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Lladser, Manuel E. Associate Professor

Positions

Research Areas research areas

Research

research overview

  • Dr. Lladser's is a probabilist and computational biologist. The overarching vision of his research and teaching is a synergism of mathematics and science. Currently, his research is mostly focussed in developing methods for dimensionality reduction of symbolic datasets, as well as assessing contamination in discrete datasets.

keywords

  • algorithmic probability, bioinformatics, computational biology, computational probability, discrete mathematics, discrete probability, mathematical biology

Publications

selected publications

Teaching

courses taught

  • APPM 3170 - Discrete Applied Mathematics
    Primary Instructor - Spring 2019
    Introduces students to ideas and techniques from discrete mathematics that are widely used in science and engineering. Mathematical definitions and proofs are emphasized. Topics include formal logic notation, proof methods; set theory, relations; induction, well-ordering; algorithms, growth of functions and complexity; integer congruences; basic and advanced counting techniques, recurrences and elementary graph theory. Other selected topics may also be covered.
  • APPM 4560 - Markov Processes, Queues, and Monte Carlo Simulations
    Primary Instructor - Fall 2018
    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 / Spring 2019
    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 - Fall 2018
    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 / Spring 2019
    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.

Background

International Activities

global connections related to teaching and scholarly work (in recent years)

Other Profiles