Web Science and Digital Libraries Research Group

In 2019, I packed my bags and flew from Sri Lanka to Virginia to begin my Ph.D. in Computer Science at Old Dominion University. I did not have a clear roadmap or any prior research experience; all I had was the hope that I would be able to figure things out along the way. After six years, I found myself diving deep into eye-tracking, human-computer interaction, and machine learning; eventually completing my dissertation in multi-user eye-tracking using commodity cameras, with the support of my advisor, Dr. Sampath Jayarathna , NIRDS Lab , and ODU Web Science and Digital Libraries Research group .        When I started my Ph.D. at ODU , I had limited knowledge and experience in eye tracking and computer vision research. After learning about ongoing research at the lab on cognitive load using eye tracking , I was fascinated by how we could use technology to better understand humans in terms of their intentions, focus, attention, and interactions with the world. Tha...

  Project Aria glasses , introduced by Meta (formerly Facebook), represent a significant leap in wearable devices. Announced as part of Meta's larger vision for the metaverse , these glasses are designed to capture rich contextual egocentric multi-modal data, providing a platform for developing augmented reality (AR) experiences grounded in real-world interactions. Aria glasses are built to collect data about the environment and user behavior while opening new frontiers for eye tracking, spatial navigation, and human-computer interaction research. NirdsLab recently became a research partner for the program researching contextualized advanced eye tracking. In this blog post, we will discuss the capabilities of Aria glasses and how we use them in eye-tracking research. Figure 1: Components of the glasses ( https://facebookresearch.github.io ) At the current stage of development at Meta, the Aria glasses take the form of a sensor array for future smart glasses, containing visual ...

Distributed Eye Tracking Distributed eye tracking refers to a system where eye-tracking technology is utilized across multiple locations. Instead of relying on a single eye-tracking device, distributed eye tracking networks use multiple eye trackers to capture eye movement data of users distributed across multiple locations. Distributed eye tracking expands the possibilities for studying visual attention and focus during collaborative tasks. Real-time visualization of data in a distributed eye tracking system allows us to monitor trends and patterns of eye tracking measures. Eye tracking measures provide informative cues for understanding how individuals visual attention and mental effort during collaborative tasks.  In this blog, I present  A-DisETrac , an advanced analytic dashboard for distributed eye tracking. A-DisEtrac is an extension of our previous work,  DisETrac  and  Gaze Analytics Dashboard . A-DisEtrac uses off-the-shelf eye trackers to mo...

Since processing speech with background noise requires appropriate parsing of the distorted auditory signal, individuals with attention deficit hyperactivity disorder (ADHD) may have difficulty processing speech with background noise due to reduced inhibitory control and working memory capacity. We conducted a study (Jayawardena et al.) by utilizing Audiovisual speech-in-noise (SIN) performance and eye-tracking measures of young adults with ADHD compared to age-matched controls for ADHD evaluation. In this study, there was five ADHD participants and six non-ADHD participants. We utilized eye tracking data recorded using a Tobii Pro X2-60 computer screen-based eye tracker. Each participant was told to watch a computer screen where a female speaks sentences out loud as levels of background noise varies and asked to repeat the sentences exactly as they heard them. The task consisted of varying six levels of background noise: 0 to 25 dB. Each participant was presented with nine senten...