• Name: Man Yeung Tai (Andy)
• Nationality: Canadian 🇨🇦, Hong Kong 🇭🇰
• Date and Place of Birth: 1994; Vancouver, Canada 🎂
• Languages:
  • English (Native) 🇬🇧
  • Cantonese (Fluent) 🀄
• Email: [email protected] 📧
• ORCID: https://orcid.org/0000-0001-5262-8615
• Dissertation: http://hdl.handle.net/2429/87759 📜

• Sep. 2019 – April 2024
  University of British Columbia (UBC), Vancouver, Canada

  • Master of Science in Neuroscience PhD program (Fast Track)
  • Supervisor: Dr. Reinhard Michael Krausz
  • Committee Members:
    • Dr. Alireza Kazemi
    • Dr. Raymond Ng
    • Dr. Christian Schuetz

• 2012 – 2017
  University of Toronto, Toronto, Canada

  • Honors Bachelor’s in Science (BSc)
  • Major: Neuroscience
  • Minors: Environmental Science 🌱, Religion 🕊️

• 2008 – 2012
  West Point Grey Academy, Vancouver, Canada

  • High School Diploma 🎒

• July 2024 – Present
  Postdoctoral Teaching and Learning Fellow
  Master of Data Science Program, Department of Statistics, UBC

  • Teaching data science courses 📊

• April 2024 – Present
  NAI Innovations, Vancouver, BC, Canada — Analyst

  • Evaluating ML-driven startups in medical cannabis symptom management 🌿
  • Leading strategic AI initiatives aligned with neuroscience and psychiatry 💡

• April 2024 – September 2024
  Concussion RX, Vancouver, BC, Canada — Data Scientist

  • Enhancing diagnosis and treatment using advanced AI tools 🤖
  • Analyzing and stratifying concussion subtypes based on demographic data 📈

Full Publication List

• July 2024
  A machine learning approach to predicting overdose risk.
  Submitted, First Author, Journal of Health Management.

• July 2024
  Utilizing machine learning for early intervention and risk management in the opioid overdose crisis.
  Submitted, under review.
  First Author, WIREs Computational Statistics.

• June 2024
  Clinical decision support systems in addictions and concurrent disorders.
  Accepted, First Author, Journal of Evaluation in Clinical Practice.

• 2021/2022
  UBC Master of Data Science (MDS) Teacher’s Assistant (TA) Award

  • For outstanding work in DSCI 524, 531, 532, and more 🎉

• 2021–2023
  President's Academic Excellence Initiative PhD Award

  • Recognizing significant contributions to UBC research 🧠

• June 4th, 2021
  2021 Research Day Lightning Talk & ePoster People’s Choice Award

  • Clinical Research Poster: "The Application of Machine Learning to Understand Overdose Risk" ⚡

• June 9-10, 2023
  1st Canadian Academy of Addiction Psychiatry (CAAP) Conference

  • Event Coordinator/Participant 🎟️

• March 9, 2023
  3rd Annual BC Concurrent Disorders Conference (Hosted by BCMHSUS)

  • Lightning Talk: "Machine Learning: A Predictive Model for Overdose" ⚙️

My research leverages interdisciplinary fields like artificial intelligence, data science, and psychiatry to address the opioid crisis in Vancouver, BC. Using machine learning techniques, I model overdose risks and develop clinical decision support systems for personalized care. My work contributes to healthcare by predicting comorbid outcomes like mental health disorders and suicide, enabling early interventions and improved outcomes.