About Me

Hi! I am Stefany Cruz, a Ph.D. candidate in Computer Engineering at Northwestern University. I work in the Ka MoaMoa lab and NU PATH lab, where I am co-advised by Josiah Hester and Maia Jacobs.


My research centers on advancing AI-driven wearable and IoT technologies to develop intelligent, efficient, and equitable solutions for real-world challenges. I specialize in designing and implementing adaptive wearables that integrate on-device machine learning, embedded systems, and ubiquitous computing to enhance health, safety, and sustainability. By leveraging AI with low-power embedded systems, my work aims to improve the accessibility and performance of wearable technologies across diverse applications.

I have published papers in top venues in ubiquitous computing (IMWUT), human computer interaction (CHI), and medical journals (JMIR mHealth and uHealth). I have been awarded Social Justice grants from Northwestern’s Office of Diversity and Inclusion and received an Ada Lovelace Microsoft Research Ph.D. fellowship to support my work in developing inclusive, equitable technologies for social good. My research has been featured across several media outlets regionally and internationally such as CBS Chicago News, Crain's Chicago Business, Digital Trends, Hackster.io, The Independent, BBC Radio, NPR, and many more.






✉️ stefanycruz2024(at)u(dot)northwestern(dot)edu

📄 CV/Resume  ▪️  🎓 Google Scholar  ▪️  🐦 twitter


Research Overview/Themes

In my work, I identify barriers within wearable and Internet of Things (IoT) technologies that limit their accessibility and functionality, and I actively develop and deploy solutions to overcome these challenges. My approach uniquely integrates embedded systems development, signal processing, on-device machine learning, qualitative insights from lived experiences, and quantitative data analytics to bridge gaps in equity, design, and computing—ultimately creating wearable and IoT technologies that empower and uplift underserved populations. My research aims to address challenges across three themes: Health, Urban Safety, and Sustainability.



Selected Research

EquityWare: Co-designing Wearables With And For Low-Income Communities (CHI'23)

This work explores how members of Latine underserved communities from Los Angeles and Chicago perceive wearables. Using semi-structured interviews and system co-design through storyboards, I uncovered a strong demand for wearables that prioritize personal safety, situational awareness, and discreet, energy-efficient designs. This led me to develop a much-needed research agenda Equityware, a framework poised to drive impactful contributions through Hardware, Software, and Research and Education. 

*This is a key publication from my Ph.D. Thesis

DOI  ▪️  Video  ▪️  Code

SmokeMon: Unobtrusive Extraction of Smoking Topography Using Wearable Energy-Efficient Thermal (IMWUT/UbiComp'23)

SmokeMon is a wearable necklace equipped with a deep-learning data analysis pipeline designed to automatically detect smoking behavior and extract detailed smoking topography. Its goal is to empower individuals to better understand the challenges of their addiction while maintaining ease of use through an unobtrusive, low-power design that remains affordable. Check out the press SmokeMon garnered worldwide!

DOI  ▪️  Video  ▪️  Code

BFree: Enabling Battery-free Sensor Prototyping with Python(IMWUT/UbiComp'21)

BFree allows the development of battery-free applications, to novices and hobbyists, using the Python (leveraging AdaFruit’s CircuitPython ecosystem) programming language and widely available hobbyist maker platforms. BFree provides energy harvesting hardware and a power failure resilient version of Python, with durable libraries that enable common coding practice and off-the-shelf sensors. This work allows makers to engage with a useful, long-term, and environmentally responsible future of ubiquitous computing. Check out the press BFree received!

DOI  ▪️  Video  ▪️  Code

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