayesian modeling (Bhattacharjee), bioinformatics and computational biology (Guo), bootstrap methods (Chang, Subramanian), censored time-to-event data analysis (Chang, Dhar, Subramanian), computational statistics (Guo, Subramanian), discrete multivariate distribution / reliability models and inverse sampling (Dhar), distribution theory and statistical inference (Bhattacharjee, Dhar, Subramanian), empirical processes (Chang, Dhar, Subramanian), functional data analysis (Chang), high dimensional inference (Chang, Guo), imaging analysis (Chang), minimum distance estimation (Dhar), multiple imputations methods (Subramanian), multiple testing (Chang, Guo), non-traditional applications of reliability theory (Bhattacharjee), orthogonal arrays in experimental designs (Dios), semiparametric estimation and inference (Dhar, Subramanian), statistical issues in clinical trials (Guo, Dhar), statistical theory of reliability and survival analysis (Bhattacharjee, Chang, Dhar, Subramanian), stochastic orders and their applications (Bhattacharjee), and survey sampling (Jain).  

The links to individual faculty web pages that contain more information can be found at the top of this page. A description of individual faculty research can be found below: