1. May2016
May2011
Mar2013
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)
TECHNICALSKILLS
Languages: Java, Python, Python-Pandas, Django, scikit-learn, Python Numpy, R, SQL, C,Pl/SQL, ETL, Javascript
Platforms: 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)
PROFESSIONALEXPERIENCE
Research Assistant (RA), Indiana University, Bloomington Oct2015–June2016
RA 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 byimplementing PLSQL procedures at backend.
 Analyzed and reduced average execution time of report generation from 10 hours to 7 hours by effective query optimization.
ACADEMICPROJECTS
Yelp DatasetChallenge [Java, Python, MySQL, Apache Lucene, scikit-learn] Oct 2015 – Dec2015
 Designed model for multi label classification problem by researchingfeatures 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(KaggleProject) [Python, scikit-learn, Machine Learning] Mar 2015 – May2015
 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 SimulatorAgent [Java] Jan 2015 – Mar2015
 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 rectifyingclassificationerrors [Python, Ensemble Learning] Nov 2014 –Dec2015
 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