Ted Tae Hwang
***** ******* ****** **. ******** City, MD 21042 443-***-**** ********@*****.***
EDUCATION
University of Maryland – College Park College Park, MD A. James Clark School of Engineering May 2013
Bachelor of Science in Electrical Engineering
Relevant College Courses: Linear Algebra, Engineering Probability, Discrete Mathematics, Calculus and C Programming PYTHON EXPERIENCE
Student (1 module) December 2016 – Present
www.Coursera.com
Read in 10 excel, .csv and .txt files into pandas dataframes. Then, set the index using an existing column rather than by order
Found specific indexes to Boolean mask in a dataframe by using a combination of control flow and conditional statements
Created datasets by appending, concatenating and merging data structures such as lists, series, dictionaries and dataframes
Retrieved quarterly averages by resampling datetime variable; year and quarter from the resample became new column name
Passed in two dataframes into a t-test function, from the scipy library, to see if two distributions were statistically different R EXPERIENCE
Personal Projects August 2016 – November 2016
Created a script that generated a list of URLs that holds web addresses where statistics on NFL players can be found
Obtained an R dataframe filled with statistics on NFL players by using control flow statements to web scrape data from the list of URLs into an array of list data structures. These lists were binded by row and then converted into the R dataframe.
Cleaned up the names of the NFL players using the grep function along with regular expressions and metacharacters
Calculated the mean, standard deviation, minimum and maximum of a metric for every row in the R dataframe
Transformed the R dataframe from a long-format to a wide-format using the dcast function found in the Reshape2 library
Visualized a metric for every individual NFL player by capitalizing on the facet_wrap feature found in the ggplot2 library
Determined the number of resources needed after 5 P.M. by manipulating POSIXlt variables and writing queries with sqldf
Found information through sapply functions which subsets dataframes by a category then applies custom functions to them Link to portfolio: www.rpubs.com/tae21042
Student (9 modules) March 2016 – September 2016
www.Coursera.com
Checked variables for skewness and applied methods, like standardizing and log transformations, to normalize them
Performed principal component analysis to create a new dataset with components that could explain 90% of the variance
Trained a random forest model to a training dataset and found the accuracy of the model to be 99% on the testing set
Analyzed the accuracy of general linear models, random forest models and boosting models through a confusion matrix
Created a multivariate regression model using the “mtcars” dataset in R to explore how a set of variables affects the output, miles per gallon. P-values, R-squared values and variance inflation factors were the tools used to create the best fit
Performed nested likelihood ratio tests to generate p-values that determine which variables are needed in a regression model
Plotted 30 bar graphs, histograms and line graphs for exploratory analysis. 5 graphs dealt with date and time variables 2
SQL EXPERIENCE
Student (1 module) June 2016 – July 2016
www.Coursera.com
Used select, from, where, group by, order by and having clauses to subset dataset in order to discover business intelligences
Used SQL subqueries to find how many NFL players had higher metrics than the average metric of an individual player
Determined the average profit per day of a department store through SQL joins; a relational schema was used as a guide PROFESSIONAL EXPERIENCE
Antenna Research Associates – Electrical Engineer April 2015 – February 2016 Beltsville, MD
Constructed an antenna prototype that met the gain specification in a new frequency band by meticulously modifying the dimensions of an older antenna one small increment at a time and then observing the outcome
Created a presentation to a customer on the measured data of 13 different antennas by transferring data from the measuring software to Excel. From Excel, line graphs were generated which was then pasted into Power Point slides
Communicated what management needed to be made to machine shop workers with very simple step-by-step instructions MasTec - Associate RF Engineer November 2013 - November 2014 Columbia, MD
Collaborated with a senior engineer to commission 10 distributed antenna systems using RF measuring instruments
Obtained 2 points of contacts for potential contracts by attending 1 AT&T convention and advertising MasTec’s services SKILLS: R, MySQL, Python, Tableau, Excel, Power Point, Regression Models, Machine Learning Algorithms, Git Hub and C