Dhananjay’s Personal Webpage
Hello!
I realize that many people don’t want to read a lot of rambling on the main page, so here’s a TL;DR version for quickly skimming, followed by a full version for anyone actually interested in reading through.
TL;DR Intro
I am Dhananjay, a data scientist interested in how statistics, machine learning, and computational tools can be used to study and challenge inequality. I recently completed a Master’s in Computational & Mathematical Engineering at Stanford, after studying Mechanical Engineering and Data Science at IIT Madras. My work has included performing healthcare access studies with the World Bank, developing indigenous AI solutions in Senegal, and using LLMs to improve governance-related tasks at the U.S. GAO.
- I care about data, society, and the politics of technology.
- My recent work has focused on topics including Causal Inference, Inequality Quantification, AI Bias, Non-Eurocentric NLP, and Data-Driven Policy
- I am especially interested in questions at the intersection of data science, governance, decolonial tech, and social justice.
- Long term, I want to use technical tools in ways that materially improve people’s lives, whether it be in the US, or in India, or other countries in the “Global South”.
Read the full version
I am Dhananjay. I am deeply interested in data science and statistics, but specifically in how they can be used to study and combat societal inequality. In general, I am interested in thinking about Tech (and STEM, broadly), from a society-centric lens.
I just graduated from Stanford, where I did my Master's in Computational & Mathematical Engineering. Before this, I did my undergraduate studies at IIT Madras, where I majored in Mechanical Engineering and Data Science. Through my time in school, I've donned many hats. In another life, I used to work in Computer Vision. However, as I got through 5 years of undergrad (which is a long time!), I gradually grew disillusioned with my work, especially as I witnessed the dire condition of the world around me. I did not like that my work felt so removed from the "real world".
Making a choice for myself, I started my MS at Stanford, where I slowly started shifting focus, looking at the "socio-technical" side of things. As I continued doing rigorous graduate level courses, I did a project on auditing LLMs for caste bias, and also with the World Bank on identifying healthcare vulnerabilities in South Africa, both of which interested me quite a bit. In the summer of 2025, I got the opportunity to do an internship at Dakar, Senegal, where I worked on indigenous AI for African-specific contexts.
Doing projects involving low-resource language transcription models, and measuring african-specific bias in AI models got me thinking about "decolonial tech", specifically giving me a critical framework for thinking about technological solutions for the people of the global south. Further, spending a summer in Africa was extremely enjoyable, rooting in me a desire to work on problems specific to "developing" countries such as Senegal and India.
By now, I had also started to tire of the hype around AI, and while I saw it as an incredibly useful tool, I also did not (and do not) believe that it will solve all of humanity's problems. I did a great causal inference course, which introduced me to new ways of thinking about data, and I did another deeply personal project about measuring caste-based health disparity in India. Along the way, I also picked up skills including GIS, R, and SQL, all of which are useful for a data scientist to have.
Through my journey, I have come to the conclusion that I would love to use my skills in the service of people, and for the betterment of their condition. Towards the end of my degree, I also got a great opportunity of doing an internship with The Innovation Lab at the Government Accountability Office (GAO), where I got to witness first-hand how new technology could radically transform the functioning of governance.
I am always looking for opportunities to learn and apply my knowledge in meaningful ways. If any of this resonated with you, feel free to reach out to me and say hi!