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I'm Vinutha Ananthachandran

LinkedIn GitHub Gmail Resume

About

MS CS Student at USC | Ex-Sr. SDE at HPE | vGHC'22 Attendee

An ardent problem solver with 5+ years of experience in software development. A quick-learner with a keen eye for detail. Proficient in designing and developing multiple products by collaborating with cross functional teams across geographies.

Education

January 2022 - December 2023

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University of Southern California

Master's In Computer Science

GPA: 3.7

September 2012 - July 2016

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Visvesvaraya Technological University

Bachelor's In Computer Science

GPA: 4.0

January 2022 - December 2023

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University of Southern California

Master's In Computer Science

GPA: 3.7

September 2012 - July 2016

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Visvesvaraya Technological University

Bachelor's In Computer Science

GPA: 4.0

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Technical Skills

Backend Languages

Python Java C C++ SQL ABAP NodeJS Express Flask

Frontend Languages

HTML CSS JavaScript EJS TypeScript AngularJS Bootstrap Android

Platforms

GCP AWS GitHub Docker

Tools

Jupyter VS Code Android Studio Google Colab Eclipse
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Backend Languages

Python Java C C++ SQL ABAP NodeJS Express Flask

Frontend Languages

HTML CSS JavaScript EJS TypeScript AngularJS Bootstrap Android

Platforms

GCP AWS GitHub Docker

Tools

Jupyter VS Code Android Studio Google Colab Eclipse

Work Experience

USC Viterbi School Of Engineering

Teaching Assistant - CSCI 585 Database Systems

Jan 2023 – Present

2023

USC Viterbi School Of Engineering

Teaching Assistant - DSCI 250 Intro to Data Science

Sep 2022 – Dec 2022

2022

Hewlett Packard Enterprise

Sr. Application Engineer

May 2017 – Nov 2021

Read More >

2017

Hewlett Packard Enterprise

Software Development Engineer

Sep 2016 – Apr 2017

Read More >

2016

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USC Viterbi School Of Engineering

Teaching Assistant - CSCI 585 Database Systems

Jan 2023 – Present

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2023

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USC Viterbi School Of Engineering

Teaching Assistant - DSCI 250 Intro to Data Science

Sep 2022 – Dec 2022

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2022

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Hewlett Packard Enterprise

Sr. Application Engineer

May 2017 – Nov 2021

Read More >

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2017

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Hewlett Packard Enterprise

Software Development Engineer

Sep 2016 – Apr 2017

Read More >

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2016

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Projects

  • A distributed & highly scalable business search and reservation web application implemented using AngularJS (HTTP callbacks) for the frontend and Node.JS (real-time AXIOS call) for the backend. [Desktop Link] [Mobile Link]
  • A full stack travel planning application; Implemented using Node.JS Express for backend, EJS for server-side rendering, Bootstrap for design, Jest test cases & JavaScript for client-side events handlers. [Desktop Link]
  • A full stack application that performs information retrieval on the web; Spearman correlation using search engine result overlap; A spider to crawl websites; An inverted index generator to enable swift searching of documents; Implemented using Flask for server-side rendering, Bootstrap for design, & JavaScript for client-side events handlers. [App Link]

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  • Android application to search locations based on location proximity, reserve and manage bookings.

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  • A DNA sequence allignment through dynamic programming approach and divide & conquer approach. [GitHub Link]
  • A genetic algorithmic approach for Travelling Salesman Problem using informed search. [GitHub Link]
  • A GO-Game agent that learns using min-max algorithm and alpha-beta pruning. [GitHub Link]

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  • A Resnet50, EfficientNetB0 and VGG16 classifier to classify videos using moving averages of the video frames. [GitHub Link]
  • A multi-layer perceptron neural network for binary classification of XOR, Gaussian, Spiral and Circle dataset. [GitHub Link]
  • A Binary Classifier of vertebral column dataset using K-Nearest-Neighbors. [GitHub Link]
  • A Linear, Multiple, and KNN Regressor to predict the Electrical Energy Output of Combined Cycle Power Plant. [GitHub Link]
  • A classifier of human activities based on time series obtained by a WirelessSensor Network. [GitHub Link]
  • A decision tree to determine if a patient has accute inflammation or has accute nephritis based on bodily symptoms. [GitHub Link]
  • A Lasso and L1 penalized gradient boosting tree for communities and crime dataset. [GitHub Link]
  • A Random Forest And XGBoost Model Trees for component failure detection in the APS system. [GitHub Link]
  • A Multi-class and Multi-Label Classification Using Support Vector Machines, K-Means Clustering, and Monte Carlo Simulation for species, genus and family detection of frogs. [GitHub Link]

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  • A Cost driven map-reduce task-level scheduling algorithm in a heterogeneous cloud environment.
  • A Website anti-spoofing technique by pattern generation and validation in a homogenous cloud environment.

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  • A distributed & highly scalable business search and reservation web application implemented using AngularJS (HTTP callbacks) for the frontend and Node.JS (real-time AXIOS call) for the backend. [Desktop Link] [Mobile Link]
  • A full stack travel planning application; Implemented using Node.JS Express for backend, EJS for server-side rendering, Bootstrap for design, Jest test cases & JavaScript for client-side events handlers. [Desktop Link]
  • A full stack application that performs information retrieval on the web; Spearman correlation using search engine result overlap; A spider to crawl websites; An inverted index generator to enable swift searching of documents; Implemented using Flask for server-side rendering, Bootstrap for design, & JavaScript for client-side events handlers. [App Link]

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  • Android application to search locations based on location proximity, reserve and manage bookings.

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  • A DNA sequence allignment through dynamic programming approach and divide & conquer approach. [GitHub Link]
  • A genetic algorithmic approach for Travelling Salesman Problem using informed search. [GitHub Link]
  • A GO-Game agent that learns using min-max algorithm and alpha-beta pruning. [GitHub Link]

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  • A Resnet50, EfficientNetB0 and VGG16 classifier to classify videos using moving averages of the video frames. [GitHub Link]
  • A multi-layer perceptron neural network for binary classification of XOR, Gaussian, Spiral and Circle dataset. [GitHub Link]
  • A Binary Classifier of vertebral column dataset using K-Nearest-Neighbors. [GitHub Link]
  • A Linear, Multiple, and KNN Regressor to predict the Electrical Energy Output of Combined Cycle Power Plant. [GitHub Link]
  • A classifier of human activities based on time series obtained by a WirelessSensor Network. [GitHub Link]
  • A decision tree to determine if a patient has accute inflammation or has accute nephritis based on bodily symptoms. [GitHub Link]
  • A Lasso and L1 penalized gradient boosting tree for communities and crime dataset. [GitHub Link]
  • A Random Forest And XGBoost Model Trees for component failure detection in the APS system. [GitHub Link]
  • A Multi-class and Multi-Label Classification Using Support Vector Machines, K-Means Clustering, and Monte Carlo Simulation for species, genus and family detection of frogs. [GitHub Link]

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  • A Cost driven map-reduce task-level scheduling algorithm in a heterogeneous cloud environment.
  • A Website anti-spoofing technique by pattern generation and validation in a homogenous cloud environment.

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Leadership & Involvement

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Contact Me

LinkedIn GitHub Gmail Resume

Copyright © 2023 Vinutha Ananthachandran. All rights reserved.

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