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Corey Pittman

Computer Science, PhD

University of Central Florida

Biography

I am an AI Engineer currently employed by Soar Technology in Orlando, FL. I completed my PhD in May 2021 at the University of Central Florida in Orlando, FL under the supervision of Joseph J. LaViola. My research interests are broadly encapsulated in Human-Computer Interaction, specifically including augmented reality, novel input techniques, and pattern recognition. I remain a part-time member of the Interactive Systems & User Experiences Lab. My dissertation topic was “Evaluating Augmented Reality Tools for Physics Education.”

Outside of my research, I am an avid fitness junky. My main focuses are bouldering and distance running, with cycling and yoga helping to round everything off.

Interests

  • Augmented Reality
  • Gesture Recognition
  • Novel User Interfaces
  • Pattern Recognition

Education

  • PhD in Computer Science, 2021

    University of Central Florida

  • MS in Computer Science, 2013

    University of Central Florida

  • BS in Computer Science, 2012

    University of Central Florida

Experience

 
 
 
 
 

AI Engineer II

Soar Technology, Inc.

Jul 2020 – Present Orlando, Florida
Responsibilities include:

  • Develop and maintain intelligent tutoring systems, learner tracking tools, and image based
  • Work with team of developers on internal research projects to augment company software portfolio
  • Demonstrate projects to customers and shareholders
 
 
 
 
 

Research Intern

Microsoft Research MIX Group

Jun 2015 – Sep 2015 Redmond, Washington
Responsibilities include:

  • Conduct research with teleoperated drones
  • Streamline control schemes for consumer flying drones
  • Present research ideas at weekly meetings
 
 
 
 
 

Graduate Research Assistant

University of Central Florida Interactive Systems and User Experiences Lab

May 2012 – May 2020 Orlando, Florida
Responsibilities include:

  • Conduct gesture recognition research
  • Perform research paper writing
  • Oversee junior graduate and undergraduate researchers
  • Attend events to promote the ISUE Lab and confer with domain experts on future directions
  • Demonstrate research projects to lab visitors and potential sponsors

Publications

Machete: Easy, Efficient, and Precise Continuous Custom Gesture Segmentation

We present Machete, a straightforward segmenter one can use to isolate custom gestures in continuous input.
Eugene M Taranta II, Corey Pittman, Mehran Maghoumi, Mykola Maslych, Yasmine M Moolenaar, Joseph J Laviola Jr
Code Dataset Video DOI

PhyAR: Determining the Utility of Augmented Reality for Physics Education in the Classroom

In this paper, we present a qualitative analysis of a prototype augmented reality application for the Microsoft Hololens with a focus on physics education.
Corey Pittman, Joseph J. LaViola, Jr.
PDF Video DOI

Moving Toward an Ecologically Valid Data Collection Protocol for 2D Gestures In Video Games

Those who design gesture recognizers and user interfaces often use data collection applications that enable users to comfortably …
Eugene M Taranta II, Corey Pittman, Jack P Oakley, Mykola Maslych, Mehran Maghoumi, Joseph J. LaViola, Jr.
PDF

Examining Training Comprehension and External Cognition in Evaluations of Uncertainty Visualizations to Support Decision Making

Building on recent work, we investigated the effect of training comprehension on performance across varying representations of uncertainty and varying degrees of visualization interactivity using a simulated course of action selection task.
Jihye Song, Olivia B. Newton, Stephen M. Fiore, Corey Pittman, Joseph J. LaViola, Jr.
PDF

Determining Design Requirements for AR Physics Education Applications

We present the results of a series of interviews with secondary school teachers about their experience with AR and the features which would be most beneficial to them from a pedagogical perspective.
Corey Pittman, Joseph J. LaViola, Jr.
PDF Video

Examining the Impact of Training and Feedback on Visualization-Supported Decision Making under Uncertainty

We evaluated how variations in training, coupled with assessments of knowledge acquisition and application, can inform uncertainty visualization research.
Jihye Song, Olivia B. Newton, Stephen M. Fiore, Jonatham Coad, Jared Clark, Corey Pittman, Joseph J. LaViola, Jr.
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