In April, students in the Applied Deep Learning and Applied Machine Learning courses presented their final projects during a poster session in Malachowsky Hall. Dr. Andrea Ramirez-Salgado, instructional assistant professor in the Department of Engineering Education, instructed both courses this spring. The students were either from the Master of Science in Artificial Intelligence Systems (MSAIS) or Master of Science in Applied Data Science (MSADS) programs.

Their work covered a variety of topics and featured advanced multimodal AI architectures applied to real world problems, and several students designed edge AI solutions. For example, one student built a drone-based application with embedded AI that classified voice commands and responded with directional movements, such as moving up three times or right four times, all processed within the drone itself. Others worked on frameworks to generate image captioning more efficiently, interpret satellite images, or generate images from speech. 

“Their work—spanning more traditional CNNs, LSTMs, GANs, autoencoders, etc, to advanced hybrid architectures and multimodal inputs/outputs—was nothing short of impressive,” said Dr. Ramirez-Salgado.

The session was attended by faculty, students, and staff from various colleges, who provided enthusiastic feedback and explored potential collaborations.