Human-Machine Intelligent Systems Lab
The Lab's Work

Research

What follows is everything the lab has published or shown: peer-reviewed papers, conference posters, undergraduate research projects, and the occasional piece of software.

Explainable AI

How can a machine show its reasoning, not just its answer? We work on visual and interactive tools that help students, teachers, and decision-makers see what is inside a model.

Developing Tools for AI Explainability

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Teaching & Learning

Most of our students learn by doing real research. The work below ranges from intelligent tutors that give feedback on student writing, to course tools that we and the rest of the college actually use.

RAG vs. Fine-Tuning in Math Education: Developing and Validating Mentir AI

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Interactive AI Theater Presentation

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Biomedical ML

Machine learning where care actually happens: ECG, sleep, wearables, and the messy realities of clinical and lab data.

Minute and Subject-Level Sleep Apnea Detection Using an ECG-Based Machine Learning Pipeline

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Wireless, IoT, and Computer Vision

Lower-level systems work that supports the rest of what we do: secure IoT layers, sensor frameworks, and a few computer vision detours.

Automated Moon Crater Detection: Exploring Algorithmic and Neural Network Approaches

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RF IoT Security Layer

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UCPlaces: Campus Orientation App Using ArcGIS

Ursinus Celebration of Student Achievement (CoSA)2023