Work Experience

Undergraduate Research Assistant at Northwestern University

  • Conducted research focused on identifying pathways to catalyze reactions yielding value-added products, such as pharmaceuticals or biofuels. Leveraged computational modeling to evaluate the feasibility of reactions
  • Designed a Python workflow to automate the generation of molecular structures for simulating enzymatic reactions, reducing manual input by 99%. Ensured seamless integration with downstream machine learning models
  • Leveraged high-performance computing to conduct large-scale enzyme-substrate interaction simulations, using a combination of QM and MM techniques to optimize computational runtime while preserving accuracy in results

Database Intern at SC Johnson & Son, Inc.

  • Developed a digital cataloging system to transition paper-based reports into a structured, searchable database, leveraging Python for data extraction and automation to enhance accessibility and visualization
  • Optimized and updated a full-text search database using SQL and metadata indexing, enabling keyword-based document retrieval with optimized query performance

Electronics & Testing Team Member at Liquid Rocketry at Illinois

  • Validated a Python script that serializes data via TCP from a Raspberry Pi to our host device, enabling seamless real-time communication with our test stand during hot fires. Logging data for accurate performance analysis
  • Developed custom PCB designs using KiCAD and applied soldering techniques to ensure long-term reliability and durability in harsh environmental conditions, including temperature extremes and vibration

Projects

Shell Shockers 🔗

  • Designed a turn-based tank game inspired by Shell Shock Live on an FPGA, incorporating an interactive menu, randomized wind patterns, real-time scorekeeping, and physics-based projectile motion
  • Developed a high-performance VGA-based graphical interface leveraging BRAM for efficient color storage and custom modules for precise VGA controller programming, allowing reuse of sprites
  • Integrated a softcore MicroBlaze processor for USB keyboard input via SPI communication, enabling responsive and intuitive game control, using the MAX3421E USB peripheral controller to take in keyboard inputs
  • Utilized the UART protocol to asynchronously transmit keycodes to the computer, enabling the display of inputs on the screen

Convolutional Neural Network 🔗

  • Developed and implemented the forward propagation of a CNN based on the LeNet-5 architecture for accurate recognition of hand-written digits, employing advanced machine learning techniques
  • Significantly enhance training and testing speeds, using parallel programming techniques on an A40 GPU such as cuBLAS and matrix multiply with shared memory tiling

PDB-Pal 🔗

  • Developed internal tools and Python functions to rapidly configure PDB files for simulations.
  • Automated the generation of large datasets using molecular mechanics on high-performance computers, enhancing accuracy and minimizing errors in quantum mechanics simulations