Jun Huang

1. Research Focus

Explainable AI (XAI)
XAI for Computer Vision
Study: Interpretable Machine Learning
Knowledge gathering: XAI

2. Education

2023 (Summer) - Now, ECE, Ph.D. Candidate: '', '', ''.
2022 (Winter) - 2023 (Winter), ECE, MASc.: Concordia University, supervised by Dr. Yan Liu.
2021 (Fall), ECE, MEng: Concordia University, Montreal, Canada.
2015-2019, SE, BE : South-Central Minzu University (SCM), Wuhan, China.

3. Publications

3.1 Journal

Li, D., Liu, Y., & Huang, J. (2024). Assessment of Software Vulnerability Contributing Factors by Model-Agnostic Explainable AI. Machine Learning and Knowledge Extraction, 6(2), 1087-1113.
Li, D., Liu, Y., Huang, J., & Wang, Z. (2023). A Trustworthy View on Explainable Artificial Intelligence Method Evaluation. Computer, 56, 50-60.
Wang, Z., Liu, Y., & Huang, J. (2024). An Open API Architecture to Discover the Trustworthy Explanation of Cloud AI Services. IEEE Transactions on Cloud Computing, 12, 762-776.

3.2 Conference

Huang, J., & Liu, Y. (2024). Guided AbsoluteGrad : Magnitude of Gradients Matters to Explanation’s Localization and Saliency. Proceedings of the Canadian Conference on Artificial Intelligence. https://caiac.pubpub.org/pub/8rzaolsn
Neghawi, E., Wang, Z., Huang, J., & Liu, Y. (2023). Linking Team-level and Organization-level Governance in Machine Learning Operations through Explainable AI and Responsible AI Connector. 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC), 1223-1230.
Huang, J., Wang, Z., Li, D., & Liu, Y. (2022). The Analysis and Development of an XAI Process on Feature Contribution Explanation. 2022 IEEE International Conference on Big Data (Big Data), 5039-5048.

4. Public Talks

2022 IEEE International Conference on Big Data (Big Data): The Analysis and Development of an XAI Process on Feature Contribution Explanation
2023 Canadian AI Responsible AI Track: The Analysis and Development of an XAI Process on Feature Contribution Explanation.
2024 Canadian AI Main Conference: Guided AbsoluteGrad: Magnitude of Gradients Matters to Explanation's Localization and Saliency
2024 CASCON The 1st International Workshop on Observability and Explainability of AI Systems (OXAI'24): How do we efficiently integrate explainable AI (XAI) to help the deep learning of medical images?

5. Academic Services

5.1 Concordia

Teaching Assistant:

Summer, 2022, COEN244, PROGRAMMING METHODOLOGY II
Fall, 2022, COEN352, DATA STRUCTURES AND ALGORITHMS
Winter, 2023, COEN448, SOFTWARE TESTING AND VALIDATION
Winter, 2023, COEN6731, DISTRIBUTED SOFTWARE SYSTEMS
Summer, 2023, COEN448, SOFTWARE TESTING AND VALIDATION
Fall, 2023, COEN424, PROGRAMMING ON THE CLOUD
Fall, 2023, COEN448, SOFTWARE TESTING AND VALIDATION
Summer, 2024, COEN424, PROGRAMMING ON THE CLOUD
Fall, 2024, COEN6311, SOFTWARE ENGINEERING

5.2 SCMU Software Engineering Lab in Computer Science College

Member and Technical Leader of Java EE Group:

Sep. 2016 – Feb. 2019:
- Lead the technical and made progress together with team members;
- Hold the recruitment and assessment of new staff;
- Seek cooperation with other teams on competitions and projects;
- Participate in software and computer science competitions;