May 2016 May 2011

Mar 2013

Masters of Science (MS) in Computer Science (CS) - Indiana University Bloomington (GPA 3.9/4.0)Bachelors of Engineering (BE) in Computer Engineering - University of Pune, India (First Class)

TECHNICAL SKILLS

Languages: Java, Python, Python-Pandas, Django, scikit-learn, Python Numpy, R, SQL, C,Pl/SQL, ETL, JavascriptPlatforms: Windows, UNIX, and Linux Databases: MySQL, Oracle, PostgreSQL Tools: Weka, MySQL Workbench, IBM InfoSphere Datastage 8.1, GitHub, Rational ClearCase, Apache Lucene, Eclipse, Highcharts Miscellaneous: Supervised learning, Modelling, Ensemble learning, Machine Learning, Scripting Language, MVC framework,REST Certifications: Oracle Certified Associate (OCA)

PROFESSIONAL EXPERIENCE

Research Assistant (RA), Indiana University, Bloomington Oct 2015 – June2016RA in STAR-AI Machine learning Lab, Prof Sriraam Natarajan [Java, Python, MySQL, PostgreSQL, Weka]

Analyzed and Designed features on medical data set using Python and pandas. Executed model RDB-Boost code on features. Built a block simulator & car simulator in Java, which generate the FOL based on state-action pair for experimentation. Generated 5-fold cross validation sets and ran soft margin RDNBoost classifier to generate regression trees for classification.

Philips Research Lab North America, USA May 2015 – Aug 2015 Research Intern, Data analysis and visualization experience.

Design Analysis & Retail Services (DARS) Platform [Django, Python, Python-pandas, jQuery, HTML5/CSS, highcharts, MySQL]

Built a research platform for Data Analysis and visualization for fast prototype development in capacity of Software Developer.

Applied Haystack tagging to data set, designed architecture for application and developed PL/SQL routine for data loading.

Developed analytical algorithms for different use cases. With help of JavaScript & Highcharts displayed results in application.

Prototyped ‘Defrost cycle problem’ in refrigeration system by identifying and analyzing problem with help of DARS tool.

IBM India Pvt. Ltd, Pune, India Feb 2012 – Jun 2014 Application Programmer, Data Warehousing

Revenue Restructuring [IBM InfoSphere Datastage 8.1, Oracle SQL] Developed an automated system to daily load and transform data using ETL tool for runtime report generation. Communicated with client for requirement gathering, was an active member of SDLC and designed flow of data for project. Awarded best performance award for passion, creativity, problem solving skills and outstanding work in project.VIL-MIS Aging Report (Vodafone India Pvt. Ltd.) [Oracle SQL]

Successfully delivered a report generation system by implementing PLSQL procedures at backend.

Analyzed and reduced average execution time of report generation from 10 hours to 7 hours by effective query optimization.

ACADEMIC PROJECTS

Yelp Dataset Challenge [Java, Python, MySQL, Apache Lucene, scikit-learn] Oct 2015 – Dec 2015

Designed model for multi label classification problem by researching features using Apache Lucene and Stanford NLP POS Tagger. Defined innovative problem statements (2) like identification of category of entity and predicting rating of restaurant for history. Used classifiers like CART, Gaussian SVM, and Random Forest. Used evaluation matric like RMSE (RMSE score : 0.92)

Don’t Get Kicked (Kaggle Project) [Python, scikit-learn, shell scripting, Machine Learning] Nov 2015 – Dec2015 Built models in Python for auto auction dataset to recommend ‘bad buy’ and ‘good buy’ for class imbalanced dataset. Performed 10-fold cross validation, statistical significance test, hyper-parameter tuning to select best model & accuracy. Modelled Gaussian SVM with different hyper parameters for classification (AUC = 0.9).

Microsoft Malware Classification Challenge (Kaggle Project) [Python, scikit-learn, Machine Learning] Mar 2015 – May 2015

Generated syntactic and semantic features from 400GB byte code data using state of the art NLP methods like n-grams. Performed feature selection and trained & tested different classifiers to build models that gives better accuracy. Used classifier like Random forest with different number of trees. Got best results with 300 trees (Log loss = 0.5234).

Car Simulator Agent [Java] Jan 2015 – Mar 2015 Built a car driving agent and environment in Java that allow the simulation of multiple car driving for learning agents. Generated the state-action pair results in discrete time space as first order logic which any learner can use for training.

Ensemble Classifier for rectifying classification errors [Python, Ensemble Learning] Nov 2014 – Dec 2015 Designed new ensemble classifier named “Assorter-Rectifier” which out performs at least one individual classifiers in each run. Written machine learning algorithms like Naïve Bayes, Logistic Regression in Python & Trained and tested on UCI-datasets.

ANIKET GAIKWAD 243 Buena Vista Ave, Apt #112, Sunnyvale CA 94086

EDUCATION

Email: anikgaik@indiana.edu Phone: +1 (812) 391-8837 LinkedIn: www.linkedin.com/in/gaikwadaniket GitHub: https://github.com/aniket-gaikwad