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.

Showing all papers
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

Michael Cummins, William M. Mongan

Ursinus Celebration of Student Achievement (CoSA)2025

explainableai ai cosa
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

Michael Cummins, Matt Latta, Claire Shoemaker, William M. Mongan

Ursinus Celebration of Student Achievement (CoSA)2026

ai education rag cosa

Interactive AI Theater Presentation

Levi Fritz, Shannon Zura, William M. Mongan

Ursinus Celebration of Student Achievement (CoSA)2026

ai performance art interactive cosa

Instructional Judgment, Not Just Correctness: Evaluating AI-Generated Feedback on Student Mathematical Thinking

A. Reinsburrow, C. Yovanov, William M. Mongan, Michael Cummins, Matt Latta, W. Shumar, V. Klein, J. Silverman, S. Weimar

Society for Information Technology & Teacher Education International Conference 20262026

ai education mathematics
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The Ursinus WebIDE: A Serverless Browser-Based Development Environment for Student Practice and Rapid Instructor Exercise Development

Christopher Tralie, William M. Mongan

Proceedings of the 55th ACM Technical Symposium on Computer Science Education (SIGCSE TS 2026)2026

cs education ide webide
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Post-It Pandemonium: Teaching Image Representation and Compression with an "Unplugged" Activity

William M. Mongan, Jeffrey L. Popyack

ACM SIGCSE 2019 Nifty Assignment2019

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

Andrei Bogdan, William M. Mongan

Ursinus Celebration of Student Achievement (CoSA)2026

machine learning healthcare ecg cosa
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

Dylan Melby, William M. Mongan

Ursinus Celebration of Student Achievement (CoSA)2023

machine learning computer vision cosa

RF IoT Security Layer

Jonas Ling, William M. Mongan

Ursinus Celebration of Student Achievement (CoSA)2023

iot security cosa

UCPlaces: Campus Orientation App Using ArcGIS

Arthur Artene, Tristan Ashcroft, William M. Mongan

Ursinus Celebration of Student Achievement (CoSA)2023

gis mobile cosa

drexelwireless/iot-sensor-framework: Public Release 1.0

William M. Mongan, Ilhaan Rasheed, Enioluwa Segun, Henry Dang, Victor S. Cushman, Charlie Rose Chiccarine, Kapil R. Dandekar, Adam K. Fontecchio

Zenodo2020

iot
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