Institute for Computational and Mathematical Engineering (ICME)
Email: jui-hsien.wang at stanford dot edu Office: 376 Gates 3B Wing, Stanford CA Curriculum Vitae ICME
I am a fourth-year PhD student at Stanford University, where I am advised
by Doug L. James. My
research interest is in developing efficient algorithms for
physics-based animation and sound synthesis. In the past, I've worked on
research problems in marine geophysics, biomechanics, and fuel cells. I
interned at Disney Research with David Levin in
2015, and at Adobe Research with Timothy Langlois in 2017.
Outside of work, I am an enthusiastic badminton
player, fifa addict (on PS4), and I enjoy outdoor activities such as
camping and swimming. I play ukulele or guitar from time to time, and I
once knew how to play the ancient Chinese instrument Sheng (簧笙).
I am a madridista. My son, Lucas, was
born in March, 2018.
There is no correct pronunciation in English for my name. "Ray" is a
close approximation for "Jui", and is what I go by (although I still
prefer to write it as Jui).
Toward Wave-based Sound Synthesis for Computer Animation
Jui-Hsien Wang, Ante Qu, Timothy R. Langlois, Doug L. James
2018, ACM Transactions on Graphics (SIGGRAPH 2018)
We explore an integrated approach to sound generation that supports
a wide variety of physics-based simulation models and computer-animated
phenomena. Targeting high-quality offline sound synthesis, we seek to resolve
animation-driven sound radiation with near-field scattering and
diffraction effects. The core of our approach is a sharp-interface
finite-difference time-domain (FDTD) wavesolver, with a series of supporting
algorithms to handle rapidly deforming and vibrating embedded interfaces
arising in physics-based animation sound. Once the solver rasterizes these
interfaces, it must evaluate acceleration boundary conditions (BCs) that involve
model and phenomena-specific computations. We introduce acoustic shaders as a
mechanism to abstract away these complexities, and describe a variety of
implementations for computer animation: near-rigid objects with
ringing and acceleration noise, deformable (finite element) models such as
thin shells, bubble-based water, and virtual characters. Since time-domain wave
synthesis is expensive, we only simulate pressure waves in a small region about
each sound source, then estimate a far-field pressure signal. To further
improve scalability beyond multi-threading, we propose a fully time-parallel
sound synthesis method that is demonstrated on commodity cloud computing
resources. In addition to presenting results for multiple animation phenomena
(water, rigid, shells, kinematic deformers, etc.) we also propose 3D automatic
dialogue replacement (3DADR) for virtual characters so that pre-recorded
dialogue can include character movement, and near-field shadowing and
scattering sound effects.
Bounce Maps: An Improved Restitution Model for Real-Time Rigid-Body Impact
Jui-Hsien Wang, Rajsekhar Setaluri, Dinesh K. Pai, and Doug L. James
2017, ACM Transactions on Graphics (SIGGRAPH 2017)
We present a novel method to enrich standard rigid-body impact models
with a spatially varying coefficient of restitution map, or Bounce Map. Even
state-of-the art methods in computer graphics assume that for a single
rigid body, post- and pre-impact dynamics are related with a single global,
constant, namely the coefficient of restitution. We first demonstrate that this
assumption is highly inaccurate, even for simple objects. We then present a
technique to efficiently and automatically generate a function which maps
locations on the object’s surface along with impact normals, to a scalar
coefficient of restitution value. Furthermore, we propose a method for twobody
restitution analysis, and, based on numerical experiments, estimate a
practical model for combining one-body Bounce Map values to approximate
the two-body coefficient of restitution. We show that our method not only
improves accuracy, but also enables visually richer rigid-body simulations.
The phenomenon regarding how cancer cell moves against and invades nearby tissue is an interesting yet difficult subject to study due to its multiphysics nature. In this work, we proposed a simplified yet elegant theoretical framework in an attempt to model the system. Physical assumptions were made to amount the modeling of cell locomotion to solving a classical elastostatic problem; during the process, cancer cells can secrete enzymes such as matrix metalloproteases to degrade the material. Therefore, in general the elastostatic problem happens on nonlinear, inhomogeneous substrate, which needs to be mathematically modeled. On the other hand, we hypothesized that multiple species of proteases can be secreted by the cell and they follow diffusion processes and can therefore react with the substrate at different rates. This is a two-way coupled system with cell invasion depth (or substrate deformation) depends on the results of both mechanical and chemical processes, whose outcome can be predicted in a very efficient way under the current framework. In particular, we first applied the regular perturbation method to give an analytical solution for the nonlinear elastostatic equation given a force profile assuming weak nonlinearity. Second, we designed and implemented a numerical, finite-difference based solver to model the diffusion-reaction system that can spatially distribute different species of proteases during the chemical process. This solver is then coupled to the elastostatic problem to close the loop. Several predictions based on this framework were given, such as the parametrized studies for invasion efficiency based on mechanical force distribution and colocalized enzyme distribution.
Effects of sea states on seafloor compliance studies
Jui-Hsien Wang, Wu-Cheng Chi, R. Nigel Edwards, and Eleanor C. Willoughby
Gas hydrates affect the bulk physical properties of marine sediments, in particular, elastic parameters. Shear modulus is an important parameter for estimating the distribution of hydrates in the marine sediments. However, S-wave information is difficult to recover without proper datasets. Seafloor compliance, the transfer function between pressure induced by surface gravity waves and the associated seafloor deformation, is one of few techniques to study shear modulus in the marine sediments. The coherence between recorded time series of displacement and pressure provides a measure of the quality of the calculated transfer function, the seafloor compliance. Thus, it is important to understand how to collect high coherence datasets. Here we conducted a 10-month pilot experiment using broadband seismic sensors and differential pressure gauges. We found that data collected in shallow water depth and during rough seas gave high coherence. This study is the first time long-term datasets have been employed to investigate seafloor compliance data quality and its dependence on sea state. These results will help designing future large-scale compliance experiments to study anomalously high shear moduli associated with the presence of gas hydrate or cold vents, or alternatively anomalously low shear moduli, associated with partial melt and magma chamber.
USYMLQ/USYMQR: Two Conjugate-Gradient-Type Methods for Unsymmetric Linear Equations
Final project for CME338: Large-Scale Numerical Optimization
USYMLQ and USYMQR algorithms generalize SYMMLQ and MINRES for solving large,
sparse, unsymmetric linear system of equations. It is based on an efficient
orthogonal tridiagonalization procedure described in Saunders et al. 1988 paper
"Two Conjugate-Gradient-Type Methods For Unsymmetric Linear Equations". USYMLQ
can be used for square or under-determined systems, whereas USYMQR can be used
for square, under-determined, and over-determined systems. They are iterative
solvers and each step has O(N) operations; the overall storage is O(N) as well
(unlike GMRES). In the symmetric case, USYMLQ falls back to SYMMLQ and USYMQR
falls back to MINRES. The implemented USYMLQ and USYMQR are then tested on
real-world data scraped from the UFL sparse matrix collection dataset, and is
found to converged relatively quickly for a majority of the problems.
In this project, I trained an AI tool to predict the object
and material class from a single input contact sound. With
the carefully chosen feature space, I was able to achieve
more than 99% test accuracy on a 18-way classification
Real-time Aerodynamic Sound Synthesis for Slender Objects
Final project for CS5643: Physically Based Animation for Computer Graphics
In this project, I explored the problem of real-time, physics-based aerodynamic sound synthesis for slender objects. It is largely inspired by the paper by Dobashi et al. [Dobashi et al. 2003]. The aerodynamic sound when we swing a slender object, such as a stick, is originated from the complex interaction between the air flow and the stick. Sufficient spatial/temporal resolution was regarded to be essential to capture the physics and thus the characteristics of the sound generated. However, the required fluid simulation is too expensive to run at audio stepping rate. To avoid such computation, I first precomputed a comprehensive database that contains relevant sound textures evaluated from high-quality grid-based fluid simulation, and then at runtime, this database is fetched and textures are blended to effectively resynthesize the aerodynamic swinging sound. Next, to increase the interactivity of the project, I interfaced the sound system with Leap Motion sensor to give real-time motion capture data. The system is proven to be quite reliable and can run at real-time even on a low-end laptop, and create realistic swinging sound.
In our SIGGRAPH 2017 paper, we showed that the coefficients
of restitution on rigid-bodies have an extremely comlicated
distribution, as opposed to what is believed/used today in
even the most advanced rigid-body solver -- a single
constant number someone typed in: "COF = 0.3". This
is a simple web-based viewer that visualizes the beautiful
restitution maps on some of the familiar 3D models.