Faculty Profile

Ting Xiao

Title
Assistant Professor
Department
Information Science
College
College of Information

    

Current Scheduled Teaching*

INFO 5502.002, Principles and Techniques for Data Science, Fall 2021
INFO 6900.710, Special Problems, Fall 2021

* Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Previous Scheduled Teaching*

CSCE 5300.001, Introduction to Big Data and Data Science, Summer 8W1 2021
CSCE 5300.002, Introduction to Big Data and Data Science, Summer 8W1 2021
CSCE 5300.002, Introduction to Big Data and Data Science, Spring 2021 SPOT
CSCE 5300.002, Introduction to Big Data and Data Science, Spring 8W2 2021
CSCE 5214.001, Software Development for Artificial Intelligence, Spring 2021 SPOT
CSCE 5214.004, Software Development for Artificial Intelligence, Spring 2021 SPOT
CSCE 5214.008, Software Development for Artificial Intelligence, Spring 2021
CSCE 4930.002, Topics in Computer Science and Engineering, Spring 2021 Syllabus SPOT
CSCE 4890.711, Directed Study, Summer 10W 2020
CSCE 5300.080, Introduction to Big Data and Data Science, Summer 8W1 2020 SPOT
CSCE 6940.711, Individual Research, Spring 2020
CSCE 5300.002, Introduction to Big Data and Data Science, Spring 2020
CSCE 4930.002, Topics in Computer Science and Engineering, Spring 2020 Syllabus
CSCE 5200.001, Information Retrieval and Web Search, Fall 2019 SPOT
CSCE 5200.600, Information Retrieval and Web Search, Fall 2019 SPOT
CSCE 4200.001, Web Search and Information Retrieval, Fall 2019 Syllabus SPOT

* Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Published Publications

Published Intellectual Contributions

Conference Proceeding
Xiao, T., Tabashum, T., Olness, G., Mahbub, I., Berman, D., Tasneem, N., Albert, M. (2020). Mobile Diarization Dashboard Application and Remote Vocalization Sensor Prototype for Evaluating Communication Rehabilitation Effectiveness. 2020 American Congress of Rehabilitation Medicine Conference.
Xiao, T., Tabashum, T., Jebamalaidass, R., Du, A., Leal, M., Oliviera, E., Metwally, B., Albert, M. V. (2020). “Conversation Moderator: A mobile app for tracking individual speaking in group conversations”, 14th IEEE International Conference on Semantic Computing (ICSC 2020), San Diego, Feb 3-5, 2020..
Journal Article
Behpour, S., Mohammadi, M., Albert, M. V., Alam, Z. S., Wang, L., Xiao, T. (2021). Automatic trend detection: Time-biased document clustering. Knowledge-Based Systems. 220(106907), 13. Denton: Elsevier. https://doi.org/10.1016/j.knosys.2021.106907
Zelman, S., Dow, M., Tabashum, T., Xiao, T., Albert, M. V. (2020). Accelerometer-based automated counting of ten exercises without exercise-specific training or tuning. Journal of Healthcare Engineering, vol. 2020, Article ID 8869134, 6 pages, 2020. https://doi.org/10.1155/2020/8869134.
Sok, P., Xiao, T., Azeze, Y., Jayaraman, A., Albert, M. (2018). Activity Recognition for Incomplete Spinal Cord Injury Subjects using Hidden Markov Models. IEEE Sensors 18(15), 6369-6374..

Awarded Grants

Contracts, Grants and Sponsored Research

Grant - Teaching
Xiao, T. (Principal), "Google Cloud Education Grant," Sponsored by Google, University of North Texas, $20000 Funded. (January 12, 2020January 11, 2022).
,
Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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