Resume

• 2009

  Master's Degree

  Applied Mathematics

  North Carolina State University

  Doctor of Philosophy (Ph.D.)

  Applied Mathematics

  North Carolina State University

  Associate Certified Analytics Professional

  INFORMS

• 2007

  BS

  Mathematics

  State University of New York College at Geneseo

• Statistical Modeling

  Control Theory

  Data Analysis

  Applied Mathematics

  Matlab

  Mathematical Modeling

  Microsoft Excel

  Differential Equations

  Research

  Simulations

  Statistics

  PowerPoint

  Optimization

  Machine Learning

  Numerical Analysis

  SAS

  Data Mining

  LaTeX

  R

  Survival Analysis

  Observer based fault detection and identification in differential algebraic equations

  Stephen L. Campbell

  Builds on an earlier paper analyzing fault detection in systems that can be modeled by differential-algebraic equations. Introduces new algorithms to isolate (identify) faults and mitigate disturbances.

  Observer based fault detection and identification in differential algebraic equations

  Stephen L. Campbell

  Introduces a novel method for fault (failure) detection in systems that can be modeled by differential-algebraic equations.

  Observer based fault detection in differential algebraic equations

  Stephen L. Campbell

  Proc. IEEE Conference on Systems

  Man

  and Cybernetics

  Explores the idea of applying an active detection signal on a window that is outside of the observation window. We find cheaper signals can be constructed in this way.

  Asynchronous auxiliary signal design for failure detection

  Stephen L. Campbell

  Investigates active fault detection in linear time invariant differential-algebraic equations in the presence of additive uncertainty and model uncertainty\n\nIntroduces a procedure to compute a minimal auxiliary signal whose purpose is to facilitate fault detection\n\nSufficient conditions for the existence of such a signal are given

  Auxiliary signal design for failure detection in differential-algebraic equations

  Quantitative professional with training in applied mathematics and data science.\n\n- Experience implementing and prototyping machine learning solutions with SAS

  R

  and MATLAB.\n\n- Experience researching and numerically solving optimal control problems and numerical integration.\n\n- Interested in combining numerical analysis

  control theory

  modeling

  and data science in future projects.\n\n- Proven researcher in failure detection in differential algebraic equations.\n\n- Strong written and verbal communicator of quantitative subjects to diverse audiences.\n\n- Peer-reviewed author in several professional publications.\n\n- Experience successfully working independently and in teams.

  Jason

  Sandia National Laboratories

  M&T Bank

  The Johns Hopkins University Applied Physics Laboratory

  M&T Bank

  North Carolina State University

  Laurel

  Maryland

  Sr. Professional Staff

  The Johns Hopkins University Applied Physics Laboratory

  Buffalo

  NY

  Developed

  back-tested

  and maintained a model for detecting individual and commercial money laundering and terrorist financing. \n\nReported and presented on audit findings from federal regulators.\n\nDeveloped a loss forecasting model for an indirect auto portfolio using survival analysis.

  Banking Officer / Quantitative Risk Analyst

  M&T Bank

  Implemented a genetic algorithm aided by a Nelder-Mead search to explore a multidimensional parameter space with binary output. Classified the space into positive and negative regions with 95 percent confidence. The exploration was done with Latin hypercube sampling.

  Technical Intern

  Albuquerque

  New Mexico Area

  Sandia National Laboratories

  Topic: Physiologically based pharmacokinetic modeling of hazardous chemicals in fetuses

  newborns

  and mothers.\n\nGuided research and filled in knowledge gaps. Worked closely with a scientist from the EPA to develop research goals for the four student undergraduate research group.

  Research Mentor

  Raleigh-Durham

  North Carolina Area

  NC State University

  Developed

  tested

  and analyzed statistical models to forecast loan losses using SAS software.

  Quantitative Risk Analyst

  Buffalo/Niagara

  New York Area

  M&T Bank

  Model development team lead for an anti-money laundering account/customer segmentation model. Lead a group of five analysts.

  M&T Bank

  North Carolina State University

  Analyzed fault detection in systems modeled by differential-algebraic equations. Wrote automated algorithms in MATLAB to detect faults using both active and passive approaches. The active approach required the solution of a complex optimization problem compelling the use of high quality industrial-grade software.

  Research Assistant

  Raleigh-Durham

  North Carolina Area

  Instructor of record for Calculus I. Delivered lectures

  prepared tests

  and administered final grades.

  Instructor of Record

  Raleigh-Durham

  North Carolina Area

  North Carolina State University