RESEARCH AND SCHOLARSHIP
At the Center of Excellence in Enterprise Technology (CEET), we believe discovery starts when we explore immersive technologies and leverage that knowledge to solve challenges here at Villanova, in our communities and on an enterprise-level around the world.
RESEARCH TECHNOLOGY
Villanova鈥檚 CAVE Automatic Virtual Environment (CAVE) is an immersive, interactive experience with 3D virtual reality worlds, 3D big-data displays and 3D models of real-world locations and objects, bringing course material to life in new and exciting ways. Funded by a $1.67 million National Science Foundation grant and managed by CEET, the CAVE opened in October 2014 and is located Falvey Memorial Hall. In addition to serving as a teaching and learning space, it is used to support faculty research projects across disciplines, as well as to collaborate with academic and industry researchers from around the world.
Funded by a $300,000 National Science Foundation (NSF) grant, Center Director Frank Klassner, PhD, is leading a group of interdisciplinary researchers from across the College and from the College of Engineering to develop high-tech sandboxes providing hands-on learning for students.
The technology is based on projecting a colorful augmented reality display onto sand in a real sandbox, and it was created by a researcher at University of California, Davis in 2012. The box was originally used in public exhibits for science education but has since been adopted by universities and research centers around the world. It allows users to evaluate hydrological processes through the shifting of the sand. Dr. Klassner says the team hopes to install four or five boxes across labs on campus and hopes the upgraded software could eventually be licensed and used by other institutions.
CURRENT RESEARCH PROJECTS
Pollinators play a crucial role in global biodiversity by providing vital ecosystem services to agricultural productivity and wild flora preservation. This US Department of Agriculture sponsored project led by Dr. Venkat Margapuri investigates unmanned aerial vehicles (UAV) and AI tools to understand the relationship between pollinator abundance and floral presence. The research outcomes aid in determining the abundance and diversity of both pollinator and flower species across large swathes of agricultural fields, prairies, and landmasses by providing accurate AI image detectors and classifiers, trained from expertly collected and curated datasets of both pollinator and flower species. The project is producing a free, public, web application with documented user guides for experts and non-experts alike that leverages the AI detection and classification models to detect, classify, and quantize both Bombus and flower species from uploaded images and targe
This project, supported by the Alfred P. Sloan Foundation, and a collaboration with UC Davis and the National Institute for Standards and Technology (NIST), will enhance the VRUI platform, a VR platform that addresses scientific need for immersive, collaborative data exploration and brings value to researchers of social interaction/collaboration in those environments, and transition VRUI to a healthy, community driven, OSS platform. This project, led at 91探花by Drs. Klassner and Margapuri, will advance research and education across a variety of domains that deal with 3- Dimensional data as part of their research endeavor and for researchers and educators needing to collaborate in real-time across distances to interrogate and manipulate 3-Dimensional data of any type.
Voice Assistants (VA) in smartphones have become very popular with millions of users nowadays and a key trend is the rise of custom VA embedding. This NSF funded project is led by Dr. Xue Qin. The project's Test2VA approach aims to simplify adding voice assistant features to mobile apps by reusing test code. It repurposes GUI test code for voice commands, creating reusable templates, mapping voice queries to code, and facilitating code execution in response to voice commands. Specifically, Test2VA extracts the task completion pattern from GUI test code and then generates an execution method to perform the same task in general. To identify the pattern, Test2VA uses a mutation-based exploration to detect the mutable GUI event in the test case and later parameterize it in the VA method.
The AR Sandbox was originally developed at UC Davis for teaching qualitiative geoscience concepts through augmented reality. This NSF funded project led by Dr. Frank Klassner is a collaboration with Dr. Kabindra Shakya from the Geography and Environment department and Dr. Virginia Smith from the Civil Engineering department to extend the AR Sandbox to support quantitative modeling of hydrological processes and investigate the new system's utility in undergraduate education. In addition to new software development, the project has a plan for a novel hardware frame design for the Sandbox, and a plan to use the sandbox as a keyboard for defining landscapes in large-scale display systems like CAVEs.
OCCAM is an ongoing Defense Advanced Research Projects Agency (DARPA)-funded project for Vencore Labs with Vijay Gehlot, PhD. The proposed research will make use of Colored Petri Nets models of the system architecture to analyze vulnerabilities. A semi-automated approach for creating a credit profile number (CPN) from the description of the system components is proposed. The generated CPN model will be instrumented with data collection monitors. The generated data will be analyzed against defined vulnerability metrics to assess and mitigate the attack surface of the underlying system.
This ongoing project for the Vatican Internet Office, managed by Frank Klassner, PhD, and the department of Communication, developed a series of virtual reality presentations of the major basilicas and Sacred Places of Rome for the Vatican's and is currently developing material for virtual reality presentations of the Vatican Radio's Marconi Museum, the Redemptoris Mater papal chapel, and other sites at the Vatican.
Recent Faculty Publications
A. Cagaanan and V. Gehlot. Model-Driven System Development for a Cloud-Based Healthcare Application Using Colored Petri Nets. Proceedings of the IEEE Systems Conference (SysCon 2024). April 2024.
V. S. K. Margapuri and P. Thapaliya. Seed Kernel Counting using Domain Randomization and Object Tracking Neural Networks. IEEE Symposium Series on Computational Intelligence, 2024
E. Rzig, N. Iqbal, I. Attisano, X. Qin, F. Hassan. Virtual Reality (VR) Automated Testing in the Wild: a Case Study on Unity-Based VR Applications. The 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis. 2024.
A. Anjum, P. Agbaje, A. Mitra, E. Osheghale, E. Nwafor, H. Olufowobi. Towards named data networking technology: Emerging applications, use cases, and challenges for secure data communications. Future Generation Computer Systems, vol. 151, 2023. pp. 12-31.
E. Nwafor, C. Schmidt, H. Olufowobi. IoT-MGSec: Mitigating Man-in-the-Middle Attacks in IoT Networks using Graph-based Learning. The 22nd IEEE International Conference on Machine Learning Applications (ICMLA), Jacksonville, FL, USA 2023, pp. 1261-1266.
P. Agbaje, E. Nwafor, H. Olufowobi. Deep Reinforcement Learning for Energy-Efficient Task Offloading in Cooperative Vehicular Edge Networks. Proceedings of the 2023 IEEE International Conference on Industrial Informatics. July 17-20, 2023.
P. Agbaje, A. Anjum, Z. Talukder, M. Islam, E. Nwafor, H. Olufowobi. FedCime: An Efficient Federated Learning Approach for Clients in Mobile Edge Computing. Proceedings of the 2023 IEEE Conference on Edge Computing and Communications. July 2-8, Chicago, IL. 2023.
V. Gehlot, D. King, J. Schaffer, E. B. Sloane, N. Wickramasinghe. Healthcare Optimization and Augmented Intelligence by Coupling Simulation and Modeling: An Ideal AI/ML Partnership for a Better Clinical Informatics. American Medical Informatics Association (AMIA), pp. 477-484. April 2023.
F. Klassner, A. Grace. Campus Visualization Centers: Reflecting and Projecting. IEEE VR 2023 Workhop on Immersive Visualization Laboratories 鈥� Past, Present, and Future. IEEE VR 2023 Conference Proceedings. Shanghai. March 25-26, 2023.
V. Gehlot, E. B. Sloane, D. King, J. Schaffer, M. Kirk, E. Miller, N. Wickramasinghe. "COVID-19 and Beyond: Taming the Virtual Healthcare Tiger with Colored Petri Nets based Modeling and Simulation." Proc. of 55th Hawaii International Conference on System Sciences (HICSS鈥�55), pp. 3773-3782, Jan 2022.
E. Nwafor, H. Olufowobi, CANBERT: A Language-based Intrusion Detection Model for In-Vehicle Networks. Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, pp. 294-299. December 2022,
X. Qin, F. Hasan. DyTRec: A Dynamic Testing Recommendation Tool for Unity-Based Virtual Reality Software.Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE 鈥�22). pp. 1-5. October 2022.
V. Gehlot, P. Rokowski, E. B. Sloane, N. Wickramasinghe. Taxonomy, Tools, and A Framework for Combining Simulation Models with AI/ML Models. Proceedings of the 2022 Annual Modeling and Simulation Conference (ANNSIM). IEEE, pp. 18-29. July 2022.
V. Gehlot, N. Wickramasinghe, E.B. Sloane, M. Kirk, E.R. Miller. 鈥淯sing Coloured Petri Nets for Optimisation of Healthcare Processes.鈥� In Digital Disruption in Health Care. Springer Nature Switzerland AG. June 24, 2022.
E. Nwafor, A. Anietie. A Survey of Machine Translation Tasks on Nigerian Languages. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pp. 6480鈥�6486, Marseille, France. European Language Resources Association. June 2022.
V. Gehlot, 鈥淎 Tutorial Introduction to Colored Petri Nets Framework for Model-Driven System Design and Engineering,鈥� Proceedings of ANNSIM鈥�21, Fairfax, VA, USA. July 19-22, 2021.E. Nwafor, C. Kolimago, R. Vaughn. "Covid Vaccine Sentiment Analysis by Geographic Regions." IEEE BigData Workshop on Big Data Analytics for COVID-19 (IEEE BDA COVID-2021). Dec 15-18, 2021, Orlando, FL, USA (Virtual).
V. Gehlot, J. Robinson, M. Tanwar, E. B. Sloane, N. Wickramasinghe. "Toolkit for Healthcare Professionals: A Colored Petri Nets Based Approach for Modeling and Simulation of Healthcare Workflows." Proceedings of the 2021 Winter Simulation Conference (WSC), IEEE, pp. 1-12, December 2021.
E. Nwafor, S. Su. Detecting Network Traffic Intrusions on Memory Constrained Embedded Systems. 2021 Virtual IEEE International Symposium on Technologies for Homeland Security. Nov 8-9, 2021.
H. M. Rando, S. M. Boca, L. D. McGown, D. S. Himmelstein, M. P. Robson, V. Rubinetti, R. Velazquez, C. S. Greene, A. Gitter. "An Open-Publishing Response to the COVID-19 Infodemic." Proceedings of the Workshop on Digital Infrastructure for Scholarly Content Objects (DISCO 2021), Sep 30, 2021 (Virtual).
M. Robson, E. Nwafor, "Dynamic Load-Sharing for Memory Constrained Devices: A Survey," Proceedings of IEEE World Forum on Internet of Things, Jun 14-Jul 31, 2021, New Orleans, LA, USA.
V. Gehlot. "A Tutorial Introduction to Colored Petri Nets Framework for Model-Driven System Design and Engineering." Proc. of 2021 Annual Simulation Conference (ANNSIM'21), Society for Modeling & Simulation Intn鈥檒, pp. 1-12, Jul 2021.
M. Robson, E. Nwafor, 鈥淒ynamic Load-Sharing for Memory Constrained Devices,鈥� Proceedings of IEEE World Forum on Internet of Things, New Orleans, LA, USA. June 14-July 31, 2021.
E. B. Sloane, V. Gehlot, N. Wickramasinghe, and R. Silva, 鈥淯sing Community Care Coordination Networks to Minimize Hospitalization of COVID-19 Patients,鈥� IEEE SoutheastCon2021, Mar 2021, p.1-4.
N. Wickramasinghe, V. Gehlot, E Sloane, P. Smart, and J. Schaffer, 鈥淎 Precision Post-Operative Wellness Monitoring Solution,鈥� Proc. 53rd Hawaii International Conference on System Sciences (HICSS-53), pp. 3720-3728, January 2020.