Experience

Stanford Data and Mapping for Society

• United States
• Higher Education
• 1 - 100 Employee

• Project Member, PODIL

  • Nov 2023 - Present

  • Working on full-stack development, data analysis, and machine learning projects for PODIL, a health startup backed by the Qatar Government to create an app for overall well-being in Qatar. • Working on full-stack development, data analysis, and machine learning projects for PODIL, a health startup backed by the Qatar Government to create an app for overall well-being in Qatar.



Notebook Labs (YC S22)

• Software Engineer Intern

  • Jul 2023 - Sep 2023

  • Co-developed Zephyr, an application that decentralizes access to crypto through a peer-to-peer onramp service, handling buy and sell orders across 3 Ethereum networks and 10+ ERC-20 tokens. • Implemented a Sybil-resistant backend server in Node.js, TypeScript, and Express.js that has 15+ functions and 10+ API endpoints for calling smart contracts and interacting with NoSQL databases. • Designed and applied over 40+ responsive frontend components for interfacing with the Zephyr web… Show more • Co-developed Zephyr, an application that decentralizes access to crypto through a peer-to-peer onramp service, handling buy and sell orders across 3 Ethereum networks and 10+ ERC-20 tokens. • Implemented a Sybil-resistant backend server in Node.js, TypeScript, and Express.js that has 15+ functions and 10+ API endpoints for calling smart contracts and interacting with NoSQL databases. • Designed and applied over 40+ responsive frontend components for interfacing with the Zephyr web application and the Zephyr landing page using React with Next.js, TypeScript, and TailwindCSS. • Wrote 20+ functions that allow interactions from the clientside to Ethereum networks, wallets, and backend servers using Node.js, Wagmi, ethers.js, and RESTful APIs. Show less • Co-developed Zephyr, an application that decentralizes access to crypto through a peer-to-peer onramp service, handling buy and sell orders across 3 Ethereum networks and 10+ ERC-20 tokens. • Implemented a Sybil-resistant backend server in Node.js, TypeScript, and Express.js that has 15+ functions and 10+ API endpoints for calling smart contracts and interacting with NoSQL databases. • Designed and applied over 40+ responsive frontend components for interfacing with the Zephyr web… Show more • Co-developed Zephyr, an application that decentralizes access to crypto through a peer-to-peer onramp service, handling buy and sell orders across 3 Ethereum networks and 10+ ERC-20 tokens. • Implemented a Sybil-resistant backend server in Node.js, TypeScript, and Express.js that has 15+ functions and 10+ API endpoints for calling smart contracts and interacting with NoSQL databases. • Designed and applied over 40+ responsive frontend components for interfacing with the Zephyr web application and the Zephyr landing page using React with Next.js, TypeScript, and TailwindCSS. • Wrote 20+ functions that allow interactions from the clientside to Ethereum networks, wallets, and backend servers using Node.js, Wagmi, ethers.js, and RESTful APIs. Show less



Fermilab

• United States
• Research Services
• 700 & Above Employee

• Scientific Computing Intern, TARGET Program

  • Jun 2022 - Aug 2022

  • Constructed a hybrid camera and Neural Network overlay with Xilinx Vivado and HDL, allowing for simultaneous Neural Network inference with a webcam on Pynq-Z2 hardware. • Produced a Computer Vision demo for FPGA architecture with Python, hls4ml, and OpenCV that can classify Pokémon with 83.5% detection accuracy. Showcased at DEFCON 30. • Assisted in training and converting optimized Convolutional Neural Networks for FPGAs with hls4ml, resulting in models with less than 5ms latency with… Show more • Constructed a hybrid camera and Neural Network overlay with Xilinx Vivado and HDL, allowing for simultaneous Neural Network inference with a webcam on Pynq-Z2 hardware. • Produced a Computer Vision demo for FPGA architecture with Python, hls4ml, and OpenCV that can classify Pokémon with 83.5% detection accuracy. Showcased at DEFCON 30. • Assisted in training and converting optimized Convolutional Neural Networks for FPGAs with hls4ml, resulting in models with less than 5ms latency with ~95% original accuracy. Show less • Constructed a hybrid camera and Neural Network overlay with Xilinx Vivado and HDL, allowing for simultaneous Neural Network inference with a webcam on Pynq-Z2 hardware. • Produced a Computer Vision demo for FPGA architecture with Python, hls4ml, and OpenCV that can classify Pokémon with 83.5% detection accuracy. Showcased at DEFCON 30. • Assisted in training and converting optimized Convolutional Neural Networks for FPGAs with hls4ml, resulting in models with less than 5ms latency with… Show more • Constructed a hybrid camera and Neural Network overlay with Xilinx Vivado and HDL, allowing for simultaneous Neural Network inference with a webcam on Pynq-Z2 hardware. • Produced a Computer Vision demo for FPGA architecture with Python, hls4ml, and OpenCV that can classify Pokémon with 83.5% detection accuracy. Showcased at DEFCON 30. • Assisted in training and converting optimized Convolutional Neural Networks for FPGAs with hls4ml, resulting in models with less than 5ms latency with ~95% original accuracy. Show less