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Ken Christofferson
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👋 Hi, I'm Ken

I am a PhD student advised by Alex Mariakakis and Joseph Cafazzo who lead the Computational Health and Interaction (CHAI) lab at the University of Toronto Department of Computer Science and the Centre for E-Health Innovation at the University Health Network respectively.

My research focuses on using the sensors embedded in common devices (e.g., mobile phone, earbud, smartspeaker) and novel machine learning techniques to acquire information relevant to human health as well as exploring how that information is best used to improve health outcomes. I am interested in a broad array of sensing modalities and use cases, please check out my research and projects pages for more.

🏫 Education

  • _PhD Computer Science - Univeristy of Toronto (in progress)
  • _MS Engineering, Data Science, and Information Technology - Tsinghua Univeristy (2021)
  • _MS Technology Innovation - Univeristy of Washington (2021)
  • _BA International Studies - American University (2011)

🧰 Mentoring and Outreach

📨 Get In Touch

kenc at cs dot toronto dot edu



Recent Updates

ReHEarSSE - Recognizing Hidden-in-the-Ear Silently Spelled Expressions using Ultrasonic Occluded Ear Canal Deformation Analysis

Abstract: Silent speech interaction (SSI) allows users to discreetly input text without using their hands. Existing wearable SSI systems typically require custom devices and are limited to a small ...

EarSteth - Cardiac Auscultation Audio Reconstruction Using Earbuds

Abstract: Cardiac auscultation is a critical component of most primary care examinations; however, this screening procedure is currently infeasible in telehealth settings because it requires that ...

Sleep Sound Classification Using ANC-Enabled Earbuds

Abstract: Standard sleep quality assessment methods require custom hardware and professional observation, limiting the diagnosis of sleep disorders to specialized sleep clinics. In this work, we l...

An AI Driven, Mechanistically-Grounded Geospatial Liquefaction Model for Rapid Response and Scenario Planning

Abstract: Geospatial models for predicting soil liquefaction infer subsurface traits via satellite remote sensing and mapped information, rather than directly measure them with subsurface tests. Fi...

Induced Acoustic Resonance for Noninvasive Bone Fracture Detection Using Digital Signal Processing and Machine Learning

Abstract: A bone fracture is a complete or incomplete discontinuity in a bone, often caused by an impact. While extreme fractures are sometimes obvious, most fractures require radiographic imaging ...