This website is a canvas of ideas, not a neatly presented portfolio.

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Books I’ve Read

Anyone can be a product leader.

20 reflections on India in 2022

theses

TechBio

2023 TechBio Reading List

SPC TechBio Forum: Lessons 0-2

How is Flagship Pioneering building biotechs with machine learning?

[WIP] What ML-focused biotechs has Flagship Pioneering created?

[WIP] How can you learn from Flagship’s ML-driven biotech platform strategy?

How to categorize computational biomedicine innovation.

5 Incredible Women Driving Computational Biomedicine Forward

Beware of public datasets in healthcare.

The Three Fundamental Forces in Healthcare

Data + ML

Things I wish I knew about the modern data ecosystem as an MLE.

What reads impacted my ML Engineering journey most?

Technical Notes

Setup your dev environment

Setting Up a Python Dev Environment Using Pyenv

Custom Algorithm Training on Sagemaker Using Docker

AWS SageMaker tackles important problems, but can fall flat.

A simple reference for common ML metrics.

My three tips to learn Big O Notation.

What is Quadratic Weighted Kappa?

Career

Why I’ve joined firsthand.

What work life balance means to me.

Three career principles I learned from Shyam Sankar.

Engineering Culture

What does engineering excellence look like?

How can you communicate effectively as an engineer?

Self Management

Don't let standing out stop you from doing good work.

Constrain your information to trusted voices.

[WIP] trusted Voices

Book Reviews

Five Lessons From Phil Knight (Shoe Dog Review)

Applied ML Paper Reviews

VideoGPT

Building CI Services for Machine Learning

Backward Compatibility in ML Systems

Fast Sparse ConvNets

Once-for-all: Train One Network and Specialize it for Efficient Deployment

Noise2Self: Blind Denoising by Self-Supervision

StyleGAN

Knowledge Hub