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Course 6-2: Electrical Engineering and Computer ScienceUndergraduate GPA: 4.8/5.0Graduate GPA: 5.0/5.0
ValedictorianGPA: 4.5/4.6
Developed an Onshape application in collaboration with PTC, hosted on Heroku and Amazon Web Services Elastic Beanstalk and using NodeJS and Python Flask with a Google Firebase database backend. Collected a custom dataset of sketches and images using a custom experiment in Amazon MTurk, and trained and modified Pytorch machine learning algorithms to allow users to create 3D CAD designs in collaboration with machines using sketch and webcam image inputs.
Created unit testing infrastructure for the Adreno debugging layer of the Vulkan graphics API in C++ to help develop a better mechanism for Vulkan users to check the efficiency rule violations of their code
Created Mock APIs using .NET Core in C# to replace commercial software used to mock responses from external REST and WCF APIs. These were used to test a Qualcomm enterprise ASP.NET MVC Web application which tracks software changes for Qualcomm’s Wireless software solutions.
Collected data and designed testing infrastructure to train and test a machine learning algorithm that would allow a camera to detect tagged objects, or effectively “see,” around a corner.
Restructured automation setup for bluetooth speakers such that performance tests could be run concurrently in the pytest framework, allowing for a more standardized approach to product testing.
Increased student understanding of computation structures and hardware synthesis languages by collaborating with course staff to develop assignments and providing guidance on exercises and projects during office hours.
Worked with the MIT Sloan cybersecurity group to build a database and real-time simulation that allows EDS dispatchers to more readily respond to cyberattacks. Worked to help design and implement both the front-end UI in HTML/CSS/Javascript and the back-end database of known cyberattack information in mySQL.
Called MIT alumni to keep them engaged in the school community and help fundraise for organizations and scholarships.
Organized company resources by creating a machine that sorted screws using a neural network coded in Mathematica that was able to correctly identify screw size and width in more than 50% of trials.
Led class of 20+ students in lectures and weekly office hours (approximately 6 hours a week), creating assignments and projects to teach students introductory Java.
Created a handheld device that combines an Inertial Navigation System (INS) to map the location of a user in 3D space with a Laser Range Finder (LRF) to detect the presence of obstacles in front of the user. The user is then notified of obstacle presence through sound and haptic feedback. The device has an increased maximum range of nearly 200% when compared to a typical navigation aid such as the white cane, increasing the amount of information a user obtains regarding their surroundings. Participated in the International Science and Engineering Fair (ISEF) and the Regeneron Science Talent Search (STS) (see Awards for more details).
Came up with original idea of selling beaded animals and keychains to raise money for people with developmental disabilities and their families, independently averaged $100 in profits per sale.
Proficiency in Spanish and Chinese (Mandarin and Cantonese)
System Verilog, LaTeX, RISC-V Assembly, Mathematica, and Microsoft Office Suite (Word, Powerpoint, Excel); experience with power tools and soldering