My research is broadly focused on developing statistical and computational methods to analyze, model, and predict the behavior of complex biological and social systems, particularly using large or complex data sets. This work is highly interdisciplinary and draws in concepts and methods from machine learning, network science, probability theory, evolutionary theory, oncology, political conflict, and more.
CSCI 3104 - Algorithms
Primary Instructor
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Spring 2018
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 3352 - Biological Networks
Primary Instructor
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Fall 2019 / Spring 2020 / Spring 2021 / Spring 2022 / Spring 2023 / Spring 2024 / Fall 2024
This course examines the computational representation and analysis of biological phenomena through the structure and dynamics of networks, from molecules to species. Attention focuses on algorithms for clustering network structures, predicting missing information, modeling flows, regulation, and spreading-process dynamics, examining the evolution of network structure, and developing intuition for how network structure and dynamics relate to biological phenomena.
CSCI 4950 - Senior Thesis
Primary Instructor
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Fall 2018 / Spring 2019 / Fall 2020 / Spring 2021 / Fall 2022 / Spring 2023
Provides an opportunity for senior computer science majors to conduct exploratory research in computer science as an option for the capstone requirement. Department enforced prerequisites: 35 hours of Computer Science coursework including Foundation courses, Upper-Division writing, CS GPA 3.0. Department consent required, contact academic advisor for details. May be repeated up to 8 total credit hours.
CSCI 5352 - Network Analysis and Modeling
Primary Instructor
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Fall 2021 / Fall 2022
Examines modern techniques for analyzing and modeling the structure and dynamics of complex networks. Focuses on statistical algorithms and methods, and emphasizes model interpretability and understanding the processes that generate real data. Applications are drawn from computational biology and computational social science. No biological or social science training is required. Recommended prerequisites: CSCI 3104 and APPM 3570.
CSCI 6950 - Master's Thesis
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Spring 2021 / Fall 2021 / Spring 2022 / Fall 2023 / Spring 2024
CSCI 7000 - Current Topics in Computer Science
Primary Instructor
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Fall 2019 / Spring 2020 / Fall 2021 / Spring 2022 / Fall 2022 / Spring 2023 / Spring 2024 / Fall 2024
Covers research topics of current interest in computer science that do not fall into a standard subarea. May be repeated up to 18 total credit hours.
