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Bhaskar  Trivedi 

Title: Clinical Assistant Professor

Department: Computer Science and Engineering

College: College of Engineering

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, University of Texas at Arlington, 2025
    Major: Computer Science
    Dissertation: Environment and Intention Awareness for Navigation and Collaboration
  • MS, University of Texas at Arlington, 2018
    Major: Computer Science
    Dissertation: DWRELU: Double weighted Rectifier Linear Unit an Activation Function with Trainable Scaling Parameters

Current Scheduled Teaching

CSCE 4110.001AlgorithmsSpring 2027
CSCE 4110.002AlgorithmsSpring 2027
CSCE 3600.002Principles of Systems ProgrammingSpring 2027
CSCE 3600.204Principles of Systems ProgrammingSpring 2027
CSCE 3600.205Principles of Systems ProgrammingSpring 2027
CSCE 3600.207Principles of Systems ProgrammingSpring 2027
CSCE 3600.501Principles of Systems ProgrammingSpring 2027
CSCE 3600.550Principles of Systems ProgrammingSpring 2027
CSCE 3600.551Principles of Systems ProgrammingSpring 2027
CSCE 2610.002Assembly Language and Computer OrganizationFall 2026 Syllabus
CSCE 2610.204Assembly Language and Computer OrganizationFall 2026 Syllabus
CSCE 2610.205Assembly Language and Computer OrganizationFall 2026 Syllabus
CSCE 2610.207Assembly Language and Computer OrganizationFall 2026 Syllabus
CSCE 3530.001Introduction to Computer NetworksFall 2026 Syllabus
CSCE 4600.001Introduction to Operating SystemsFall 2026 Syllabus
CSCE 4600.201Introduction to Operating SystemsFall 2026 Syllabus
CSCE 4600.501Introduction to Operating SystemsFall 2026 Syllabus
CSCE 4600.551Introduction to Operating SystemsFall 2026 Syllabus

Previous Scheduled Teaching

No previous courses scheduled.

Published Intellectual Contributions

    Conference Proceeding

  • Sayed, S., Ghoddoosian, R., Trivedi , B., Athitsos, V. (2023). A new dataset and approach for timestamp supervised action segmentation using human object interaction. Vancouver, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops.
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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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