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zhanyl-tech/README.md

Hi there, I'm Zhanyl πŸ‘‹

I am a Senior Quant Research Engineer bridging the gap between High-Performance Computing and Alpha Generation.

  • πŸ”­ Currently building: Autonomous DeFAI trading agents (LLM + RL) on distributed infrastructure.
  • πŸŽ“ Education: MS CS (Machine Learning) @ Georgia Tech | CQF (Quantitative Finance).
  • ⚑ Core Stack: Python, C++, PyTorch, CUDA, Slurm, AWS ParallelCluster, Kubernetes, Docker.
  • πŸ“ˆ Focus: HFT Infrastructure, Market Microstructure, and AI-driven Trading Strategies.

Website | LinkedIn | X / Twitter


πŸ›  Open source

slurm-scheduler-lab β€” test Slurm priority and backfill policy against a job trace before it reaches a live controller.

Implements priority/multifactor and EASY backfill, reads PriorityWeight* straight from a slurm.conf, and replays real sacct traces. I built it to answer a question I couldn't safely test in production β€” and the answer turned out not to be the weights:

backfill OFF                          backfill ON
  cpu utilization      72.2 %           cpu utilization      83.6 %
  mean wait          1913.0 min         mean wait           373.7 min

More in progress β€” agentic inference infrastructure, 128-GPU distributed training, and CUDA volatility surface calibration. They go public as they get good enough to defend.

✍️ Writing

I publish at zhanyl-tech.github.io β€” deep dives on inference optimization and HPC, plus shorter lab notes on whatever I'm currently measuring.

β™ŸοΈ Chess and poker outside of work β€” both cheaper places to practise reasoning under uncertainty than production is.

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