Resume_Pan
1
Alexander Victor Pan Email: [email protected] https://www.linkedin.com/in/alexandervictorpan Phone Number: (812) 552-4013 https://github.com/avpan U.S. Citizen Physics M.S. with 7+ years of computational research experience transitioning into Data Science Skills Programming/Software: C, C++, Python, MATLAB, Mathematica, ROOT, Github, LaTeX, Basic: Flask, Heroku, HTML, SQL, MapReduce, Hadoop, Machine Learning, Bokeh, Pandas, Matplotlib, Spark Mathematics/Computation: Monte Carlo Simulations, Linear Algebra, Differential Calculus, Probability Distributions, Runge-Kutta, Fourier Series, Statistics, Computational Physics Experience The Data Incubator Fellow September 2016 – October 2016 • Identified(top 4% among 3000+ prospective data scientists) for skills in statistics, mathematics, data analysis, and computer science to participate in a rigorous 8 week data science fellowship program • Each week consisted of miniprojects related to Spark, distributed systems, machine learning, time series forecasting, digital audio analysis, and natural language processing. • Accomplished a capstone project that focused on uses match data from Riot Games’ API to in order to create a machine learning model that can predict the win percentage of a team based on features in a match. (More info on hextechmodeling.herokuapp.com) Lawrence Berkeley National Laboratory Berkeley, CA Graduate Research Assistant October 2013 – August 2015 • Distinguished background noise in MAJORANA Low Mass Front End Electronics wrt to experimental parameters. Best performance occurs with a minimal drain to source voltage of 0 V • Conducted Monte Carlo simulations and analyzed multiple 10 gb datasets to produce probabilities due to various systematic effects to investigate non-adiabatic effects in the KATRIN spectrometer • Determined that KATRIN needs to increase the magnetic field strength from 3 G to 15 G in order to achieve 100% transmission rates for sterile neutrino searches Purdue University West Lafayette, IN Dark Matter Research Assistant January 2012 – August 2012 • Investigated academic inconsistencies between peculiar velocities of the Sun and Milky Way for dark matter particle annual modulation research • Calculated yearly WIMP particle velocities and errors for four academic results. A parametric regression was used to find curve fittings. Results showed maximum at December 1st and minimum at June 2nd Purdue University West Lafayette, IN High Energy Astrophysics Research Assistant May 2010 – August 2011 • Constructed energy spectrums with (<1gb) datasets with error propagation and polynomial curve fitting • Conducted Monte Carlo simulations for photons and calculated the χ 2 values using Bessel’s corrections Los Alamos National Laboratory Los Alamos, NM Material Design Institute’s Summer Research Program Internship June 2009 – August 2009 • Studied the efficacy of different parameters in discriminating theoretical models of dark energy using 10-20 gb datasets • Discovered geometric parameters gave the most accurate information about the nature of dark energy by two orders of magnitude less than physical parameters. Publications “Transmission properties of the KATRIN main spectrometer”, August 2015 “Reconstructing Dark Energy: A Comparison of Cosmological Parameters”, December 2010 Education San Francisco State University San Francisco, CA Master of Science in Physics August 2012 – August 2015 Purdue University West Lafayette, IN Bachelor of Science in Applied Physics January 2007 – December 2010
-
Upload
alexander-pan -
Category
Documents
-
view
12 -
download
1
Transcript of Resume_Pan
Alexander Victor PanEmail: [email protected] https://www.linkedin.com/in/alexandervictorpanPhone Number: (812) 552-4013 https://github.com/avpanU.S. Citizen
Physics M.S. with 7+ years of computational research experience transitioning into Data Science
Skills
Programming/Software: C, C++, Python, MATLAB, Mathematica, ROOT, Github, LaTeX, Basic: Flask,
Heroku, HTML, SQL, MapReduce, Hadoop, Machine Learning, Bokeh, Pandas, Matplotlib, Spark
Mathematics/Computation: Monte Carlo Simulations, Linear Algebra, Differential Calculus, Probability
Distributions, Runge-Kutta, Fourier Series, Statistics, Computational Physics
Experience
The Data IncubatorFellow September 2016 – October 2016
• Identified(top 4% among 3000+ prospective data scientists) for skills in statistics, mathematics, data analysis, andcomputer science to participate in a rigorous 8 week data science fellowship program
• Each week consisted of miniprojects related to Spark, distributed systems, machine learning, time series forecasting,digital audio analysis, and natural language processing.
• Accomplished a capstone project that focused on uses match data from Riot Games’ API to in order to create amachine learning model that can predict the win percentage of a team based on features in a match. (More info onhextechmodeling.herokuapp.com)
Lawrence Berkeley National Laboratory Berkeley, CAGraduate Research Assistant October 2013 – August 2015
• Distinguished background noise in MAJORANA Low Mass Front End Electronics wrt to experimental parameters.Best performance occurs with a minimal drain to source voltage of 0 V
• Conducted Monte Carlo simulations and analyzed multiple 10 gb datasets to produce probabilities due to varioussystematic effects to investigate non-adiabatic effects in the KATRIN spectrometer
• Determined that KATRIN needs to increase the magnetic field strength from 3 G to 15 G in order to achieve 100%transmission rates for sterile neutrino searches
Purdue University West Lafayette, INDark Matter Research Assistant January 2012 – August 2012
• Investigated academic inconsistencies between peculiar velocities of the Sun and Milky Way for dark matter particleannual modulation research
• Calculated yearly WIMP particle velocities and errors for four academic results. A parametric regression was used tofind curve fittings. Results showed maximum at December 1st and minimum at June 2nd
Purdue University West Lafayette, INHigh Energy Astrophysics Research Assistant May 2010 – August 2011
• Constructed energy spectrums with (<1gb) datasets with error propagation and polynomial curve fitting• Conducted Monte Carlo simulations for photons and calculated the χ2 values using Bessel’s corrections
Los Alamos National Laboratory Los Alamos, NMMaterial Design Institute’s Summer Research Program Internship June 2009 – August 2009
• Studied the efficacy of different parameters in discriminating theoretical models of dark energy using 10-20 gbdatasets
• Discovered geometric parameters gave the most accurate information about the nature of dark energy by two ordersof magnitude less than physical parameters.
Publications
“Transmission properties of the KATRIN main spectrometer”, August 2015
“Reconstructing Dark Energy: A Comparison of Cosmological Parameters”, December 2010
Education
San Francisco State University San Francisco, CAMaster of Science in Physics August 2012 – August 2015
Purdue University West Lafayette, INBachelor of Science in Applied Physics January 2007 – December 2010
