• Contact Info

Hoenigman, Rhonda

Associate Teaching Professor

Positions

Research Areas research areas

Research

research overview

  • Dr. Hoenigman's research focuses on modeling underlying dynamics of relevant social issues such as hunger and food waste. A novel component of her work is the application of predictive modeling and learning algorithms to domains where these algorithms are not frequently used. Dr. Hoenigman also coordinates with local relief agencies to affect change in her community by involving the community in her research, and using the research findings to inform community practices.

keywords

  • predictive modeling, applying computer science modeling to social problems such as hunger and drought, modeling food waste in boulder, understanding underlying dynamics of social problems

Teaching

courses taught

  • COEN 1830 - Special Topics
    Primary Instructor - Spring 2021 / Fall 2023 / Fall 2024
    Explores topics of interest in engineering. Content varies by instructor and semester. May be repeated up to 9 total credit hours.
  • CSCI 1300 - Computer Science 1: Starting Computing
    Primary Instructor - Fall 2023 / Fall 2024
    Teaches techniques for writing computer programs in higher level programming languages to solve problems of interest in a range of application domains. Appropriate for students with little to no experience in computing or programming. Degree credit not granted for this course and ECEN 1310. Same as CSPB 1300.
  • CSCI 2270 - Computer Science 2: Data Structures
    Primary Instructor - Spring 2018
    Studies data abstractions (e.g., stacks, queues, lists, trees, graphs, heaps, hash tables, priority queues) and their representation techniques (e.g., linking, arrays). Introduces concepts used in algorithm design and analysis including criteria for selecting data structures to fit their applications. Knowledge OF C++ is highly recommended. Degree credit not granted for this course and CSCI 2275. Same as CSPB 2270.
  • CSCI 2275 - Programming and Data Structures
    Primary Instructor - Fall 2018 / Fall 2020
    Combines the content in CSCI 1300 and CSCI 2270 and is intended for students with experience with at least one object oriented programming language. Assumes knowledge of programming constructs- data types, conditionals, loops and classes. Students must pass a programming competency exam administered by the computer science department to take this class. The course includes an expedited instruction in the C++ programming language and then primarily focuses on the content in CSCI 2270: data abstractions (e.g., stacks, queues, lists, trees, graphs, heaps, hash tables, priority queues) and their representation techniques (e.g., linking, arrays). Introduces concepts used in algorithm design and analysis including criteria for selecting data structures to fit their applications. Degree credit not granted for this course and CSCI 2270 or CSPB 2270.
  • CSCI 3104 - Algorithms
    Primary Instructor - Fall 2018 / Fall 2019
    Covers the fundamentals of algorithms and various algorithmic strategies, including time and space complexity, sorting algorithms, recurrence relations, divide and conquer algorithms, greedy algorithms, dynamic programming, linear programming, graph algorithms, problems in P and NP, and approximation algorithms. Same as CSPB 3104.
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Background

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