Urban Intelligence Lab

What we do

The Urban Intelligence Lab Enterprise is a hands-on, interdisciplinary team where students design, build, and deploy data-driven solutions for smarter, more sustainable communities. We combine sensing, analytics, and system-level thinking to tackle real challenges on campus and in the Keweenaw region.

Computer Vision & Sensing

Develop and deploy computer vision systems alongside other sensors to detect, classify, and track activity in real environments.

Intelligent Infrastructure

Use data from sensors and computer vision to understand how people and resources move through public open spaces and infrastructure. Translate these insights into recommendations and strategies that guide the design, planning, and management of parks, transit corridors, and other community assets.

Applied Data & AI

Use machine learning and analytics to turn raw sensor and vision data into actionable insights for decision-makers in communities and industry partners.

Interdisciplinary Teamwork & Data Science

Collaborate across data science, computer science, and diverse engineering fields—alongside social science and human-factors expertise—to design, test, and deploy solutions that are technically sound and responsive to community needs.

Campus Activity Tracking at the SDC

This project uses computer vision to detect and track crowd occupancy in the SDC multipurpose room and to develop a tool that analyzes and visualizes it. It helps users find the best time and space for activities such as running, basketball, and other recreational activities, and maps how students move through campus and interact with its infrastructure. By generating data on traffic patterns, gathering spots, and asset usage, it provides a clearer picture of campus dynamics.

Vessel Tracking & Fisheries Monitoring

Working with the Great Lakes Research Center, the team is developing computer vision systems to track and classify vessels traveling through the Portage Canal. This work will expand to monitor fishing activity at remote locations like Stannard Rock, where collecting reliable data has historically been difficult. By producing high-quality usage data, the project strengthens fisheries research and supports collaborative management with tribal and state partners, ultimately benefiting recreational anglers and regional ecosystems alike.

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Team

Gabriel Draughon, Ph.D.

Advisor • Engineering Fundamentals • Assistant Professor

Interests: Smart and Connected Cities, Self-efficacy in STEM undergraduates

Anna Tolles

President • Data Science (Statistics Minor) • BS '27

Interests: Data Analysis, Database Management and Design, Statistics Education, Human Factors

Jeremiah Branch

Vice President • Computer Science (Psychology Minor) • BS '28

Interests: Human-Computer Interaction, Software Development, UI/UX Design, Psychoinformatics

Michael Dennis

Grad Student • Computer Science • MS '27

Interests: Hobbies, Running, Coding, Biking

Noah Zabinski

Undergrad Student • Software Engineering (Cybersecurity Minor) • BS '28

Interests: Security, Machine Learning, Automation

Dominic Teddy

Undergrad Student • Computer Science (Business Minor) • BS '29

Interests: Machine Learning, AI Ethics, Software Development

Ben Peters

Student • Computer Science • BS '28

Interests: Remote Sensing, Data Visualization

Violet Blake

Student • Data Science • BS '29

Interests: Data Analytics, Machine Learning, Piano

Ephraim Rogina

Student • Civil Engineering • BS '29

Interests: Road Systems, History of Maps, Mathematics, Coding

Lydia Peterson

Student • Data Science • BS '29

Interests: Data analytics, Hiking, Reading

Claire Steigelman

Student • Data Science (Rail Transportation Minor) • BS '28

Interests: Intercity passenger and high-speed rail, Transit, Architecture, Environment, Urban planning

Adeline DeToy

Student • Mechanical Engineering (Business and Psychology Minor) • BS '28

Interests: Manufacturing, Design, Aerospace field, Outdoors

Anna Acher

Grad Student • Applied Cognitive Science and Human Factors Psych (Certificate in Artificial Intelligence in Business Information Systems) • MS '27

Interests: Macro-scale behavioral science, Urban design, Emerging technologies, Architecture, Movies

Arthur van den Berg

Student • Software Engineering • BS '29

Interests: Coding, Machine Learning, Game Development, Acting, Dungeons & Dragons

Egor Aliakseyeu

Student • Computer Engineering • BS '28

Interests: Data Communications, Machine Learning, Embedded Systems

Josh Arango

Student • Josh Arango • BS '27

Interests: Guitar, Skiing

Blaze

Good boy • CS (Chaos and Spunk) • Team Mascot

Interests: Beach, Sticks, Biting

Contact form

Please reach out if you are interested in learning more about our projects, collaborating with the Urban Intelligence Lab, or joining our team. Let us know who you are and your areas of interest!