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malikakarsh/README.md

Akarsh Malik

MS Computer Science @ NYU, focused on ML systems, LLM inference, GPU performance, and distributed systems.

Previously a Data Scientist at Anheuser-Busch InBev, where I built production LLM, RAG, NLP, and optimization systems.

Selected Projects

  • FastInfer - LLM inference runtime with custom Triton kernels, real-model integration, and reproducible GPU benchmarks
  • Weave - natural-language data visualization platform for generating interactive dashboards from CSVs
  • Snatch - real-time distributed auction platform with WebSockets, PostgreSQL concurrency control, and non-blocking scheduling

Current Focus

  • LLM inference and serving
  • Triton / GPU kernel optimization
  • High-performance ML systems
  • Distributed systems and infrastructure

Website · LinkedIn · GitHub

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  1. fastInfer fastInfer Public

    LLM inference runtime centered on custom Triton GPU kernels and reproducible performance measurements.

    Python

  2. storyForge storyForge Public

    A playground for training tiny GPT models from scratch - exploring tokenization, storytelling, and GPU optimization with PyTorch

    Jupyter Notebook

  3. Transformer-GPU-Kernel-Optimization Transformer-GPU-Kernel-Optimization Public

    LLM Inference Optimization Benchmarks - Speculative Decoding, Fused Triton Kernels, KV Cache, Quantization

    Jupyter Notebook

  4. Weave Weave Public

    Turn a CSV file and a plain-English prompt into an interactive D3.js chart - no code required.

    HTML

  5. Snatch Snatch Public

    A real-time, multi-phase auction platform supporting descending (Dutch) and ascending (English) auction mechanics with round-based elimination.

    TypeScript 1

  6. algos_recap algos_recap Public

    A curated repository of deep-dives into algorithmic patterns and competitive programming concepts.