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Weishi Shi

Assistant Professor

University of North Texas

Department of Computer Science and Engineering

Email: Weishi.Shi@unt.edu

Education

  • PhD, Rochester Institute of Technology, 2022
    Major: Computing and Information Sciences
  • MS, Rochester Institute of Technology, 2016
    Major: Information Sciences and Technologies

Teaching

Teaching Experience

    University of North Texas

  • CSCE 5210 - Fundamentals of Artificial Intelligence, 3 courses.
  • CSCE 5215 - Machine Learning, 2 courses.
  • CSCE 5934 - Directed Study, 2 courses.
  • CSCE 6940 - Individual Research, 5 courses.

Directed Student Learning

  • Doctoral Advisory Committee Member, Computer Science and Engineering. (September 22, 2023).
  • Doctoral Advisory Committee Chair, Computer Science and Engineering. (August 21, 2023).
  • Doctoral Advisory Committee Member, Computer Science and Engineering. (July 12, 2023).
  • Doctoral Advisory Committee Member, "PhD candidate qualification exam.," Computer Science and Engineering. (October 13, 2022 - November 30, 2022).

Research

Published Intellectual Contributions

    Conference Proceeding

  • Forhad, A., Shi, W. Enhancing Annotation Quality through Active Re-labeling Strategies in Deep Active Learning. International Jounral on Artificial Intelligence Tools (IJAIT). International Joint Conferences on Artificial Intelligence(Name of the conference).
  • Rafiq, R., Shi, W., Albert, M.V. Wearable Sensor-Based Few-Shot Continual Learning on Hand Gestures for Motor-Impaired Individuals via Latent Embedding Exploitation. International Jounral on Artificial Intelligence Tools (IJAIT). International Joint Conferences on Artificial Intelligence (Name of the conference).
  • Yu, D., Shi, W., Qi, Y. Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning. Machine Learning: Science and Technology. International Conference on Machine Learning (name of the conference, did not shown in drop down menu).
  • Shi, W., Yu, D., Yu, Q. Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice. International Conference on Neural Information Processing. Conference on Neural Information Processing Systems(Conference name, does not shown in drop downs.).
  • Zhu, Y., Shi, W., Bao, W., Yu, Q. Prompt is All You Need: Towards Open World Learning. International Conference on Computer Vision (ICCV). IEEE.
  • Shi, W., Yu, D., Shi, Q. STARS: Spatial-Temporal Active Re-Sampling for Label-Efficient Learning from Noisy Annotations. AI Magazine. United States AAAI Press.

    • Journal Article

  • Shi, W., MOSES, H., Yu, Q., MALACHOWSKY, S., KRUTZ, D. ALL: Supporting Experiential Accessibility Education and Inclusive Software Development. IEEE Transactions on Software Engineering. Association for Computing Machinery.

Presentations Given

    Panel Presentation

  • Pears, R.L. (Panelist), Murali, B. (Panelist), Shi, W. (Panelist), Research Seminar for UNT Graduate Students, How does ChatGPT impact Computer Science Education?, UNT Department of Computer Science and Engineering, K150, United States of America. (2023 - 2023).

Service

University Service

  • Committee Member, CSE PhD Admissions Committee. (October 1, 2022 - September 1, 2024).
  • Committee Member, CSE Tenure Track Hiring Committee. (October 1, 2022 - September 1, 2024).

Professional Service

  • Reviewer, Conference Paper, AAAI. (January 1, 2022 - Present).
  • Reviewer, Conference Paper, Artificial Intelligence and Statistics Conference. (January 1, 2022 - Present).
  • Reviewer, Conference Paper, Conference on Computer Vision and Pattern Recognition. (January 1, 2022 - Present).
  • Reviewer, Conference Paper, International Conference on Service-Oriented Computing. (January 1, 2022 - Present).
  • Reviewer, Conference Paper, International Conference on Learning Representations. (January 1, 2021 - Present).