Hi, my name is Mayank Pandey
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About me

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I'm an international student at the University of South Florida pursuing a Bachelor's degree in Computer Science. I have completed an independent web development course from Udemy which has allowed me to work on some of the most exciting projects.

As a developer, I'm wildly enthusiastic about coding, problem-solving, and software development. I am always ready to learn to grow professionally in this field.

I am proficient in JavaScript, Python, Java, HTML5, CSS3, React, SCSS, Flask, Express.js, Node.js, SQL, PostgreSQL, and Git. Furthermore, I am familiar with Redux, SQLite, and Django.

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Experience

Salesforce - Tableau

Spearheaded creation of a smoke test framework, with 20 predefined manual tests, utilizing the Embedding API v3 to sign off on test passes for various test environments at different points in our software development life cycle.

Reconciled cypress tests for the Embedding API v3 by introducing functionality to run tests against both local and hammerhead servers via Gradle on the monolith and gitlab pipeline.

USF - Computer Science Department

Developed a quiz tool web application that supports asynchronous peer instruction as part of NSF-Funded research aimed at identifying distractor answers for multiple choice questions.

Debugged and tested the features developed by creating and utilizing shell scripts to automate the task of generating quiz attempts and checking them against expected hand-calculated results.

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USF - Mechanical Engineering Department

Developed robust web-based simulations for a course in Numerical Methods using HTML, CSS, Javascript, and open-source libraries aiding NSF-Funded research on the benefits of adaptive learning by providing explorable explanations.

Crafted requirements for the simulations and ideas after consultation with distinguished professor, Dr. Autar Kaw, resulting in a holistic deliverable encompassing a range of concepts including Runge’s Phenomenon, Riemann sum, and many more.

Authored an extensive documentation of over 80 pages to help novice developers understand the PhET framework reducing the difficulty in comprehension by 70%

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Leadership

Hackabull Director

Organized USF’s fourth-annual hackathon, Hackabull, overseeing a team of 10 in constructing the sponsorship packet, planning workshops, handling logistics and budget, and communicating with sponsors to host an incredible event with over 240 attendees.

Acted as the liaison between the SHPE USF chapter and Hackabull team, as the head of communications for SHPE, to ensure proper communication and support by defining clear targets, objectives, and expectations for both bodies.

Head of Communications

Designed and distributed weekly newsletters curated to meet the needs of STEM students, providing information about upcoming events and employment opportunities resulting in greater retention, participation, and career development.

Supervised USF’s annual Engineering Expo to educate over 10,000 K-12 students on the importance of math, science, engineering, and technology within their lives

Projects

Detect This Face

Detect This Face is a magic brain that lets users insert an image URL to then capture and display the faces present in that image.

Comprehensive and attractive design at the Front-End allows for optimal user experience.

This Web App was developed with tools like React.js, Node.js, Express.js, PostgreSQL, Clarifai API, bcrypt and many more.

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Twitter Revamped

Twitter Revamped is a social networking platform. Users are able to register and create posts which are then displayed on the stream.

Supports features like followers and following. In addition, logged in users can checkout the posts created by any specific user.

This Web App was developed with Flask, PostgreSQL, bcrypt, HTML5, and CSS3.

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Ping Me!

Ping Me is a Web Chat App that features different chat rooms like Lounge room, Games room, News room, and Coding room.

It also has user registration and authentication functionalities.

This chat app was implemented using Flask, Flask-SocketIO, PostgreSQL, JavaScript, HTML5, and CSS3.

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Publications

Probabilistic Machine Learning Using Bayesian Inference

This project explores how Machine Learning algorithm is improved by using Bayesian Inference. For this purpose, I suggested a problem regarding Youtube's use of Machine Learning to predict how many people will watch a video they come across on their recommendations or search feed and how this data develops an intelligent sorting algorithm that can be used to model such data for future videos. This is one of the ways I believe services like Youtube can improve their algorithms, However, such a large scale service could potentially have smarter methods for implementing this idea.

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Contact

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