ABOUT ME

I am passionate about helping people become the best they can be. I try to teach what I know and learn as much as I can from those around me. My goal is to make a lasting positive difference in the lives of others.

I became interested in Vision Science in college when I realized that I was stereo-blind and recovered my stereo vision through vision therapy exercises. During the early part of my PhD at Berkeley I learned to write basic scripting code for experiments and discovered a love for engineering. Eventually I went on to earn a Masters in Computer Science in 2016 and a PhD in Vision Science in 2018. I am currently a full time researcher in the Human Perception & Performance group at NVIDIA, based in Portland, Oregon.

EDUCATION

2012 - 2018

Graduated

DOCTOR OF PHILOSOPHY

University of California, Berkeley

The focus of my PhD thesis in Vision Science was capturing the reflectance of interesting materials with a mobile phone camera for use in rendering virtual objects.

2014 - 2016

Graduated

MASTER OF SCIENCE

University of California, Berkeley

For my masters in Computer Science I created an image editing tool to help photographers match the perceived color of their subject to the captured photo in real time.

2006 - 2011

Graduated

BACHELOR OF SCIENCE

The College of William & Mary

I earned a double major in Biology and Psychology with research projects in plant genetics and EEG.
I also fenced Épée on the varsity fencing team.

WORK EXPERIENCE

2017 - Now

NVIDIA

Research Scientist

I am part of the Human Perception & Performance Group, focusing on presenting visual stimuli in a way that is optimized for the human visual system.

2016

NVIDIA

Intern

My summer internship project focused on measuring the acceptable level of eye tracking latency for foveated rendering in head-mounted and desktop displays.

2015

Adobe

Intern

During my summer in Seattle I began the initial research that eventually led to my PhD thesis work capturing surface reflectance.

RESEARCH

2022

Image features influence reaction time

Duinkharjav, B., Chakravarthula, P., Brown, R., Patney, A., & Sun, Q. (2022). Image features influence reaction time: a learned probabilistic perceptual model for saccade latency. ACM Transactions on Graphics (TOG), 41(4), 1-15.

Best Paper Award, ACM Special Interest Group in Computer Graphics (SIGGRAPH)

Link to PDF


2021

Efficient Dataflow Modeling of Peripheral Encoding in the Human Visual System

Brown, R., DuTell, V., Walter, B., Rosenholtz, R., Shirley, P., McGuire, M., & Luebke, D. (2021). Efficient Dataflow Modeling of Peripheral Encoding in the Human Visual System. arXiv preprint, arXiv:2107.11505.

Link to PDF


2018

Approximate svBRDF Estimation From Mobile Phone Video

Albert, R. A., Chan, D. Y., Goldman, D. B., & O'Brien, J. F. (2018). Approximate svBRDF Estimation From Mobile Phone Video. Eurographics Symposium on Rendering (EGSR) EI&I. doi:10.2312/sre.20181168.

Link to PDF


2017

Latency Requirements for Foveated Rendering in Virtual Reality

Albert, R., Patney, A., Luebke, D., & Kim, J. (2017). Latency Requirements for Foveated Rendering in Virtual Reality. ACM Transactions on Applied Perception (TAP), 14(4), 25.

Best Paper Award, ACM Symposium on Applied Perception (SAP)

Link to PDF


2015

Optimal presentation of imagery with focus cues on multi-plane displays

Narain, R., Albert, R. A., Bulbul, A., Ward, G. J., Banks, M. S., & O'Brien, J. F. (2015). Optimal presentation of imagery with focus cues on multi-plane displays. ACM Transactions on Graphics (TOG), 34(4), 59.

Link to PDF

PORTFOLIO

CONTACT

Snail Mail

  • NVIDIA Office
  • 9030 NE Walker Rd
  • Hillsboro, OR 97006