Hi, I'm Girish! I'm from England and am currently bouncing around Europe before moving to the United States in 2021.
I’ve got a background in physics, two decades of full-stack programming experience and my investigative and multimedia reporting from Venezuela, the Americas and Middle East has been published by everyone from Reuters to the New Yorker. I’m now CTO of a machine learning startup that aims to identify quality journalism. Throughout my varied career, I have used strong analytical skills to do everything from solve differential equations and architect neural networks to demonstrate multi-billion dollar government corruption and stay safe amid war and violence. I enjoy playing music, photography, keeping fit and, ultimately, satiating my curiosity.
Please get in touch if you're keen to chat. I'm always open to meeting enthusiastic and interesting new people.
I started teaching myself to code at eleven, assembling computers, writing software and building database-driven websites from scratch. A popular music site I created in my early teens, in 2000, was listed by MTV as one of the then nascent web’s top twenty sources.
I was the first person in my family to go to university and began studying math, physics, chemistry and geology at Cambridge though, not excited by the medieval city’s social life, I moved on to Manchester where I focused on physics. My primary interests lie broadly on the theoretical end of the spectrum—spacetime, quantum mechanics and particles—though my Master’s project, the abstract to which was published, was more practical: a simulation of the heart to investigate atrial fibrillation.
I then bought a one-way ticket to become a foreign correspondent. As a reporter, I was based primarily in Venezuela for nearly a decade where I produced groundbreaking investigations, covered daily clashes and reported on a humanitarian crisis. From Caracas, I traveled the world—often its most hostile environments: Colombia, Egypt, Iraq, Afghanistan, Cuba, Mexico and many others.
As a freelancer, I investigated diamond smuggling from illegal jungle mines in the Amazon, Glencore profiting from a Colombian paramilitary massacre and, separately, the killing of wildcat gold miners there. I worked with some 40 news outlets and stood up to sloppy reporting, slow payments and unpaid work in my own industry—as my career began, not just at its height. As a Senior Correspondent at Reuters covering Venezuela, I demonstrated—always with documents—high-level, multi-billion-dollar government corruption, military missile inventories, exaggeration of electoral results and that the country’s Chief Justice was arrested on suspicion of murder.
I went beyond traditional media by bringing math and code to journalism, automating data acquisition, simple story-writing and other mind-numbing tasks that pull resources from actual reporting. And, wanting to properly understand the roots of Venezuela’s humanitarian crisis, I created web and mobile applications to provide thousands of people with live and historic data on the country’s dire economy.
I left Reuters and expanded the Venezuela Econ platform into a company, Data Drum, which offered automated, clean and elegant global macroeconomic data.
I then spent just over a year in Mumbai where I created a data science unit at a public policy non-profit that advised government on applying computing to everything from urban planning and mapping to data governance and the COVID-19 response.
Now, as Chief Technology Officer at Stanford-conceived, Google-funded startup Deepnews.ai, I’m building a machine learning algorithm to identify quality journalism at scale.