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Juan Alvarez

· Teaching Associate Professor

University of Illinois Urbana-Champaign · Statistics and Computer Science

Active 2002–2025

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Citations0
Papers3936 last 5y
Funding—

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About

Juan Alvarez is a Teaching Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, starting from August 2025. He holds a Ph.D. and M.S. in Electrical Engineering from the University of Illinois at Urbana-Champaign, earned in 2004 and 2000 respectively, and a B.Sc. in Electronics and Communications from ITESM-CCM obtained in 1997. His academic career includes positions as a Lecturer and Visiting Lecturer at various institutions, as well as postdoctoral fellowships in Canada at York University, the University of Toronto, and the University of Saskatchewan. His research interests encompass applied probability and mathematical modeling of polymers and biophysical systems, with specific focus areas such as the configurational and statistical properties of lattice models for polymers, steric stabilization and flocculation of colloidal dispersions, adsorption and localization of random copolymers, and ion transport. Alvarez is actively involved in engineering education, working on improving study skills among undergraduate students and exploring innovative teaching methods, including the use of AI and concept maps in communication systems. He has contributed to the academic community through numerous publications in journals and conference presentations, emphasizing topics like polymer physics, communication systems, and engineering pedagogy.

Research topics

  • Computer Science
  • Engineering
  • Medical education
  • Psychology
  • Aerospace engineering
  • Mechanical engineering
  • Reliability engineering
  • Medicine
  • Pedagogy

Selected publications

  • Identifying Student Profiles Related to Success in Discrete Math CS Courses

    2024-02-07 · 2 citations

    articleOpen access

    Abstract Researchers in Computer Science education are working to identify sets of student features that play a role in course performance with the goal of helping students improve their outcomes. Specifically, researchers identified motivation, certain study behaviors, sense of belonging, and growth mindset as important factors. This prior work mainly focused on introduction to programming courses. In this paper we focus on another important gateway course in the computing sequence: Discrete Ma…

    PublisherOA PDFDOI

  • Assessing the Impact of Weekly In-class Pop Quizzes on Student Performance in a Fundamental ECE Course

    2024-02-07 · 1 citations

    articleOpen accessSenior author

    Abstract This work evaluates the effect of weekly in-class pop quizzes on the learning outcomes of ECE sophomore-level undergraduate students in a signals & systems course at the University of Illinois Urbana-Champaign. The quizzes pursued two goals: to increase class attendance and to motivate students to keep up with the material in a timely manner. While the quizzes may help achieve both goals, in-class pop quizzes may also result in the elevation of students' stress as well as they may negat…

    PublisherOA PDFDOI

  • Identifying Student Profiles Related to Success in an Analog Signal Processing Course

    2024-02-07 · 1 citations

    articleOpen access1st authorCorresponding

    Abstract Researchers in Engineering education are working to identify sets of student features that play a role in course performance with the goal of helping students improve their outcomes. Specifically, researchers identified motivation, certain study behaviors, sense of belonging, and growth mindset as important factors. This prior work mainly focused on introduction to programming courses. In this paper we focus on an important sophomore course in Electrical Engineering: Analog Signal Proce…

    PublisherOA PDFDOI

  • DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulation

    ArXiv.org · 2025-09-04

    preprintOpen access

    We introduce perioperation, a paradigm for robotic data collection that sensorizes and records human manipulation while maximizing the transferability of the data to real robots. We implement this paradigm in DEXOP, a passive hand exoskeleton designed to maximize human ability to collect rich sensory (vision + tactile) data for diverse dexterous manipulation tasks in natural environments. DEXOP mechanically connects human fingers to robot fingers, providing users with direct contact feedback (vi…

    PublisherOA PDFDOI

  • WIP: Students’ Emotional and Study Strategies Responses to ECE Exam Success and Failure

    2025-08-21

    article1st authorCorresponding
    PublisherDOI

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