Jie Liu14 Duh Drive, Apt 324

Bethlehem, PA 18015, USAH +1 (716) 535-7117B jild13@lehigh.edu

Í www.linkedin.com/in/jie-liu-a0b03642

ProfileResults-oriented, skilled professional with excellent problem-finding, problem-solving andprofessional communication skills, with extensive experiences on large-scale/huge-scaleoptimization algorithms and its applications in machine learning, parallel and distributedcomputing, deep learning and statistical learning; solid data science background andexperience on different kinds of projects related to "Big Data"; technically proficient withprogramming skills.

Skills Summary• Excellent written and oral communication skills• Proficient in both English and Chinese• Excellent basic programming skills with C/C++, R, Python, Matlab• Proficient in using mathematical optimization tools such as Maple, Mathematica, AMPL,

CPLEX, MOSEK, Gurobi, Apache Spark• Familiar with and used to employ various machine learning algorithms and techniques

in projects, including SVM, decision tree, random forest, gradient boosting, MapReduceframeworks, etc.

• Familiar and proficient in data search, data processing and simulation with prevalentsoftwares, including SQL, Arena, EViews, SAS, R, Microsoft Office

• Familiar with training and teaching skills• Experienced as a Research Aide Intern in Mathematics and Computer Science Division at

Argonne National Laboratory• Trained as a Business Data Analyst at Siemens Corporate Research• Corporated with IBM Research (Ireland) on some project of large-scale power systems.

EducationAug 2013 – Jun 2018 PhD in Industrial Engineering, Lehigh University, Bethlehem, PA, USA.

(expected) Advisor: Martin Takáč, Assistant Professor at Department of Industrial and SystemsEngineering, Lehigh University, PA, USA.

Aug 2011 – Jun 2013 M.A. in Mathematics, University at Buffalo, the State University of New York, Buffalo,NY, USA.Coursera: Machine Learning (Stanford University, completed with certificate), Computingfor Data Analysis (Johns Hopkins University, completed with certificate with distinction).

Sep 2007 – Jun 2011 B.S. in Mathematics and Applied Mathematics, Nankai University, Tianjin, China.

Computer SkillsProgramming C, C++ (OpenMP, Boost, BLAS, etc.), R, Python (Numpy, Pandas, Pyspark, Sklearn, TensorFlow,

Tkinter, etc.), Matlab

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Optimization Maple, Mathematica, AMPL, CPLEX, MOSEK, GurobiOthers LATEX, SQL, Arena, EViews, SAS, Mac OS/Linux, Microsoft Office

Honors and AwardsSep 2015 – May 2016 Gotshall Fellowship, Lehigh University.

March 13, 2015 American Express Machine Learning Contest Award, 9th Machine Learning Sym-posium, The New York Academy of Sciences.

Sep 2014 – Jan 2015 RCEAS Dean’s Fellowship, Lehigh University.Sep 2013 – Aug 2014 Dean’s Doctoral Assistantship, Lehigh University.Sep 2011 – May 2013 Teaching Assistantship, University at Buffalo, SUNY.Sep 2008 – Jun 2009 Francis Cheung of the Hong Kong Friends Scholarship, Nankai University.

Jun 2008 2nd in Nankai University of “Huatai Securities Cup” Index Futures Contestfor Students, Nankai University.

Sep 2007 – Jun 2008 First Prize of National Grants, Nankai University.

Research InternshipsMay 2016 – Sep 2016 Research Intern, IBM Research, Dublin, Ireland.

Project Title Hybrid Methods Applied to Large-scale Alternating-Current Power FlowsSupervisor Jakub Marecek, Research Staff Member, IBM Research - Ireland; Martin Mevissen,

Research Staff Member and Manager, IBM Research - Ireland;.Keywords Large-scale Power Systems, Randomized Coordinate Descent, Newton’s Method, Lasserre’s

Hierarchy of SDP relaxations, α-β theory, Parallel Computing, C++ and Python.May 2015 – Aug 2015 Graduate Research Intern, Siemens Corporate Research (SCR) , Princeton, NJ, USA,

(Return Offer from 2014).Jun 2014 – Aug 2014 Graduate Research Intern, Siemens Corporate Research (SCR) , Princeton, NJ, USA.

Project Title Predictive Research in Energy Applications.Supervisor Amit Chakraborty, Project Manager, SCR; Ioannis Akrotirianakis, Senior Research

Scientist, SCRKeywords Time Series, Forecasting, ARIMA, Wavelet Transforms, Deep Neural Networks, Gaussian

Process Modeling, (Stochastic) Variational Inference, R, Rshiny App.Jun 2012 – Aug 2012 Research Aide, Argonne National Laboratory, Lemont, IL, USA.

Project Title Gaussian Process Modeling for Physics-Based Building Energy SimulationsSupervisor Victor Zavala, Computational Mathematician, Argonne National LaboratoryKeywords K-means Clustering, Latin Hypercube Sampling, Regression Problems Based On Statistical

Bayesian Gaussian Process Modeling (GP) with Different Kernels, R and Matlab.

Publications: Journals and Conference ProceedingsOctober, 2015 Jie Liu, Jakub Mareček (IBM Research) and Martin Takáč. Hybrid Methods in Solving

Alternating-Current Optimal Power Flows. Submitted, 2015.December, 2015(initial submit)

Jakub Konečný, Jie Liu, Peter Richtárik and Martin Takáč. Mini-Batch Semi-StochasticGradient Descent in the Proximal Setting. IEEE Journal of Selected Topics in SignalProcessing, 10(2): 242-255, 2016.

December, 2014 Jakub Konečný, Jie Liu, Peter Richtárik and Martin Takáč. mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting. NIPS Workshop on Optimization forMachine Learning, 2014.

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