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Fleming, Ioana

Senior Instructor

Positions

Research Areas research areas

Research

research overview

  • Ioana Fleming’s research work lies at the intersection of Computer Vision and Medical Imaging, with applications to ultrasound elastography, thermal imaging and image guided surgery. She was the PI of a three year fellowship funded by the Department of Defense under the Congressionally Directed Medical Research Program for Prostate Cancer.

Teaching

courses taught

  • CSCI 1300 - Computer Science 1: Starting Computing
    Primary Instructor - Spring 2018 / Fall 2018 / Spring 2019 / Fall 2019 / Fall 2020
    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 2824 - Discrete Structures
    Primary Instructor - Fall 2019
    Covers foundational materials for computer science that is often assumed in advanced courses. Topics include set theory, Boolean algebra, functions and relations, graphs, propositional and predicate calculus, proofs, mathematical induction, recurrence relations, combinatorics, discrete probability. Focuses on examples based on diverse applications of computer science. Same as CSPB 2824.
  • CSCI 3100 - Software and Society
    Primary Instructor - Fall 2021
    Provides students with an understanding of the professional, ethical, legal and social issues and responsibilities of software developers, as well as providing them with the ability to analyze the local and global impacts of computing on individuals, organizations and society. Credit not granted for this course and CSCI 4308 and CSCI 4328 and CSCI 4338 and CSCI 4348. Required for, and restricted to, students completing a Senior Thesis for the Computer Science BS.
  • CSCI 4229 - Computer Graphics
    Secondary Instructor - Fall 2021
    Studies design, analysis and implementation of computer graphics techniques. Topics include interactive techniques, 3D viewing and models, clipping, transformations, projection, removal of hidden surfaces, lighting, textures and shadows. Knowledge of basic linear algebra is required. Same as CSCI 5229.
  • CSCI 4831 - Special Topics in Algorithms
    Primary Instructor - Spring 2018 / Spring 2019 / Spring 2020 / Spring 2021 / Spring 2022
    Covers topics of interest in computer science at the upper-division undergraduate level. Content varies from semester to semester. Only 9 credit hours from CSCI 4830 and/or CSCI 4831 can count toward Computer Science BS or BA.
  • CSCI 5229 - Computer Graphics
    Secondary Instructor - Fall 2021
    Studies design, analysis and implementation of computer graphics techniques. Topics include interactive techniques, 3D viewing and models, clipping, transformations, projection, removal of hidden surfaces, lighting, textures and shadows. Knowledge of basic linear algebra is required. Same as CSCI 4229.
  • CSCI 5722 - Computer Vision
    Primary Instructor - Spring 2018 / Spring 2019 / Spring 2020 / Spring 2021 / Spring 2022
    Explores algorithms that can extract information about the world from images or sequences of images. Topics covered include: imaging models and camera calibration, early vision (filters, edges, texture, stereo, optical flow), mid-level vision (segmentation, tracking), vision-based control and object recognition. Recommended prerequisite: probability, multivariate calculus and linear algebra.
  • DTSA 5707 - Deep Learning Applications for Computer Vision
    Primary Instructor - Spring 2022
    Students will learn about Computer Vision as a field of study and research. They explore several Computer Vision tasks and suggested approaches, from the classic Computer Vision perspective. They'll be introduced to Deep Learning methods and apply them to some of the same problems. They will analyze the results and discuss advantages and drawbacks of both types of methods. Examples of Computer Vision tasks where Deep Learning can be applied include: image classification, image classification with localization, object detection, object segmentation, facial recognition, and activity or pose estimation.
  • DTSA 5900 - Special Topics
    Primary Instructor - Fall 2021
    Examines a special topic in Data Science. May be repeated up to 9 total credit hours.

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