Department of Computer Science
Funded Projects
High-Performance Intelligent Data Science Institute (HIDI)
Principal Investigator(s): Hoda El-Sayed
Grantor: National Science Foundation
Award Period: May 1, 2021 through April 30, 2024
Award Amount: $1,000,000
Research Area: Data Science and High-Performance Computing
Laboratory: CHIP – Center for High Performance Information Processing
The $1M NSF HBCU-RISE grant: High-Performance Intelligent Data Science Institute (HIDI), proposes a project designed to increase the number of minority candidates who pursue and complete doctoral programs of study in Computer Science. HIDI will increase institutional infrastructure to support a new specialization in High-Performance Data Science within the Computer Science doctoral program to diversify learning options for interested students and increase the number of minority doctoral candidates who enter into and succeed in diverse Computer Science fields.
The proposed Specialization in High-Performance Data Science will empower Bowie State University to more fully utilize the capacity of one of its outstanding university assets – Bowie State University is host to the only supercomputer (Cray X40) within the greater HBCU network of postsecondary institutions of study. Through implementation of HIDI, critical research to advance the field of Data Science and add to the body of scholarly work in advanced Data Science and its implications for future understanding, innovation and emerging trends will be conducted.
NSF Grant: Harnessing the Data Revolution (HDR) Data Science Corps (DSC): Collaborative Research: Creating and Integrating Data Science Corps to Improve the Quality of Life in Urban Areas, Award #1923986
Principal Investigator(s): Sharad Sharma
Grantor: National Science Foundation
Award Period: 1 October 2019 through 30 Sep 2022
Award amount: $1,198,769.00 (BSU: $180,000.00)
Research Area: Data Science, Data Visualization, Artificial Intelligence, Virtual Reality
Laboratory: Virtual Reality Laboratory
This project is a collaborative effort with the University of Maryland Baltimore County as the coordinating as well as an implementing organization, and the University of Baltimore, Towson University, and Bowie State University as implementing organizations. This project focuses on the city of Baltimore as an example for other cities in the US and across the globe. The project team will collaborate with a number of communities in the city of Baltimore to integrate real-world data science projects into classroom instruction in data science. The specific objectives of this project are as follows: (i) Develop the technical, analytical, modeling, and critical thinking skills that are key to success as a data science professional; (ii) Connect a cohort of students to communities, organizations, and projects that can benefit from the power of data science; (iii) Nurture and support innovative thinking in solving some of the key challenges facing the real world; (iv) Promote a better understanding of the power and pitfalls of data-driven discoveries to improve the quality of life in urban communities; (v) Increase the data science workforce capacity to support this critical area that is of growing importance in society; and finally, (vi) Evaluate the effect of the proposed data science corps on student learning. The project includes development of instructional phase modules such as Virtual Reality in Data Science as well as Real-world implementation projects such as Augmented Reality with HoloLens for building evacuation led by Sharma.
NSF Grant: RAPID: VAPOC: Visualization, Analysis and Prediction of COVID-19, Award #2032344
Principal Investigator(s): Sharad Sharma
Grantor: National Science Foundation
Award Period: 1 June 2020 through 31 May 2021
Award amount: $100,000.00 (BSU: $40,000.00)
Research Area: Data Science, Data Visualization, Artificial Intelligence, Virtual Reality
Laboratory: Virtual Reality Laboratory
The goal of VAPOC (Visualization, Analysis and Prediction of COVID-19) project is to find out reasons as to why the black community is disproportionally impacted during the coronavirus pandemic. We believe that a combination of factors is responsible for the African Americans’ susceptibility to the COVID-19. This study is based on pattern recognition, knowledge discovery and scientific principles. We hypothesize that pre-existing conditions, type of employment, and access to healthcare among other factors have significant influence in the higher death rate of African Americans during the COVID-19 pandemic. The visualization, analysis, and prediction of COVID-19 in the African American community is necessary for; 1) the community to be well informed on the precautionary and cautionary measures in ameliorating the affliction of coronavirus and measures to reduce its spread, 2) a proper understanding of what factors medical professionals should prioritize when performing health assessment and diagnoses test for a COVID-19 patient, and 3) VAPOC will also help decision makers in improving mitigation strategies. This project is a collaborative effort between the University of the District of Columbia and Bowie State University. To accomplish the above goal, the following 3 objectives are proposed; 1) Design, develop and evaluate a COVID-19 model to determine vulnerability to coronavirus, 2) Development of a visualization and interaction tool to analyze COVID-19 patients’ dataset in an immersive and non-immersive environment, and evaluate how graphical objects (such as data-shapes) developed in accordance with the user’s requirements can enhance situational awareness, and 3) Design, develop and evaluate a deep learning model to predict extent of COVID-19 damage to discharged patients. VAPOC combines neural networks predictions with human centric situational awareness and data analytics to provide accurate, timely and scientific strategy in combatting and mitigating the spread of the coronavirus plague in the black community.
Planetary Data System - Small Bodies Node
Principal Investigator(s): Bo Yang
Grantor: NASA
Award Period: 12/1/2015 - 11/30/2020
Award Amount: $982,415
Laboratory: Big Data Research Lab
Dr. Bo Yang is the director of Big Data Research Lab, and working with his students on a funded project of NASA’s planetary database system (PDS) that aims to improve the discoverability of new scientific findings, and to convert the content-rich PDS archive data into information useful to expert and non-expert users. Dr. Yang along with Computer Science students have done research and written a paper called ICSSA: Association-Aware Data Retrieval in Planetary Data Systems.
Principal Investigator(s): Jie Yan
Grantor: National Science Foundation
Award Period: 8/1/2017 to 8/1/2020
Award Amount: $899,000
Research Area: Cybersecurity and network security visualization
Laboratory: Cyber Security Lab
The main objectives of this project are to develop a flexible and scalable computer and network security visualization application that captures and displays, in a usable and coherent fashion, information that is pertinent to spectator understanding of cybersecurity attacks and defense as played out between blue and red teams in a cybersecurity competition. And, to explore methods of visualizing team participant activities and to develop a system to monitor and broadcast live team participant activities in real time that will be displayed to a central monitor screen in a coherent fashion.
Principal Investigator(s): Jie Yan
Grantor: National Science Foundation
Award Period: 8/1/2017 to 8/1/2020
Award Amount: $400,000
Research Area: Cybersecurity and Education
Laboratory: Cyber Security Lab
This grant will fund the expansion of cyber security education at BSU using new and innovative methods. The purpose of this project is to develop a cloud-based cryptographic simulator for enhancing undergraduates learning experience in cyber security education. Dr. Yan, students, and other professionals will be building a cloud-based cryptographic simulator over the next three years that will simulate real-world cyber threats and other challenges as a training tool for students and educators. This tool will enable students to explore the adversary’s perspective of cryptography through real-life cryptographic attacks for problem-based group learning.
Principal Investigator(s): Sharad Sharma
Grantor: U.S. Army Reserach Laboratory (ARL)
Award Period: 09/05/2018 to 08/28/2020
Award amount: $85,000.00
Research Area: Artificial Intelligence, Virtual Reality, and Behavioral Modeling.
Laboratory: Virtual Reality Laboratory
The goal of this project is to develop algorithms for avatars (player controlled and non-player controlled) interaction in an immersive Collaborative Virtual Environment (CVE) using oculus rift where users from multiple locations come together and interact in unique ways. The user can enter the CVE as a fireman or a soldier or a policeman or a medic. The VR Lab at BSU proposes to accomplish the following objectives during one year of the project: a) Develop an immersive Collaborative Virtual Environment (CVE) using oculus rift touch for course of action, visualization, and situational understanding for a mega city. b) Develop graphical user interface (GUI) for communicating between PCs (Player characters) and NPCs (Non-Player Characters or AI Characters ) with a unique interface in the immersive environment for user interaction. c) Develop graphical user interface (GUI) for communicating between PCs and NPCs with a unique interface in the immersive environment for user interaction. d) Implementing algorithms for human behavior for Non-Player Characters (NPCs) and real world behaviors in mega city.
Principal Investigator: Sharad Sharma
Grantor: U.S. Army Reserach Laboratory (ARL)
Award Period: 08-04-2017 to 09/30/2019
Award amount: $85,000.00
Research Area: Virtual Reality and Artificial Intelligence
Laboratory: Virtual Reality Laboratory
This project uses game creation as a metaphor for creating an experimental setup to study human behavior in a megacity for emergency response, decision-making strategies, and what-if scenarios. The proposed collaborative VR environment includes both immersive and non-immersive environments. The participant can enter the CVE setup on the cloud and participate in the emergency evacuation drill, which leads to considerable cost advantages over large-scale, real-life exercises. We present two ways for controlling crowd behavior. The first defines rules for agents, and the second provides controls to the users as avatars to navigate in the VR environment as autonomous agents. The novelty of this work lies in modeling behaviors (hostile, non-hostile, selfish, leader-following) for computer-controlled agents so that they can interact with user-controlled agents in a CVE.