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Work Experience

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Software Engineering Intern – Procter & Gamble

May 2025 – Aug 2025

  • Sole developer of an automated QA system integrated into P\&G’s artwork labeling pipeline, performing multi-source validation of inputs and outputs using API-fed enums, regex, and GPT-based models to catch data anomalies across thousands of global product rules.
  • Designed and implemented an OCR solution to extend P\&G’s automated artwork compliance system, enabling detection of multilingual and variably structured text in smart PDFs previously missed by rule-based methods.
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Database Engineering Intern – Procter & Gamble

May 2024 – Aug 2024

  • Developed and deployed a Python-based reporting pipeline for hundreds of Oracle DB instances, eliminating \$5M+ in daily licensing cost fluctuations and saving 400+ FTE hours annually by automating license and feature usage monitoring.
  • Integrated and cleaned daily telemetry from Oracle Enterprise Manager and DB instances using Azure Edge Functions and Postgres, driving a dashboard that enabled license compliance and anomaly detection at scale.
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Connected Data Software Intern – Ford Motor Company

May 2023 – Aug 2023

  • Developed a real-time transmission torque monitoring module in C for Ford’s Powertrain Control Module, using a customized rainflow algorithm to track hysteresis loops and estimate transmission fatigue, achieving a 98.3\% memory reduction over raw data storage.
  • Validated performance on real-world drive data in a simulated PCM environment, enabling future fleet-wide deployment of torque fatigue tracking without hardware upgrades.
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Software Engineering Technician – Michigan Medicine

May 2023 – Aug 2023

  • Built a reusable reporting pipeline in Python to process quantitative and qualitative teaching feedback for Michigan Medicine lecturers, saving 98\% of manual effort and streamlining reviews across hundreds of faculty.

Projects

MHacks 2025

MHacks 2025

Led the Tech Team for MHacks 2025, the largest hackathon in Michigan, overseeing a team of 8 developers to build the event's website and infrastructure.

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Smith-Waterman Hardware Accelerator

Smith-Waterman Hardware Accelerator

Achieved 30× speedup over SPOA using systolic array-based Verilog implementation.

Code Available upon request.
Jester

Jester

Built a custom chess engine in C++ using minimax, alpha-beta pruning, and a polymorphic bitboard architecture.

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Bubble

Bubble

Led backend development for Bubble, a secure Life360-style app enabling real-time user tracking, encrypted messaging, and group coordination, built entirely in Rust using Axum.

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Out-of-Order RISC-V Processor

Out-of-Order RISC-V Processor

Designed and synthesized an N-way superscalar out-of-order RISC-V processor with early branch resolution, speculative execution, and a GShare predictor.

Code Available upon request.
LLM-powered Hot Path Identifier

LLM-powered Hot Path Identifier

Developed a novel approach to identify performance bottlenecks in code using large language models.

Code Available upon request.
MHacks 2024

MHacks 2024

Built the website and infrastructure for MHacks 2024, the largest hackathon in Michigan, as part of the Tech Team.

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Ultrasound Parallelization

Ultrasound Parallelization

Achieved 80x speedup to serial ultrasound algorithm using Xeon Phi and OpenMP.

Code Available upon request.
Google x MHacks

Google x MHacks

Built the website and infrastructure for the MHacks x Google Hackathon, as part of the Tech Team.

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Virtual Memory Manager

Virtual Memory Manager

Created a virtual memory manager which supports both file backed and swap backed pages. Processes address spaces are maintained by the pager and syscalls are administered through the pager interface.

Code Available upon request.
Thread Manager

Thread Manager

Created a thread manager to administer the creation, lifetime, and execution of various thread bodies on a multi-core system.

Code Available upon request.
Support Vector Machine Multiclass Classifier

Support Vector Machine Multiclass Classifier

Developed a multiclass classifier using SVMs, mapping text reviews to a rating scale of 1-5.

Code Available upon request.
Convolutional Neural Network Classifier

Convolutional Neural Network Classifier

Built a CNN image classifier to predict the landmark in images, achieving 83% accuracy on a test set of 2000 images of 8 landmarks.

Code Available upon request.

Relevant Classes

Education

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University of Michigan – MSE in Computer Science Engineering

Jan 2024 - Dec 2025

GPA: 3.7

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University of Michigan – BSE in Computer Science Engineering

Minor in Electrical Engineering

Aug 2021 - Dec 2024

GPA: 3.8

Get in Touch

Feel free to reach out for collaborations, questions, or a coffee chat.