Gurprit Singh


I am leading the sampling and rendering group in the computer graphics department at the Max Planck Institute for informatics in Saarbrücken, Germany. Before that, I spent two wonderful years at Dartmouth College working with Wojciech Jarosz followed by another two-year postdoc working with Karol Myszkowski. I obtained my PhD from Université Lyon 1 in France, under the supervision of Victor Ostromoukhov.

How To Do Research (Bill Freeman's notes)
Writing tips (Wojciech Jarosz)

Pipeline teaser image
Best way to reach me.


2021-02-10: I am co-chairing EGSR 2021 conference with Pascal Grittmann and Philipp Slusallek (Saarland University). Looking forward to your submissions.


My research revolves around sampling which is the basic building block in many domains including computer graphics, computer vision and financial mathematics. I strive to understand how different sample correlations affect specific applications and I enjoy developing models to characterize these correlations using various mathematical tools. For example, sample distributions directly affect the error during Monte Carlo and Quasi-Monte Carlo (MCQMC) based numerical estimations of global illumination integrals. Similar numerical approximations are extremely important in quantitative analysis in financial math. On the vision side, the data obtained from scanners in the form of noisy point clouds needs constant improvement for fast and better detection, segmentation and reconstruction of underlying objects/material properties. Similar problems are also encountered in computational geometry for remeshing. In all, I am interested in various aspects of sample correlations/distributions. If you have a specific question or if you wonder why some distributions in nature are the way they are, feel free to send me an email.

Open positions

PhD positions

We are looking to hire PhD candidates in different areas related to sampling and rendering including (but not limited to):
1) Monte Carlo and Quasi-Monte Carlo (MCQMC) sampling for rendering algorithms and/or quant analysis in finance,
2) volumetric rendering for computational fabrication (in collaboration with Vahid Babaei),
3) characterization and synthesis of correlations for content creation in virtual worlds,
4) understanding of hidden structures/details in noisy point clouds.
Practical knowledge of (convolutional) neural networks is highly recommended. If you are interested, contact me with your CV attached.

Internship positions

We also have few internship positions available (6 months or more) in the above mentioned areas. Preference will be given to (Master level) students who would like to develop their ideas towards a PhD. Please contact me directly if you are interested.


SS2020: Realistic Image Synthesis (MPI Saarbrücken, Summer Semester 2020)
SS2019: Realistic Image Synthesis (MPI Saarbrücken, Summer Semester 2019)
SS2018: Realistic Image Synthesis (MPI Saarbrücken, Summer Semester 2018)
CS294: Prior work on Digital Arts, Instructor (Dartmouth College, Fall 2016)
CS87/187: Rendering Algorithms, Guest Lecturer (Dartmouth College, Spring 2016, Instructor Prof. Wojciech Jarosz)
CS77/177: Computer Graphics, Guest Lecturer (Dartmouth College, Fall 2015, Instructor Prof. Emily Whiting)


Quan Zheng (Oct 2019 - present)

PhD students

Corentin Salaün (Oct 2020 - present)
Xingchang Huang (Feb 2021 - present)

MS Students

Shishir Reddy (MS Thesis) (ongoing)
Varshini Muthukumar (MS Thesis) (ongoing)
Tianqi Fan (MS Thesis) (2020) (now Google Munich)
Vassillen Chizhov (MS Thesis) (2019 October) (PhD student at Saarland Univ.)
Alexander Köhn (MS Thesis) (2019 October)


Benjamin Sommer (Oct 2020 - present)
Xingchang Huang (June 2020 - Jan 2021)
Geremy Hutin (2019 Summer intern)
Arezou Fatemi (2018 Summer intern)



Blue Noise Plots

Eurographics 2021 / Computer Graphics Forum, Volume 40 issue 2, May 2021
Christian van Onzenoodt, Gurprit Singh, Timo Ropinski, Tobias Ritschel
arXiv source code


Neural Light Field 3D Printing

SIGGRAPH ASIA 2020 / ACM Transactions on Graphics, Volume 39 issue 6, December 2020
Quan Zheng, Vahid Babaei, Gordon Wetzstein, Hans-Peter Seidel, Matthias Zwicker, Gurprit Singh

LadyBird: Quasi-Monte Carlo Sampling for Deep Implicit Field Based 3D Reconstruction with Symmetry

ECCV (Oral), August 2020
Yifan Xu*, Tianqi Fan*, Yi Yuan, Gurprit Singh (*contributed equally)

Real-time Monte Carlo Denoising with the Neural Bilateral Grid

Eurographics Symposium on Rendering (EGSR), June 2020
Xiaoxu Meng, Quan Zheng, Amitabh Varshney, Gurprit Singh, Matthias Zwicker


Deep Point Correlation Design

SIGGRAPH ASIA 2019 / ACM Transactions on Graphics, Volume 38 issue 6, October 2019
Thomas Leimkühler, Gurprit Singh, Karol Myszkowski, Hans-Peter Seidel, Tobias Ritschel

Analysis of Sample Correlations for Monte Carlo Rendering

Computer Graphics Forum (Proceedings of Eurographics - State of the art reports) 2019
Gurprit Singh, Cengiz Öztireli, Abdalla G.M. Ahmed, David Coeurjolly, Kartic Subr, Oliver Deussen, Victor Ostromoukhov, Ravi Ramamoorthi, Wojciech Jarosz

Fourier Analysis of Correlated Monte Carlo Importance Sampling

Computer Graphics Forum, 38(1), 2019
Gurprit Singh, Kartic Subr, David Coeurjolly, Victor Ostromoukhov, Wojciech Jarosz

A Perception-driven Hybrid Decomposition for Multi-layer Accommodative Displays

IEEE VR 2019
Hyeonseung Yu, Mojtaba Bemana, Marek Wernikowski, Michał Chwesiuk, Okan Tarhan Tursun, Gurprit Singh, Karol Myszkowski, Radosław Mantiuk, Hans-Peter Seidel, Piotr Didyk


Spectral Measures of Distortion for Change Detection in Dynamic Graphs

Complex Networks 2018 (Oral)
Luca Castelli Aleardi, Semih Salihoglu, Gurprit Singh, Maks Ovsjanikov

Sampling Analysis using Correlations for Monte Carlo Rendering

SIGGRAPH Asia Courses 2018
Cengiz Öztireli, Gurprit Singh

End-to-end Sampling Patterns

Thomas Leimkühler, Gurprit Singh, Karol Myszkowski, Hans-Peter Seidel, Tobias Ritschel
Technical Report


Convergence Analysis for Anisotropic Monte Carlo Sampling Spectra #

SIGGRAPH 2017 / ACM Transactions on Graphics, 36 (4), July 2017
Gurprit Singh, Wojciech Jarosz

Variance and Convergence Analysis of Monte Carlo Line and Segment Samples #

Computer Graphics Forum (Proceedings of EGSR), 36 (4), June 2017
Gurprit Singh, Bailey Miller, Wojciech Jarosz
webpage source code (AO example)


Monte Carlo Convergence Analysis for Anisotropic Sampling Power Spectra

Gurprit Singh, Wojciech Jarosz
Technical Report

Fourier Analysis of Numerical Integration in Monte Carlo Rendering: Theory and Practice #

SIGGRAPH Courses 2016
Kartic Subr, Gurprit Singh, Wojciech Jarosz
webpage source code


Variance and Sampling Analysis for Monte Carlo Integration in the Spherical Domain #

Ph.D. Dissertation, Université Lyon 1, France, September 2015.
Gurprit Singh

Variance Analysis for Monte Carlo Integration #

SIGGRAPH 2015 / ACM Transactions on Graphics, 34 (4), 2015
*Adrien Pilleboue, *Gurprit Singh, David Coeurjolly, Michael Kazhdan, Victor Ostromoukhov (*joint first authors)
webpage source code

Variance Analysis for Monte Carlo Integration: A Representation-Theoretic Perspective

Michael Kazhdan, Gurprit Singh, Adrien Pilleboue, David Coeurjolly, Victor Ostromoukhov
arXiv Report


Fast Tile-Based Adaptive Sampling with User-Specified Fourier Spectra #

SIGGRAPH 2014 / ACM Transactions on Graphics, 33 (4), 2014
Florent Wachtel, Adrien Pilleboue, David Coeurjolly, Katherine Breeden, Gurprit Singh, Gaël Cathelin, Fernando de Goes, Mathieu Desbrun, Victor Ostromoukhov

Imprint / Data Protection