• Contact Info
Publications in VIVO
 

Larremore, Daniel Benjamin Assistant Professor

Positions

Research Areas research areas

Research

research overview

  • Dr. Larremore's research focuses on developing methods of networks, dynamical systems, and statistical inference, to solve problems in social and biological systems. In particular, his work focuses on (1) Networks and theory, (2) Malaria's antigenic variation and evolution, and (3) Academic labor market dynamics. In 2020, his focus shifted to meet the needs of the COVID-19 pandemic.

keywords

  • Network science, dynamical systems, statistical models and inference, computational social science, recombinant genetics, epidemiology, infectious disease, applications, science of science, evolution, patterns in academic science, COVID-19, SARS-CoV-2,

Publications

selected publications

Teaching

courses taught

  • CSCI 2897 - Calculating Biological Quantities
    Primary Instructor - Spring 2021 / Fall 2021
    Master practical mathematical techniques for representing and analyzing biological quantities of different kinds. Develop mathematical intuition about biological calculations. Learn to model and solve simple feedback processes. Learn to model and solve simple accumulation processes. Learn to model and decompose simple vector spaces. Learn standard approximation and optimization strategies. Adapt and combine methods to solve real-world problems. Background in biology not required. This course is intended for students who are interested in Computational Biology, but will not take Differential Equations (APPM 2360/MATH 3430) as part of their degree plan. Does not count as Computer Science credit for Computer Science majors or minor.
  • CSCI 3022 - Introduction to Data Science with Probability and Statistics
    Primary Instructor - Spring 2018 / Fall 2018
    Introduces students to the tools methods and theory behind extracting insights from data. Covers algorithms of cleaning and munging data, probability theory and common distributions, statistical simulation, drawing inferences from data, and basic statistical modeling. Same as CSPB 3022.
  • CSCI 4802 - Data Science Team Companion Course
    Primary Instructor - Spring 2019 / Fall 2019
    Gives students hands-on experience applying data science techniques and machine learning algorithms to real-world problems. Students work in small teams on internal challenges, many of which will be sponsored by local companies and organizations and will represent the university in larger teams for external challenges at the national and global level, such as those hosted by Kaggle. Students will be expected to participate in both internal and external challenges, attend meetings and present short presentations to the group when appropriate. Same as CSCI 5802.
  • CSCI 4950 - Senior Thesis
    Primary Instructor - Spring 2019 / Fall 2019 / Spring 2020 / Fall 2020 / Spring 2021
    Provides an opportunity for senior computer science majors to conduct exploratory research in computer science. Department enforced restriction, successful completion of a minimum of 36 credit hours of Computer Science coursework and approved WRTG. May be repeated up to 8 total credit hours.
  • CSCI 5352 - Network Analysis and Modeling
    Primary Instructor - Fall 2018 / Fall 2019 / Fall 2020
    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 5802 - Data Science Team Companion Course
    Primary Instructor - Spring 2019 / Fall 2019
    Gives students hands-on experience applying data science techniques and machine learning algorithms to real-world problems. Students work in small teams on internal challenges, many of which will be sponsored by local companies and organizations and will represent the university in larger teams for external challenges at the national and global level, such as those hosted by Kaggle. Students will be expected to participate in both internal and external challenges, attend meetings and present short presentations to the group when appropriate. Instructor consent required. Same as CSCI 4802.
  • CSCI 6950 - Master's Thesis
    Primary Instructor - Fall 2019 / Spring 2020
    -
  • CSCI 7000 - Current Topics in Computer Science
    Primary Instructor - Fall 2019 / Spring 2020 / Fall 2020 / Fall 2021
    Covers research topics of current interest in computer science that do not fall into a standard subarea. May be repeated up to 8 total credit hours.

Background

International Activities

Other Profiles

Github

  • dblarremore