My Personal Website

- 😄 I'm currently currently a Tenure-Track Assistant Professor in the Faculty of Business and IT at Ontario Tech University, and an Adjunct Research Professor at Western University.
- 👯 I'm included in Stanford University/Elsevier's List of the World's Top 2% Scientists for 2024 and 2025. I am ranked among the world's Top 0.3% of researchers in 'Networking & Telecommunications' in 2025, and 27th in Canada.
- 🌱 I completed my Ph.D. degree in Software Engineering - Electrical and Computer Engineering at Western University, Canada, in Aug 2022, as a Top-3 graduate student with excellent research.
- 👯 I've been working on automated machine learning algorithms (e.g., machine learning, deep learning, optimization, online learning, and concept drift adaptation methods) to solve various data analytics problems, such as network security, intrusion detection, anomaly detection, IoT data stream analytics, network traffic data analytics, time-series analytics, etc.
- 👯 I've also been working on the tutorials on applying automated and optimized machine learning algorithms to general data analytics tasks.
- 👯 I've also an Associate Editor of IEEE Transactions on Industrial Informatics (TII) and IEEE Transactions on Network and Service Management (TNSM).
- 🌱 My paper and code publications have received more than5,000Google Scholarcitations and3,000 GitHub stars (including my contributions to the organization accounts "Western OC2 Lab" and "ANTS OntarioTechU").

Please feel free to contact me for any questions or cooperation opportunities. I'd be happy to help.

• Email:liyanghart@gmail.com
• GitHub:LiYangHart
• LinkedIn:Li Yang
• Google Scholar:Li Yang
• Researchgate:Li Yang
• Personal Website:Li Yang

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1. Hyperparameter-Optimization-of-Machine-Learning-AlgorithmsHyperparameter-Optimization-of-Machine-Learning-AlgorithmsPublic

   Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

   Jupyter Notebook 1.3k 302

2. Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-AnalyticsWestern-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-AnalyticsPublic

   Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

   Jupyter Notebook 629 113

3. Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-LearningWestern-OC2-Lab/Intrusion-Detection-System-Using-Machine-LearningPublic

   Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

   Jupyter Notebook 546 149

4. Western-OC2-Lab/Intrusion-Detection-System-Using-CNN-and-Transfer-LearningWestern-OC2-Lab/Intrusion-Detection-System-Using-CNN-and-Transfer-LearningPublic

   Code for intrusion detection system (IDS) development using CNN models and transfer learning

   Jupyter Notebook 196 43

5. Western-OC2-Lab/PWPAE-Concept-Drift-Detection-and-AdaptationWestern-OC2-Lab/PWPAE-Concept-Drift-Detection-and-AdaptationPublic

   Data stream analytics: Implement online learning methods to address concept drift and model drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework …

   Jupyter Notebook 217 45

6. Western-OC2-Lab/MSANA-Online-Data-Stream-Analytics-And-Concept-Drift-AdaptationWestern-OC2-Lab/MSANA-Online-Data-Stream-Analytics-And-Concept-Drift-AdaptationPublic

   Data stream analytics: Implement online learning methods to address concept drift and model drift in dynamic data streams. Code for the paper entitled "A Multi-Stage Automated Online Network Data S…

   Jupyter Notebook 34 8