About Me

I’m interested in a fairly simple question: what happens when we start handing important decisions over to AI?

It sounds like a straightforward question. It usually isn’t.

My work sits at the intersection of AI governance, education, institutional accountability, and human–AI decision-making. I’m particularly interested in what happens inside organisations when AI systems move from being tools that assist people to systems that begin to shape how decisions are made, evaluated, and justified.

At Emeritus, I work on academic delivery and AI-assisted evaluation systems for executive education. My work involves turning academic and programme requirements into processes that actually function,  from assessment and rubric design to grading workflows, faculty coordination, and AI-assisted feedback and evaluation. In other words, I spend a fair amount of time thinking about what happens after the exciting AI demo ends and someone has to make the system actually work.

Earlier in my career, I worked across academic and research environments at IIM Udaipur, the Indian School of Business, and IIM Ahmedabad, supporting research projects, programmes, and learning initiatives. These experiences shaped my interest in the organisational side of research and education: not just what institutions want to achieve, but how systems, people, incentives, and technologies determine what actually happens.

From July 2023 to May 2026, I taught a two-credit course in Media Laws & Ethics for M.Sc. students in the Department of Media & Communication Studies at the University of Pune. Teaching media law and ethics while watching AI systems increasingly enter classrooms, assessment processes, and institutional decision-making has made questions of authority, responsibility, evidence, and accountability particularly difficult to ignore.

I’m currently researching and writing about AI, education, institutional power, and human–AI decision-making. My work asks questions such as: Who gets to make decisions when AI enters an institutional workflow? Where does accountability sit when those decisions are distributed across people and systems? And what does meaningful human oversight look like once the machine is already part of the process?

I’m especially interested in the space between AI governance as an idea and AI governance as a practice, the policies, evaluation frameworks, workflows, incentives, and organisational choices that determine whether principles like human oversight and accountability actually survive contact with reality.

Increasingly, I’m interested in helping AI safety and governance researchers turn important questions into research, programmes, and operational work that can inform real decisions. I’m drawn to the work or roles where I can define the problem properly, figuring out what evidence would actually help, designing processes that people can use, and making sure interesting research does not simply sit in a PDF quietly waiting to be cited.

Alongside my academic and professional work, I write about technology, institutions, education, and the politics of how systems get built and used.

I’m still figuring out some of the answers. The questions, however, seem to be multiplying quite efficiently.