Data Scientist @ From June 2015 to Present (7 months) Sr. Engineer @ Sr Engineer in Cloud Research Analytics team. Mathematician turned data scientist with expertise in machine learning, big data. Projects: ----------- • Process Input Variables (KPIV) identification for Seagate’s manufacturing data (highly imbalanced). Tools: python (pandas, scikit-learn, web2py). • Implemented hard drive failure prediction model using Support Vector Machine (SVM), ensemble methods with random forest, gradient boosting as weak learners. Tools: python, libsvm, bash. • Testing Hadoop ecosystem for Seagate’s Hadoop on Lustre Project. See opensfs.org/seagates-apache-hadoop-on-lustre-connector/ Tools: Hadoop, pig, bash. • Spark Analytics for tiered storage optimization. Tool: Spark, python. Have prototyped using wikipedia page count data. Created python modules of start Spark, preprocess, frequency analysis, time series analysis for the whole team. • Benchmarking Spark on Lustre. Tool: Spark, python, scala, bash For fun --------- Project Euler: https://github.com/kuol/Project_Euler From August 2013 to Present (2 years 5 months) Postdoctoral Research Associate @ Postdoc for Prof Max Gunzburger in Department of Scientific Computing, Florida State University. Research on Monte Carlo, stochastic collocation method for partial differential equations(PDEs) with random input; mathematical modeling for nonlocal problems, peridynamics. From October 2012 to August 2013 (11 months) Tallahassee, Florida AreaResearch Assistant @ Research assistant for Prof Tom Manteuffel and Prof Steve McCormick in Department of Applied Maths in the area of Numerical Analysis. Focused on developing least-squares finite element algorithms, error anlysis, specialize in fluid dynamic equations(Stokes, Navier Stokes equations) and fast iterative solver(preconditioner, multigrid). From January 2010 to October 2012 (2 years 10 months) Summer Intern @ Implemented high order(polynomial degree up to 20) finite element method with electrostatic points for elliptic partial differential equations(PDEs) with Matlab, C and parallel software package PETSc. Conducted research of developing efficient preconditioner for resulting high-conditioned matrices. From 2012 to 2012 (less than a year) Summer Intern @ Summer intern in Computational Information Systems Laboratory(CISL), NCAR. Worked on developing additive Schwarz preconditioner for the bi-CG iterative wrapper of the parallel software package High-Order Method Modeling Environment(HOMME), which models the atmospheric circulation of the earth. From June 2009 to August 2009 (3 months)

Ph.D, Applied Mathematics, 4.0/4.0 @ University of Colorado at Boulder From 2007 to 2012 BS, Mathematics and Applied Mathematics @ University of Science and Technology of China From 2003 to 2007 Chengdu Shude High School From 2000 to 2003 Kuo Liu is skilled in: Machine Learning, Big Data, Python, R, Hadoop, Spark, MySQL, MongoDB, Matlab, Numerical Analysis, Scientific Computing, C++, C, Finite Element Analysis, Partial Differential Equations