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  • Contact Info

Kim, Geena Instructor

Positions

Research Areas research areas

Research

research overview

  • My research interest is in applications of artificial neural networks. Previously I worked on computer vision problems using neural networks for healthcare applications: 1) brain tumor substructure segmentation using neural network architectures on multimodal brain MRI data, and 2) prediction of blood pressure in the coronary arteries and STENT surgery recommendation using neural network and machine learning models on intravascular ultrasound images. I’m also interested in studying/emulating cognitive mechanism in brain. My recent projects include 1) learning association of vision and sound using generative adversarial network, 2) utilizing memory structure and curriculum learning for improving neural network training (currently applying to the brain tumor segmentation task), 3) how a visual memory can be represented as a graph and be used in a navigation problem using deep reinforcement learning.

keywords

  • machine learning, artificial intelligence, medical image

Teaching

courses taught

  • CSCI 1300 - Computer Science 1: Starting Computing
    Primary Instructor - Spring 2019
    Teaches techniques for writing computer programs in higher level programming languages to solve problems of interest in a range of application domains. Appropriate for students with little to no experience in computing or programming. Degree credit not granted for this course and CSCI 1310 or CSCI 1320 or ECEN 1310. Same as CSPB 1300.
  • CSCI 3022 - Introduction to Data Science with Probability and Statistics
    Primary Instructor - Spring 2019
    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 4622 - Machine Learning
    Primary Instructor - Spring 2020
    Introduces students to tools, methods, and theory to construct predictive and inferential models that learn from data. Focuses on supervised machine learning technique including practical and theoretical understanding of the most widely used algorithms (decision trees, support vector machines, ensemble methods, and neural networks). Emphasizes both efficient implementation of algorithms and understanding of mathematical foundations.
  • CSPB 1300 - Computer Science 1: Starting Computing
    Primary Instructor - Summer 2019
    Teaches techniques for writing computer programs in higher level programming languages to solve problems of interest in a range of application domains. Appropriate for students with little to no experience in computing or programming. Degree credit not granted for this course and CSCI 1310 or CSCI 1320 or ECEN 1310. Same as CSCI 1300.
  • CSPB 3022 - Introduction to Data Science with Probability and Statistics
    Primary Instructor - Summer 2019 / Fall 2019 / Summer 2020 / Fall 2020 / Spring 2021 / Fall 2021
    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 CSCI 3022.
  • CSPB 3202 - Introduction to Artificial Intelligence
    Primary Instructor - Spring 2020 / Summer 2020 / Fall 2020 / Spring 2021 / Summer 2021 / Fall 2021
    Surveys artificial intelligence techniques of search, knowledge representation and reasoning, probabilistic inference, machine learning, and natural language. Same as CSCI 3202.
  • CSPB 3287 - Design and Analysis of Data Systems
    Primary Instructor - Fall 2019 / Summer 2020 / Fall 2020
    Introduces the fundamental concepts of database requirements analysis, database design, and database implementation with emphasis on the relational model and the SQL programming language. Introduces the concepts of Big Data and NoSQL systems. Same as CSCI 3287.
  • CSPB 4830 - Special Topics in Applied Computer Science
    Primary Instructor - Spring 2020
    Covers topics of interest in applied computer science at the undergraduate level. Content varies from semester to semester.

Background

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