I am a senior AI researcher. I have 50+ publications, including papers and patents. I did my Ph.D. in Computer Science at University of Ottawa under Professor Stan Matwin. I was co-advised by Professor Nathalie Japkowicz. My research interests include machine learning and applications of AI, as well as other use cases.
I have completed 80+ of AI projects, including LLM, Large AI platform, Anomaly detection, Generative AI, Series Forecasting, Data-driven credit scoring model, Deep Neural Network Interpretability, Multiple Instance Learning, Imbalanced Learning, AI In Healthcare and so on.

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For a complete list, see Google Scholar.

• Training method, credit estimation method and the device of credit evaluation model. Patent number : CN107301577A
• Model training method, sample balancing method, model training device, sample balancing device and personal credit scoring system Patent number : CN106909981B
• Model data updating method, device and system Patent number : CN107229966B
• Model training method, apparatus and system and sample set optimization method, device Patent number : CN106934413A
• A kind of Risk Forecast Method and equipment Patent number : CN106779272A
• Method and device for determining user intention based on user voice information Patent number : CN108205525B
• The method and device that the belonging kinds of data are predicted Patent number : CN107203774A
• The sorting technique and system of data Patent number : CN106934410A
• A kind of method and device for optimizing user credit model modeling process Patent number : CN106997484A
• A kind of Feature Selection method and device Patent number : CN107169571A
• Feature engineering strategy determination method and device Patent number : CN107168965B
• User characteristics sorting technique, user credit appraisal procedure and the device of user credit model Patent number : CN106997472A
• A kind of method and device for screening user characteristics Patent number : CN106874286A
• A kind of information extracting method and device Patent number : CN107133207A
• User group classification method and device Patent number : CN106897282B
• User credit model establishing method and device Patent number : CN107203916B
• object grouping method, model training method and device Patent number : CN106874925A
• Intelligent operation and maintenance system based on data middling platform technology Patent number : CN112182077B
• Intelligent operation and maintenance framework system based on AIOps Patent number : CN112181960B
• Three-dimensional microscopic road network generation method capable of realizing real-time interaction Patent number : CN111535099B
• Method and system for adaptively calculating IT intelligent operation and maintenance health index Patent number : CN113360358A
• Fault root cause positioning method and system based on multidimensional data map Patent number : CN113360722A
• Semi-supervised man-machine combined operation and maintenance fault library generation method and system Patent number : CN112783865A
• Disk capacity prediction method for identifying manual cleaning behavior based on second-order difference method Patent number : CN113157204B

1)Presentations(part):

(1) “AIOps – Using Data Analytics, Machine Learning, and AI in IT Operations”, WAIC2022, Shanghai, China.

(2) “Empowering Generative AI with Alibaba Cloud PAI’s Advanced Features”, WAIC2019, Shanghai, China.

(3) “Automatic Target Recognition using multiple-aspect sonar images”, IEEE Congress on Evolutionary Computation 2014, Beijing, China.

(4) “Vessel track correlation and association using fuzzy logic and Echo State Networks”, IEEE Congress on Evolutionary Computation 2014, Beijing, China.

(5) “Explicit feature mapping via multi-layer perceptron and its application to Mine-Like Objects detection”, IJCNN 2014, Beijing, China.

(6) “Cost-Sensitive Boosting Algorithms for Imbalanced Multi-instance Datasets”, 2013 Canadian Conference on Artificial Intelligence, Regina, Saskatchewan, Canada.

(7) “Ensemble of Multiple Kernel SVM Classifiers”, Canadian Conference on AI 2014, Montreal, Quebec, Canada.

(8) “Resampling and Cost-Sensitive Methods for Imbalanced Multi-instance Learning”, 2013 IEEE International Conference on Data Mining (ICDM), Dallas, Texas, USA.

(9) “Machine learning algorithm for Autonomous Underwater Vehicles operations”, 2012 University of Ottawa Research Day, Ottawa, Ontario, Canada

(10) “Boosting Support Vector Machines for Imbalanced Data Sets”, 2008 Tamale seminar in University of Ottawa, Ottawa, Ontario, Canada

(11) “Resampling and Cost-Sensitive Methods for Imbalanced Multi-instance Learning”, 2013 Tamale seminar in University of Ottawa, Ottawa, Ontario, Canada

(12) “Cost-Sensitive Boosting Algorithms for Imbalanced Multi-instance Datasets. In Advances in Artificial Intelligence”, 2013 Tamale seminar in University of Ottawa, Ottawa, Ontario, Canada

• 2008 ISMIS best paper award

Personal Teaching Philosophy

My teaching philosophy is grounded in the belief that effective education empowers students to become independent, critical thinkers and problem-solvers. I strive to create an inclusive and engaging learning environment that encourages active participation, fosters curiosity, and supports diverse learning styles. My goal is to provide students with a solid foundation in theoretical concepts and practical skills, preparing them for successful careers in the ever-evolving field of computer science.

Teaching Experience

1. Adjunct Lecturer

Zhejiang University of Technology

• CSI 536: Introduction to Artificial Intelligence (Fall 2018, Fall 2019)
  • Developed and delivered lectures covering fundamental AI concepts, algorithms, and applications.
  • Designed course materials, including assignments, quizzes, and exams, to assess student understanding and progress.
  • Utilized various teaching methods such as interactive discussions, hands-on projects, and real-world case studies to enhance learning.

Dalhousie University

• CSCI 4144: Introduction to Data Mining and Data Warehousing (Winter 2015)
  • Taught core concepts of data mining and warehousing, including data preprocessing, classification, clustering, and association analysis.
  • Created and graded assessments to evaluate student comprehension and practical application of the material.
  • Provided guidance on term projects, fostering research and analytical skills.

2. Lab Lecturer

Dalhousie University

• CSCI 2110: Data Structures and Algorithms (Fall 2014)
  • Conducted laboratory sessions to reinforce lecture material through hands-on coding exercises and algorithm analysis.
  • Assisted students in implementing data structures and solving algorithmic problems using various programming languages.

University of Ottawa

• SEG 3101: Software Requirements Analysis (Fall 2004)
  • Led lab sessions focusing on the elicitation, analysis, and documentation of software requirements.
  • Guided students through practical exercises and case studies to apply theoretical knowledge.
• CSI 2372: Advanced Programming Concepts With C++ (Fall 2011)
  • Supervised lab activities that emphasized advanced programming techniques and object-oriented design in C++.
  • Helped students debug and optimize their code, fostering a deeper understanding of programming paradigms.
• ELG 5255: Applied Machine Learning (Fall 2013)
  • Facilitated labs on machine learning algorithms and their applications in various domains.
  • Supported students in implementing machine learning models and interpreting results.

3. Teaching Assistant

University of Ottawa

• CSI 2132: Databases I (Winter 2004)
  • Assisted with lectures, graded assignments, and provided support during office hours.
  • Helped students grasp fundamental database concepts and SQL programming.
• CSI 3105: Design and Analysis of Algorithms I (Winter 2011)
  • Supported the instructor in delivering lectures and tutorials on algorithm design and complexity analysis.
  • Evaluated student performance through assignments and exams.
• SEG 3101: Software Requirements Analysis (Fall 2012)
  • Assisted in teaching requirements analysis techniques and tools.
  • Provided feedback on student projects and assignments.
• CSI 3120: Programming Language Concepts (Winter 2012)
  • Helped deliver course content on the principles and paradigms of programming languages.
  • Assisted students with programming assignments and conceptual understanding.
• CSI 2372: Advanced Programming Concepts With C++ (Winter 2013)
  • Supported the course instructor in teaching advanced C++ programming.
  • Provided assistance during lab sessions and evaluated student assignments.

Teaching Strategies and Methods

• Interactive Lectures: Encourage active participation through questions, discussions, and collaborative problem-solving activities.
• Hands-On Projects: Integrate practical assignments and projects that require students to apply theoretical knowledge to real-world problems.
• Continuous Assessment: Utilize quizzes, assignments, and exams to regularly assess student progress and provide timely feedback.
• Inclusive Environment: Foster an inclusive classroom atmosphere that respects diverse perspectives and learning styles.
• Technology Integration: Leverage online tools and resources to enhance learning and engagement, including virtual labs, coding platforms, and discussion forums.