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🎯
Focusing
🎯
Focusing
4 followers · 24 following
  • University of Minnesota Twin Cities
  • Minneapolis,MN
  • 02:39 (UTC -05:00)
  • LinkedIn in/agnesspei

Achievements

Achievement: Pair Extraordinaire

Achievements

Achievement: Pair Extraordinaire

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pippipincs/README.md

Hi there 👋

I’m an undergraduate at University of Minnesota Twin Cities majoring in Computer Science. I’m drawn to system-level thinking, and I enjoy designing and building software where complex components interact in a scalable and reliable way. My interests focus on distributed backend systems and AI engineering.

I am looking for Software Engineer Internships opportunities in USA.

💼Experience:

  • 2026 summer Intern @ Imagine.
  • Ex intern @ World Salon, Urbot.
  • software engineer & board member @ App Development Club at UMN

🔭Projects I built:

  • Meditrack: a microservice-based patient-management system. Built with Java, gRpc, Kafka, Docker.
  • Key-value Store: a redis-compatible tcp key-value store server. Built with Golang.
  • distributed-matmul : A progressively optimized implementation of Cannon's algorithm for distributed matrix multiplication using MPI.
  • PairGEMM : Optimized a high-performance CUDA kernel for pair-wise batched 4x4 matrix multiplication on NVIDIA T4 GPUs.
  • NAND-to-Computer: Built a fully functional 16-bit computer from the ground up. Using HDL(simplified verilog)
  • to be continued...

My Skills

Pinned Loading

  1. Key-Value-Store Key-Value-Store Public

    A lightweight, Redis-compatible in-memory key-value store built from scratch in Go. Integrated the RESP (Redis Serialization Protocol) for wire-level compatibility with standard Redis clients.

    Go

  2. Meditrack Meditrack Public

    A microservice-based patient management system. Build using Java SpringBoot, gRpc, Kafka, Docker, LocalStack, AWS

    Java

  3. NAND-to-Computer NAND-to-Computer Public

    Built a fully functional 16-bit computer from the ground up — starting from a single NAND gate through to a working CPU, ALU, and memory hierarchy — using a hardware description language(simplified…

    Hack

  4. distributed-matmul distributed-matmul Public

    A progressively optimized implementation of Cannon's algorithm for distributed matrix multiplication using MPI.

    C

  5. PairGEMM PairGEMM Public

    Optimized a high-performance CUDA kernel for pair-wise batched 4x4 matrix multiplication on NVIDIA T4 GPUs.

    Cuda