cv
Education
Massachusetts Institute of Technology
Master of Engineering in Electrical Engineering and Computer Science [Sept. 2024]
- GPA: 5.0/5.0
- Concentrations in Computer Graphics and Artificial Intelligence
- Thesis: Recovery of Herschel-Bulkley Fluid Parameters from Video via Differentiable Simulations
- Notable Courses: Computational Design and Fabrication, Advances in Computer Vision, Machine Learning for Inverse Graphics, Shape Analysis, Advanced Computational Photography.
Bachelor of Science in Computer Science and Engineering, Minor in Japanese [June 2023]
- GPA: 4.7/5.0
- Notable Courses: Computer Graphics, Machine Learning, Design and Analysis of Algorithms, Operating System Engineering, Computer Systems Engineering, Software Construction.
Experience
Massachusetts Institute of Technology [Sept. 2023 - Dec. 2023]
Graduate Teaching Assistant
- Served as a TA for the Advanced Undergraduate Subject: Computer Graphics (6.4400) in Fall ‘23.
- Conducted office hours, assisted students with and graded C++ OpenGL coursework, and graded exams.
Second Front Systems [July 2023 - Aug. 2023]
Data Science Intern
- Engineered Dash and Plotly dashboards with dynamic filtering and pagination for real-time data visualization.
- Implemented regression models for advanced trend analysis and future performance prediction.
- Structured the Python codebase for modularity and Docker deployment.
MIT Computer Science and Artificial Intelligence Laboratory [Feb. 2023 - May 2023]
Undergraduate Researcher - Computational Design and Fabrication Group
- Collaborated with a multidisciplinary team to develop a rigid body physics simulation for underwater gliders.
- Implemented differentiable hydrodynamic forces, including lift and drag, as well as changes in mass into Nvidia’s differentiable simulation Python framework “Warp”, utilizing CUDA acceleration.
- Optimized glider hull design using gradient descent on differentiated forces with respect to glider shape.
- Enabled glider to optimize controls for faster horizontal speed or faster vertical descent.
Massachusetts Institute of Technology [Sept. 2022 - Dec. 2022]
Undergraduate Teaching Assistant
- Served as a TA for the Advanced Undergraduate Subject: Computer Graphics (6.4400) in Fall ‘22.
- Conducted office hours, assisted students with and graded C++ OpenGL coursework, and graded exams.
Intel Corporation [May 2022 – Aug. 2022]
3D Acceleration Software Engineer Intern
- Developed discrete GPU driver updates in C++ to resolve bugs and enhance Direct3D performance.
- Performed in-depth GPU performance profiling and analysis utilizing advanced analysis tools.
- Engaged with modern DirectX9, DirectX11, and DirectX12 3D titles in Windows.
- Provided technical support to developers using GPU systems for performance analysis.
MIT Mechanical Engineering Dept. [June 2021 – Sept. 2021]
Undergraduate Researcher
- Collaborated with MindHandHeart to develop a website hosting therapeutic audio files for mental health support.
- Established a server backend using Python in Django, hosted by Nginx on an Ubuntu server.
- Designed a custom log-on system with use, content creator, moderator, and server administrator roles.
The Picower Institute for Learning and Memory [June 2021 – Sept. 2021]
Undergraduate Researcher - Choi Lab
- Adapted open-source embedded mouse feeder systems for remote monitoring capabilities in C++.
- Engineered new hardware to interface offline mouse feeder using Raspberry Pi for internet connectivity.
- Developed software in Python for Raspberry Pi to monitor the mouse feeders and transmit data and alerts autonomously.
Andeno [June 2020 – Aug. 2020]
Data Science Intern
- Developed Python command-line scripts to process raw bank statement data and perform data analysis.
- Categorized transactions into groups using Natural Language Processing techniques.
- Verified users’ income, expenses, spending, and credit history and generated customer analysis and statistics.
Projects
Tiny Light Field Network for Efficient 3D Scene Rendering
- Developed a compact version of a Light Field Network (LFN) in Python using novel deep learning methods to efficiently synthesize 3D scenes from 2D data.
- Utilized a RELU hypernetwork to optimize scene reconstruction and novel view synthesis.
Mesh Simplification for Accelerated Physics Simulation
- Engineered Garland-Heckbert mesh decimation and Van Gelder volume decimation algorithms in C++.
- Integrated Finite Element Method (FEM) for non-linear physics simulation on simplified meshes.
- Implemented Biharmonic weights to project simulated deformation from simplified mesh to the original mesh.
Improved Loss Function for Frame Recurrent Video Super Resolution
- Augmented original implementation of FRVSR model in Python using PyTorch and retrained it.
- Integrated cutting-edge pre-trained RAFT flow network model to increase flow accuracy.
- Developed novel loss function, leveraging Perceptual Loss using VGG19 model to improve visual quality.
Photon Mapping
- Implemented a raytracing algorithm in C++, incorporating refraction, total internal reflection (via Snell’s law), and global illumination through Photon Mapping with k-d tree acceleration.