About me

I am Prof. Sheldon Andrews, an Associate Professor at the École de Technologie Supérieure in Montreal, Canada. I conduct research in the field of physics-based animation, character animation, and motion capture. The nature of the research is applied, but also quite mathematical. A basic knowledge of linear algebra, numerical optimization, machine learning, and mechanical systems is therefore required for many of my research projects.

Knowledge of video games, physics simulation, and/or 3D graphics is beneficial. Many of my projects also build on concepts in machine learning, such as supervised learning and reinforcement learning. Experience with motion capture technology is also helpful (cameras, IMUs, optical markers). All candidates should have strong programming skills, particularly in C++ or Python.


Financing is available for all projects, and accepted candidates will be funded through a stipend provided by me. Funding is competitive with other Quebec universities.

Contact information

A list of projects for which I am actively recruiting can be found below. Interested candidates should send the following to me by email (sheldon.andrews@etsmtl.ca):

  • Two-page CV
  • Transcripts from recently completed degrees
  • Examples of a technical report or scientific article they have authored

Please visit ETS admissions for information on applying to the Master's and Doctoral program at ETS.


High-fidelity simulations of micro-scale geometry (MASc or MSc)

Keywords: physics-based animation, geometry, contact, friction
Start date: Autumn 2022 or Winter 2023

This project focuses on development of a framework for synthesizing frictional behavior through very fine-scale elastic simulations. The student will construct high resolution elastic models from scans of real-world objects. Simulations using the scanned surfaces should match the frictional behavior of the real-objects, which is measured as part of a related project. A key challenge here will be achieving stable simulations that are tractable.

Inverse computational design of friction (PhD)

Keywords: geometry, generative models, 3D printing, computational design, physics-based animation, friction
Start date: Autumn 2022 or Winter 2023

This project will focus on developing an inverse computational design pipeline for fabricating 3D surfaces that meet specific requirements. This pipeline will leverage novel friction models being developed by other students and researchers in the group. The student will explore generative models for synthesizing micro-geometry of 3D surfaces that meet user-defined specifications. For instance, aggregate properties of the surface such as roughness, microfacet distributions, and friction. A simulation platform will be used to optimize for surface micro-geometry such that specific frictional behavior is realized. A consideration will be to investigate differentiable simulations, such that changes in frictional behaviour based on the input parameter space of the friction model have a differential. Fabrication of the surfaces resulting from this computational design framework will be undertaken in collaboration with junior students in the group.

Fabrication and validation of frictional surfaces (MASc or MEng)

Keywords: 3D printing, computational design, physics-based animation, friction
Start date: Summer 2023 or Autumn 2023

The student will develop a methodology for fabricating and validating the micro-surfaces generated by a computational design pipeline. A FormLabs 3D printer will be used for fabricating prototypes, which will then be validated using a motion capture system. The goal is to ensure that the fabricated surfaces match functional and kinematic specifications. The student will collaborate closely a PhD student.

Efficient continuous collision detection (MASc or MSc)

Keywords: collision detection, optimization, implicit representations, signed distance function
Start date: Autumn 2022 or Winter 2023

The student will develop novel continuous collision detection techniques using collision between implicit representations (e.g. signed distance fields) and polygonal meshes. The target application will be surgical simulation using haptic rendering, and so the developed techniques will be evaluated on a 5 DoF force feedback device.

Multi-scale methods for contact and elastic simulation (PhD)

Keywords: physics-based animation, multiscale methods, numerical methods, solvers
Start date: Autumn 2022 or Winter 2023

The student will focus on developing multi-scale techniques for large-scale soft- and rigid-body simulations with contact. A particular interest will be on developing a multi-scale solver for heterogenous elastic models using a homogenization strategy. Additionally, the project will investigate accelerating frictional contact simulations using multi-scale approaches where contact is modeled as a linear complementarity problem. Combining multi-grid methods with numerical acceleration techniques (Anderson, Nesterov) will also be explored.

Contact rich motion synthesis for 3D characters (PhD or MASc or MSc)

Keywords: character animation, reinforcement learning, contact, motion synthesis
Start date: Autumn 2022

The focus will be on developing controllers for physics-based characters involved in contact rich physical interactions, such as climbing, wrestling, getting up, and manipulating objects. The research will include data captured from real world sensors (motion capture) to learn controllers that produce natural human motions. The learned controllers will then be used to generate motion for 3D characters in a real-time environment. Another objective will be to determine novel feature mappings and exploration strategies that accelerate the learning process.

Contact rich performance capture (PhD or MASc or MSc)

Keywords: motion capture, supervised learning, contact, inverse dynamics
Start date: Autumn 2022 or Winter 2023

This research axis will combine supervised learning techniques and a physics-based body model for robust motion tracking from a single RGB camera. Movement where there is significant contact between the person and the environment will be targeted by the project.