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Publications in VIVO

Corcoran, Jem

Professor Emerita/Emeritus

Positions

Research Areas research areas

Research

research overview

  • Dr. Corcoran's research is focused on fast and accurate Markov chain Monte Carlo (MCMC) algorithms with applications to problems in high-dimensional Bayesian network inference, target tracking, statistical mechanics, high-energy physics, and rarefied gas dynamics. Most recently, she has been involved in target tracking via data fusion, perfect sampling for Bayesian principal components analysis, the development of perfect simulation algorithms for chemical kinetic networks, and new statistical methods for edge detection in images.

keywords

  • Monte Carlo algorithms, multi-target tracking, Bayesian network recovery, edge detection in image processing, particle filtering , chemical reaction networks, data fusion

Publications

selected publications

Teaching

courses taught

  • APPM 4560 - Markov Processes, Queues, and Monte Carlo Simulations
    Primary Instructor - Spring 2019 / Spring 2020 / Spring 2021 / Spring 2022 / Spring 2023
    Brief review of conditional probability and expectation followed by a study of Markov chains, both discrete and continuous time, including Poisson point processes. Queuing theory, terminology and single queue systems are studied with some introduction to networks of queues. Uses Monte Carlo simulation of random variables throughout the semester to gain insight into the processes under study. Same as APPM 5560 and STAT 4100.
  • APPM 4720 - Open Topics in Applied Mathematics
    Primary Instructor - Spring 2018
    Provides a vehicle for the development and presentation of new topics that may be incorporated into the core courses in applied mathematics. Department enforced prerequisite: variable, depending on the topic, see instructor. May be repeated up to 15 total credit hours. Same as APPM 5720.
  • APPM 5560 - Markov Processes, Queues, and Monte Carlo Simulations
    Primary Instructor - Spring 2019 / Spring 2020 / Spring 2021 / Spring 2022 / Spring 2023
    Brief review of conditional probability and expectation followed by a study of Markov chains, both discrete and continuous time, including Poisson point processes. Queuing theory, terminology and single queue systems are studied with some introduction to networks of queues. Uses Monte Carlo simulation of random variables throughout the semester to gain insight into the processes under study. Same as APPM 4560, STAT 4100 and STAT 5100.
  • APPM 5720 - Open Topics in Applied Mathematics
    Primary Instructor - Spring 2018 / Fall 2018
    Provides a vehicle for the development and presentation of new topics that may be incorporated into the core courses in applied mathematics. Department enforced prerequisite: variable, depending on the topic, see instructor. May be repeated up to 6 total credit hours. Same as APPM 4720.
  • APPM 6560 - Measure-Theoretic Probability
    Primary Instructor - Fall 2020
    Introduces a series of fundamental concepts and results in probability theory, using rigorous measure-theoretic language. Provides a solid foundation for further studies and research in probability, stochastic processes, statistics, and data science. Recommended prerequisites: Undergraduate analysis at the level of APPM 4440.
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