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Zeenat Tariq

Title: Clinical Assistant Professor

Department: Computer Science and Engineering

College: College of Engineering

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, University of Missouri Kansas City, 2021
    Major: Computer Science
    Specialization: Data Science, Machine learning
    Dissertation: Design of Multi-Modality Deep Fusion Architecture for Deep Acoustic Analytics
  • MS, National University of Sciences and Technology, 2015
    Major: Computational Science and Engineering
    Specialization: Computer communication systems
    Dissertation: Energy Efficient Load Balancing in Computational Grid

Current Scheduled Teaching

CSCE 5934.827Directed StudyFall 2024
CSCE 5300.001Introduction to Big Data and Data ScienceFall 2024
CSCE 5300.007Introduction to Big Data and Data ScienceFall 2024
CSCE 5215.004Machine LearningFall 2024
CSCE 5290.002Natural Language ProcessingFall 2024
CSCE 5290.003Natural Language ProcessingFall 2024
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 5320.001Scientific Data VisualizationSummer 10W 2024 SPOT
CSCE 5300.006Introduction to Big Data and Data ScienceSpring 2024 SPOT
CSCE 4290.400Introduction to Natural Language ProcessingSpring 2024 Syllabus SPOT
CSCE 5290.400Natural Language ProcessingSpring 2024 SPOT
CSCE 5320.005Scientific Data VisualizationSpring 2024 SPOT
CSCE 5934.827Directed StudyFall 2023
CSCE 5300.001Introduction to Big Data and Data ScienceFall 2023 SPOT
CSCE 4205.001Introduction to Machine LearningFall 2023 Syllabus SPOT
CSCE 5215.001Machine LearningFall 2023 SPOT
CSCE 5215.600Machine LearningFall 2023 SPOT
CSCE 5290.002Natural Language ProcessingFall 2023 SPOT
CSCE 5290.003Natural Language ProcessingFall 2023 SPOT
CSCE 5215.004Machine LearningSummer 10W 2023 SPOT
CSCE 5215.005Machine LearningSummer 10W 2023 SPOT
CSCE 5320.001Scientific Data VisualizationSummer 10W 2023 SPOT
CSCE 5300.006Introduction to Big Data and Data ScienceSpring 2023 SPOT
CSCE 5300.008Introduction to Big Data and Data ScienceSpring 2023 SPOT
CSCE 5290.003Natural Language ProcessingSpring 2023 SPOT
CSCE 5320.005Scientific Data VisualizationSpring 2023 SPOT
CSCE 5934.827Directed StudyFall 2022
CSCE 5300.002Introduction to Big Data and Data ScienceFall 2022 SPOT
CSCE 5290.002Natural Language ProcessingFall 2022 SPOT
CSCE 5290.003Natural Language ProcessingFall 2022 SPOT
CSCE 5934.845Directed StudySummer 10W 2022
CSCE 5300.002Introduction to Big Data and Data ScienceSummer 10W 2022 SPOT
CSCE 5300.003Introduction to Big Data and Data ScienceSummer 10W 2022 SPOT
CSCE 5320.001Scientific Data VisualizationSummer 8W2 2022 SPOT
CSCE 5300.003Introduction to Big Data and Data ScienceSpring 2022 SPOT
CSCE 5300.006Introduction to Big Data and Data ScienceSpring 2022 SPOT
CSCE 4600.001Introduction to Operating SystemsSpring 2022 Syllabus SPOT
CSCE 4600.002Introduction to Operating SystemsSpring 2022 Syllabus SPOT
CSCE 4600.201Introduction to Operating SystemsSpring 2022 SPOT
CSCE 4600.202Introduction to Operating SystemsSpring 2022 SPOT
CSCE 4600.203Introduction to Operating SystemsSpring 2022 SPOT
CSCE 4600.204Introduction to Operating SystemsSpring 2022 SPOT
CSCE 4600.205Introduction to Operating SystemsSpring 2022 SPOT
CSCE 4600.206Introduction to Operating SystemsSpring 2022 SPOT
CSCE 5320.001Scientific Data VisualizationSpring 2022 SPOT
CSCE 2100.002Foundations of ComputingFall 2021 Syllabus SPOT
CSCE 2100.003Foundations of ComputingFall 2021 Syllabus SPOT
CSCE 2100.004Foundations of ComputingFall 2021 Syllabus SPOT
CSCE 2100.202Foundations of ComputingFall 2021 SPOT
CSCE 2100.203Foundations of ComputingFall 2021 SPOT
CSCE 2100.204Foundations of ComputingFall 2021 SPOT
CSCE 2100.206Foundations of ComputingFall 2021 SPOT
CSCE 2100.207Foundations of ComputingFall 2021 SPOT
CSCE 2100.208Foundations of ComputingFall 2021 SPOT
CSCE 2100.211Foundations of ComputingFall 2021 SPOT
CSCE 2100.212Foundations of ComputingFall 2021
CSCE 2100.213Foundations of ComputingFall 2021 SPOT
CSCE 5290.002Natural Language ProcessingFall 2021 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 Intellectual Contributions

    Conference Proceeding

  • Gillette, J., Shah, S., Tariq, Z., Algamdi, S. (2022). Data protections for minors with named entity recognition. IEEE. https://ieeexplore.ieee.org/abstract/document/10021086
  • Algamdi, S., Albanyan, A., Shah, S., Tariq, Z. (2022). Twitter Accounts Suggestion: Pipeline Technique SpaCy Entity Recognition. IEEE Access. IEEE. https://ieeexplore.ieee.org/abstract/document/10020570
  • Tariq, Z., Shah, S., Lee, Y. (2021). Automatic Multimodal Heart Disease Classification using Phonocardiogram Signal. IEEE. https://ieeexplore.ieee.org/abstract/document/9378232
  • Shah, S., Tariq, Z., Lee, J., Lee, Y. (2021). Real-Time Machine Learning for Air Quality and Environmental Noise Detection. IEEE. https://ieeexplore.ieee.org/author/37088809485
  • Tariq, Z., Shah, S., Lee, Y. (2021). Multimodal Lung Disease Classification using Deep Convolutional Neural Network. IEEE. https://ieeexplore.ieee.org/abstract/document/9313208
  • Shah, S., Tariq, Z., Lee, Y. (2020). IoT based Urban Noise Monitoring in Deep Learning using Historical Reports. IEEE. https://ieeexplore.ieee.org/abstract/document/9006176
  • Tariq, Z., Shah, S., Lee, Y. (2020). Speech Emotion Detection using IoT based Deep Learning for Health Care. IEEE. https://ieeexplore.ieee.org/abstract/document/9005638
  • Tariq, Z., Shah, S., Lee, Y. (2020). Lung Disease Classification using Deep Convolutional Neural Network. IEEE. https://ieeexplore.ieee.org/abstract/document/8983071
  • Tariq, Z., Shah, S., Lee, Y. (2019). Smart 311 Request System with Automatic Noise Detection for Safe Neighborhood. IEEE. https://ieeexplore.ieee.org/abstract/document/8656773
  • Shah, S., Tariq, Z., Lee, Y. (2019). Audio IoT Analytics for Home Automation Safety. IEEE. https://ieeexplore.ieee.org/abstract/document/8622587

    • Journal Article

  • Tariq, Z., Shah, S.K., Lee, Y. (2022). Feature-Based Fusion Using CNN for Lung and Heart Sound Classification. MDPI. https://www.mdpi.com/1424-8220/22/4/1521
  • Shah, S., Tariq, Z., Lee, Y. (2021). Event-Driven Deep Learning for Edge Intelligence (EDL-EI). Sensors. https://www.mdpi.com/1424-8220/21/18/6023
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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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