As represented in my resume, I have a strong interest in theoretical work in sequential analysis. Also, I branched out to a variety of applied areas. The combinations of these two interests lead into an extensive work on dynamic sampling and on statistical modeling.

In industrial statistics, I have determined innovative statistical methodologies that have a great impact on design for manufacturing, on software testing and on computer security. In the design for manufacturing, I introduced sampling designs that reduced cost while optimizing product performance (projects funded by Advanced Research Project Agency, US Army, Sematech Center of Excellence, Advanced Electronics Technology, Florida High Technology and Industry Council Program, and NASA). In software testing, I determined new predictive models and new software testing methogologies that enhance existing software testing (project funded by IBM). In computer security, I determined an innovative statistical approach for predicting computer intrusions (projects funded by US Air Force and US Navy).

In medical statistics, I have developed sampling techniques and new applied statistical methodologies that reduce the cost of the overall experiment and still yield very significant results (projects funded by DBA Systems, Dyshpasia Systems (DSI), HealthFirst Heart Institute, Melbourne and Cocoa Walk-In Clinics, and Neurolgy Group Inc.). I am leading a Phase III statistical design for approval by the Food and Drug Administration (project funded by Dysphasia Systems Inc.).

In mathematical statistics, I determined Bayesian sampling schemes with applications in software reliability and in clinical trials. In some papers, I also used a non-Bayesian approach to determine asymptotic optimality of sequential sampling schemes. I have also done research in optimal testing and sequential point estimation to name a few. I still have a strong interest in theoretical work in sequential analysis, as represented in my resume. I am serving as an associate editor for seqential analysis. This is a leading and a highly respectable statistics journal.

From January 1990 until July 1998, I was a principal investigator along with Dr. T. Sanders of a project entitled, "Predictive Bicmos Process research has involved applying advanced statistical methods to solve engineering design problems which resulted in the software package, STADIUM (Statistical TCAD Analysis for Design for Manufacturing). The primary funding sources have been DARPA, SEMATECH and Texas Instruments. The project has attracted substantial funding to Florida Tech. Using my expertise in the Design of Experiments, I have worked closely with industry engineers to determine which methods are most useful and needed in practice. I have helped considerably in writing the proposals, papers, and presenting the statistics behind this project. I am very delighted to use my statistical knowledge in applied fields.

From June 2001 until August 2003, I was fully funded by the US Air Force and the US Navy to determine an innovative statistical tool to predict intrusions based on the internet protocol characteristics. Instead of using data mining techniques, I proposed a new test for anomaly detection based on advanced statistical techniques. I was able to predict anomalies while minimizing false alarms and maximizing intrusion detection. This work provides a direct application to homeland security and the security of computer systems.

From September 2003 until the present, I am managing a Phase III statistical design for approval by the Food and Drug administartiion. The goal of this study is to test Pneumoflex, a drug that utilizes an inhaled substance (tartaric acid) to direclty assess the laryngeal cough reflex and the integrity of the neurological airway protection mechanism in humans (project funded by Dysphasia Inc.).

From May 1, 2004 until May 2005, I am a principal investigaor along with Dr. F. Ham of a project entitled "Infrasound Classifier Development". This research consists on determining an innovative statistical approach that enables a real-time neural network to efficiently classify several types of infrasonic transient and continous waves signals.

I have been very successful in implementing sequential designs in both industrial and medical settings. Historically, designs were very theoretical and thus very hard to implement in practice. Today, the trend is to use the theoretical approach but to make it applicable to the real world.

My peers consider me both a theoretical and an applied statistician. This is a very unique quality in the statistical discipline. Very few statisticians have the ability to achieve respect in both. Consequently, I feel that I am one of the pioneers who are forging the way to close the gap between the theory and the application of statistics.

I feel that it is very important as a faculty member to aggressively search for other individuals throughout the global community in which to share ideas and to work with to promote a global unity. In conclusion, I have developed a strong interdisiplinary research program and my ultimate goal is to keep narrowing the gap between mathematical statistics and real world applications.