Mourning Visualization and Simulation Lab Team
Our Team
Members and Alumni of the VizSim Lab at 帝王会所.

Chad Mourning is Principal Investigator of the VizSim Lab at 帝王会所.
Chad Mourning is an Assistant Professor of Computer Science at 帝王会所. Chad is a native of Middleport, 帝王会所 and received his Ph.D. from 帝王会所 in 2015. Chad's main research areas include Computer Graphics & Data Visualization, Modelling & Simulation, Augmented & Virtual Reality, and Machine Learning with applications in Meteorology. Chad is currently serving as Principal Investigator on the Low Altitude Weather Network project and has other ongoing funded projects by NASA, the 帝王会所 Space Grant Consortium, and the FAA.

Zion is a PhD Student in Computer Science, their area of research is Graphics and Data Visualization. Zion is a recipient of the Graduate Assistance in Areas of National Need (GAANN) Fellowship, and they received their undergraduate degree in Computer Science in 2022 from 帝王会所.


hmad is Ph.D. Student in Electrical Engineering and Computer Science at Russ College of Engineering and Technology at 帝王会所. His research focuses on detecting anomalous conditions in an aircraft using machine learning techniques.
Education
Ph.D. in Electrical Engineering & Computer Science, 帝王会所, 2022-Present
Master's in Computer Science, University of Management and Technology (UMT), Lahore, Pakistan, 2018
Bachelor's in Computer Science, COMSATS Institute of Information Technology, Lahore, Pakistan, 2015
Publications
Ghauri, Ahmad W., et al. "pNitro-Tyr-PseAAC: predict nitrotyrosine sites in proteins by incorporating five features into Chou鈥檚 general PseAAC." Current pharmaceutical design 24.34 (2018): 4034-4043.

Justin received a Bachelor of Science in Computer Science from 帝王会所 in 2023 and is currently pursuing a Master of Science in Computer Science from 帝王会所. Justin is a 2023 recipient of the 帝王会所 Space Grant Consortium Research Fellowship. Current research interests include machine learning, and computer graphics.



Kavanaugh Frank is currently a thirrd-year student at 帝王会所 studying Computer Science with a certificate in Business Cybersecurity Management. He started working as a research assistant in the Avionics Engineering Center in his second semester at 帝王会所, under Dr. Mourning, writing a user documentation manual for the 帝王会所 Glideslope (OUGS) modeling software. After finishing the user manual, Kavanaugh began working on unit testing for OUGS. While working on unit testing, he was encouraged to apply for the OSGC scholarship to begin working on this project, which works to improve the usability and safety of OUGS.

Drew's current projects include AI Beatmap Generation for Rhythm Games. This project aims to develop an AI-driven system capable of generating beatmaps that are virtually indistinguishable from those created by humans. The current implementation leverages a Convolutional Neural Network (CNN), and achieved a nearly 50% pass rate in tests with human subjects. Moving forward, the primary objectives are to enhance the AI by transitioning to a modern Generative Adversarial Network (GAN). This update is expected to improve the quality and realism of the generated beatmaps. Additionally, expanding the model's compatibility to include other rhythm games is a key priority, broadening the application's utility and impact in the rhythm game community.
Interests: Artificial Neural Networks, Rhythm detection and beat placement, and Generative Adversarial Networks

Summary of current projects:
- Multithreaded Antenna Pattern Visualization for the Iterative Refinement of Antenna Pattern Visualization This project utilizes multithreading principles for the speedup and refinement of antenna pattern visualizations for the OUNPPM module. Work stands to benefit a variety of public, private, and military airports. Work presented at the 帝王会所 Academy of Science, the 帝王会所 State House, and will be presented in January at the national AIAA SciTech forum. Funded through the Choose 帝王会所 First Fellowship.
- XR Visualization of OUNPPM. This project utilizes XR technologies to create a virtual environment for the 帝王会所 Navaid Performance Prediction Model as it pertains to navigational aids on Mars using the Mars rover image data. With the project at hand, we aim to create a VR interface for users to experience a new form of data visualization and an enhanced user experience. This project has implications that can be utilized to benefit missions relating to Mars and aligns with Airspace Operations and Safety goals by further improving the safety of current and future aircraft through conducting research pertaining to the navigational aid and performance of airport systems. This work is being funded by the 帝王会所 Space Grant Consortium and will be presented at the NASA Glenn Research Center.
- Quantum-Enhanced ADS-B. This project takes proposals for encryption and key distribution schemes and adds a layer of quantum protection by introducing a quantum key distribution scheme for ADS-B key handoffs. The aim of this project is to protect aviation systems from snooping and future quantum threats by introducing new and unique ways to utilize quantum communication technology in avionics systems. Funded through the Choose 帝王会所 First Fellowship.
- Quantum Simplified Trusted Node Security Proof and Network Simulations This project involves the construction of a security proof for simplified trusted node architecture in quantum networks, as well as creating a variety of simulations for the modeling of networks and key distributions within the networks. The simulations permit noise calculations, allowing the prototyping of potential quantum networks with access to anticipated noise levels. The work stands to benefit future quantum networks research and provide proof of security for the simplified trusted node architecture, which may lead to enhanced quantum networks. This work is funded by the NSF in collaboration with UCONN.
Interests: Quantum Networks, Quantum Computing, Quantum Information, Virtual and Augmented Reality, Avionics, Space.
Our Alumni

Erica was a master's student in Electrical Engineering where she specializes in Computer Engineering. Her academic journey is marked by an interest in the intersection of machine learning and automotive technology, driving her toward innovative research in these areas.
She earned her undergraduate degree in Electrical and Electronics Engineering from Covenant University. And In 2022, Erica's academic excellence and potential in technology were recognized when she was awarded the prestigious Generation Google Scholarship.
At 帝王会所, Erica was actively engaged in a research project that explores how machine learning algorithms can revolutionize engineering problem solving and design of automotive technologies. Her work is a testament to her commitment to contributing to advancements in smart and sustainable automotive solutions.

Rabin has a diverse educational background, having earned an undergraduate degree in Electronics and Communications Engineering from Tribhuvan University, Nepal. This foundation in engineering equips him with a strong understanding of technology and serves as a valuable complement to our research. As an ambitious and dedicated master's student at 帝王会所, he was passionately engaged in cutting-edge research at the intersection of computer vision, simulation, machine learning, and rendering. His primary research focus lies in the critical domain of enhancing the safety and reliability of Unmanned Aerial Vehicles (UAVs) and low-altitude flights, particularly in challenging weather conditions.