Curriculum Vitae

Education & Scholarships

  • PhD (in progress), Biomedical Sciences, Université de Montréal (2025–2029)
    Thesis: Modeling the neurological sequelae of head impacts during contact sports

  • MSc, Neuroscience (Vision), University of Waterloo (2023)
    Thesis: Characterizing & modeling visual attention during motion tracking in high-performance athletes
    Awards: Lyle S. Hallman Graduate Research Scholarship, QEII-GSST

  • Honours BSc, Mathematics & Physics, University of Toronto (2021)
    Thesis: Gait distinction via hip-knee coordination: Applications of dynamical systems theory & computational topology

  • Diploma, Fitness & Health Promotion, Centennial College (2017)

Current Appointments

  • PhD Researcher — CIUSSS–NIM Research Center
    Concussion risk and severity modeling using HR, GPS, IMU, and MRI data

  • Data Analytics Coordinator — Gait & Mobility Network
    Clinical-grade gait analysis software and motor control metrics development

Selected Prior Experience

  • Lead Data Scientist / Sport Scientist — Sport Performance Analytics Inc. (2017–2025)
    Modeling athlete fatigue and tactical behavior; introduced flow field, hyper-network, and topological braid models to quantify team and player dynamics; collaborated with national federations

  • Graduate Researcher — University of Waterloo (2021–2024)
    Modeled functional connectivity and cognitive/motor performance using graph theory, information theory, and control systems; integrated eye-tracking & motion capture technologies

  • Research Assistant — University of Toronto (2018–2021)
    Gait event detection, data fusion, and mobile diagnostics in clinical biomechanics; modeling teaching discourse & 4D fMRI analysis in numerical cognition

Research Publications (selected)

  1. Zafar, A., Guay, S., et al. Game-aware prediction and interpretation of heart rate dynamics in contact sports using contextually tuned linear time-invariant models (2025, In-review: BMC Digital Health)
  2. Zafar, A., Martens, G., et al. Effects of head impact exposure on in-game heart rate dynamics in Canadian varsity football athletes (2025, In-review: JSAMS)
  3. Zafar, A., Guay, S., et al. Automated play event detection from sparse GPS American football data using recurrent neural networks (2025, Pre-print: Research Square)
  4. Yousefian, F., Zafar, A., et al. Peak Kinematic and Mechanical Demands According to Playing Positions in Professional Male Soccer (2025, Research Quarterly for Exercise and Sport)
  5. Zafar, A., Guay, S., et al. Heart Rate Dynamics and Quantifying Physical Fatigue in Canadian Football (2024, Applied Sciences)

(Full list available on Google Scholar)

Projects & Software (selected)

  • TRACE (in-development) — Python, multi-modal Time-Series Representation, Annotation, and Computation for Experiments: A modular framework for managing, annotating, and analyzing multimodal time series data in behavioral experiments.

  • TrakScribe (in-development) — Python, GPS Open-source toolkit for analyzing and annotating sport GPS data.

  • Athletic Barcodes & BreakAway Apps — Computer vision and performance analytics platforms
    Mobile/web apps for talent identification, coaching, and athlete monitoring.

Conference & Seminar Presentations (selected)

  • Characterizing eye movement patterns in 1v1 situations in elite futsal, World Congress on Science and Soccer (2022)
  • Characterizing team movement patterns in elite football, World Congress on Science and Soccer (2022)
  • Hyper-Networks for Team Selection in Professional Football, Canadian Undergraduate Mathematics Conference (2019)
  • Structuring Patterns in Team Movement Using Vector Fields, MathSport International (2019)

(Full list available on request)