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Clauset, Aaron

Professor

Positions

Research Areas research areas

Research

research overview

  • 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.

keywords

  • Network science (methods, data, theories, applications), Epistemology (data science, statistical inference, machine learning, complex systems), Science of science (social and epistemic inequalities, prestige economy, faculty), Computational biology (oncology, genomics, networks, macroevolution)

Publications

selected publications

Teaching

courses taught

  • APPM 6950 - Master's Thesis
    Primary Instructor - Spring 2024
    May be repeated up to 6 total credit hours.
  • CSCI 3104 - Algorithms
    Primary Instructor - 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 - 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 - 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 - 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.
    • ... more

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