Artificial Intelligence and High Performance Computing
The Artificial Intelligence and High Performance Computing research cluster at Miami University’s College of Engineering and Computing (CEC) explores how intelligent systems and advanced computation can be leveraged to solve real-world problems—ranging from cybersecurity to accessibility to autonomous reasoning.
Labs and resources
Led by Liran Ma, D. Sc., EUREKA Labs supports students, practitioners, and educators in learning and teaching AI and cybersecurity through hands-on, inquiry-based labs. Funded by the NSF, the lab's current initiative—The AI Voyage—aims to integrate AI literacy into computer science curricula using accessible and interactive learning activities.
The Emerging Multimedia Lab focuses on improving the security and accessibility of multimedia technologies. Current research includes developing new frameworks to secure machine learning algorithms and protect user privacy. The lab is also exploring augmented reality (AR) solutions to help individuals with hearing loss by converting acoustic signals into visual ones.
This lab uses NI-USRP devices to analyze over-the-air signals. Research here applies machine learning to classify communication and radar signals, model behaviors of these systems, and detect anomalies. Applications include RF environment surveillance, cognitive radio, and intrusion detection.
This lab is equipped with an AI workstation optimized for deep and reinforcement learning, along with programmable quadcopters (DJI MAVIC Air 2 and Tello) for applied AI research. These tools are used in communication systems, autonomous networks, and intelligent control.
The MyPath Project, led by associate professor of Computer Science and Software Engineering Vaskar Raychoudhury, Ph.D., aims to build an accessible routing and navigation system for wheelchair users to get to their destination from any location. Accessible routes can be determined by classifying surfaces from vibration data. The data collected by sensors is analyzed and classified and the ML model is used to predict any new surface data. The road surface information is then updated in a research-oriented open-source mapping system known as the OpenStreetMap (OSM). The user’s personalized requirements and the accessibility of each road are combined to generate an accessible route for wheelchair users.
Faculty research projects
Faculty in this cluster are developing AI and computing solutions to address modern-day challenges in education, healthcare, national security, and beyond. Select a faculty researcher below to learn more about their work and recent publications.
Michael Zmuda, Ph.D
Ensemble Creation Using Fuzzy Similarity Measures and Feature Subset Evaluators
Daniela Inclezan, Ph.D.
Solar Cells; Plan Selection for Policy-Aware Autonomous AgentsArtificial Nasal Cavity
Xianglong Feng, Ph.D.
Security and Privacy in Machine Learning Applications
Chi-Hao Cheng, Ph.D.
Machine Learning Aided Electronic Warfare System
Liran Ma, D.Sc.
ClassifAI Instructional Equity Observing Tool
John Femiani
Computer Vision and Computer Graphics
DJ Rao, Ph.D.
Applied Machine Learning, Large-Scale Simulation
Vaskar Raychoudhury, Ph.D.
Accessible Routing Using Smart Crowd-Sensed Surface Classification for Wheelchair Users
If your company is interested in benefiting from research opportunities and faculty expertise at the College of Engineering and Computing, please contact:
Jenni Szolwinski
Director of Industry Relations
Miami University
513-529-0702
You can also learn more about partnership opportunities by following the button below.
Below, you’ll find contact information for the faculty members involved in this research cluster. Feel free to reach out if you’d like to get involved as a student researcher!
