2019-2020: Assessment of MTA Paratransit Call Center Performance
Sponsor: Disability Rights Maryland
Description. The AML team analyzed the performance of the MTA Mobility call center. The students
determined trends in the number of calls received by the center, developed tools to
visualize the performance in relation to the federal standards for paratransit call
centers, and developed tools to build an optimal staff schedule to handle the calls
in a timely manner.
2018: Donation Record Analysis for the Baltimore Humane Society
Sponsor: PNC Bank
Description. The AML team analyzed the historical donations data provided by the Baltimore Humane
Society (BHS) and researched possible ways to help BHS increase the amount of future
2016–2018: Forecasting Natural Gas Demand
Sponsor: Exelon Corp.
Description. The AML team used advanced statistical methods to create a model for forecasting
demand for natural gas in the residential/comercial and industrial markets.
2015–2016: Particle Swarm Optimization Method for Automated Model Baselining
Sponsor: RTR Technologies, LLC
Description. The AML team used a particle swarm optimization method to develop an algorithm to
predict the ideal number of checkpoints needed to process passengers from international
2011–2013: Mathematical Modeling of Segregation Patterns in Urban Areas
Sponsor: US Department of Housing and Urban Development
Description. The AML developed mathematical models of multi-group residential segregation in
urban areas. The racial distribution of neighborhoods in urban areas has been front
and center of the wider debate about racial disparity. The teams tackled this problem
with probabilistic tools using Markov chain models to analyze and study the evolution
of residential segregation at the census tract level.
2009–2011: Risk Analysis: Toxic Materials Transportation Security
Chemical Security Analysis Center (CSAC)Description.
The AML worked with CSAC, a unit of the US Department of Homeland Security, to design
a mathematical model to assess and manage the risk to the population involved in transporting
toxic chemicals and to evaluate the available tools for solving the resulting mathematical
problem. The student team adapted a minimum cost network flow model with randomized
cost coefficients. This work was supported by the US DHS through the grant TCN 10-030.
Dennis Howell, Alexei Kolesnikov, Angel Kumchev, Patrick O’Neill and Matthew Tiger.
Estimation of the commodity flow of chlorine from storage data. Journal of Transportation Security 5 (2012), 51–68.
2008–2009: A Study of the Deer Population in Baltimore County
Sponsor: Baltimore County Government
Description. The AML worked with the Baltimore County Department of Environmental Protection
and Resource Management and with the Towson University Environmental Science Program to
estimate the deer population in Baltimore County and to model the population in the
2005–2008: The Mathematics of Geographic Profiling
National Institute of JusticeDescription.
The AML worked with the National Institute of Justice to determine the optimal police
search area for a serial criminal. This is the question of how, given the location
of the crimes committed by a single offender, to determine an optimal search area
for that offender's home base. This work was supported by the National Institute of
Justice through grants 2007-DE-BX-K005 and 2005-IJ-CX-K036.
M. O'Leary. The Mathematics of Geographic Profiling. Journal of Investigative Psychology and Offender Profiling 6 (2009), 253–265.
2004–2005: Analysis of the Carroll Area Transit System
Carroll Area Transit SystemsDescription.
The AML worked with Carroll Area Transit Systems to provide statistical models that
can be used to predict the optimal number of vehicles needed for the system. The team
also analyzed the current operations of the system, and compared different bus scheduling
algorithms. The team's results were published in the following article.
G. Han and J. Zimmerman. Predicting Demand for the Carroll Area Transit System. UMAP Journal 27.1 (2006).
2003–2005: Rural Baltimore County Domestic Well Analysis
Baltimore County GovernmentDescription.
Two AML teams analysed data provided by the Baltimore County Department of Environmental
Protection and Resource Management to look for patterns in the failure rates of rural
domestic water wells. The teams' results were published in the following article.
K. Koepnick and X. Wang. Logistic Regression Analysis of Well Failures in Baltimore County. Journal of Data Science 7 (2009), 111-127.
2002–2003: An Analysis of the Optimal Staffing Level of the Baltimore City Fire Department
Baltimore City Fire DepartmentDescription.
This project determined an approximately optimal staffing level for the Baltimore
City Fire Department. The team's results were published in the following article.
A. Engel and C.L. May. Optimal Staffing at the Baltimore City Fire Department. UMAP Journal 26.1 (2005).
1998–1999: Validation and Enhancement of Applications of Models from Epidemiology
to INFOSEC Assurance Metrics
Science Applications International Corporation (SAIC)Description.
This project investigated the use of epidemiological models to simulate and analyze
the spread of computer viruses through a corporate network. The team's results were
published in the following article.
J.L. Aron, R.A. Gove, M. O'Leary, S. Azadegan, and M.C. Schneider. The Benefits of a Notification Process in Addressing the Worsening Computer Virus
Problem: Results of a Survey and a Simulation Model. Computers and Security 21 (2002), 142-163.
1996–1997: Customer Usage Profile for Fast-Packet Frame Relay
Sponsor: Bell Atlantic
Description. The AML team developed customer usage profiles for the relay of fast packets through
the communications network. Data communications engineering and queueing theory were
used to develop models for projection of network impact, processor occupancy, and
link utilization in the network serving Bell Atlantic's industrial and business clients.
1995–1996: A Computer-Adaptive Mathematics Placement Test
Sponsor: Towson State University
Description. The AML adapted a computer-based mathematics placement test from the nationally recognized
series of tests available from the Mathematical Association of America. The AML test
is computer-adaptive and uses information about the student's background to customize
the level of the test and adjusts as the student takes the examination. Students are
advised on placement in accordance with their skill level and their major.
1993–1994: Interface Between a Database System and Statistical Software
Sponsor: Martin Marietta Aero and Naval Systems
Description. The AML team wrote a front and back end to a statistical package linked at the laboratory
bench to a materials database used in the production of state-of-the-art marine and
1990–1992: Scheduling Production of Prepared Plated Media
Sponsor: Becton Dickinson Microbiology Systems
Description. Plates treated with growth media used for cultivation of bacteria used in disease
diagnosis are produced on several production lines at the Becton Dickinson Hunt Valley
installation. The scheduling package designed by the AML optimizes the weekly schedule
and takes account of inventory, quarantines, cleanup and setup times on three of the
1989–1990: An Enrollment Model for Resource Scheduling
Sponsor: Towson State University
Description. An AML team developed software to help the registrar's office schedule courses based
on the changing demands within majors and in the requirements for degrees.
1988–1989: Statistical Survey of Long-Term Care Patients
Sponsor: BlueCross BlueShield of Maryland
Description. Towson actuarial science students and other mathematics majors investigated the length-of-stay
of Marylanders in nursing homes for the purposes of helping the sponsor to evaluate
the marketing and pricing strategy for long-term care insurance policies.
1986–1987: Estimation of Sales Tax Liability
Sponsor: State of Maryland, Comptrollers Office
Description. Calculation of the liability of sales tax to be paid to the State of Maryland by retail
companies doing business in the state had been obtained by teams of auditors combing
through all of the business' records. The AML team wrote software to allow for just
one or two auditors to select a stratified sample to estimate the tax liability with
a high degree of accuracy.
1985–1986: Customer Service Queuing Model
Sponsor: Citicorp of Maryland
Description. The Citicorp Choice credit card service desk had varying needs for operators and telephone
lines. By setting up a real-time scheduling device, the AML team helped Citicorp meet
its service goals on the help-line.
1984: Acoustical Pattern Recognition
Sponsor: AAI Corporation
Description. Students in physics and mathematics joined together to study the acoustical signatures
of several vehicles in an attempt to design a remote recognition device.
1983–1984: Collection of Cancelled Checks for Processing
Sponsor: Union Trust Company of Maryland
Description. Union Trust had 85 branch offices in all parts of Maryland. The AML team developed
an algorithm for the collection of cancelled checks from the branch offices for processing
at the central Guilford Avenue center. The system was written to take into account
the volume of check activity at branch offices, the monetary value of the checks,
and the efficiency of routes.
1982–1983: Optimal Test Station Loading
Sponsor: Westinghouse Electrical Corporation
Description. Westinghouse's Electronics Repair Center serviced parts for airplanes used by the
Armed Forces. The AML team developed a scheduling program to help the service center
minimize the time that a part is in the center for evaluation, repair and inspection.
1980–1981: Student Housing at Towson State University
Sponsor: Towson State University
Description. The AML team investigated demographic and enrollment trends and projected the on-campus
residential needs for the University. The projections were used in presenting the
funding package to the state legislature.