GOOGLE DEVELOPER STUDENT CLUBS

As part of the Core team at Google Developer Student Club, Ramaiah Institute of Technology (DSC-RIT), We conduct workshops about technologies like Android, Web, and Machine Learning and conduct competitions like Capture the Flag, Least Code, and Bug Bounty. We actively mentor and help Juniors and Students from different branches of engineering learn practical Computer Science.

  • I was the Lead Coordinator for the Internal Smart India Hackathon- 2022 in my college, with 200+ participants to shortlist teams that would represent the college at the Nation level Smart India Hackathon 2022.
  • Taught the basics of python in a workshop to over 120 participants.
  • Organized a Bug Bounty competition where the participants had to eliminate various kinds of bugs in code. This competition aimed at improving the debugging skills of the participants.
  • Organized a "Capture the Flag"(CTF) event where participants had to find the flags in the various questions which were hidden in websites, games, GitHub, and many more. This competition aimed to introduce the participants to developer tools, cookies, local storage, bugs in websites, GitHub, steganography, cryptography, and most importantly innovative thinking.
  • Organized a Code wars competition during which the participants were made to compete with their opponents in a knockout format. This competition tests the participants in their problem-solving skills and design skills.

THE BHARAT SCOUTS AND GUIDES

The Mission of Scouting and Guiding is to contribute to the education of young people, through a value system based on the Scout Promise and Law, to help build a better world where people are self-fulfilled as individuals and play a constructive role in society.I was a member of THE BHARAT SCOUTS AND GUIDES from 2010 to 2016 . I volunteered for the Swatch Bharat Abhiyaan and Sanitation awareness campaigns in villages near Doddaballapur and Davanagere.I am a Recipient of the Rajyapuraskar Award.

AWARDS

Winner Smart India Hackathon 2019

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Winner Smart India Internal Hackathon 2019

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Runner-up Code Rush 2019

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Best Student of the School, Class of 2018

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Work Experience

Grab

Software Engineer Intern (Feb 2022 - Present)

Working as a Backend Developer in the compliance team of Grab Financial Group.

Graphene Services Pte Ltd

AI Engineering Intern (Feb 2021 - May 2021)

Graphene uses AI-powered market research to provide unbiased insights better, faster and cheaper.
Developed and implemented a hierarchical clustering algorithm using fastText embeddings.
Built a model to detect Continuous Sentiment Intensity that achieved state-of-the-art results in the FMCG domain.
Built modules to find intracluster similarity and intercluster similarity by exploring the use of fasttext embeddings,glove embeddings and fuzzy matching.

Projects

ENGINETUBE

Built an object-detection based recommendation engine for advertising with 87% using deep learning. The main idea of the project is a unique recommendation system which analyses the objects in a video and recommend the most relevant advertisement to the customer on the basis of the frequency of the objects detected in the frames of the video as well as the various parameters related to the business model. The technologies and languages which were used for this purpose were Tensorflow for the implementation of object detection, Python for building the recommender & the object detection model and MERN stack for the web application to demonstrate the working of "EngineTube".

PULMACARE

The goal of the project was to build a web platform which enables detection of Pneumonia from ChestXrays and stores records of Patients history. I developed a CNN to detect Pneumonia in patients from their Chest X-Rays and built a web app for the same.Technologies Used: Flask, TensorFlow , MySQL, HTML5, CSS3.

FACEPE

The goal of the project was to build a android app with web-based backend for a payment system which doesn’t require a device or internet availability from the customer end.The payment app contains a easy-to-use wallet for shopkeepers. It includes three-factor authentication consisting of Face recognition, Fingerprint recognition and an unique pin for all the customers. I Developed a Face Verification system for over 10000 images by Implementing the Face Net model architecture. I developed RESTFUL APIs and designed the database of the application. Technologies Used: Flask, TensorFlow ,MYSQL.

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