Xun Wang

412-***-****

actewg@r.postjobfree.com

Education

• Stanford University Stanford, CA

Graduate Certificate of Foundations in Computer Science, Computer Science Department & SCPD Sep 2014 – Jun 2016

• University of Pittsburgh Pittsburgh, PA

Ph.D. Computational Chemistry, Department of Chemistry GPA: 3.86/4.00 Sep 2010 – Apr 2016 Awards: Telluride School of Theoretical Chemistry Fellowship (2013).

• China Pharmaceutical University Nanjing, China

B.S., Pharmaceutial Sciences, in National Science Class GPA: 3.75/4.00 Sep 2006 – Jun 2010 Awards: Honor Graduate (2010), Academic Merit Scholarship every year (2006-2010). Experience

• The Data Incubator New York, NY

Fellow Jan 2016 – Feb 2016

– Built a website to predict the house prices in the United States using text mining and several Machine Learning algorithms including the Decision Tree and Neural Networks, from raw data with the size of 10GB.

– Accomplished several projects involving social network analysis with graph, SQL, machine learning for yelp rating, natural language processing and spark.

• University of Pittsburgh Pittsburgh, PA

Graduate Student Researcher Jul 2011 – present

– Utilized a Boltzmann-weighted electrostatic switching algorithm to sample the phase space of proton-disordered ice Ih and methane hydrates (MH) ergodically and performed both classical molecular dynamics simulations and ab initio calculations at the MP2 level to predict their static dielectric constant s from anisotropic dipole fluctua- tions. It was found that explicit inclusion of the many-body electronic polarization in force fields used for classical simulations is necessary to achieve better agreement with ab intio predictions.

– Developed a two-channel Dispersion-Corrected Atom-Centered Pseudopotential (DCACP2) for correcting BYLP and PBE density functionals for long-range dispersion on all the possible helium, neon and argon dimers, based on the parametrization using the genetic algorithm. The accurate binding curves of these clusters givemore significant improvement in the interaction energies than the previous single-channel DCACP approach did. Selected Projects

• Exact Solutions of European Equity Options and Perpetual American Options (C++, Boost Library, Visual Studio)

– Programmed the generalized Black Scholes pricingmodel to calculate the price of call/put options on Equitywith C++ STL and Boost library features in Visual Studio.

– Implemented analytical Greeks (sensitivities) calculation and call/put parity pricer for option prices.

• Monte Carlo (MC) Simulation for Option Pricing (C++, Visual Studio, Excel)

– Priced various option payo s by implementing a Monte Carlo simulation pricer.

– Solved option pricing SDE with the Euler-Maruyama scheme under MC.

• Real-World Network Analysis (C++, Make)

– Implemented various graph algorithms to investigate various properties of five real-world networks, including Web-Google ( 1million nodes, 5million edges), such as the number and sizes of the strongly connected components

(Kosaraju algorithm), network diameter, degree distribution, etc.

• Spell Checker (C, gdb, Valgrind, Mercurial)

– Designed a spell checker to find misspellings and provide a prioritized set of corrections.

– Realized two generic collections, CVector and CMap (the C-equivalents of vector and hash map). Core Technical Skills/Relevant Courses

Programming Languages: Python (SciPy, NumPy, Pandas, Scikit-learn, Matplotlib, Scrappy), C, C++(OOP, STL, Boost, Generic programming),Java, Matlab, Shell script, LATEX, SQL Computer Science: Git, Flask, Heroku, Data Structures, Algorithm Design and Analysis, Computer Organizations and Systems, Computational Theory, Machine Learning, Artificial Intelligence Math and Statistics: Partial Di erential Equations, Numerical Methods, Intermediate Probability, Stochastic Calculus Certificates:

• C++ Certificate of Financial Engineering from Baruch MFE

• Foundations in Computer Science Graduate Certificate from Stanford

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