“If you are not confused, you are not paying attention” — Tom Peters
Resource: It can feel overwhelming to become a college student and time management skills can come in handy. For all students in need of help regarding time management, please take 5 minutes to visit this link to a time management diagnostic tool.
Service to the MS in CS as advisor to the program: I am the advisor to all students in the Master’s of Computer Science program (as of Fall 2022, about 43 students). This service includes also advising and guiding students who want to complete our MSCS as part of the fast-track BS to MS program. Below is a presentation for undergraduate students: Presentation about the MSCS and the fast-track program BS to MSCS
Courses I teach: Over the years I have spent at UTEP (since 2003), I have taught a number of courses. At the undergraduate level: Introduction to Computer Science, Elementary Data Structures, Automata, Programming Languages, Problem Solving. At the graduate level: Algorithms, Logical Foundations of Computer Science, Algorithms. More recently, I have focused my effort on the introductory CS courses, taking a close look at what we teach and how we teach it, in a constant effort to enhance our students’ success and in particular, to increase retention. I have also designed two courses in problem solving and a 1CH+2CH sequence in discrete structures (formerly 3CH discrete math). Below, you can find the list of courses that I have taught recently.
- CS2401 — Elementary Data Structures: since Fall 2018, every Spring and Fall semester
- CS5350 — Advanced Algorithms: Fall 2020, 2021, 2022
- Discrete Structures 1 and 2: Maymester 2019 (DS1 only), Spring 2020 (DS1 and 2)
- CS1301/1101 — Intro to Computer Science: from Spring 2015 to Fall 2018
- CS1190 — Problem Solving: offered twice in fall 2017 (twice 6 weeks): Fall 2017
- CS5303 — Logical Foundations of Computer Science: Spring 2010, 11. 13, 18
- CS4365/5314 — Topics in Soft Computing — Constraint Solving and Optimization: Summer 2020, 2021
- CS4365/5314 — Topics in Soft Computing — Problem Solving and Algorithm Design: Summer 2016 [This course is intended to enhance students’ problem solving abilities. Through problem solving, they will learn an array of general strategies for algorithm design, they will practice performance analysis and develop critical thinking skills. They will review and apply in context notions about data structures, algorithms, discrete math, and logical foundations of computer science.]
Fall 2015 and prior: see Teaching Archives
For a while, I used piazza, so a lot of material, assignments, etc. I have used up until Spring 2020 are available there. Since 2020, as we pivoted to remote instruction, I started using MS Teams combined with OneNote for all of my classes (and more: research group, other committees, etc.). Although I find it very convenient for instruction, it is not great for sharing. If you need any material from my classes, I am always happy to help, so please do contact me.
- Students: Here is some guidance about how to work and seek help.
- You can also access information about the projects I am involved in that aim at increasing the number of women in computing.
“Computer science is no more about computers than astronomy is about telescopes.” E. W. Dijkstra
“There is no “have to” in the journey of life. You don’t “have to” do anything… nothing, nada, zip, zilch. You can either choose to do it or you can choose the consequences.” Pat Croce