Software Engineering InternMay 2017 - June 2017 HackerRank
The aim of my internship was to get testcases parallelization in execution from scratch.
Whenever a client makes a request to the CodeChecker (judge) to run a submission on multiple test files. Judge process the request and execute submission on each testfile one by one in a sandbox environment. Concept of testcases parallelization is to run the same submission on multiple servers on different testfiles i.e. splitting test files over multiple servers. This will increase the average throughput and decreases turnaround time for the submission.
After 4 weeks of started working on parallelization the code was finally merged to master. And went in production on Monday 26th June 2017.
Kernel Driver DeveloperMay 2016 - Dec 2016 ReactOS Foundation
My project proposal was selected in Google Summer of Code 2016 by ReactOS organization. There I developed SATA-AHCI driver from scratch.
Web Security and Vulnerability ResearcherNov 2014 - Dec 2016 Collegespace.in
I contributed this society by managing up the website in terms of web security, website management, and development. I also took part in all active tech event being conducted by this society.
Execomm MemberSep 2015 - Jun 2016 IEEE NSIT
I worked in IEEE-NSIT college society as a core member that organizes various technical events and SIGs for students.
- Website Development
- Conducted Programming SIGs
- Organized technical events and Quizzes
Software Engineering InternDec 2015 - Jan 2016 HackerRank
During my one-month winter internship, I worked on Platform security and Aws SDK.
- Automated security testing framework
- CodeChecker Performance & Analytics
- Integrated Aws C++ SDK in CodeChecker
Computer Science UG2014 - Current NSIT, Delhi
High School2008 - 2014 RPVV, Shalimar Bagh
Atom OS2014 - Current GitHub
A multitasking monolithic Kernel based x86 targeting Operating System written in C# from scratch aiming for high-level implementation of drivers in managed environment.
An interactive editor to design complex neural network without a single line of code, including many machine learning algorithms written from scratch.
An offline handwriting recognition pen like hardware and tensorflow based model implementation that will type what you write with it. Right now it supports English alphabets and numbers. That are 62 symbols!