MS in Data And Information Management
- Biology Department
- Pre-Health Advisory Committee
- GIS Center
- Medical Laboratory Science
- Museum of the Earth Sciences
- Mathematics and Statistics
- REALISE
- Chemistry Department
- Radford University Planetarium
- Department of Physics
- Anthropological Sciences
- Geology
- Selu Observatory
- Center for Information Security
- Forensic Science Institute
- Biomedical Science
- Geospatial Science
- School of Computing and Information Sciences
- MS in Data And Information Management
Capstone Projects
In the last academic year, each student is paired with industry mentors to solve real world problems with the tools they have learned.
- Below you will find student project abstracts, information about their mentors, and a short five minute project presentation from previous years.
Active Projects
Cyber RADaR
Presented by: Caitlyn Robinson
Online social networks are emerging as a primary source for sharing and consuming the latest information on cybersecurity threats. Most organizations lack the resources to effectively monitor social media. Consequently, organizations are vulnerable months, even years, after a threat is discovered. The Cyber RADaR service uses artifical intelligence (AI) and machine learning (ML) to crowdsource information and provide clients with a customized dashboard alerting them to relevant threats and provide references to mitigation methods.
- Mentors:
- Bobby Keener, Chief Executive Officer at Civilian Cyber
- Bill Cramer, Business Analyst/Process Engineer at Virginia Commonwealth University
Modeling Infectious Disease Transmission in Southwest Virginia Using Electronic Medical Records
Presented by: Nicole Linkous
Infectious disease transmission within communities presents complex challenges for public health. Recognizing the potential of Electronic Medical Records (EMRs) to reveal these patterns, this study focuses on assessing the impact of demographic, disease, and community features on transmission dynamics. Using EMR data from the southwest Virginia region, two distinct feature engineering methods – feature selection and dimensionality reduction – will be evaluated for their efficacy in preparing highly dimensional patient data for predictive modeling. Once refined through these methods, the data undergoes agglomerative clustering to identify intrinsic relationships, and multivariate logistic regression is employed to predict influenza transmission within the sample population. The results of this research provide insights for future epidemiological predictive modeling and inform public health strategies.
- Mentor: Mattie Tenzer, Technology Services Group Director for Health Analytics Research at Carilion Clinic
2023 Project Abstracts
Predicting the Community Spread of Infectious Disease with EMR Data
Presented by: Sai Chandrika Peeta
Infectious diseases significantly impact patient health and healthcare expenses. To understand and predict the spread of infectious diseases and resulting outcomes, we seek to identify the factors that most influence transmission. These factors include developing a process that automate the processes of cleaning datasets that links individuals together based on co-location, their visits to the hospital, diagnosis, and cohabitation. Additionally, we will identify data features within electronic medical records (EMR) that present statistical evidence of explaining and predicting contagion among patients. Our data models are then tested and validated on specific infectious disease data points, including several variants of influence, Norovirus, SARS and its related coronavirus variants, and other comorbid infectious diseases as features are revealed. Our results have two-fold advantage: informing organizational policy to prevent internal contagion and workforce downtime and allocating resources more effectively during outbreaks.
- Mentor: Mattie Tenzer, Technology Services Group Director for Health Analytics Research at Carilion Clinic
Simplify Amazon Analytics to Manage Ad Campaigns More Effectively
Presented by: Noah Bieker
Amazon Ads provides companies with the tools to run and manage advertisement campaigns on Amazon. However, the amount of data is overwhelming and the analytics are not insightful enough to measure performance. This project will develop a dashboard of visual indicators to quickly and accurately evaluate campaigns and take action.
- Mentor: Chris Geiger, Solutions Architect at Amazon Web Services (AWS)
2022 Project Abstracts
Reduce Waste and Optimize Utilization: Managing Blood Effectively
Presented by: Tracey Dudding
In 2013, the American Association of Blood Banks, AABB, estimated a total of 932,000 whole blood units wasted due to expiration [1]. To reduce blood waste, inventory needs to be managed effectively and attributes associated with utilization need to be identified. Blood inventory data should be offloaded from operational systems to a data warehouse to produce automated, or without human interaction, reports and dashboards in order to efficiently communicate inventory. Wasted blood products can also be improved by using clustering and multiple correspondence analysis, or MCA, to identify variables associated with each other in regard to blood use. These variables can be used to start studying blood use and may be identified in waste. Blood waste can be reduced by conveying the inventory effectively and by first identifying variables associated with blood usage.
- Mentor: Mattie Tenzer, Technology Services Group Director for Health Analytics Research at Carilion Clinic
TRUST: A Tool for Reporting and Understanding Site Tracking
Presented by: Nolan Ierardi
Online privacy is an important concern for many internet users. By showing users how their data is being collected and presenting this information in a useful, actionable manner, they can make informed decisions on whether to continue using a website or seek out a more privacy-focused competitor. A fully integrated cloud solution will collect, ingest, store, and present data. Easily-interpreted scores and a ranking system will provide context and drive awareness.
- Mentor: Linwood Hudson, Senior Software Architect at Peraton
Automated Misinformation Pipeline and Extended Repository (AMPER)
Presented by: Amanda Tolman
Many social media users are unaware that most of the information within social media platforms is false. Consequently, this hinders users of social media from making informed decisions for themselves and others. The unintentional spread of false information, also known as misinformation, and the deliberate spread of false information, disinformation, poses an alarming threat to trust, civic discourse, reputations, and democracies. Researchers are using various techniques in artificial intelligence and machine learning to combat these destructive outcomes. However, many researchers are trying to solve this problem with small amounts of data. Large datasets are scarce because data collection is time consuming. AMPER is an automated pipeline to extract, collect, integrate, and store news articles from multiple sources. AMPER runs on Amazon Web Services (AWS) and provides a dashboard summarizing the contents of the repository to increase usability for researchers and consumers.
- Mentor: Mike Spence, Sr. Solutions Architect at Amazon Web Services (AWS)
2021 Project Abstracts
How Price Influences Customer Reviews
Presented by: Michael Hammond
The PC gaming platform Steam built a successful business by frequently discounting and slashing prices. General consensus in the gaming community associates price cuts with positive user reviews. This presentation not only shows a relationship between price changes and review scores, the research also shows a relationship with community interaction.
- Mentor: Linwood Hudson, Senior Software Architect at Peraton
- Specialties: Java, Javascript, jQuery, SQL, ASP .NET, C#, SQL Server, Crystal Reports, Oracle ADF, C++, MFC, Application design and development, software system architecture and integration, database design and management, knowledge engineering, Bayesian networks
Analyzing Virginia’s Public COVID Data
Presented by: Hari Talari
Since the start of the pandemic, the Virginia Department of Health (VDH) has been a primary source of the Virginia’s COVID-19 data. The VDH collects data on new cases, hospitalizations, and deaths. The data includes information on age group, county, health district, and other properties. The VDH data impacts decisions made by the state, local communities, and individuals regarding lockdowns, hospital preparation, funding, and whether it is safe to get groceries. This presentation describes the publicly available VDH data and makes recommendations to improve the data to enable critical analysis.
- Mentor: Robbie Hiltonsmith, Analytics and Elasticity Engineer at 1901 Group
- I conduct research on and advocate for policy changes involving many of the most critical issues facing our country, including retirement security, higher education, and the role of the federal government.
Using Big Data to Enhance Small Businesses
Presented by: Zachary Bryan
Business Intelligence helps people and organizations make better decisions. Until recently, only large companies had the resources to take advantage of business intelligence. Today, even the smallest organizations are making data-driven decisions. This presentation describes an automated data pipeline to help a small veterinary hospital improve customer service and manage their practice more effectively.
- Mentor: Chuck Hicks, COO and CFO at NCI
- Experienced Chief Financial Officer with a demonstrated history of working in the commercial real estate industry. Strong finance professional skilled in Government Procurement, Analytical Skills, Government, Generally Accepted Accounting Principles (GAAP), and Proposal Writing.
Time is the Secret to Building Wealth
Presented by: Noah Bledsoe
Retirement is often the last thing on a young individual’s mind, but investing early is the key to building wealth and securing a comfortable lifestyle. This presentation explains how to make money work for you by analyzing stocks with data visualization, optimizing your portfolio using the capital asset price model and sharpe ratio, and predicting stock prices with machine learning.
- Mentor: Gehard Pilcher, President and CEO at Elder Research
- Gerhard has extensive industry experience in government oversight, financial, construction and telecommunication industries both as a business owner and executive. He is a recognized expert in three dimensional roadway modeling and automated machine guidance using Global Positioning Satellite systems and has presented to various agencies including the Transportation Research Board. In his role as Chief Technology Officer and VP of Engineering for Pulse Communications, Gerhard directed the design of early digital subscriber line systems (internet over the telephone line) and was a member of the international forum defining the standards for DSL implementation. Prior to Pulse Communications he was Director of Operations for Bell Northern Research leading the design and delivery of hardware and software for large scale telephony switching and fiber optic systems.
Summarizer Improves Reading Speed and Comprehension
Presented by: Pralad Neupane
Twitter is popular because messages are short and easy to read. What if book pages and news articles could be more like tweets? This presentation introduces Summarizer, a system that extracts and summarizes key points from a text while analyzing sentiment to produce a short gist that improves reading speed and comprehension.
- Mentor: Jagat Dhami, Hadoop System Engineer at Amazon Web Services (AWS)
- Graduated in first DAIM cohort
- Experienced Data Specialist with a demonstrated history of working in the information technology and services industry. Skilled in Oracle Database, Risk Management, Amazon Web Services (AWS), R, and ETL Tools. Strong information technology professional with a Master of Science (MS) focused in Big Data Management from Radford University.
2019 Project Abstracts
Data Governance - Protecting Data While Adding Value
Presented by: Jesse Harden
Radford University acquired a senstive data set with the potential to enhance and improve advising, teaching, and student success. This project unlocked the value of the data without compromising confidentiality.
Data Analysis - Data Science Transforms Tweets to Trends
Presented by: Jasman Shakya
Companies and organizations want authentic feedback from customers about their brand and their products. This project analyzed tweets to gauge customer sentiment about the Samsung S8 iris scanner.
Data Analysis - Data Science Helps You Grab a Cab in a New York Minute
Presented by: Sajan Rai
Ever tried to catch a cab in the busiest city in the world? This project analyzed New York taxi data discovering valuable insights to help people maximize transportation options.
Data Visualization - Enhanced Data Access Dramatically Improves Response Time
Presented by: James Caldwell
Radford University manages over 150 systems running on hundreds of servers. Each server must be checked daily for attacks, failures, and other critical problems. The current process drains productivity and leaves many systems vulnerable. Splunk enabled the University to create a common infrastructure facilitating hourly system checks to significantly improve response time.