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Portrait of Ali Bozorgian

Cambridge, UK · AI Researcher

Ali Bozorgian

Computer vision researcher with 6+ years of experience shipping perceptual rendering features on edge devices at Huawei, and camera ISP algorithms at Apple. Published at SIGGRAPH Asia, JOSA A, and IEEE.

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contact@alibozorgian.com +44 7570 236296 LinkedIn GitHub

About

I work at the intersection of human visual perception, computer vision, and computer graphics — building perceptual algorithms that make rendered content look better on the displays people actually use.

Computer Vision Perceptual Rendering Color Science HDR & Displays VR / AR Psychophysics Edge AI

01 · Career

Experience

Research prototypes in perceptual rendering and display algorithms, built in close collaboration with production teams.

Huawei

Current

Senior Algorithm Researcher

– Present · Cambridge, UK · 1 yr 6 mos

  • Developed an algorithm for 3D Gaussian Splatting inference under edge hardware constraints, addressing rasterization cost through adaptive frame rate and achieving a 10–20% improvement over baseline power consumption
  • Shipped an adaptive resolution rendering algorithm, delivering a 10–20% power-usage reduction across several devices and game titles
  • Delivered a gamut mapping algorithm for wide-gamut HDR displays on the new generation of Huawei phones
  • Improved inference of a deep-learning frame interpolation solution on edge devices, reducing visual artefacts
3D Gaussian Splatting Real-time Rendering HDR & Gamut Mapping Edge AI Deep Learning Inference

Apple

Camera Algorithm Engineer · Intern

– · Cambridge, UK · 5 mos

  • Designed and ran visual experiments to characterise observer white-balance preferences for camera imaging pipelines
Psychophysics Color Science Camera ISP

University of Cambridge

Visiting Researcher

– · Cambridge, UK · 5 mos

  • Researched and developed perceptual models of temporal vision for variable-frame-rate displays, informing display and rendering technologies; findings published at SIGGRAPH Asia and Electronic Imaging
Temporal Vision VRR Displays Perceptual Modeling

02 · Academia

Education

PhD, Computer Science

–

Norwegian University of Science and Technology (NTNU)

Thesis: Contrast sensitivity in peripheral vision for colour imaging — novel CSF-based perceptual metrics for immersive display quality assessment
  • Built and published a VR image-quality dataset of 360° foveated images with eye-tracking ground truth; developed the Unity + Varjo pipeline from scratch
  • Proposed peripheral CSF models that improved foveated image-quality prediction — directly applicable to foveated rendering systems

MSc, Color Science

Tehran Polytechnic

–

Thesis: Enhancement and evaluation of chromatic adaptation models
  • Optimization of the chromatic adaptation transform matrix
  • Psychophysical experiments evaluating cues for illuminant estimation

BSc, Engineering

Tehran Polytechnic

–

03 · Research

Publications

Peer-reviewed work on temporal vision, contrast sensitivity, and image quality in VR.

  1. ElaTCSF: A temporal contrast sensitivity function for flicker detection and modeling

    Yancheng Cai, Ali Bozorgian, Maliha Ashraf, Rafal Mantiuk

    SIGGRAPH Asia 2024 VRR flicker
    doi.org/10.48550/arXiv.2503.16759

  2. Subjective Quality Assessment of Foveated Omnidirectional Images in Virtual Reality

    Ali Bozorgian, Marius Pedersen, Jean-Baptiste Thomas, Mohamed-Chaker Larabi

    IEEE OJID 2024 doi.org/10.1109/OJID.2025.3556364

  3. Spatiotemporal contrast sensitivity functions, predictions for the critical flicker frequency

    Ali Bozorgian, Maliha Ashraf, Rafal Mantiuk

    Electronic Imaging 2024 doi.org/10.2352/EI.2024.36.11.HVEI-209

  4. The Effect of Peripheral Contrast Sensitivity Functions on the Performance of the Foveated Wavelet Image Quality Index

    Ali Bozorgian, Marius Pedersen, Jean-Baptiste Thomas

    London Imaging Meeting 2022 doi.org/10.2352/lim.2022.1.1.03

  5. Modification and evaluation of the peripheral contrast sensitivity function models

    Ali Bozorgian, Marius Pedersen, Jean-Baptiste Thomas

    JOSA A 2021 doi.org/10.1364/JOSAA.445234

04 · Open Source

Projects

Research tooling built from scratch and released on GitHub.

Subjective Image Quality Assessment in Virtual Reality

Developed a Unity application for participants to view and evaluate 360° images using controllers, with eye-tracking data recorded.

Unity C# Varjo Eye-tracking API
github.com/alibzr/VRIQA

Viewport Extractor for Varjo VR Headsets

Developed a C++ app for capturing VR headset screenshots for an image-quality dataset.

C++ Varjo Native SDK DirectX 12 Unity C# Socket programming
github.com/alibzr/varjo-viewport-extraction

05 · Toolbox

Technologies

Programming Languages

Python C++ C# MATLAB

Machine Learning Libraries

PyTorch Fast.ai scikit-learn

Other

Linux Docker Git OpenCV Amazon AWS Psychtoolbox PsychoPy Isetbio

Get in touch

Let's connect

Happy to talk perceptual rendering, display science, or potential collaborations.

Email me +44 7570 236296 LinkedIn GitHub