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.
Projects
From signal to system
Building at the intersection of neuroengineering, AI, and product
Research
Mapping signals to clinical insight
From EEG decoding to self-supervised learning — building diagnostic tools that bridge biology and computation
Confidential Neuromodulation Research Initiative on Transcranial Focused Ultrasound
Owen Kim, Adam Waspe, Natalie Rhodes, Sebastian Coleman, George Ibrahim
Ibrahim Lab, The Hospital for Sick Children, University of Toronto.
Semi-Supervised Reinforced Active Learning for Label-efficient Semantic Segmentation
Anonymus Authors
Vision & Image Processing Lab + Critical ML Lab, University of Waterloo.
Deep Learning Based Segmentation of the Myenteric Plexus to Support Diagnostics of Parkinson's Disease
Owen Kim, Rosanna Hanke, Francisco Benavides, Guillermo Tearney
Tearney Lab, Massachusetts General Hospital, Harvard Medical School.
Experience
Where the work happened
Research labs, startups, and hospitals — building real things in high-stakes environments
The Hospital for Sick Children
R&D Engineer
Jan 2026 - Apr 2026
Toronto, ON
Leading a cross-lab initiative evaluating transcranial focused ultrasound neuromodulation with simultaneous 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
- SNR improvement via shielded cabling and signal filtering in MNE-Python
- Prototyped a wearable neuromodulation helmet through 11+ transducer/sensor configurations
Critical ML Lab
Undergraduate Research Assistant
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
Harvard Medical School — Tearney Lab
Machine Learning Research Intern
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
- Completed the Biomedical Optics Summer Institute through the Health Science and Technology program at Harvard Medical School and MIT
- Presented at the Wellman Center for Photomedicine, Massachusetts General Hospital
DataFix
Junior Software Developer
Apr 2024 - Aug 2024
Toronto, ON
Implemented database solutions using Microsoft SQL Server, optimizing data storage and retrieval for optimal website performance.
Key outcomes
- Developed and repaired website features using C#, HTML and CSS improving user interface
- Successfully delivered a major project for Halifax Regional Municipality, developing a poll book system used in their next election by retrieving, implementing, and displaying data, ensuring the project was completed on time and met all functional requirements
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