Chris Bailey

Academic Data Scientist with 8+ years of experience in the human health domain, currently focused on solutions for evaluating and monitoring how humans control their movement to optimize health.

Seeking an opportunity to contribute and grow as a Data Scientist in health.

RECENT PROJECTS

Classification of male and female walking strategies (University of Ottawa) Sep 2022 – Present

• Developing a k-means clustering model in Python to classify nuanced movement strategies from a large array of noisy optoelectronic and wearable sensor time series data
• The model output would be used as a feature to better explain an individual’s risk of falling
• Awarded $90,000 in federal funding from the Natural Sciences and Engineering Research Council of Canada (NSERC)

Prediction of walking stability using a smartwatch (University of Ottawa) Sep 2021 – Present

• Principal Investigator of a successful grant awarded by Apple Inc.
• Led a 6-member team in experimental design and in-lab data acquisition from 41 participants using 4 asynchronous motion capture systems
• Created programs in Matlab and in Python to synchronize, aggregate, explore, and clean terabytes of structured and semi-structured data containing hundreds of features
• Predicted walking stability to within 7% of gold standard by training regression models using support vector machines, extreme gradient boosting, and LSTM networks on features I engineered from an Apple Smartwatch using principal component analysis
• The smartwatch alternative to the gold standard ($100,000+ set of location-restrictive hardware) enables an inexpensive option to monitor walking stability anywhere and anytime

Simulation of movement variability from wearable sensors (University of Ottawa) Sep 2020 – Aug 2021

• Pioneered and validated the first simulation of trunk and lower limb movement variability in an open-source musculoskeletal model from 8 wearable sensors, using the OpenSim API in Matlab
• Optimized parameter weights to enhance simulation accuracy by 25% 
• The wearable sensor-based simulation measures 18 joint angles (outputs key to understanding movement strategies) to within 5° of gold standard at <1% of gold standard cost
• Awarded $90,000 in funding from the Children’s Hospital of Eastern Ontario Research institute

Characterization of movement variability in aging men and women (McGill University) Sep 2016 – Aug 2020

• Applied field knowledge and principal components analysis to engineer features from biological time series data (kinematics, electromyography, near-infrared spectroscopy, ultrasonography)
• Developed a Matlab program to automatically explore, clean, and process time series data across thousands of files acquired from aging populations, saving my team weeks of time
• Debugged and refined numerous Matlab programs for greater user-friendliness by incorporating file selection UIs, creating a batch processing option, and handling different data input formats
• Established the currently-used lab data visualization, poster, and presentation formats

University of Ottawa Ottawa, ON

Postdoctoral Fellowship, Human Kinetics Sep 2020 – Present

McGill University Montreal, QC

Doctor of Philosophy, Kinesiology Sciences Sep 2016 – Aug 2020

CGPA: 4.00/4.00; Relevant Coursework: Computational modelling, Advanced Biomechanics

Queen’s University Kingston, ON

Master of Science, Biomechanics Sep 2013 – Aug 2015

CGPA: 3.93/4.00; Relevant Coursework: Research Methods, Statistics, Signal Processing

Bachelor of Science (Honours), Kinesiology Sep 2009 – Apr 2013

CGPA: 3.89/4.00; Relevant Coursework: Research Methods, Introductory Statistics