Wade Genders

Machine Learning Engineer at Flow Labs

Hamilton, Ontario, Canada
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Summary

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Senior
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Top School
Wade Genders is a Machine Learning Engineer with eight years of experience specializing in deep reinforcement learning, traffic microsimulation, and computer vision, currently applying those skills at Flow Labs. He holds a PhD from McMaster University where his thesis developed AI-driven adaptive traffic signal control, and has translated research into real-world impact—most notably field-testing AI signal control that yielded multimillion-dollar annualized savings. Comfortable moving models from lab to deployment, he has built and tested production traffic-control software with transportation agencies and led ITS research teams at the University of Toronto. Wade combines a strong mathematical and machine-learning foundation with interests in philosophy, and maintains an academic presence on Google Scholar reflecting his ongoing research-oriented approach.
code8 years of coding experience
job3 years of employment as a software developer
bookDoctor of Philosophy (Ph.D.), Civil Engineering, Doctor of Philosophy (Ph.D.), Civil Engineering at McMaster University
languagesEnglish, Chinese
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Stackoverflow

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Github Skills (7)

pressure9
sumo8
traffic8
dqn6
signal6
ddpg6
reinforcement-learning1

Programming languages (1)

Python

Github contributions (5)

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docwza/deep-rl-tsc

Jan 2019 - Mar 2019

Contributions:19 commits in 1 month
docwza/sumolights

Aug 2019 - Oct 2019

SUMO adaptive traffic signal control - DQN, DDPG, Webster's, Max-pressure, Self-Organizing Traffic Lights
Contributions:14 commits in 1 month
signalddpgadaptivelightspressure
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Wade Genders - Machine Learning Engineer at Flow Labs