Experience

MIT EECS

• United States
• Higher Education
• 1 - 100 Employee

• Course Lab Assistant

  • Oct 2022 - Present

  Guide students in understanding lab material, debugging programs, and improving code style Provide feedback on course curriculum on programming in Python, C, and RISC-V Guide students in understanding lab material, debugging programs, and improving code style Provide feedback on course curriculum on programming in Python, C, and RISC-V



MIT STEP Lab

• Cambridge, Massachusetts, United States

• Undergraduate Researcher

  • Jun 2023 - Aug 2023

  - Overhauled rendering system of 3D simulation engine using THREE.js and TypeScript - Increased efficiency by up to 10x, improved robustness, error handling, and platform compatibility - Collaborated with game designers to develop multiplayer AR games with Unity and Photon Fusion, providing hands-on learning experiences for children - Presented developments to local teachers, led discussions and used feedback to make crucial design revisions - Overhauled rendering system of 3D simulation engine using THREE.js and TypeScript - Increased efficiency by up to 10x, improved robustness, error handling, and platform compatibility - Collaborated with game designers to develop multiplayer AR games with Unity and Photon Fusion, providing hands-on learning experiences for children - Presented developments to local teachers, led discussions and used feedback to make crucial design revisions



MIT AI Alignment Research Fellowship

• Cambridge, Massachusetts, United States

• Research Assistant

  • Nov 2022 - May 2023

  Investigating methods of inducing steganography in language models with chain of thought prompting Identifying neuron function in transformers through prompt optimization and iterative reduction of prompts Winter ML Bootcamp — studied transformers, RL, mechanistic interpretability; implemented models in PyTorch Investigating methods of inducing steganography in language models with chain of thought prompting Identifying neuron function in transformers through prompt optimization and iterative reduction of prompts Winter ML Bootcamp — studied transformers, RL, mechanistic interpretability; implemented models in PyTorch



University of Maryland

• United States
• Higher Education
• 700 & Above Employee

• Intern

  • Jun 2021 - Aug 2021

  Ported Python program for decoding data from the JPSS satellites into C. Documented decoding process of satellite communication protocols and data formats. Ported Python program for decoding data from the JPSS satellites into C. Documented decoding process of satellite communication protocols and data formats.