• Contact Info

Hoenigman, Rhonda Senior Instructor

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

  • CSCI 2270 - Computer Science 2: Data Structures
    Primary Instructor - Spring 2018
    Studies data abstractions (e.g., stacks, queues, lists, trees, graphs) 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 2275. Same as CSPB 2270.
  • CSCI 2275 - Programming and Data Structures
    Primary Instructor - Fall 2018
    Combines the content in CSCI 1300 and CSCI 2270 and is intended for students with experience with at least one object oriented programming language. The course includes an expedited instruction to the C++ programming language and then primarily focuses on the content in CSCI 2270. 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. 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.
  • CSCI 4831 - Special Topics in Algorithms
    Primary Instructor - Spring 2018 / Spring 2019
    Covers topics of interest in computer science at the upper-division undergraduate level. Content varies from semester to semester.

Background

Other Profiles