Yunyun Wei - Michigan State University

Yunyun Wei 5218 Madison Avenue, Apt. B12 Okemos, MI 48864 Mobile: (517) 775 -­‐ 7813 Email: [email protected] ABILITIES AND SKILLS X •
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Experience in software programming, modeling, and analysis with MATLAB, R, SPSS, SQL, Python, C, and C++ Analytical thinking and details orientated Efficient learner and problem solver Received professional training in project development and in modes of industrial communication Project management, organizational, coordinating, and technical report writing skills INDUSTRIAL PROJECT EXPERIENCE X Data Analyst, Project Jan. 2014 – Present QED Environmental Systems Inc. | Dexter, Michigan •
Visualized and characterized large landfill gas data sets using principle component and cluster analysis •
Used 3D and time based data visualization tools to discover hidden data relationships Software Development, Project Jan. 2014 – Present OR Research | Belmont, CA •
Assisted in porting and migration of commercial DSP (TI TMS64xx) firmware from TI Code Composer 3.3 to 5 •
Dealt with compiler, linker, DSP intrinsic, integer fixed-­‐point arithmetic, and some algorithm details Software and Data Analysis, Summer Internship July 2013 – Aug 2013 Pachira Communication, Inc. | Sunnyvale, California •
Analysis on telecommunication system using queuing theory using MS Access, SPSS and Mathematica •
Conducted forecast analysis to subscription-­‐based sales using a non-­‐traditional time-­‐series model •
Presented projects and reported to CTO and senior managers in Pachira Communication, Inc. Project Lead and Data Analyst, Project Jan. 2013 – May 2013 Spectrum Health | Grand Rapid, Michigan •
Led effort to conduct a short-­‐term forecast analysis on patient admission at Spectrum Health •
Performed multiple regression and time series analysis based on large data sets Data Analyst, Project Jan. 2012 – May 2012 Herman Miller Inc. | Holland, Michigan •
Analyzed the relationship between space types and effect of utilization on the success of a company •
Recommended measures for improving utilization and optimization analysis UNIVERSITY WORK and LEADERSHIP EXPERIENCE X Graduate Teaching Assistant Aug. 2012 – Present Michigan State University | East Lansing, Michigan •
Taught courses: Multivariate Calculus, Applied Calculus •
Full lecture responsibility, authored/ graded quizzes and exams, held office hours to assist students •
Achieved excellence on student Evaluation Surveys Representative: Council of Graduate Students (COGS) Aug. 2013 – Present Michigan State University | East Lansing, Michigan • Represented graduate students in Mathematics Department to express students’ interests • Provided input on various matters affecting graduate life at the monthly meetings Organizer: 2013 Industrial Advisor Contact Day (IACD) Sep. 2013 – Nov. 2013 Michigan State University | East Lansing, Michigan • Produced detailed proposals for events • Invited and communicated with potential participants regarding attendance, information input, and logistics • Improved the outcomes of the event and achieved positive feedbacks • Enhanced communication and leadership skills through organizing the IACD event successfully EDUCATION X M S Industrial Mathematics Aug. 2012 – May 2014 Michigan State University | East Lansing, Michigan GPA 3.81/4.0 Certificate in Project Management Aug. 2012 – May 2014 Michigan State University | East Lansing, Michigan B A Physics Aug. 2008 – Aug. 2012 Michigan State University | East Lansing, Michigan GPA 3.63/4.0 •
Minor in Mathematics •
Dean’s Honor List, College of Natural Science, Fall 2009, Fall 2010 GRADUATE LEVEL COURSE WORK X Computer Science •
Data Mining •
Pattern Recognition and Analysis •
Design and Theory of Algorithms Applied Mathematics •
Numerical Computations and Analysis •
Statistical Reasoning; Monte Carlo Method; Data Acquisition and Analysis; Discrete Fourier Transform; Linear Programming; Cost-­‐Benefit Analysis; Microeconomics; Divided Differences; Galerkin's Method •
ODE, PDE, and Boundary Value Problems Statistics •
Probability and Statistics •
Applied Statistics Methods: Multiple Regression Models Marketing •
Marketing analysis •
Advanced Marketing Research Project Management REFERENCES X Available upon request •