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Last Update on Nov 22th 2024.

Basics

Name Tim (Tiange) Zhou
Email tim dot tiange dot zhou at gmail dot com
Phone (778) 683-7511
Website https://timothyzg.github.io/
Research interest Uncertainty Quantification, Robust Transfer Learning, Computer Vision, Human-AI Intertaction

Work

  • 2024.09 - 2024.12

    Vancouver, BC, Canada

    Teaching Assistant, CPSC 320: Intermediate Algorithm Design and Analysis
    Computer Science Department, University of British Columbia
    I lead three weekly tutorial sessions for over two hundred students, where I explain lecture concepts in detail, present challenging problem examples, facilitate student discussions, and work through problem solutions and proofs in detail.
    • Greedy Algorithm
    • Dynamic Programming
    • P vs. NP
  • 2024.05 - 2024.08

    Vancouver, BC, Canada

    Undergrad Researcher (full-time paid), Machine Learning
    Statistics Department, University of British Columbia
    I lead the Deep Duo Project, focusing uncertainty quantification and robustness methods for deep learning.
    • Computer Vision
    • Tansfer Learning
    • Uncertainty Quantification
  • 2023.09 - 2024.08

    Vancouver, BC, Canada

    Research Assistant, Robotics & HCI
    Computer Science Department, University of British Columbia
    I lead software development in the happraisal project, developing multithreaded tetherless software for real-time robotics control and data gathering, demoed at Eurohaptics 2024, manuscript in construction.
    • Human Computer Interaction
    • Robotics Software
    • Human Experiment Design
  • 2022.09 - 2023.04

    Calgary, AB, Canada

    Data Scientist Co-op
    Innovation and Technology Lab, Enbridge Inc.
    I implemented unsupervised models for real-time energy consumption outlier detection and trained transfer-learned convolutional neural networks to identify undesirable objects in aerial imagery of energy pipelines.
    • Computer Vision
    • Unsupervised Learning
    • Applied ML

Volunteer

  • 2024.09 - 2025.04

    Vancouver, BC, Canada

    Senior Student Mentor
    Science Undergraduate Sociaty || UBC
    Provide mentees with support on degree planning, Co-op search, and study advice.
  • 2024.09 - 2025.04

    Vancouver, BC, Canada

    Senior Student Mentor (undergrad research focus)
    Women in Computer Science || UBC
    I guide mentees through undergrad research opportunities, and support them in reaching out to potential research labs.
  • 2024.09 - 2025.04

    Vancouver, BC, Canada

    Course Developer: Computer Vision
    GIRLsmarts4Tech || UBC
    My team developed an intro workshop for the grade 6-9 girls in Greater Vancouver Area, we're in the refinement & finalization phase and the workshop is expected to be taught in Spring 2025 on UBC Campus:)
  • 2023.09 - 2024.04

    Vancouver, BC, Canada

    Student Mentor
    Computer Science Tri-Mentoring || UBC
    Provide mentees with support on degree planning, Co-op search, resume refinement, and networking.

Education

  • 2020.09 - 2025.04

    Vancouver, BC, Canada

    Bachelor of Science
    University of British Columbia || UBC
    Combined Honours, Computer Science and Statistics

Awards

Languages

Mandarin
Native speaker
English
Fluent; 160/160 Duolingo English Test; CEFR C2 Proficiency

Interests

Machine Learning
Deep Learning
Computer Vision
Uncertainty Quantification
Machine Learning for Ecology
HCI
Human-AI Interaction
Human-Robot Interaction
Uncertainty grounded Decision Making

References

Dr. Geoff Pleiss
Research Supervisor
Dr. Karon Maclean
Research Supervisor
Dr. Anne Condon
TA Supervisor

Projects

  • 2024.05 - ongoing
    Deep Duo
    Deep Duo is a method developed to yield meaningful uncertainty measure through disagreement betwee a larger neural network and a smaller neural network. It builds on the success of Deep Ensemble's strengths in providing calibrated uncertainty measure, take advantage from the growing capabilities and transferabilities of foundation models.
    • Uncertainty Quantification
    • Ensemble Method
    • Deep Learning
  • 2023.09 - 2024.08
    Happraisal
    Building on established links between touch, emotion and cognition, this project aims to understand the impact of a person’s haptic interaction with an animate, affective, zoomorphic robot on their cognitive reappraisal success.
    • Real-time System Design
    • Human-Robot Interaction