Simon Ho
Quantitative Researcher
Survey design
A/B testing
User recruitment
Experimental design
Hypothesis testing
Data analysis
Data visualization
Machine learning

Computer vision, natural language processing

Eye tracking
Linear regression
Analysis of variance
Factor analysis
Measurement theory and psychometrics
Multivariate statistics
Structural equation modelling

Quantitative researcher with expertise in data analysis, statistics, and machine learning. Over 10 years of experience in planning and execution of data-driven projects; including the development of data collection and analytics pipelines, and clearly communicating insights to stakeholders.

User Researcher
Sprung Studios2021 - Present
  • Research partner for AAA PC, console, and mobile games.
  • Conducted surveys and A/B tests to extract usability insights from real-world users.
  • Worked in tandem with designers to apply iterative research to concepts.
  • Programmed internal tools (Python, C#) to collect, analyze, and visualize datasets.
  • Led client meetings to scope project requirements, develop research plans, and present reports.
  • Developed quantitative onboarding program for training new researchers.
Research Scientist (visiting)
Microsoft2019 - 2020
  • Designed and implemented algorithms for extracting novel spatial metrics from HoloLens 2 sensors.
  • Constructed data pipeline to collect, clean, and analyze hardware sensor data.
  • Performed exploratory analysis to evaluate the usability of new metrics in different production contexts.
  • Presented insights to the data science team regarding the value and potential pitfalls of implementing the spatial metrics in production.
Research Scientist
Attentional Neuroscience Lab2013 - 2020
  • Extensive training in statistics, which was applied to the analysis of over 16 published experiments.
  • Constructed data pipelines, from data collection, transformation/aggregation, to data analysis.
  • Developed algorithms to extract model features from raw multidimensional sensor data.
  • Created Python dashboards to aid cleaning of structured data. Reduced data cleaning time by 90%.
  • Programmed open-source data collection platform to collect experiment data across 9 projects, resulting in 50% faster project completion. Link: GitHub/cognitive-battery
  • Created open-source Python package to analyze time-series data. Link: GitHub/sensormotion
  • Modelled time-series data using multilevel regression and analysis of variance.
  • Published results in 7 peer-reviewed journals and gave presentations at 11 research conferences.
Data Analyst
UBC Centre for Teaching, Learning and Technology2016 - 2019
  • Employed experiments and quantitative methods to help instructors evaluate new teaching methods.
  • Analyzed A/B test involving 6000 online students to identify factors that affected engagement.
  • Conducted experiments to determine whether the benefits of a novel visualization technique outweighed the cost. Results saved over $2000 in future production cost.
  • Used statistical methods to streamline a multi-institution survey. Reduced total survey length by 28%.
Technical Projects

Webcam eye tracker

  • Developed a webcam-based eye tracker to predict real-time eye gaze location.
  • Programmed data collection pipeline to collect and transform 50k webcam images.
  • Built deep learning computer vision architecture, using PyTorch, to model webcam images.
  • Achieved a final eye tracking error of 1cm, rivalling more expensive infrared-based approaches.

Smartphone walking kinematics

  • Published novel method to measure outdoor walking kinematics using smartphone sensors.
  • Technical lead on cross-functional, collaborative research project with the University of Bristol.
  • Designed algorithms to compute walking metrics from 60 million data points.
  • Used multilevel regression to model the relationship between walking kinematics and cognitive function.
  • Method was faster and cheaper than traditional techniques, saving over $7000 in equipment cost.

Game character planner

  • Developed web character planner, used by 250,000 players, for a mobile game using JavaScript/React.
  • Incorporated insights from usability testing into the design of 3 new site features.
University of British Columbia2015 - 2020

Cognitive Science, minor in Quantitative Methods

University of British Columbia2013 - 2015

Cognitive Science

BA (Honours)
University of British Columbia2009 - 2013


Neural Networks and Deep Learning
Coursera (
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera (
Structuring Machine Learning Projects
Coursera (