Wade Genders
Machine Learning Engineer at Flow Labs
Hamilton, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolWade 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.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Civil Engineering, Doctor of Philosophy (Ph.D.), Civil Engineering at McMaster University
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
ddpg7
dqn7
algorithm5
deep-reinforcement-learning4
python4
reinforcement-learning2
openai-gym2
tensorflow1
Programming languages (1)
Github contributions (5)
docwza/deep-rl-tsc
Jan 2019 - Mar 2019
Distributed Deep Reinforcement Learning Traffic Signal Control
Contributions:19 commits in 1 month
deep-reinforcement-learning
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
ddpgdqn
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