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
This project aims to support students, practitioners, and educators in learning and teaching AI and cybersecurity concepts through hands-on, inquiry-based labs. It has received funding from the NSF under three awards, including the latest grant titled The AI Voyage: Integrating AI Literacy into Computer Science Curricula with Accessible Hands-On Learning Activities.
The Emerging Multimedia Lab is focused on improving both security and accessibility in multimedia technologies. The lab is currently working on improving the security of ML algorithms and protecting user privacy in ML applications by designing new protection frameworks. The lab is exploring the use of AR to help people with hearing loss by detecting and converting acoustic signals into corresponding visual signals using AR devices.
This lab is equipped with several NI-USRP which can be programmed to receive different types of signals over the air for investigation. The major focus of this lab is to apply machine learning to classify communication/radar signals, model communication system/radar behaviors, and detect anomaly radar/communication system behaviors. Our research can be applied in numerous areas such as RF environment surveillance, cognitive radio, intrusion detection, etc.
The Laboratory for Smart Wireless Communication Networks lab has an AI workstation for fast deep learning and reinforcement learning and a group of DJI MAVIC Air 2 and Tello quadcopters that are programmable with dedicated remote controllers and software development toolkits.
The MyPath Project 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.
Plan Selection for Policy-Aware Autonomous Agents
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.
Parallel and Distributed Heterogeneous Computing
Vaskar Raychoudhury, Ph.D.
Distributed, Mobile, and Pervasive Computing
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!
