Engineer Machine

*** **** ***, *** *** Pradosa Patnaik Ph: +1-352-***-****

San Jose, CA, 95134 linkedin.com/in/pradosa-patnaik github.com/pradosa127 LeetCode HackerRank mail:**********@*****.***

Education

Master of Science University of Florida, Gainesville FL May 2018

Computer Science GPA: 3.81/4

Bachelor of Technology Veer Surendra Sai University of Technology, India May 2013

Electronics and Telecommunication Engineering GPA: 9/10

Skills & Abilities

Languages: Java, Python, C++, Elixir, Hadoop, Spark Databases: Oracle, PostgreSql, MongoDB

Web Frameworks: Spring boot, Hibernate, Phoenix Tools: Git, Maven, AWS, Docker, Kubernetes, Kafka

Machine learning Framework: Tensor flow, Keras, Scikitlearn, SparkML Web Languages: HTML, CSS, JavaScript

Professional Experience

Cadence Design Systems, Inc. San Jose Machine Learning Intern (R&D) May 2017-Aug 2017

Participated in all phases of machine learning steps including data cleaning, developing models, validation, and visualization.

Developed a Transfer Learning based, assisted labeling system using Tensorflow and Scikitlearn with 77% accuracy.

Implemented Generative Adversarial Network (GAN) for semi supervised data generation with Tensorflow and Keras for computer vision applications.

Designed an occupancy detection system to predict occupancy of a room from various sensor data, using multivariate SVM with 99% accuracy.

TATA Consultancy Services Ltd., Bangalore System Engineer Aug 2013-Jul 2016

Developed RESTful API for pricing module of store management system for BestBuy, with JAVA/Spring boot with Oracle backend.

Involved in all stages of Software Development Life Cycle (SDLC) and worked in Agile Model to meet timelines

Automated regression test suite for RSS application with Selenium Web-driver and Java TestNG frame-work by reducing the testing effort by 80%.

Academic Projects

Restaurant Menu App [Flask, Python] June 2018

Designed a Restaurant Menu app using Python Flask framework performing CRUD operation through REST API endpoints on MySQL database.

Twitter Simulator [Elixir, JavaScript, PostgreSQL] Feb 2018

Simulated a highly scalable Twitter engine and multiple Twitter clients using JSON based Phoenix Web Sockets API.

Simulated 10000 JavaScript clients on a single Twitter engine performing login, tweet, retweets, and search operations.

Video prediction with Generative Adversarial Network (Deep-Learning) [Python, Keras] Oct 2017

Modeled a Generative Adversarial Network (Deep learning) to predict future video frames from the knowledge of previous frames for self-driving cars using Keras .

Distributed Bitcoin mining software on multiple cores [Elixir] Aug 2017

Designed a multi node Bitcoin-mining software using Elixir actor-model concurrency model.

Mined bitcoin up to 12 leading zeros utilizing more than 790% CPU capacity on an 8-core intel i7 machine.

Prediction of closed questions on StackOverflow (Kaggle data set) [PySpark, AWS] Apr 2017

Designed a Logistic regression classifier to predict ‘Close Questions’ on the Stack Overflow using PySpark on AWS clusters.

Mined Stack Overflow posts (6GB text data) using NLTK libraries for preprocessing and feature extraction.

Achieved test accuracy up to 85% on a test set of 100 questions.

Lexical Analyzer, Parser, and Interpreter [Java] Nov 2016

Built a lexical analyzer/scanner and a recursive descent parser for a small JVM based programming language.

Implemented abstract syntax tree, LeBlanc Cook table, type checking, code generation and other compiler components.

Relevant Courses

Elements of Machine Intelligence Advanced Datamining Deep-learning Analysis of Algorithms Advanced Data Structures Distributed Systems Datacenter-management Programing Language Principles UX Design Approximate query processing

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