Made with Kleap

* Available for AI × Finance work

Hi, I'm Ayush — an AI engineer building at the intersection of machine learning and finance.

I implement research papers the moment they drop, train neural networks from scratch, and ship open-source. Currently exploring time-series models, LLM agents, and quantitative systems.

India · 20:50 UTC+0


01 — About

I work on machine learning with a tilt toward finance — reading papers, reimplementing them, and stress-testing them against real-world data. My background spans deep learning, time-series forecasting, and quantitative modeling.

Most of what I build ends up on GitHub. I share course notes, from-scratch implementations, and the occasional side project — because the best way to learn something is to teach it.

When I'm not training models, I'm reading about markets, writing about what I'm learning, or breaking a build I should've left alone.


02 — Focus

  • 2025

    AI Research

    Implementing papers the moment they drop — architectures, training tricks, evaluation harnesses.

  • 2025

    Finance × AI

    Where quantitative methods meet modern ML: signals, forecasting, and decision systems.

  • 2024

    Open Source

    Sharing the AI/ML foundations I've learned so the next builder can move faster.


03 — Projects

  • AI-ML-Course

    A structured curriculum covering AI & ML foundations, from classical models to modern deep learning.

    Python · Jupyter

  • neural-network-from-scratch

    Pure NumPy implementation of neural networks — backprop, optimizers, and training loops without a framework.

    Python · NumPy

  • flowise

    Drag & drop UI to build customized LLM flows using LangChainJS — visualized AI pipelines.

    TypeScript · LangChain


04 — Connect

The fastest way to reach me is email. I'm open to conversations about research, prototypes, and production work at the boundary of AI and finance.