Li Yang
Associate Editor, IEEE Transactions On Network And Service Management (TNSM)
Oshawa, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolLi Yang is a tenure-track Assistant Professor at Ontario Tech University and an active AI and networking researcher blending machine learning, AutoML, and cybersecurity for 5G/6G and IoT systems. With a PhD from Western University, a postdoctoral stint in OC2 Lab, and over 15 first-author publications, his work focuses on time-series analytics, concept drift, adversarial ML, and model optimization with practical network traffic applications. He serves as an associate editor for IEEE TNSM and TII and maintains strong industry-facing impact—over 2,000 citations and 2,500+ GitHub stars—reflecting both academic rigor and widely used open-source contributions. A multi-award recipient for research excellence, he also mentors graduate students and retains ties to Western as an adjunct, signaling a collaborative academic network across Canada and beyond.
9 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Electrical and Computer Engineering - Software Engineering, 4.0/4.0 (92.5/100), 11 first-author publications, 1,000+ citations, Doctor of Philosophy - PhD, Electrical and Computer Engineering - Software Engineering, 4.0/4.0 (92.5/100), 11 first-author publications, 1,000+ citations at Western UniversityMaster of Applied Science - MASc, Engineering - Engineering Systems and Computing, 3.7/4.0, one journal paper publication, Master of Applied Science - MASc, Engineering - Engineering Systems and Computing, 3.7/4.0, one journal paper publication at University of Guelph
English, Chinese
Github Skills (85)
data-stream10
xgboost10
anomaly-detection10
python10
svm10
feature-engineering10
hyperparameter-optimization10
deep-learning10
automl10
random-forest10
optimization10
genetic-algorithm10
convolutional-neural-networks10
tuning-parameters10
machine-learning-algorithms10
Programming languages (3)
Github contributions (5)
Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning
May 2021 - Jan 2023
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
Contributions:49 commits, 2 PRs, 33 pushes in 1 year 7 months
bayesiandecision-treeintrusion-detectionkmeansmachine-learning
Western-OC2-Lab/Intrusion-Detection-System-Using-CNN-and-Transfer-Learning
Jan 2022 - Oct 2022
Code for intrusion detection system (IDS) development using CNN models and transfer learning
Contributions:33 commits, 17 pushes, 1 comment in 8 months
cnn-modelintrusion-detectiontransfer-learningmachine-learningdeep-learning
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