Hi! I'm Rohan Chandra. Thanks for visiting my website!
I'm 26 years old, and am currently a Fullstack Machine Learning Engineer for Bana Solutions,
I have a BS in Computer Engineering with a Business Minor
from the University of Virginia (May, 2022). I'm currently pursuing a Master's of Science
in Robotics and Autonomous Systems from Johns Hopkins University (December, 2026).
Outside of work, I love to do the following things:
I built a RAG Powered AI Agent to synthesize the numerous hard-to-read, verbose, and scattered help articles on USDA.gov into a single source. Users could then send natural language queries to the chatbot and recieve natural language responses back. Placed in the top 10 finalists among 50+ teams scattered across the East Coast.
Led the creation and development of the robotics software education program for
Nova Labs Robotics, ensuring that its 5 FTC (First Tech Challenge) teams receievd
the training needed to become excellent developers and future leaders.
Established and taught RobotGo, an 8 week FTC Software bootcamp giving students
hand-on experience with robotics programming concepts (object recognition, sensor fusion,
obstacle avoidance, odometry, tele operation and autonomous movement)
and software development best practices e.g. using software version control systems.
Video lectures were produced as well, and can be seen on the
Nova Labs Robotics YouTube channel.
As a result, students have advanced to the state championships the past two seasons,
and regularly volunteer to help rookie teams develop their own software skills.
Built TrueForm as a submission to the HooHacks 2022 Hackathon competition. TrueForm analyzes real-time video of users performing exercises to spot and highlight potential injury-causing form mistakes.
Created Virtual Fitness Trainer, an echoAR-powered augemented reality fitness app that shows guides users in performing complex exercises like squats by providing them a human-like avatar that they can follow. Achieved a finalist position in our category (Health and Wellness). Won the "echoAR - Best Use of echoAR" award, and was invited to participate in the Microsoft Garage program.
Wrote 13 Artificial Intelligence algorithms from scratch, covering topics including, but not limited to, Reinforcement Learning, Naive Bayes Classifiers, Decision Trees, State Space Search, and Constraint Satisfaction Problems
Implemented Perception, Planning, and Control algorithms using ROS in Python. Because of COVID-19, algorithms were tested on a simulated robot in Rviz. Algorithms developed included PID, Follow-the-Gap, and SLAM
Assembled and programmed a line-following robot using the TI-RSLK MAX Robot Learning Kit. Planned the control flow using a Mealy FSM and used sensor data from bump and line sensors to inform a PWM Control Loop how to run the motors. Achieved the second-fastest time in a race against my peers