akhil is currently a CS student at Georgia Tech.
he is a full-stack dev and is looking to learn as much as possible.
he usually doesn't describe himself in the third person.
things he uses the most:
• Created the first implementation of the popular word game ghost – where players build upon a word without saying the last letter
• Built live, scalable multiplayer functionality and three singleplayer bots using web sockets, Datamuse API, and intelligent data filtering and processing
• Created an affordable, compact home security device using Raspberry Pi Zero and 3D printed parts
• Coded RaspController website controls and Open CV Facial Recognition capabilities for the device
• Constructed a formal protocol for the Tor handshake, a cryptographic protocol with over 2 million daily users, with information from capturing Tor network traffic and analyzing source code.
• Developed an upgraded Tor handshake protocol, with improved censorship resistance, latency, and packet size, by changing certificate authentication and message ordering.
• Solved subcases of a mathematics optimization problem involving the value verification of unknown coins and computational efficiency.
Optimized SolutionHealth’s investments into medical equipment and advertising by analyzing patient demographics, facility leakage, and contributors to patient outmigration.
Developed a user interface to display cardiovascular and oncology treatment trends for 40+ health facilities
*my presentation and findings cannot be shared due to confidentiality reasons
• Trained a machine learning model using Tensorflow and Python to predict sign language gestures
• Developed an online educational platform with React and Flask to teach sign language words and translate webcam-inputted sign language in real time
• Designed a mobile application to eliminate bad that uses facial recognition to intelligently capture photos only when all subjects smile and open their eyes.
this website!
• Built a telematics device to detect driver distractedness based on movements including eating, talking, and removing a hand from the wheel, using Raspberry Pi, artificial intelligence, and the State Farm driving distractions dataset
• Currently building a website for users to easily configure a Raspberry Pi device and view a data dashboard displaying their driver distractedness score, speed, braking, and more
• Trained a machine learning model to predict crop yield in different countries based on location, year, weather, etc. with a 98.60 R2 score using sci-kit learn.
• Developed a website which displays predicted metrics and shows farmers how to optimize their crop choices.
• Programmed autonomous robot movement, camera vision processing, autonomous scoring mechanisms, and driver controls for three FRC robots.
• Served as a mentor, motivator, and organizer for a 20+ member robotics team. Hosted and organized FLL Jr. events for over 400 children in 30+ teams.
