Bhargav Srinivasan

Software Engineer

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About Me

I'm Bhargav, a second-year graduate student from University of Southern California, majoring in Computer Science. I am looking for full-time opportunities as a Software Engineer after my graduation (May 2019). My interests are full-stack software development, machine learning and data analytics.

I'm currently interning this fall as a Software Developer at Emotive, a startup based in Los Angeles, California. I developed the core features of the product using Django and built the frontend using HTML, CSS and AngularJS.

I'm also enthusiastic about machine learning and deep learning. During my senior year in my undergrad, I interned at Bosch, where I developed a deep learning convolutional neural network (CNN) algorithm, to detect disorders in the eye. I used Python and libraries such as Theano, Lasagne and Tensorflow to build the neural network and train it. My project improved the performance of the model, achieving an accuracy of 92%.

My interests outside the computer sciences include, but not limited to, movies, soccer, playing video games and listening to podcasts.


Software Developer Intern

  • Emotive helps brands retain their customers through personal relationships over text message.
  • Developed REST APIs for the Emotive messaging platform to communicate with the backend server, using Django. Used Twilio API to handle messaging and Google NLP to obtain customer feedback sentiment.
  • Streamlined integrations with customer support tools such as Zendesk and Freshdesk for brands.
  • Designed the core feature called Sequences, where brands can schedule periodic texts to customers to obtain feedback, send reminder messages or recommend new products. Built schedulers using Celery and RabbitMQ.

Robert Bosch Engineering and Business Solutions


  • Developed, optimized and deployed a deep learning convolutional neural network (CNN) algorithm, to detect the condition called Diabetic Retinopathy in the retina of the eye.
  • Trained the model on over 80,000 images of retinal scans and achieved an improved accuracy of 92%.
  • Researched and created methods to find regions of hemorrhages and exudates in the eye with R-CNN (Regions with CNN).
  • Programmed with several machine learning tools such as Theano, Lasagne, Caffe, Keras, and TensorFlow.


University of Southern California

Aug 2017 - May 2019

Master of Science in Computer Science

GPA: 4.0

Courses Taken

Sir M. Visvesvaraya Institute of Technology

Aug 2013 - June 2017

Bachelor of Engineering in Computer Science

Aggregate Score: 78.3% (First Class with Distinction)


Marvel Character ChatBot

An educational chat-bot app for kids to interact with their favorite marvel superheroes. Implemented with Marvel API and Microsoft Cognitive Services API to create the chatbot.
Demoed at Hacktech 2018 (Caltech)

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Fantasy League Market Watch

A simple Python script to keep a tab on players' rise and fall in price and aid the user in making transfers.

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An interactive web application to demonstrate the working of a simplified blockchain.
Developed using HTML,CSS, AngularJS and SHA-256 javascript library for encryption.

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Fruit Rage

A game-playing AI agent in C++ to determine the best next move for a player up to 9 moves ahead.

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Sorting Algorithm Visualizer

A computer graphics project using OpenGL and C++. Visualized various types of sorting algorithms on a randomly generated array of numbers.

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