SRL MS Thesis Defense of Siddharth Subramaniyam. Monday June 3. Title: Sketch Recognition Based Clarification for Eye Movement Biometrics in Virtual Reality

Thesis Defense
Monday, June 3

Title:  Sketch Recognition Based Classification for Eye Movement Biometrics in Virtual Reality

Abstract: 
Biometrics is an active area of research in the HCI, pattern recognition, and machine learning communities. In addition to various physiological features such as fingerprint, DNA, and facial recognition, there has been an interest in using behavioral biometric modalities such as gait, eye movement patterns, keystroke dynamics signature, etc. In this work, we explore the effectiveness of using eye movement as a biometric modality by treating it as a sketch and develop features using sketch recognition techniques. For testing our methods, we built a system for authentication in virtual reality (VR) that combines eye movement biometric with passcode based authentication for an additional layer of security against spoofing attacks.


Bio:Siddharth is currently a Masters student in Computer Science at Texas A&M University, working in the Sketch Recognition Lab. His research interests are in computer human interaction, especially the application of statistics and machine learning to understand human perception and cognitive behavior.

Advisor: Dr. Tracy Hammond

SRL MS Thesis Defense of Sharmistha Maity. Thursday May 30. Title: Combining Paper -Pencil Techniques with Immediate Feedback for Learning Chemical Drawings

Thesis Defense
Thursday, May 30

Title:

Combining Paper-Pencil Techniques with Immediate Feedback for Learning Chemical Drawings

Abstract:
Introductory chemistry courses teach the process of drawing basic chemical molecules with the use of Lewis dot diagrams. Many beginner students, however, have difficulty in mastering these diagrams. While several computer applications are being developed to help students learn Lewis dot diagrams, there is a potential hidden benefit from paper and pencil that many students may not realize. Sketch
recognition has been used to identify advanced chemical diagrams, however using the recognition in an educational setting requires a focus beyond identifying the final drawing. The goal of this research is to infer whether paper-pencil techniques provide educational benefits for learning Lewis dot diagrams. An analysis of pre-post assessments
shows how combining sketch recognition of paper-pencil techniques and immediate feedback allows
greater benefits for students with a basic chemistry understanding.

Biography:
Sharmistha Maity is currently a Masters student studying Computer Science at Texas A&M University. She
received her Bachelors in Electrical Engineering at The University of Texas at Austin, and her research
interests include Human-Centered Computing, Artificial Intelligence, and Cognitive Science. As a graduate
student in the Sketch Recognition Lab, she is studying the integration of educational psychology and
computer science, and how it can be combined to improve education that effectively reaches a wider
audience and increases the motivation to learn.

Advisor: Dr. Tracy Hammond