Yuehaw Khoo

I'm a post-doc at the Department of Mathematics, Stanford University, working with Lexing Ying. Previously, I obtained my Ph.D. under the supervision of Amit Singer at Princeton University.

Education

Ph.D., Physics, Princeton University (2016).

B.Sc., Physics, University of Virginia (2009).

Research Interests

Computational structural biology
Convex programming approaches for protein structuring from NMR spectroscopy.

High-dimensional function compression
Tensor decompositions, neural-network applications in physics and PDE.

Computer vision
Matching and registration problems with medical and biological applications.

Publications and Preprints

Drop-Activation: Implicit Parameter Reduction and Harmonic Regularization.
S. Liang, Y. Khoo, H. Yang. Preprint. [arXiv]

SwitchNet: a neural network model for forward and inverse scattering problems.
Y. Khoo and L. Ying. Preprint. [arXiv]

Convex relaxation approaches for strictly correlated density functional theory.
Y. Khoo and L. Ying. Preprint. [arXiv]

Efficient construction of tensor ring representations from sampling.
Y. Khoo, J. Lu, and L. Ying. Preprint. [arXiv]

Solving parametric PDE problems with artificial neural networks.
Y. Khoo, J. Lu, and L. Ying. Preprint. [arXiv]

Bias correction in Saupe tensor estimation.
Y. Khoo, A. Singer, and D. Cowburn. Preprint. [arXiv]

Solving for high dimensional committor functions using artificial neural networks.
Y. Khoo, J. Lu, and L. Ying. Research in the Mathematical Sciences, Accepted. [arXiv]

Semidefinite Programming Approach for the Quadratic Assignment Problem with a Sparse Graph.
J.F.S. Bravo Ferreira, Y. Khoo, and A. Singer. Computational Optimization and Applications, 2017. [arXiv, DOI]

Integrating NOE and RDC using sum-of-squares relaxation for protein structure determination.
Y. Khoo, A. Singer, and D. Cowburn. Journal of Biomolecular NMR, 2017. [arXiv, DOI]

Fast and Robust Discrete Computational Imaging.
A. Tuysuzoglu, Y. Khoo, and W.C. Karl. Electronic Imaging, 2017. [DOI]

Non-Iterative Rigid 2D/3D Point-Set Registration Using Semidefinite Programming
Y. Khoo, and A. Kapoor. IEEE Transactions on Image Processing, 2016. [arXiv, DOI]

Variable splitting techniques for discrete tomography.
A. Tuysuzoglu, Y. Khoo, and W.C. Karl. IEEE International Conference on Image Processing (ICIP), 2016. [DOI]

Global registration of multiple point clouds using semidefinite programming.
K.N. Chaudhury, Y. Khoo, and A. Singer. SIAM Journal on Optimization, 2015. [arXiv, DOI]

Large scale sensor network localization via rigid subnetwork registration.
K.N. Chaudhury, Y. Khoo, and A. Singer. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015. [arXiv]

Open problem: Tightness of maximum likelihood semidefinite relaxations.
A.S. Bandeira, Y. Khoo, and A. Singer. Proceedings of The 27th Conference on Learning Theory (COLT), 2014. [arXiv]

Tuning the quantum oscillations of surface Dirac electron in the topological insulator Bi2Te2Se.
J. Xiong, Y. Khoo, S. Jia, R.J. Cava, and N.P. Ong. Physical Review B, 2013. [arXiv, DOI]

High field Shubnikov-de Haas oscillation in the topological insulator Bi2Te2Se.
J. Xiong, Y. Luo, Y. Khoo, S. Jia, R.J. Cava, and N.P. Ong. Physical Review B, 2012. [arXiv, DOI]

Patents

System and Method for Real-Time Ultrasound Guided Prostate Needle Biopsies Using a Compliant Robotic Arm.
J. Benson, R. Chiao, D. Comaniciu, A. Kamen, A. Kapoor, Y. Khoo, and A. Milkowski.

Initialization independent approaches towards registration of 3D models with 2D projections.
Y. Khoo, A. Kapoor

Teaching Experiences

Contact

Department of Mathematics, Stanford University
450 Serra Mall, Bldg. 380, Stanford, CA 94305
ykhoo (at) stanford (dot) edu