REU Students

Students are selected and funded by the DIMACS REU Program. A select few have partnered with the Experiential Learning Program and are highlighted below.

Michael Bsales

Anti-Terrorism Data Analysis for Mass Transit in New York City

Year: Summer 2022

Home Institution: University of Notre Dame

Mentor: Dr. Christie Nelson

Abstract: The current state of surveillance and security measures in public transit, such as high-traffic subway and train stations, is very vulnerable to mass casualty and terrorist attacks. In recent years, since the start of the pandemic, violent crime rates (e.g., shootings) have grown, impacting public transportation use. Exploring new and emerging screening technologies and publicly available datasets on NYC and NJ crimes, transportation, and census data can be utilized to create a predictive model that assesses which stations are at greater risk. This would involve using a risk analysis model to make these predictions. Overall, the end goal of this project is to use the predictions and understanding of different types of active and passive security measures to improve stations without adversely affecting passenger throughput.

View Project

Nithya Nalluri

Data Analysis: Improving Security for Mass Transit in New Jersey

Year: Summer 2022

Home Institution: The College of New Jersey

Mentor: Dr. Christie Nelson

Abstract: The current state of surveillance and security measures in public transit, such as high-traffic subway and train stations, is very vulnerable to mass casualty and terrorist attacks. In recent years, since the start of the pandemic, violent crime rates (e.g., shootings) have grown, impacting public transportation use. Exploring new and emerging screening technologies and publicly available datasets on NYC and NJ crimes, transportation, and census data can be utilized to create a predictive model that assesses which stations are at greater risk. This would involve using a risk analysis model to make these predictions. Overall, the end goal of this project is to use the predictions and understanding of different types of active and passive security measures to improve stations without adversely affecting passenger throughput.

http://reu.dimacs.rutgers.edu/~nn410/

Fiona Shafer

Health Disparities & Covid-19

Year: 2021

Home Institution: Rutgers University-New Brunswick

Major: Public Health

Mentor: Dr. Christie Nelson

Abstract: This project will focus on disparities related to COVID in three main areas: long-term care, education settings, and mobility trends. Health disparities are preventable burdens of disease that exist in disadvantaged populations. Through this project, I plan to identify existing disparities to promote health equity domestically and internationally. After compiling datasets and sources, I will visualize the results to answer research questions in all three areas.

http://reu.dimacs.rutgers.edu/~fcs38/

Therese Asevedo

Topic Modeling and Sentiment Analysis of COVID-19 Press Conference Transcripts

Year: 2020

Home Institution: Sonoma State University

Major: Statistics

Mentor: Dr. Christie Nelson

Abstract:  This project is focused on the current pandemic of COVID-19. In particular, our goals are to apply topic modeling and assess sentiment towards COVID-19 via press conferences by state to predict outbreaks or diminishing cases of COVID-19.

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Ryan Aponte

Homeland Security and Policing Data Analysis

Year: 2020

Home Institution: University of Florida

Mentor: Dr. Christie Nelson

Abstract: Previous work done by Teresa Ngo and Hannah Fell was built upon to help construct career pathways and determine the criminal implications of digital forensics. The Federal Law Enforcement Training Center needed additional knowledge to understand the training, certification, and skills necessary at different levels of a career. Certification providers CompTIA and Global Information Assurance Certification were analyzed to find certifications relevant to digital forensics. Additional analysis of Thomson Reuters Westlaw criminal case documents was also completed to determine the relevance of digital forensics.

http://reu.dimacs.rutgers.edu/~ra868/

Rachael Tovar

COVID-19 Data Analysis and Risk Management Assessment

Year: 2020

Home Institution: Wheaton College, MA

Mentor: Dr. Christie Nelson

Abstract: In the United States alone, over 3.8 million people have contracted the Covid-19 virus. Due to the increased demand for testing, there have been shortages and issues revolving around testing. Despite rates continuing to rise and testing becoming more scarce, the United States government pushes for the economy to reopen. This may lead to multiple consequences such as case numbers surging to the negative social impact, making research on methods to help protect individuals from infection a necessity. Continuing to see the changes and trends of this virus is crucial to understanding causation of case spikes, finding solutions to help flatten the curve, and determining effective ways to distribute resources. To understand the full scope of the Pandemic’s impact on the United States, we considered a wide range of information regarding the virus while focusing on the changing mobility patterns and state government mandates to understand the risk management of state governments as well as the social impact of Covid-19.

http://reu.dimacs.rutgers.edu/~rt625/

Hannah Fell

Digital Forensics Certification Training for the Department of Homeland Security and State and Local Law Enformcement

Year: 2019

Home Institution: Westminister College

Major: Math

Mentor: Dr. Christie Nelson

Abstract: The advancements and widespread use of technology across the nation have made digital forensics an important component of the criminal justice system. Digital forensics is a branch of forensic science involving the recovery and investigation of data from digital devices (“Law Technology,” 2018). This type of evidence can be very useful for providing vital information during investigations. However, it can be challenging for professionals to manipulate, store, access, and use in courtroom settings. To help avoid these challenges, digital forensics professionals should be properly trained and receive relevant certifications. The purpose of this project is to analyze digital forensics training and certification requirements for the Department of Homeland Security investigative units and State and Local Law Enforcement, working with the Federal Law Enforcement Training Center (FLETC) to identify opportunities and gaps in digital forensics training and recommend digital forensics training and certification pathways to standardize training and certification across all of Homeland Security. This project is a part of the funded Department of Homeland Security project, “Best Practices for Sharing Digital Evidence” and is through the Criminal Investigations Network Analysis (CINA) Center of Excellence at George Mason University.

http://reu.dimacs.rutgers.edu/~hf193/

Yetunde Oloko

Drone and Metal Detection at Stadiums

Year: 2019

Home Institution: New Jersey City University

Mentor: Dr. Christie Nelson

Abstract:  Digital forensics is the collection, analysis, and reporting of various types of electronic data. It can be preserved and potentially be used in various types of investigations and/or court proceedings. There are numerous type of forensic tools used to capture data that can be used as evidence in a court of law. However, without the proper knowledge and certification; it is difficult for local law enforcement to use digital evidence effectively for an investigation. Furthermore, Technology is constantly changing so it is significant to maintain constant training for patrol officers, prosecutors, and judges. The point of this research is to analyze, and improve training and certification requirements for digital forensics. This help Homeland Security units as well as state and local law enforcement to effectively collect digital evidence. We will be partnering up with the Federal Law Enforcement training center to identify gaps in DHS digital forensics training with the help of the National Institution of Standard and Technology (NIST) recommendation. Lastly, this project is under the Criminal Investigation and Network Analysis (CINA) Center at George Mason University.

http://reu.dimacs.rutgers.edu/~yo79/