Jyotirmay Nag Setu
Portrait
Ph.D. Candidate & Graduate Research Assistant
Logo The University of Texas at San Antonio

I am a Ph.D. candidate in Computer Science at the University of Texas at San Antonio, where I work in the San Antonio Virtual Environment Lab (SAVE Lab) under the supervision of Dr. John Quarles. My research sits at the intersection of extended reality and artificial intelligence, focusing on cybersickness prediction, cognitive load estimation, and affective modeling in VR using multimodal physiological signals and deep learning.

My work has been published in venues including IEEE TVCG, IEEE ISMAR, IEEE VR, and ACM VRST.

Before joining UTSA, I worked as a Data Engineer at Bangladesh Bank and Robi Axiata, where I built large-scale ETL pipelines and data analytics systems. I bring a strong foundation in PyTorch, TensorFlow, computer vision, and AR/VR development.

Curriculum Vitae
Google Scholar GitHub LinkedIn ORCID
Education
  • The University of Texas at San Antonio
    The University of Texas at San Antonio
    Department of Computer Science
    Ph.D. Candidate
    Jan. 2023 - present
  • The University of Texas at San Antonio
    The University of Texas at San Antonio
    M.S. in Computer Science (CGPA - 4.00)
    Jan. 2023 - Jul. 2026
  • University of Dhaka
    University of Dhaka
    B.Sc. in Computer Science & Engineering (CGPA - 3.37)
    Jan 2015-Jan 2019
Experience
  • University of Texas at San Antonio
    University of Texas at San Antonio
    Graduate Research Assistant
    Jan. 2023 - Present
  • Bangladesh Bank
    Bangladesh Bank
    Data Engineer
    Nov. 2020 - Dec. 2023
  • Robi Axiata Ltd.
    Robi Axiata Ltd.
    Data Engineer
    May. 2020 - Nov. 2020
News
2026
Our paper "A Statistical Abstraction Framework for Integrating Heterogeneous VR Datasets in Ordinal Cybersickness Prediction" was published at IEEE VR 2026. Read more
Mar 20
2025
Our paper "PatchFusionVR: Multitask Prediction of User Gaze, Reaction Time, and Cognitive Load in Virtual Reality from Multimodal Signals" was published at ACM VRST 2025. Read more
Nov 11
Became a PhD Candidate.
Oct 19
Our paper "Towards Cybersickness Severity Classification from VR Gameplay Videos Using Transfer Learning and Temporal Modeling" was published at IEEE ISMAR-Adjunct 2025. Read more
Oct 07
Our paper "Predicting and Explaining Cognitive Load, Attention, and Working Memory in Virtual Multitasking" was published in IEEE Transactions on Visualization and Computer Graphics (TVCG). Read more
Apr 30
Our paper "Investigating the Potential of Multi-Task Learning for Enhancing SSQ Prediction" was published at IEEE VRW 2025. Read more
Mar 07
Passed the PhD Qualifier Exam.
Feb 24
2024
Our paper "Mazed and confused: A dataset of cybersickness, working memory, mental load, physical load, and attention during a real walking task in VR" was published at IEEE ISMAR 2024. Read more
Oct 20
Selected Publications (view all )
A Statistical Abstraction Framework for Integrating Heterogeneous VR Datasets in Ordinal Cybersickness Prediction
A Statistical Abstraction Framework for Integrating Heterogeneous VR Datasets in Ordinal Cybersickness Prediction

Jyotirmay Nag Setu, John Quarles

IEEE Conference on Virtual Reality and 3D User Interfaces (VR) 2026 Conference

We developed a comprehensive statistical feature abstraction framework combined with dual-head ordinal regression to enable cybersickness prediction across heterogeneous VR datasets. Our approach transforms diverse sensor modalities from VR.net (Meta Quest Pro proprietary systems), SIM21, and VRWalking (HTC VIVE/Tobii) platforms into standardized statistical descriptors that capture cybersickness-relevant behavioral patterns while remaining invariant to study design and data collection methodologies.

[Paper]

A Statistical Abstraction Framework for Integrating Heterogeneous VR Datasets in Ordinal Cybersickness Prediction

Jyotirmay Nag Setu, John Quarles

IEEE Conference on Virtual Reality and 3D User Interfaces (VR) 2026 Conference

We developed a comprehensive statistical feature abstraction framework combined with dual-head ordinal regression to enable cybersickness prediction across heterogeneous VR datasets. Our approach transforms diverse sensor modalities from VR.net (Meta Quest Pro proprietary systems), SIM21, and VRWalking (HTC VIVE/Tobii) platforms into standardized statistical descriptors that capture cybersickness-relevant behavioral patterns while remaining invariant to study design and data collection methodologies.

[Paper]

Predicting and Explaining Cognitive Load, Attention, and Working Memory in Virtual Multitasking
Predicting and Explaining Cognitive Load, Attention, and Working Memory in Virtual Multitasking

Jyotirmay Nag Setu, Joshua M Le, Ripan Kumar Kundu, Barry Giesbrecht, Tobias Höllerer, Khaza Anuarul Hoque, Kevin Desai, John Quarles

IEEE transactions on visualization and computer graphics 2025 Journal

This study shows the similarity between cybersickness and cognitive load prediciton research. We showed how the same modalities can be used to build prediciton models for cogntiive load assessment.

[Paper]

Predicting and Explaining Cognitive Load, Attention, and Working Memory in Virtual Multitasking

Jyotirmay Nag Setu, Joshua M Le, Ripan Kumar Kundu, Barry Giesbrecht, Tobias Höllerer, Khaza Anuarul Hoque, Kevin Desai, John Quarles

IEEE transactions on visualization and computer graphics 2025 Journal

This study shows the similarity between cybersickness and cognitive load prediciton research. We showed how the same modalities can be used to build prediciton models for cogntiive load assessment.

[Paper]

Mazed and confused: A dataset of cybersickness, working memory, mental load, physical load, and attention during a real walking task in VR
Mazed and confused: A dataset of cybersickness, working memory, mental load, physical load, and attention during a real walking task in VR

Jyotirmay Nag Setu, Joshua M Le, Ripan Kumar Kundu, Barry Giesbrecht, Tobias Höllerer, Khaza Anuarul Hoque, Kevin Desai, John Quarles

IEEE International Symposium on Mixed and Augmented Reality (ISMAR) 2024 Conference

A dataset that collects multimodal data including eye-tracking, head-tracking, Hear Rate (HR), Galvanic Skin Response (GSR) alongside ground truth values for cybersickness, physical load, mental load, attention and working memory while participants are performing multiple tasks.

[Paper]

Mazed and confused: A dataset of cybersickness, working memory, mental load, physical load, and attention during a real walking task in VR

Jyotirmay Nag Setu, Joshua M Le, Ripan Kumar Kundu, Barry Giesbrecht, Tobias Höllerer, Khaza Anuarul Hoque, Kevin Desai, John Quarles

IEEE International Symposium on Mixed and Augmented Reality (ISMAR) 2024 Conference

A dataset that collects multimodal data including eye-tracking, head-tracking, Hear Rate (HR), Galvanic Skin Response (GSR) alongside ground truth values for cybersickness, physical load, mental load, attention and working memory while participants are performing multiple tasks.

[Paper]

All publications