Data Software Developer
Resume:
Anshuman Dev Vyas
*************@*****.***
https://www.linkedin.com/pub/anshuman-d-vyas/3a/473/bb8
Education:
The John Hopkins University, Baltimore, Maryland
Specialization in Data Science May 2015
The George Washington University, Washington, D.C.
Masters in Computer Science, GPA: 3.3/4.0 May 2013
Jaypee Institute of Information Technology, Noida, India.
Bachelors of Technology in Information Technology, GPA: 66% May 2011
Professional Experience:
Junior Software Developer, Eze Software Group, Boston Sept 2013 - Present
o Responsible for the development and maintenance of the Eze Trad ing application which allows the users to create,
allocate, and execute orders with flexible, real-time blotters.
o Worked on a 4 month project which required adding functionality in the Eze Execution Management System, so the
user can slice child orders out under a single trade quickly.
o Worked on a 4 month project which required adding functionality in the Eze Order Management System, so the user
can group multiple trades under a list, and then send to one or more brokers.
o Worked on a couple of small 1-month enhancements in the Eze Execution Management System.
o Worked on several client hotfixes, showstoppers and other bugs.
o Created test documents.
Software Engineer – Machine Learning, Veritas Scientific Corporation, Virginia May 2012 - Sept 2013
o Performed analysis on ERP brain responses of humans.
o Data Cleaning and outlier removal was performed in Weka.
o Signals were classified using both self-designed and well known existing classification algorithms in Weka.
o Performed an experiment on people from different nationalities and analyzed their brain responses to discover their
recognition of celebrity faces.
Business Analyst, Department of Health Policy, George Washington Univers ity June 2013 - Sept 2013
o Responsible for communicating effectively with d ifferent departments to gather requirements.
o Solved organizational information problems by analyzing data received from staff and faculty.
o Version control of documents was also performed.
Student Financial Assistant, Department of Health Policy, George Washingt on University July 2012 - May 2013
o Responsible for calculation and maintenance of the labour distribution, redistribution and rent sheets of the
department.
Web Developer, Academic Technologies, George Washington University March 2013 - May 2013
o Responsible for developing web applications using PHP, JavaScript, CSS and HTML.
Related Projects:
Natural Language Processing – Text Prediction: April 2014
The goal of this project was to build a predictive text application, which takes a phrase with one or more words as input and
predicts the next word as output. Data used to build the model was from different sources such as tweets, blogs and news. Data
cleaning was performed on the data, after which tokenization was done. Techniques such as Linear Interpolation and Backoff
models were implemented. The final app was deployed on shinnyapps.io.
Link to my work published on RPubs: http://rpubs.com/anshumanvyas29/nlp_text_prediction
Link to the application: https://anshumanvyas29.shinyapps.io/ShinyApp/
Machine Learning - Human Activity Recognition: November 2014
The goal was to predict the manner in which the participants did exercise. Data cleaning was done, after which machine learning
algorithms such as Decision Trees and Random Forests were applied to build prediction models. 99.3% accuracy was achieved.
Link to my work published on RPubs: http://rpubs.com/anshumanvyas29/44766
Regression Models - Motor Trend Analysis: October 2014
The purpose of this analysis was to explore the relationship between a set of variables and miles per gallon (outcome) . The
most relevant variables for predicting the outcome were calculated and linear models were fit. Q uestions such as “Is an
automatic or manual transmission better for mpg” were answered.
Link to my work published on RPubs: http://rpubs.com/anshumanvyas29/motor_trend_analysis
Statistical Inference – Analyzing the ToothGrowth Data September 2014
Performed basic exploratory data analyse s. Confidence intervals were calculated manually and through Hypothesis tests to
calculate the true difference in means for length.
Built a Search Engine August 2012
A web crawler was built which was used to collect content from web pages to use in the search engine. Following that, an index
was made which was fast enough to scale to a large collection of pages. Finally, a method for finding the best page for a search
query, similar to the way Google ranks pages, was implemented.
Data Mining- Classification May 2012
Naive Bayes and K-nearest neighbour algorithms were used to classify a breast cancer data set in Weka and t he two results
were compared. Attribute selection was performed to note changes in accuracy. New incoming instances were also scored by
the Weka scoring plugin in Pentaho Data Integration tool.
Localization techniques of a robot April 2012
The following techniques were implemented:
o Monte-Carlo Localization
o Kalman Filters
o Particle Filters
A* Search and Dynamic Programming: April 2012
The two algorithms were implemented to solve the path finding problem of a robot. Both of them were analyzed for their
advantages and disadvantages in different scenarios.
Handwriting Recognition and Matching Software April 2011
Handwritten input was taken and was recognized by the software. Matching of input with already existing text in the database
was also done.
Related Research Papers:
Wrote a research paper on Mining Sequential Patterns.
Frequent subsequences as patterns were discovered in a sequence database. Approaches such as the Apriori Based Approach
and Frequent Pattern Growth Approach were discussed along with a numerical example for each.
Wrote a research paper on Anti-Patterns.
Patterns which are ineffective or counterproductive in practice were identified. They were presented from three major
viewpoints: the software developer, the software architect and the software manager.
Technical skills:
Programming : C#, Java, R, Python, SQL Server, C
Data Mining: Weka
Data Products: Shiny(Web application framework for R), RStudio Presenter, Slidify
Web Technologies: HTML, CSS, JavaScript
Version Control: Team Foundation Server, GIT
Issue Tracking Software Jira
Software Development Methodologies: Agile, Waterfall
Other: MS Word, Excel, PowerPoint, Statistical Methods, SQL Server Profiler
Certification:
The Data Scientist’s Toolbox by John Hopkins University on Coursera. Certification earned on August 3, 2014.
R Programming by John Hopkins University on Coursera. Certification earned on August 3, 2014.
Getting and Cleaning Data by John Hopkins University on Coursera. Certification earned on September 4, 2014.
Exploratory Data Analysis by John Hopkins University on Coursera. Certification earned on August 31, 2014.
Reproducible Research by John Hopkins University on Coursera. Certification earned on September 28, 2014.
Statistical Inference by John Hopkins University on Coursera. Certification earned on September 28, 2014.
Regression Models by John Hopkins University on Coursera. Cer tification earned on November 2, 2014.
Practical Machine Learning by John Hopkins University on Coursera. Certification earned on November 30, 2014.
Developing Data Products by John Hopkins University on Coursera. Certification earned on December 27, 2014.
Data structures from Aztech computer consultancy division, India. Certification earned in 2007-2008.
Introduction to java programming from New Horizons computer learning centers, India. Certification earned in 2010.
Additional Courses:
Scored 92.2 percentage in “Introduction to Artificial Intelligence” by Stanford University on udacity.
Scored 95 percentage in "Programming a Robotic Car" on udacity.
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