Neeraj Devadath

acryh7@r.postjobfree.com https://www.linkedin.com/in/neerajdevadath +1-631-***-****

Objective Seeking a full time opportunity that involves continual increase in my learning curve. Education

Stony Brook University Masters in Computer Science (GPA 3.67) Expected Graduation: Dec 2015 University of Pune, India Bachelors in Computer Science (77.8%) June ‘09 Ranked second in University in Second, Third and Fourth Year of Engineering Courses Algorithms Databases Data Mining Distributed Systems Network Security Data Science Technical Skills

Proficient - C++, Visual C++,Java,VB .NET, Python, .Net Framework 3.5, Spring, MS Visio,SQL,NoSQL Self-learnt – Python, C#.NET, R, Matlab, Hibernate, Microsoft Project Planner Development Tools/Platforms – Visual Studio 2012, Eclipse, NetBeans, Visual Studio 2005, Pycharm Modeling and Simulation Tools – NIMAX, MATLAB (Simulink), R, Tableau, Shiny Operating System – Windows 7, Windows XP, Linux

Version Control – Microsoft Visual Source Safe, Tortoise SVN, Git Repository Web – XML, HTML, Web Services using WCF, WPF,CSS

Work Experience

Amazon

Roles handled - Software Development Intern

Global Secondary Indexes AWS DynamoDB, S3, Redis, C#.NET, Java May ’15 - Aug ‘15

Secondary Indexing Solutions to resolve important storage concerns that exist in multi-tenant storage systems.

Highly coordinated interaction between multiple AWS Services that explored different areas, sparked new ideas.

High performance, low latency code was developed that was scalable for intermediate machine load.

Concept level presentation to higher management that potentially leads to product development. TATA CONSULTANCY SERVICES LIMITED

Roles handled – Module Lead, Designer, Software Developer Text Mining in Bio-Medical and Automobile Domain C++, C# .NET, Python, Weka May ’13 - May ‘14

Developed a Hidden Markov model based bi-gram and tri-gram predictor that had an accuracy score of 85 %

Prototyped document summarization by identifying domain-specific terms in a paragraph.

Adjudged as one of the potential path-breakers at Tata Research Design Development Center. Auto Evaluation System C++, C#.Net, Visual Studio 2005, Microsoft Access DB, Orca Jan ‘11 - May ‘13

Designing new Automobile vehicle models from designs provided by equipment manufacturers to reduce variation and delay in the vehicle production cycle.

Process Improvement by reducing cycle time by 20% by implementing a Six Sigma in Java for automation.

Worked on an Entire Integrated Setup for a live Demo Launch guiding as well as coordinating all aspects. Diagnosis and Automobile Log Converter C++,C#.NET, National Instruments Explorer, SQL Dec ‘09 - Dec ‘10

Diagnose vehicle component health through various tests and predict next failure of individual components.

Client Appreciation in terms of robust design as well as prediction accuracy.

Involved in mentoring fresh talent to Industry Domain Knowledge. Hardware Driver Development C++, C#, Java, National Instrument Vector CAN Hardware Mar ‘11 - Oct ‘11

Design and development for building a testing framework for effective Automobile testing before the actual start of Production reducing costs and efforts by virtual testing.

Developed Analog, Digital Drivers, Synchronization module to handle inter-driver real-time synchronization using National Instruments Hardware, dSPACE Hardware. Explored MATLAB Simulink prototypes for verification. Recent Projects

Implementation of Chain Replication Protocol for Fault Tolerance C#.NET,Java, Python, distAlgo Spring 2015

Implemented Chain Replication and Handling failures in a multi-threaded environment simulating a Banking Domain Environment. Comparison of performance of two languages based on language constructs and concurrency control mechanisms. Applying transactional logic to a lower level activity, increased reliability.

Further applied chain replication knowledge to craft solutions at Internship to produce a product with better vision and end-to-end customer focus.

Answer Quality Prediction on Stackoverflow Python, Weka, Google Fusion Tables Fall 2014

Identification of subjective measures and features of quality using principles of Data Mining and applying machine learning algorithms for prediction with an accuracy of over 85%.

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