This project is a collaborative effort with UMBC as the coordinating as well as implementing organization and the University of Baltimore (UB), Towson University, and Bowie State University as implementing organizations. BNIA-JFI will be a part of a team of experts with multidisciplinary academic expertise and complementary training experiences in parallel computing, data science, big data, cybersecurity, virtual reality, geospatial data analysis, and urban and regional planning. BNIA-JFI will support integration of real-world data science projects by 1) recruiting and introducing data science tools and techniques to undergraduate students at UB; 2) accelerating the adoption of advanced data science techniques, such as geospatial analysis for projects in urban communities through community-based real-world projects.
This project has been supported by NSF grant IIS-1923982.
Degree: Information Technology and Systems Management
Graduation Date: Spring 2023
“I am interested in being a part of this cohort to gain fundamental data science skills and work on real-life projects.”
Degree: Environmental Sustainability
Graduation Date: 2023
“Data can be compiled, aggregated, analyzed, etc. to help solve problems. I would love to do that for environmental problems, or other related issues around Baltimore City”
Degree: Cyber Forensics
Graduation Date: Winter 2022
“I would love to impact my community in a positive way. I’m interested in helping the City of Baltimore by collecting data that could make the change needed for the future. I would also like to work on real projects to fix these issues.”
Degree: Information Systems and Technology Management
Graduation Date: 2024
“I believe that the data science techniques that I will learn during my time as a Data Science Corps intern will be invaluable in my own journey to better my city. Baltimore is such an underrated place despite its wealth of knowledge, history, culture, and the people’s aptitude to always strive for better. I want to use my skills to aid in that fight for a Better Baltimore.”
NSF Student Data Science Corps Description
How to Apply: Will open in May 2023
If you are interested in getting conceptual and hands-on experience in data science and get paid for it, consider applying for the following opportunity. The Baltimore Neighborhood Indicators Alliance (BNIA) at the University of Baltimore is seeking Undergraduate students to be a part of a Baltimore regional Data Science Corps. Students will be trained on data processing best practices for analysis, geographic information systems, effective and ethical data visualization techniques for applications that help communities in Baltimore understand the current impacts of the COVID19 pandemic. The students will work with BNIA staff and faculty mentors and will be involved in real-world projects.
This position will run for three months in the summer of 2022. Students will be introduced to several data science learning opportunities with BNIA staff and other online training in order to work on the projects outlined above. Learning modules and team meetings will be approximately 3-5 hours per week. Time spent on projects will be approximately 8 hours per week.
Our students are going through rigorous training on Data Science techniques that can be used for social good. We are looking for organizations that have a data science question or need that could serve as both a learning opportunity for the students as well as a service to your organization/agency.
If you are interested in hosting a student for a semester, please fill out this Host Intake Form
1) Analyze databases regarding internet speeds by neighborhood
2) Create a web scraper to collect routinely updated data on websites that don’t have an open data API
3) Review real time service of new bus schedules and see if different neighborhoods are
experiencing service disruptions
4) Analyze city budgets for youth related spending and programs
Jaia Russell – 211 Data for Maryland
Kabah Selli – Analyzing Open Checkbook
Ibraheem Sule – Social Determinants of Mental Health in Baltimore City
Bozkurt Karaoglan – An Ongoing Project to Predict Crime Rate in Baltimore Using Neural Network Algorithms
Jonathan Cleary – Analysis on Correlation Between Homicides/Shootings and Demolitions in Baltimore City, 2019 & 2020
Charles Lac – Visualizing Criminal Intelligence Debriefings in Baltimore
Bozkurt Karaoglan – Quantifying Criminal Intelligence Gathering for Baltimore Police Department’s Operational Dashboard
John Cleary – Creating a Dashboard for the City of Baltimore
Amivi Atsu – Exploration of Data Works MD’s Membership
Loveth Akinyemi – Analysis of Federal and State Coronavirus Funds
Kaitlyn Baker – Improving the Accuracy of a Web Scraper
Ruth Robinson – Recycling Cart Rollout ’21
Lalla N’diaye – AI Solar Output In The Baltimore Metropolitan Area
Hannah Boyd – Covid-19 Vaccine Distribution in Baltimore City
Brian Kelly – Developing an Index for Communities Underserved by Transit
Michael Vandi – Understanding the Importance of Data Documentation
Ruth Robinson – Social Media Alert System for COVID-19 Illicit Behavior
Brian Kelly – An Analysis of Baltimore City E-Scooter Distribution
Michael Vandi and Naomi Weiss – GIS with the BNIA Data Science Corp
Ruth Robinson and Priya Kanneboyina – Is Baltimore City Getting Fast Enough Internet Speeds?
Data Science Corps Ignite Session Recording – Session Resource Guide
Charles Lac, Degree: Health Systems Management, Graduation Date: Spring 2023
Zachary Clayton, Degree: Information Systems and Technology Management, Graduation Date: Spring 2022
Kaitlyn Baker, Graduation Date: Fall 2021
Loveth Akinyemi, Degree: Applied Information Technology/Cybersecurity, Graduation Date: Winter 2021
Bhawana Pradhan, Degree: Information System and Technology Management, Graduation Date: Fall 2021
Amivi Atsu, Degree: B.S. in Accounting, Graduation Date: Winter 2022
Ruth Robinson, Degree: Business Administration – Real Estate and Economic Development, Graduation Date: Spring 2022
Brian Morrison, Degree: M.S., Applied Industrial & Organizational Psychology, Graduation Date: Spring 2022
Lalla N’diaye, Degree: Business Administration-Accounting, Graduation Date: Spring 2021
Michael Vandi, Degree: Applied Information Technology, Graduation Date: Fall 2020
Brian Kelly, Degree: Upper-Division Certificate in Computer Programming, Graduation Date: Fall 2020
Surafel Beyene, Degree: Applied Information Technology – Application Development & Programming, Graduation Date: Fall 2020
Naomi Weiss, Graduation Date: Fall 2020
Priya Kanneboyina, Degree: Applied Mathematics, Graduation Date: Spring 2023
This project has been supported by NSF grant IIS-1923982