Harris Nisar

Harris Nisar

PhD Candidate, Industrial & Enterprise Systems Engineering · UIUC
Data Scientist · John Deere

I am a PhD Candidate in Industrial & Enterprise Systems Engineering at the University of Illinois Urbana-Champaign (UIUC) and a Part-Time Data Scientist at John Deere. My research spans human-computer interaction, extended reality (XR), and applied machine learning, with a focus on building tools that help people learn and make better decisions.

Advised by Prof. Dušan M. Stipanović (ISE, UIUC). During my time at the Healthcare Engineering Systems Center (HCESC), I had the pleasure of collaborating with Prof. James M. Rehg and Prof. Thenkurussi “Kesh” Kesavadas.

News

Mar 2026 🎉 Placeholder — add your latest news item here!
Nov 2025 📄 Our paper DiffEye — a diffusion-based model for continuous eye-tracking data generation — was accepted at NeurIPS 2025.
Aug 2019 📄 Our paper on IMR for Sepsis Prevention Medical Education was presented at IEEE VR 2019 in Osaka, Japan.

Education

UIUC
PhD, Industrial & Enterprise Systems Engineering
University of Illinois Urbana-Champaign
In Progress
UIUC
MS, Industrial Engineering (Advanced Analytics)
University of Illinois Urbana-Champaign
December 2022
UIUC
BS, Bioengineering
University of Illinois Urbana-Champaign
May 2017

Experience

John
Deere
Data Scientist (Part-Time)
John Deere
– Present
HCESC
Simulation Engineer
Healthcare Engineering Systems Center, UIUC
August 2019 – Present
  • Led multi-disciplinary teams to develop virtual reality (VR) simulations for medical education and surgical training.
  • Managed end-to-end project lifecycles: ideation, proposal writing, and software production.
  • Administered $100,000+ in Jump Trading ARCHES funding.
  • Collaborated with Prof. James M. Rehg and Prof. Thenkurussi “Kesh” Kesavadas on research initiatives.

Publications & Projects

🧠
NeurIPS 2025
DiffEye: Diffusion-Based Continuous Eye-Tracking Data Generation Conditioned on Natural Images
Ozgur Kara, Harris Nisar, James M. Rehg

We propose DiffEye, a diffusion-based generative model for creating realistic, raw eye-tracking trajectories conditioned on natural images, which outperforms existing methods on scanpath generation tasks.

🏥
IEEE VR 2019
Efficacy Study on Interactive Mixed Reality (IMR) Software with Sepsis Prevention Medical Education
Naveen Sankaran, Harris J. Nisar

Presented at IEEE Virtual Reality, Osaka, Japan, March 25–27, 2019. Evaluated the effectiveness of an interactive mixed reality application for teaching sepsis prevention.

🍽️
Under Review · IEEE SeGAH
Face and Content Validation of Food Safety Training in Virtual Reality (VR)
Lydia Lee, Harris J. Nisar

Validation study for a VR-based food safety training module, assessing fidelity and content coverage for educational effectiveness.

Data Collection Portal
Project
Data Collection Portal for Pose Estimation
Harris Nisar

A modular, scalable web portal for collecting images and videos for pose estimation research. Features a demo facial landmark detector powered by deep learning.

🥽
Project
Medical & Surgical VR Simulations
Harris Nisar · Healthcare Engineering Systems Center, UIUC

A suite of VR training applications built in Unity3D for the Oculus Quest 2, covering: Joviality (psychotherapy for terminal illness), Neonatal UVC training, ECMO procedure teaching, Spay VR (veterinary surgery), Brain VR (neuroanatomy), and Road to Birth (obstetrics). All projects involve end-to-end development from SME consultation to deployment.