Timothy Langlois
801 N 34th St.
Seattle, WA 98103
About me

I'm currently a research scientist at the Adobe Creative Technologies Lab. I received my Ph.D. from the Cornell Computer Science Graphics Lab where I was advised by Doug James.

My research interests include physically-based animation and physical simulation. I aim to make it easier and more efficient to simulate various phenomena, and also to make it easier to create physically realistic animations.

My CV (pdf)


  • Ph.D., Computer Science
    Cornell University
  • B.S., Computer Engineering
    University of Massachusetts Amherst

  • Technical paper reviewer: SIGGRAPH, SIGGRAPH Asia, ACM Transactions on Networking
  • Volunteer with Expand Your Horizons
    Helped organize an educational workshop for middle school students
    Spring 2012

  • Research Scientist at Adobe Research Creative Technologies Lab
  • Research Intern at Disney Research Boston
    2015 (summer)
  • Software Engineer in the MIT Lincoln Laboratory Weather Sensing Group
    Developed weather prediction algorithms, distributed real-time systems
  • Software Engineering Intern at Raytheon
    Summer 2008
  • Software Engineering Intern at DEKA Research and Development
    Embedded systems development on several medical devices
    Summers and winters 2006-2008

    One of the main projects running some of my code is the DEKA Arm
    Videos of coverage from 60 Minutes and IEEE Spectrum

Toward Animating Water with Complex Acoustic Bubbles
Timothy R. Langlois, Changxi Zheng, and Doug L. James
ACM Transactions on Graphics (SIGGRAPH 2016)
This paper explores methods for synthesizing physics-based bubble sounds directly from two-phase incompressible simulations of bubbly water flows. By tracking fluid-air interface geometry, we identify bubble geometry and topological changes due to splitting, merging and popping. A novel capacitance-based method is proposed that can estimate volume-mode bubble frequency changes due to bubble size, shape, and proximity to solid and air interfaces. Our acoustic transfer model is able to capture cavity resonance effects due to near-field geometry, and we also propose a fast precomputed bubble-plane model for cheap transfer evaluation. In addition, we consider a bubble forcing model that better accounts for bubble entrainment, splitting, and merging events, as well as a Helmholtz resonator model for bubble popping sounds. To overcome frequency bandwidth limitations associated with coarse resolution fluid grids, we simulate micro-bubbles in the audio domain using a power-law model of bubble populations. Finally, we present several detailed examples of audiovisual water simulations and physical experiments to validate our frequency model.
PDF Project page
author = {Timothy R. Langlois and Changxi Zheng and Doug L. James},
title = {Toward Animating Water with Complex Acoustic Bubbles},
journal = {ACM Transactions on Graphics (Proceedings of SIGGRAPH 2016)},
year = {2016},
volume = {35},
number = {4},
month = Jul,
doi = {10.1145/2897824.2925904}
url = {http://www.cs.cornell.edu/projects/Sound/bubbles}
Eigenmode Compression for Modal Sound Models
Timothy R. Langlois, Steven S. An, Kelvin K. Jin, and Doug L. James
ACM Transactions on Graphics (SIGGRAPH 2014)
We propose and evaluate a method for significantly compressing modal sound models, thereby making them far more practical for audiovisual applications. The dense eigenmode matrix, needed to compute the sound model's response to contact forces, can consume tens to thousands of megabytes depending on mesh resolution and mode count. Our eigenmode compression pipeline is based on nonlinear optimization of Moving Least Squares (MLS) approximations. Enhanced compression is achieved by exploiting symmetry both within and between eigenmodes, and by adaptively assigning per-mode error levels based on human perception of the far-field pressure amplitudes. Our method provides smooth eigenmode approximations, and efficient random access. We demonstrate that, in many cases, hundredfold compression ratios can be achieved without audible degradation of the rendered sound.
PDF Project page
author = {Timothy R. Langlois and Steven S. An and Kelvin K. Jin and Doug L. James},
title = {Eigenmode Compression for Modal Sound Models},
journal = {ACM Transactions on Graphics (Proceedings of SIGGRAPH 2014)},
year = {2014},
volume = {33},
number = {4},
month = Aug,
doi = {10.1145/2601097.2601177}
url = {http://www.cs.cornell.edu/projects/Sound/modec}
Inverse-Foley Animation: Synchronizing rigid-body motions to sound
Timothy R. Langlois and Doug L. James
ACM Transactions on Graphics (SIGGRAPH 2014)
In this paper, we introduce Inverse-Foley Animation, a technique for optimizing rigid-body animations so that contact events are synchronized with input sound events. A precomputed database of randomly sampled rigid-body contact events is used to build a contact-event graph, which can be searched to determine a plausible sequence of contact events synchronized with the input sound's events. To more easily find motions with matching contact times, we allow transitions between simulated contact events using a motion blending formulation based on modified contact impulses. We fine tune synchronization by slightly retiming ballistic motions. Given a sound, our system can synthesize synchronized motions using graphs built with hundreds of thousands of precomputed motions, and millions of contact events. Our system is easy to use, and has been used to plan motions for hundreds of sounds, and dozens of rigid-body models.
PDF Project page
author = {Timothy R. Langlois and Doug L. James},
title = {Inverse-Foley Animation: Synchronizing rigid-body motions to sound},
journal = {ACM Transactions on Graphics (Proceedings of SIGGRAPH 2014)},
year = {2014},
volume = {33},
number = {4},
month = Aug,
doi = {10.1145/2601097.2601178}
url = {http://www.cs.cornell.edu/projects/Sound/ifa}
Receptor Arrays
Protein Identification using Receptor Arrays and Mass Spectrometry
Timothy R. Langlois, Ramgopal R. Mettu, and Richard W. Vachet
Advances in Computational Biology (2010)
Mass spectrometry is one of the main tools for protein identification in complex mixtures. When the sequence of the protein is known, we can check to see if the known mass distribution of peptides for a given protein is present in the recorded mass distribution of the mixture being analyzed. Unfortunately, this general approach suffers from high false-positive rates, since in a complex mixture, the likelihood that we will observe any particular mass distribution is high, whether or not the protein of interest is in the mixture. In this paper, we propose a scoring methodology and algorithm for protein identification that make use of a new experimental tech- nique, which we call receptor arrays, for separating a mixture based on another differentiating property of peptides called isoelectric point (pI). We perform extensive simulation experiments on several genomes and show that additional information about peptides can achieve an average 30% reduction in false-positive rates over existing methods, while achieving very high true-positive identification rates.
booktitle={Advances in Computational Biology},
series={Advances in Experimental Medicine and Biology},
editor={Arabnia, Hamid R.},
title={Protein Identification Using Receptor Arrays and Mass Spectrometry},
publisher={Springer New York},
keywords={Receptor; Array; Mass; Spectrometry; Protein; Identification; Isoelectric; Point},
author={Langlois, Timothy R. and Vachet, Richard W. and Mettu, Ramgopal R.},
Project page

Pool Table Analyzer

My group's Senior Design Project at UMass. We designed and built a system which watched a game of pool using webcams, suggested the best shot to the player, and assisted them with aiming the cue stick, all in realtime. More details here.