Yanni Zhuang Yanni Zhuang
Headshot of Yanni Zhuang

Hi, I'm Yanni.

Distributed Systems, Performance Engineering, HPC

Incoming SWE @ Jump · Chicago, IL

I am a recent graduate from the combined Bachelor's/Master's in Computer science at the University of Illinois Urbana-Champaign with a minor in Mathematics. This past summer, I was an intern at Jump Trading, where I worked on performance optimisations for post-trade analysis pipelines. Before that, I was at Modern Treasury, where I optimised a financial data ingestion pipeline.

University of Illinois Urbana-Champaign Urbana, IL
2025 – 2026

Master of Computer Science

2022 – 2025

Bachelor of Science in Computer Science, Minor in Mathematics

Academic Committee Chair; Vice Chair; Banks Editor – ACM @ UIUC.

Software Developer – [Reflections | Projections; Disruption Lab; Illinois Space Society]

Jump Trading Jun 2025 – Aug 2025
Software Engineer Intern Chicago, IL
  • Optimized post-trade analytics pipelines for latency and throughput
Modern Treasury May 2024 – Aug 2024
Software Engineer Intern New York, NY
  • Employed profiling tools to identify bottlenecks in pre-existing data ingestion system
  • Designed and implemented new data ingestion infrastructure, resulting in 275× improvement in throughput
  • Improved validation and error handling for better observability
University of Illinois Urbana-Champaign Aug 2023 – Dec 2025
Course Staff & Research Assistant Urbana, IL
  • Course Assistant for CS 128 (Intro to Computer Science II), CS 374 (Algorithms), CS 433 (Computer System Organsation)
  • Lead Course Developer for CS 341 (Systems Programming)
  • Prototyped a permissioning system for PrairieLearn
Parallel Programming Laboratory May 2023 – May 2025
Undergraduate Research Assistant Urbana, IL
  • Constructed benchmarks to verify correctness of non-shared and shared memory Charm++ builds
  • Analyzed benchmark results and hardware performance counter data to identify bugs and anomalies
  • Assisted with development of parallel I/O library for Charm++
GPU-Accelerating the 1 Billion Row Challenge

GPU-based processing pipeline using DirectStorage for the 1BRC dataset.

PyCoRa

PyTorch reimplementation of CoRa ragged tensor functionality.

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