Max Jiang

About Me

I am Haoyan (Max) Jiang, a direct-entry Ph.D. student at the University of Toronto under the supervision of Professor Mark Chignell

Exploring Human Factors with Machine Learning solutions

Professional Experiences

• Support Researcher (ML & HCI)

  @Huawei Noah’s Arc Lab HCI

  08/2020 - 08/2021, 3/2022 - 3/2023

  • Research and develop state-of-the-art technology in human-computer interaction and machine learning, supervised by Sachi Mizobuchi

  • Optimized and designed ensembled novelty detection models to detect online driving distractions

  • Conducted HCI research in gesture recognition using deep learning on Android devices

  • Worked on driving workload prediction and designed in-car application sensible of driving context

• Research Internship (Cybersecurity)

  @Sun Life Canada

  07/2021 - 03/2022

  • Designed and implemented a visualization platform to monitor internal information filtration risks, which was compatible with anomaly detection and incorporated active learning architecture

  • Implemented features to provide real-time insights into potential risks and inform strategic decision-making

  • Collaborated with cross-functional teams to identify key risk indicators, designed and built a scalable and intuitive data integration pipeline

• Machine Learning Researcher (Health Care)

  @University of Toronto Interactive Media Lab

  03/2020 - 01/2021

  • Co-leading data science team to perform the Hamilton Depression Rating Scale (HDRS) data exploration on medical effects upon anti-depression medications.

  • Framingham data from NIH, risk factor analysis for dementia and heart failure; Manage a team of five developing data mining tools for medical data cleaning, preprocessing, and visualization on Flask and Dash.

  Working in multiple projects:

  • Interactive Med-Multi-task Learning Toik(iMD-MTL)
  • NIH heart failure data mining challenges
  • Antidepression Drug Efficiency Analysis Based on HAMD score
  • fMRI image prediction brain dementia
  • Braintagger Centivizer system
  • Long-Short Term Memory Model in Time Series

• Software Engineer & 3D Modeling

  @University of Toronto Interactive Media Lab

  05/2019 - 09/2019

  Driving Simulation Game for Elder People; Engine building, game logic and modeling of real-time driving experiences on web-serving applications using Babylon.js

  Building and importing 3D models for famous scenic views in the world using Blender

  Provide data insight with MongoDB, using learning algorism to analyze player’s brain functionality

Teaching Experiences

• Teaching Assistant

  @University of Toronto

  05/2021 - present

  Nominated for the MIE 2022-2023 Mechanical & Industrial Engineering Teaching Assistant Awards

  Designed teaching syllabus, prepared course materials, hold tutorials and Q&A sessions

  Teaching courses:

  • MIE1513 Decision Support System
  • STA302/STA1001 – Methods of Data Analysis I
  • APS 1070 - Foundations of Data Analytics and Machine Learning
  • MIE350 Design and Analysis of Information Systems
  • MIE 236 - Probability
  • CSC 236 - Introduction to Theory of Computation
  • CSC165 Mathematical Expression and Reasoning for Computer Science

Educations

• Ph.D. Student

  2020.09 - 2024.05

  • The University of Toronto, Mechanical & Industrial Engineering department
  • supervised by Prof.Chignell

• Honored B.Sc with high distinction

  2016.09 - 2020.10

  • cGPA: 3.74/4.0
  • The University of Toronto, double major in Computer Science and Statistics

Inventions/Patents

• Driving Cookies: Updating e-Commerce Models of Users Based on Attention to Roadside Objects and Displays

  • Haoyan Jiang, Mark Chignell
  • Patent pending

Publications

• Scenario Fidelity And Driver Mental Workload Assessment: Do You Get What You Pay For?

  2023.04

  • Haoyan Jiang, Mark Chignell, Sachi Mizobuchi
  • Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2023

• Lower Executive Function Ability in Older Drivers Creates Higher Perceived Mental Workload in Driving Scenarios

  2023.04

  • Haoyan Jiang, Mark Chignell, Sachi Mizobuchi
  • Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2023

• Discovering the Causal Structure of the Hamilton Rating Scale for Depression Using Causal Discovery

  2021.07

  • Lu Wang, Mark Chignell, Haoyan Jiang, Sachinthya Lokuge, Geneva Mason, Kathryn Fotinos, Martin Katzman
  • Accepted by 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI 2021)

• Demographic Effects on Mid-Air Gesture Preference for Control of Devices: Implications for Design

  2021.06

  • Haoyan Jiang, Mark Chignell, Sachi Mizobuchi, Farzin Farhadi Niaki, Zhe Liu, Wei Zhou, Wei Li
  • Accepted by International Ergonomics Association (IEA 2021)

• MD-MTL: An Ensemble Med-Multi-Task Learning Package for Disease Scores Prediction and Multi-Level Risk Factor Analysis

  2020.09

  • Lu Wang, Haoyan Jiang, Mark Chignell

• Cluster- Boosted Multi-Task Survival Analysis

  2020.08

  • Lu Wang, Mark Chignell, Haoyan Jiang, and Nipon Charoenkitkarn.
  • Accepted by the 20th IEEE International Conference on Bioinformatics and Bioengineering (BIBE 2020).

Awards

• Dean’s List Scholar

  2020.06

  • honor issuer: University of Toronto Faculty of Arts & Science
  • Outstanding group of Faculty of Arts & Science students who have a cumulative GPA of 3.50 or higher after having completed your tenth credit.

• Dean’s List

  2018.01

  • honor issuer: University of Toronto Applied Science and Engineering
  • Top student with high academic achievement in the Engineering department

• Dean’s List

  2017.01

  • honor issuer: University of Toronto Applied Science and Engineering
  • Top student with high academic achievement in the Engineering department

Skills

Python, R, JAVA, Latex, React.js, AWS, PySpark, Unreal Engine