Tyler Spitzer-Wu


// University of Michigan
// B.S. Urban Technology
// Taubman College of Architecture and Urban Planning
// Minors in Computer Science and Real Estate Development
// Class of 2027

I am fascinated with the use of technology within the processes and systems of the built environment to improve efficiency and delight in development and user experience. Cities are centers of innovation, culture, and economy with unparalleled vitality; I am interested in how scalable products and efficient services can be deployed in them to maximally respond to the needs of a city’s users. I aspire to deploy my programming skills, design intuition, and entrepreneurial approach to positively impact cities in product, design, and technology roles.


Product Intern
    Cedar (AI + architecture startup)
    Summer 2025

VP External Affairs, Co-Founder
    URB Consulting
    Oct 2024 - Present

Design Intern
    Fletcher Studio Landscape Arch. + Urban Design
    Oct 2023 - Dec 2023





tylersw@umich.edu
Résumé
LinkedIn

Crosswalks

UT 230: Design and Urban Inquiries
APR 2025


// Figma
// storytelling, field research, user research This project was a month-long group effort focused on understanding human behavior at Ann Arbor’s crosswalks, developing meaningful insights, and proposing possible changes. It culminated in the creation of a zine explaining the archetypes we discovered through repeated field research and a set of proposed changes for Ann Arbor’s urban planners and residents.  
I co-led the creation of the archetypes section, shown here. Click through the carousel to see the 6 archetypes we constructed from our data collection, along with their key characteristics and behavior.

A key decision we made here was to provide insights for both the archetype and for planners. We thought that a one-sided argument for one party or the other to change while the other remains the same would be not only unfair, but simply more difficult in execution. So, we included recommendations for both planners and the archetypes on how to change the environment and change their behavior, respectively, to create a safer, more comfortable, and more predictable experience for everyone at the crosswalk.

We collected our data by standing at our campus’ most busy crosswalk during rush period and taking photos and videos of the activity. This crossing is adjacent to our central bus station and connects two parts of campus, meaning there is a ton of foot traffic, car traffic, and bus traffic. Our choice of crosswalk yielded the most meaningful data, as we encountered pretty much every type of possible interaction between pedestrians, cars, and buses.

motorcylist crossing? (”Hot Rod”)
solo strollers (baseline user)
cyclist crossing (”Hot Rod”)
tour group (”Leader-Followers”)
another cyclist (”Hot Rod”)
scrolling and strolling (”Digitally Consumed”)
more baseline users
Affinity mapping. How do we make sense of high quantity of data?
Affinity mapping
Field notes
Messily trying to make sense of our data. The spectrum at the top ended up making it into our final zine.
Initial sketch specifying how we would represent each archetype.




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