### Eric Chi

**Program Years:**2008-2011**Academic Institution:**Rice University**Field of Study:**Bioinformatics/Statistics**Academic Advisor:**David Scott**Practicum(s):**

Lawrence Berkeley National Laboratory (2009)

Sandia National Laboratories, California (2010)**Degree(s):**

Ph.D. Statistics, Rice University, 2011

M.A. Statistics, Rice University, 2010

M.S. Electrical Engineering, University of California, Berkeley, 2001

B.A. Physics, Rice University, 1999

#### Current Status

**Status:**Associate Professor, Dept of Statistics, Rice University**Research Area:**Statistics and Machine Learning**Personal URL:**http://ericchi.com/

#### Publications

Q. Heng, E.C. Chi, and Y. Liu, Tucker-L2E: Robust Low-rank Tensor Decomposition with the L2 Criterion, Technometrics, in press.Q. Heng, H. Zhou, and E.C. Chi, Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo, Journal of Computational and Graphical Statistics, in press

X. Liu, E.C. Chi, and K. Lange, A Sharper Computational Tool for L2E Regression. Technometrics, 64(1):117-126, 2023.

J.T. Chi and E.C. Chi, A Computational Framework for Robust Structured Regression Using the L2 Criterion, Journal of Computational and Graphical Statistics, 31(4):1051-1062, 2022.

M. Zhang, G. Mishne, and E.C. Chi, Multi-scale Affinities with Missing Data: Estimation and Applications, Statistical Analysis and Data Mining, 15(3):303--313, 2022.

X. Liu and E.C. Chi}, Revisiting Convexity-Preserving Signal Recovery with the Linearly Involved GMC Penalty, Pattern Recognition Letters, 156:60-66, 2022.

E.C. Chi, Discovering Geometry in Data Arrays. Computing in Science and Engineering, 23(6):42-51, 2021.

X. Liu, M. Vardhan, Q. Wen, A. Das, A. Randles, E.C. Chi, An Interpretable Machine Learning Model to Classify Coronary Bifurcation Lesions, Annual International Conference of the IEEE Engineering in Medicine & Biology Society, Guadalajara, Mexico, Oct 31 - Nov 4, 2021.

W. Zhou, H. Yi, G. Mishne, and E.C. Chi. Scalable Algorithms for Convex Clustering, IEEE Data Science and Learning Workshop, Toronto, ON, Canada, Jun 5-6, 2021.

H. Yi, L. Huang, G. Mishne, and E.C. Chi, COBRAC: A Fast Implementation of Convex Biclustering with Compression, Bioinformatics, 37(20):3667-3669, 2021.

M. Vardhan, J. Gounley, S. J. Chen, E.C. Chi, A. M. Kahn, J. A. Leopold, and A. Randles,

Non-invasive Characterization of Complex Coronary Lesions, Nature Scientific Reports, 11(1):8145, 2021.

Y. Feng, L. Xiao, and E.C. Chi, Sparse Single Index Models for Multivariate Responses, Journal of Computational and Graphical Statistics, 30(1):115-124, 2021.

J.S. Stanley III, E.C. Chi, and G. Mishne, Multi-way Graph Signal Processing on Tensors: Integrative Analysis of Irregular Geometries, IEEE Signal Processing Magazine, 37(6):160-173, 2020.

E.C. Chi, B.R. Gaines, W. W. Sun, H. Zhou, and J. Yang, Provable Convex Co-clustering of Tensors, Journal of Machine Learning Research, 21(214):1-58, 2020.

H. L. Brantley and J. Guinness and E.C. Chi, Baseline Drift Estimation for Air Quality Data using Quantile Trend Filtering, Annals of Applied Statistics, 14(2), 585-604, 2020.

J. Rhyne, E.C. Chi, J-Y. Tzeng and X. Jeng, Fast-LORS: Joint Modeling for eQTL Mapping in R, Stat, 9(1):e265, 2020.

E.J. Min, E.C. Chi, and H. Zhou, Tensor Canonical Correlation Analysis, Stat, 8(1):e253, 2019.

B. Lusch, E.C. Chi, and J.N. Kutz, Shape Constrained Tensor Decompositions, IEEE International Conference on Data Science and Advanced Analytics, Washington, DC, Oct 5-8, 2019.

E.C. Chi and S. Stienerberger, Recovering Trees with Convex Clustering, SIAM Journal on Mathematics of Data Science, 1(3), 383-407, 2019.

E.C. Chi and T. Li, Matrix Completion from a Computational Statistics Perspective, Wiley Interdisciplinary Reviews: Computational Statistics, e1469, 2019.

G. Mishne, E.C. Chi, and R.R. Coifman, Co-manifold learning with missing data, International Conference on Machine Learning, 97:4605-4614, 2019.

E.C. Chi, L. Hu, A.K. Saibaba, and A.U.K. Rao, Going off the Grid: Iterative Model Selection for Biclustered Matrix Completion, Journal of Computational and Graphical Statistics, 28(1):36-47, 2019.

J. Xu, E.C. Chi, M. Yang, and K. Lange, A Majorization-minimization Algorithm for Split Feasibility Problems, Computational Optimization and Applications, 71(3):795-828, 2018.

J. Xu, E.C. Chi, and K. Lange, Generalized Linear Model Regression under Distance-to-set Penalties, Advances in Neural Information Processing Systems 30:1385-1395, 2017

E.C. Chi, G.I. Allen, and R.G. Baraniuk, Convex Biclustering, Biometrics, 73(1):10-19, 2017.

J.P. Long, E.C. Chi, and R.G. Baraniuk, Estimating a Common Period for a Set of Irregularly Sampled Functions with Applications to Periodic Variable Star Data, Annals of Applied Statistics, 10(1):165-197, 2016.

J.T. Chi, E.C. Chi, and R.G. Baraniuk, k-POD: A Method for k-Means Clustering of Missing Data, The American Statistician, 70(1):91-99, 2016.

E.C. Chi and K. Lange, Splitting Methods for Convex Clustering, Journal of Computational and Graphical Statistics, 24(4):994-1013, 2015.

G.K. Chen, E.C. Chi, J.M.O Ranola, and K. Lange, Convex Clustering: An Attractive Alternative to Hierarchical Clustering, PLOS Computational Biology, 11(5): e1004228, 2015.

E.C. Chi and K. Lange, Stable Estimation of a Covariance Matrix Guided by Nuclear Norm Penalties, Computational Statistics & Data Analysis, 80:117-128, 2014.

E.C. Chi, H. Zhou, and K. Lange, Distance Majorization and Its Applications, Mathematical Programming Series A, 146:409-436, 2014.

K. Lange, E.C. Chi and H. Zhou, A Brief Survey of Modern Optimization for Statisticians, International Statistical Review, 82(1):46-70, 2014.

E.C. Chi and D.W. Scott, Robust Parametric Classification and Variable Selection by a Minimum Distance Criterion, Journal of Computational and Graphical Statistics, 23(1):111-128, 2014.

E.C. Chi and K. Lange, A Look at the Generalized Heron Problem through the Lens of Majorization-Minimization, The American Mathematical Monthly, 121(2):95-108, 2014.

E.C. Chi, G.I. Allen, H. Zhou, O. Kohannim, K. Lange, and P.M. Thompson, Imaging genetics via sparse canonical correlation analysis, In IEEE Proceedings of ISBI 2013.

E.C. Chi, H. Zhou, G.K. Chen, D. Ortega Del Vecchyo, and K. Lange, Genotype Imputation via Matrix Completion, Genome Research 23:509-518, 2013.

E.C. Chi and T.G. Kolda, On Tensors, Sparsity, and Nonnegative Factorizations, SIAM Journal on Matrix Analysis and Applications 33(4):1272-1299, 2012.

E.C. Chi, S.B. Mende, M-C. Fok, and G.D. Reeves, Proton auroral intensifications and injections at synchronous altitude, Geophysical Research Letters 33:6104, 2006.

R. Gupta, E. Chi, and J. Walrand, Different Algorithms for Normal and Protection Paths, Journal of Network and Systems Management 13(1):13-33, 2005.

E. Chi, M. Fu, and J. Walrand, Proactive Resource Provisioning, Computer Communications 27(12):1174-1182, 2004.

R. Gupta, E. Chi, and J. Walrand, Sharing Normal Bandwidth During a Failure, Proceedings Seventh INFORMS Telecommunications Conference, Boca Raton, Florida, March 2004.

R. Gupta, E. Chi, and J. Walrand, Different Algorithms for Normal and Protection Paths, Proceedings DRCN 2003, Banff, Canada, October 2003.

E. Chi, M. Fu, and J. Walrand, Proactive Resource Provisioning for Voice over IP, Proceedings SPECTS 2003, Montreal, Canada, July 2003.

S. Thomsen, B. Baldwin, E. Chi, J. Ellard, J.A. Schwartz, Histopathology of laser skin resurfacing, Proceedings of SPIE Vol 2970: May 1997

#### Awards

LeRoy and Elva Martin Award for Teaching Excellence, NCSU, College of Sciences, 2020Faculty Early Career Development Program (CAREER) Award, National Science Foundation, 2018

ORAU Ralph E. Powe Junior Faculty Award, 2017

R25 Cancer Prevention Fellowship, 2008

Jack C. Pollard Graduate Fellowship in Engineering, 2007

UC Berkeley Outstanding Graduate Student Instructor Award, 2001

Bonner Book Award Recipient 1997, 1998, 1999

Phi Beta Kappa, 1999

Sigma Pi Sigma, 1998

Xerox Technical Minority Scholarship, 1997