Available · Fall 2026

Owen Kim

Biomedical Engineer · Neuroengineering · Machine Learning

Biomedical Engineering student at the University of Waterloo (GPA 3.9/4.0) exploring the intersection of neuroengineering and machine learning — building diagnostic AI and medical devices that translate biological signals into clinical impact.

SickKids · R&D EngineerHarvard Medical · Tearney LabUWaterloo · Critical ML Lab
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Projects

From signal to system

Building at the intersection of neuroengineering, AI, and product

AI & HealthReal-time fall risk detection

FORTif.AI

AI-powered safety assistant for seniors

Real-time gait analysis and fall prevention system for elderly users, combining computer vision with wearable sensor data to detect fall risk before it happens.

PythonComputer VisionGait AnalysisPyTorchHealthcare AI
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SoftwarePeople's Choice Award — UW Velocity Future Cities Pitch Competition

United Mobility

Decentralized micro-mobility platform

Co-founded and built a decentralized e-scooter platform from the ground up, owning engineering, partnerships, and product design. Won People's Choice Award at UW Velocity Future Cities.

Product DesignApp DevelopmentFull-StackStartup
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StrokeAlert

Real-time stroke detection via facial landmarks

PythonOpenCVComputer VisionMediaPipeHealthcare
GitHub
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KidsAbility Design Project

Promoting physical activity for kids with cerebral palsy

Human-Centered DesignQFDPrototypingAccessibilityBiomedical
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CryptoCompanion

Beginner-friendly crypto investing platform

ReactJavaScriptFinTechAPI IntegrationHackathon
Devpost
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QR Code Generator

Java-based QR generator with GUI and storage

JavaSwingGUIFile I/O
GitHub
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Research

Mapping signals to clinical insight

From EEG decoding to self-supervised learning — building diagnostic tools that bridge biology and computation

SI

Transcranial Focused Ultrasound Neuromodulation & OPM-MEG Neural Monitoring

R&D Engineer

The Hospital for Sick Children

CurrentJan 2026 – Present

Leading feasibility evaluation of transcranial focused ultrasound (tFUS) neuromodulation combined with OPM-MEG neural monitoring. Coordinating across 3 independent research groups spanning neuroscience and hardware engineering.

Co-authored a $225,000 internal research grant to initiate project development

tFUSOPM-MEGNeuromodulationSignal ProcessingMNE-Python
UW

Reinforcement Learning–Based Active Learning for Semantic Segmentation

Undergraduate Research Assistant

Vision & Image Processing Lab + Critical ML Lab, University of Waterloo

CurrentAug 2025 – Present

Implementing and benchmarking active learning pipelines to improve annotation efficiency for medical image segmentation. Applied to brain tumor datasets, with a focus on RL-based sampling strategies.

Co-authored manuscript under review at ICML 2026

Active LearningSemantic SegmentationPyTorchMedical ImagingRL
HA

Parkinson's Disease Diagnosis via Esophageal OCT Segmentation

ML Research Intern

Harvard Medical School — Tearney Lab

CompletedMay 2025 – Aug 2025

Developed a deep learning pipeline for Parkinson's disease diagnosis by segmenting esophageal OCT images. Translated 16+ clinician-defined design requirements into model architecture and training strategy. Validated LT-U-Net achieving 85%+ classification accuracy.

Presented at the Wellman Center for Photomedicine, Massachusetts General Hospital

OCT ImagingDeep LearningLT-U-NetPyTorchParkinson's Disease

Experience

Where the work happened

Research labs, startups, and hospitals — building real things in high-stakes environments

TH

The Hospital for Sick Children

R&D Engineer

Research

Jan 2026 – Present
Toronto, ON

Leading a cross-lab initiative evaluating transcranial focused ultrasound neuromodulation and OPM-MEG neural monitoring across neuroscience and hardware teams.

Key outcomes

  • Led 9+ researchers/engineers across neuroscience and hardware teams
  • Co-authored a $225,000 internal research grant
  • ~67% SNR improvement via shielded cabling and signal filtering in MNE-Python
  • Prototyped a wearable neuromodulation helmet through 11+ transducer/sensor configurations
MNE-PythonSolidWorksSignal ProcessingOPM-MEGUltrasound
VI

Vision & Image Processing Lab + Critical ML Lab

Undergraduate Research Assistant

Research

Aug 2025 – Present
Waterloo, ON

Implementing and evaluating active learning pipelines for annotation efficiency and segmentation performance. Applying methods to brain tumor datasets for medical imaging.

Key outcomes

  • Compared annotation efficiency across active learning sampling strategies
  • Led medical imaging implementation on brain tumor dataset
  • Co-authored manuscript on RL-based active learning under review at ICML 2026
PythonPyTorchActive LearningSemantic SegmentationMedical Imaging
HA

Harvard Medical School — Tearney Lab

Machine Learning Research Intern

Research

May 2025 – Aug 2025
Boston, MA

Developed a deep learning pipeline for Parkinson's disease diagnosis through segmentation of esophageal OCT images. Presented at the Wellman Center for Photomedicine at MGH.

Key outcomes

  • Built deep learning pipeline for Parkinson's diagnosis via esophageal OCT
  • Translated 16+ clinical design requirements into model architecture decisions
  • Achieved 85%+ classification accuracy with LT-U-Net model
  • Presented at the Wellman Center for Photomedicine, Massachusetts General Hospital
PythonPyTorchOCT ImagingLT-U-NetDeep Learning
UN

United Mobility

Co-founder

Startup

Mar 2025 – Sep 2025
Waterloo, ON

Led development and deployment of a decentralized e-scooter platform, owning execution across engineering, partnerships, and app product design.

Key outcomes

  • Drove cross-functional execution across software and business strategy
  • Won People's Choice Award at UW Velocity Future Cities Pitch Competition
Product DesignCross-functional LeadershipApp Development

Contact

Let's build something
worth remembering.

Actively seeking R&D, product, and engineering roles in neurotech, medical AI, and health tech — available Fall 2026.

Based in Waterloo, ON · Open to remote and hybrid roles