1. Bill Chang billchang.e@gmail.com page 1 of 2
BILL CHANG, M.S. | (314) 526 0774| billchang.e@gmail.com | www.linkedin.com/in/billchang1
HIGHLIGHTS OF QUALIFICATIONS
– SOFTWARE ENGINEEER – COMPUTER RESEARCH SCIENTIST – DATA SCIENTIST – SOFTWARE DEVELOPER –
– COMPUTER VISION ENGINEER – SKILLED INNOVATOR / COLLABORATOR / COMMUNICATOR –
Specialties Include: Machine Learning – Computer Vision – Big Data – Web Applications – Object Oriented Design –
– Analytical softwareengineer skilled in cutting-edge data mining,machine learning, computer vision and other artificial
intelligenceapplications.
– Tackleambitious projects,divedeeply into technical problems and identify insightful solutions for real-world,large-scale
concerns.Efficiently make recommendations and implement solutions to improve people’s lives.
– Showcase extensive knowledge by applyingmachinelearningtools to organize, visualizeand interpret data.
– Use in-depth, scholarly and hands-on research and analytical skills to develop novel solutions to problems.
– Adeptly work individually and in team environments with colleagues and stakeholders from varied disciplines.
TECHNICAL, PROGRAMMING AND LANGUAGE SKILLS
 Program lifecycleexperienceranges from requirements gathering to testing and implementation.
 Strong background in MachineLearning and Computer Vision and extensive experience working on UI aspectof research
websites and buildingand testing user-facingprojects.Demonstrate intuition aboutboth user behavior and product design.
 Use Python and SQL databases in real-world applications.
 Experienced in Agilesoftware development environment (both Linux and Windows) and with ObjectOriented software
design and development.
 Hands-on experience developing with Django,JDBC/JPA/Hibernate, HTML, CSS, JavaScript,MySQL and PostgreSQL.
 Extensive experience with Amazon Mechanical Turk and Amazon Elastic Compute Cloud (EC2).
 Proficientin Java,C++/C#, Python, Matlab, JavaScriptand HTML/CSS.
 Familiarwith Human-Computer Interaction (HCI) design principles.
 Some experience with PHP and Angular.js.
 Languages: Bilingual in Chinese
EXPERIENCE
Research Assistant/Data Scientist, Media and Machines Lab, Washington University in St. Louis,St. Louis,MO (2012 – 2014)
Flexibly tackled and easily switched between projects in fast-paced, evolving lab. Worked effectively both autonomously and in teams.
Made decisions in short time frames as needed to move results forward. Tools used: Matlab, Django, Amazon Mechanical Turk,
Python, JavaScript, HTML/CSS.
 Worked as data scientistto develop effective system to gather bike and pedestrian activity level using Amazon Mechanical
Turk. Communicated clearly and concisely when collaboratingwith co-author on several publications.
 Delivered robust, production-quality codethat solves complex, real-world problems regardinghuman behavior data.
 Championed high quality,data-driven decision-making,resultingin well-developed metrics data analysisskills. Efficiently
collected and analyzed human behavior data (car,cyclistand pedestrian data) and co-authored paper published in American
Journal Of Preventive Medicine.
 Managed independent research process:identified and executed on key projects and brought them to conclusion in timefor
results to be beneficial.Created tools for collaborators to more easily extractuseful data from archives.
 Identified and used combination of technologies to create novel solutions. For example, used Amazon Mechanical Turk to
create tools and applied them to tag 25,000+ webcams within very small budget.
 Made important contributions towards development and maintenance of Archive of Many Outdoor Scenes (AMOS,
http://amos.cse.wustl.edu/), including novel montage viewinginterface and several features for webcam viewingand time-
lapseanalysis.
 Demonstrated flexibility,adaptability and creativity whilemovingthrough tactical implementation details,resultingin swiftly
deploying new features on AMOS and producinguseful data for collaborators.

2. Bill Chang billchang.e@gmail.com page 2 of 2
EXPERIENCE, CONTINUED
Research Assistant/Data Scientist Projects Included:
Exploratory Analysis on Large Image Datasets. Tools used: Matlab, Django, Amazon Mechanical Turk, Python, JavaScript, HTML/CSS.
 Refined, evolved and innovated new features to improve speed and functionality of software application.Created montage
viewing feature for camera view on Archive of Many Outdoor Scenes (AMOS), one of the only existinginteractivetools for
analyzingand retrievingimages directly on website.
 Created tools to find exemplar camera images and identified similarimages fromgiven exemplar by using combination of
subset PCA and unsupervised machinelearningtechniques.
 Invented and refined tool to compare side-by-sideimages from two different timestamps for given camera, which became
core website feature.
AMOS Image Tagging. Tools used: Amazon Mechanical Turk, Amazon EC2, Python.
 Created user-friendly HITon Amazon Mechanical Turk that allows workers to providekeyword tags for camera based on
several images pulled from liveAMOS website.
 Implemented automated command linetools to create, gather and retrieve results from batches of HITs.
 Used Amazon Mechanical Turk to tag majority of cameras on AMOS (25,000+) for lowcost ($0.05 per camera).
Detecting Physical Activity Level From Webcam Images. Tools used: Amazon Mechanical Turk, Python.
 Created user-friendly HITs on Amazon Mechanical Turk to allowworkers to find and label pedestrians,bikes and cars in
images pulled from several livewebcams on AMOS.
 Efficiently gathered data on total number of pedestrians and bikes observed from several traffic webcams located in
Washington,D.C. before and after a builtenvironment change.
 Collaborated closely with co-authors to publish findings regardingimpactof public policies on pedestrian and bikeactivity.
Supervised Classification Systems For High Dimensional Gene Expression Data. Tools used: Python, Scikit-learn, Java, WEKA
 Demonstrated familiarity with data structures,algorithms and complexity analysis. Parsed and imputed largeset of high-
dimensional gene expression data on Alzheimer's diseasepatients (300+ samples,8000+features).
 Used supervised machinelearning techniques and statistical techniques to build three different classification systems and
compared their effectiveness in predicting small setof test samples.
 Developed novel solutions using combination of technologies based on engineering requirements. Achieved 93% accuracy
usingSVM classifier and k-clusteringfeatureselection.
 Exhibited expertise with all aspects of softwaredevelopment lifecycle(architecturethrough release) and strongcodingskills
when developing efficient routines for testing and resultgathering.
 Used excellent written and verbal communication skillsand ability to communicate effectively to both technical and
nontechnical audiences. Co-authored high-quality research paper detailing results.
EDUCATION
M.S., Computer Science, 2014.B.S., Computer Science, second major in Psychology, 2011, Washington University in St. Louis,MO
PUBLICATIONS
Hipp, J., Pless,R., Adlakha,D., Chang, B., & Eyler, A. (2012). Can publicly availablewebcams and mechanical Turks beused to evaluate
physical activity policy and builtenvironment change?. Journal Of Science And Medicine In Sport, 15,S33.
doi:10.1016/j.jsams.2012.11.078.
Hipp, J., Adlakha,D., Eyler, A., Chang, B., & Pless,R. (2013).Emerging Technologies Webcams and Crowd-Sourcingto Identify Active
Transportation. American Journal Of Preventive Medicine, 44(1),96-97. doi:10.1016/j.amepre.2012.09.051.