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MY PROJECTS
Welcome to my projects gallery. Click through each entry below to see the corresponding project details, and feel free to view them in fullscreen mode by clicking once on the images.
Projects: Text
Battlebot
For our final project in our Mechatronics course in spring 2021, my team and I designed and built a battlebot from scratch to fight against another team (see our victory here: https://www.youtube.com/watch?v=1hA2X_bso_s). The battlebot was equipped with proximity-triggered rotary saws, a 2 DOF automatic turret with computer vision aiming using a Pixy 2 camera, and Bluetooth-controlled driving.
Maze-Solving Robot
For my Mechatronics course in Spring 2021, I designed and built a maze-solving robot that used a Pixy 2 camera for color detection and infrared sensors for front and side wall obstacle avoidance.
Self-Balancing Robot
For my Mechatronics course in Spring 2021, I designed and built a self-balancing robot that uses PID control as the balancing mechanism. I tested 5V input (https://www.youtube.com/watch?v=uzDpoHJTUEc) vs. 9V input (https://www.youtube.com/watch?v=1qWrGrp72kY), and the latter proved to be much more stable.
Smart Haptic Cane
This cane is designed to help the visually impaired navigate through their daily lives with ease. The cane uses ultrasonic sensors to detect obstacles within 3 feet of the front of the cane, and sends feedback to the user by vibrating the handle when objects approach.
Autonomous Electric Vehicle
In the fall of 2019, I joined the Johns Hopkins Electric Jays team which aimed to create an autonomous electric vehicle to race in the upcoming 2020 EV Grand Prix. Each team member contributes to different subsystems of the kart, and my focus is on the steering system and track navigation.
Breathing Pattern Detection
For an advanced lab class in fall 2019 at Johns Hopkins, the class aimed to integrate multiple subsystems of a remote-control drone capable of detecting wounded soldiers on a battlefield and injecting the them with adrenaline or other saline compounds. My subsystem was breathing pattern detection, and I built multiple circuits to achieve this functionality.
HPC Embedded Bluetooth Low Energy Printing Service
From June to August 2019, I worked at Hal Technology, LLC to help embed a Bluetooth Low Energy (BLE) chip (HM-10) inside the motherboard of the HPC device so that it can print its test results to a BLE-compatible printer. Using BLE protocol, AT serial commands and the C-language platform for the device, I programmed the embedded chip successfully and wirelessly printed its first test case before the end of my term.
Magnetic Press for Creating BaM Pucks
For two continuous summers, I worked at the Naval Research Lab under Dr. Scooter Johnson. While assigned to the tedious task of pressing and annealing barium hexaferrite powder into magnetic pucks, I started to develop an idea for a faster and more automated method. In July 2017, I started to design a CAD model for my idea, and by August 2018, the design was published and a patent is pending for the device (No. 62/715406).
PillBox
During the 2018 fall semester, I participated with a partner in the PennApps fall hackathon, held at University of Pennsylvania. We started a project called PillBox, which is a device that reminds a frequent medication user to take their pills. An app will remind the user to take their meds, while an automated pill box will open the corresponding compartment to dispense pills.
ColorBeats
During the spring 2019 semester, I participated in HackTech, a hackathon hosted by the California Institute of Technology. My team and I built a device capable of identifying musical rhythm in a song and live outputting an LED spectrum to match the rhythm.
Malaria Detection Using Electrical Impedance Analysis
From 2016-2018, I worked under Dr. William Tang at the UCI Microbiomechanics Lab. It was previously discovered that plasmodium lactate dehydrogenase (pLDH), a compound found in all strains of malaria, has a higher electrical impedance when subjected to a current. Using this fact, I built a Wheatstone Bridge with a malaria saliva sample as the variable component, and programmed a Raspberry Pi 3 to help compute thousands of test cases to confirm whether or not samples contained malaria. The resulting test cases proved a nearly 95% accuracy.
Projects: Work
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