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About Me

I am Rohan Pillai, currently a Software Engineer at Alkira, Inc. I pursued Master of Computer Science at North Carolina State University, Raleigh & my Bachelors in Information Technology from Nirma University, India. I have done three internships at Samsung Research Institute, Bombardier Transportation and L&T Technology Services. I am quite interested in working on software development using different paradigms. I have done projects in several programming languages like Java, Python, Ruby, JavaScript, etc. Outside my professional life, I like to travel ✈, swim πŸŠβ€ & watch movies πŸŽ₯.

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Rohan Pillai's Projects

expertiza icon expertiza

Expertiza is a web application through which students can submit and peer-review learning objects (articles, code, web sites, etc). The Expertiza project is supported by the National Science Foundation.

go-coverage-report icon go-coverage-report

Github action that publishes the Go Coverage report as a comment in the Pull Request

student-progress-card-app icon student-progress-card-app

This is an Android application which helps students access their marks of Mid-Terms and Semester End Examinations in real time. It uses Gmail API & Graph API among various other tools for basic functionalities.

web-based-graphical-password-authentication-system icon web-based-graphical-password-authentication-system

Web Based Graphical Password Authentication System is a web based application that can be used in any system to allow users to sign up and log in using a different model other than the static passwords. In normal authentication systems, static passwords are used by users to get in the system but it is a known fact that static passwords are very easy to hack. Thus in this system, a user can select certain points in an image and use them as their password. They are immune to basic hacking techniques like brute force attack & dictionary attacks.

wikipedia_article_count_words icon wikipedia_article_count_words

Query https://en.wikipedia.org/w/api.php?action=parse&section=0&prop=text&format=json&page=[topic] to get the [topic] Wikipedia article, and then count how many times the string [topic] appears in the article's text field.

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