ACM SIGCSE TS'25
This paper investigates the implementation of AI-driven chatbots as a solution to streamline academic advising and improve the student experience. Through a review of preliminary results from the Nittany Advisor chatbot, we show how AI chatbots can boost advising efficiency, increase student satisfaction, and examine how chatbots can provide information on course requirements, prerequisites, and academic policies while suggesting the need for human intervention for more complex queries. We conclude that AI chatbots hold considerable promise for transforming academic advising by addressing routine questions, streamlining access to crucial information, and fostering a more responsive and supportive educational environment.
ASEE Mid-Atlantic Spring '25
Drones struggle to fly in icing and cloudy conditions, especially when the two are combined. This research project focuses on the automation of drones for monitoring rotational speed (RPM) and torque loss when traversing cloud and icing conditions. Cameras and radar systems are either not reliable or too complicated to mount on a compact UAV. By monitoring the UAV's torque and RPM loss, the project aims to precisely measure the impact of cloud and icing environments on drone performance using the Han-Palacios correlation between icing conditions and torque loss to estimate the volume of water within the clouds and assess general icing severity.