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Eduardo Blanco

Title
Assistant Professor
Department
Computer Science and Engineering
College
College of Engineering

Education

PhD, The University of Texas at Dallas, 2011.
Major: Computer Science
BS, Technical University of Catalonia (Universitat Politècnica de Catalunya), 2007.
Major: Computer Science

Current Scheduled Teaching*

CSCE 5380.001, Data Mining, Spring 1 2019
CSCE 6950.816, Doctoral Dissertation, Spring 1 2019
CSCE 5950.816, Master's Thesis, Spring 1 2019
CSCE 6950.816, Doctoral Dissertation, Fall 1 2018
CSCE 6940.816, Individual Research, Fall 1 2018
CSCE 4290.001, Introduction to Natural Language Processing, Fall 1 2018 Syllabus
CSCE 5290.001, Natural Language Processing, Fall 1 2018 Syllabus

* 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 6933.002, Advanced Topics in Computer Science and Engineering, Spring 2018
CSCE 6950.816, Doctoral Dissertation, Spring 2018
CSCE 6940.816, Individual Research, Spring 2018
CSCE 6950.816, Doctoral Dissertation, Fall 2017
CSCE 6940.816, Individual Research, Fall 2017
CSCE 5950.816, Master's Thesis, Fall 2017
CSCE 5290.001, Natural Language Processing, Fall 2017 Syllabus
CSCE 4930.004, Topics in Computer Science and Engineering, Fall 2017 Syllabus SPOT
CSCE 6290.021, Advanced Topics in Human/Machine Intelligence, Summer 8W2 2017
CSCE 4110.021, Algorithms, Summer 10W 2017 Syllabus
CSCE 6940.817, Individual Research, Summer 10W 2017
CSCE 3110.002, Data Structures and Algorithms, Spring 2017 Syllabus SPOT
CSCE 5934.816, Directed Study, Spring 2017
CSCE 6940.816, Individual Research, Spring 2017
CSCE 5950.816, Master's Thesis, Spring 2017
CSCE 5934.816, Directed Study, Fall 2016
CSCE 6940.816, Individual Research, Fall 2016
CSCE 5950.816, Master's Thesis, Fall 2016
CSCE 5290.001, Natural Language Processing, Fall 2016 Syllabus
CSCE 4930.004, Topics in Computer Science and Engineering, Fall 2016 Syllabus SPOT
CSCE 6940.817, Individual Research, Summer 10W 2016
CSCE 4890.816, Directed Study, Spring 2016
CSCE 5934.816, Directed Study, Spring 2016
CSCE 6940.816, Individual Research, Spring 2016
CSCE 4999.817, Senior Thesis, Spring 2016 Syllabus
CSCE 4110.002, Algorithms, Fall 2015 Syllabus SPOT
CSCE 4890.816, Directed Study, Fall 2015
CSCE 6940.816, Individual Research, Fall 2015
CSCE 5290.001, Natural Language Processing, Fall 2015
CSCE 4930.004, Topics in Computer Science and Engineering, Fall 2015 Syllabus SPOT
CSCE 4110.002, Algorithms, Spring 2015 Syllabus
CSCE 5290.001, Natural Language Processing, Fall 2014
CSCE 4930.004, Topics in Computer Science and Engineering, Fall 2014 Syllabus

* 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.

,
Overall
Summative Rating
1
Challenge and
Engagement Index
2
Response Rate
0
out of 5
0
out of 7
%
of
students responded
A Challenge and Engagement Index of "n/a" means
there were not enough student responses to calculate a score.
  • 1 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
  • 2 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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