I'd say my biggest role is stress-testing our ideas. I tend to take a hypothesis and keep pushing at it, questioning the assumptions, asking my teammates for opposing views, and looking for explanations we might have missed. I want us to know not just whether an alpha works in the IS period, but why it works, when it could fail, and whether that reasoning holds in other years and situations.

I'm also the people person in the team. I handle a lot of the outreach and networking, but I see that as part of the research process, bringing in new perspectives, asking the right people the right questions, and turning those conversations into better ideas for the team.

The toughest part was probably the final stretch, when the pressure increased much faster than the time available. We had ideas that looked promising but weren't robust enough, deadlines getting closer, and very little room to experiment blindly.

The way we got through it was by becoming much more ruthless about prioritisation. Instead of trying to make every idea work, we focused on what had evidence behind it, tested aggressively, and cut what wasn't working.

That was probably one of the biggest lessons from the competition: sometimes the most useful research decision is deciding what not to spend another three hours on.

I don't think you need to act like a man to enter a domain that has nothing to do with gender. If you like it, you simply do it. Of course you'll look stupid at the start, but that's true when you enter any new domain.

And honestly, I think a little audacity goes a long way. There are plenty of people who walk into quant with ridiculous confidence before they actually know what they're doing. You don't need to wait until you feel completely ready. Start, be willing to look stupid for a while, and let yourself get good at it.

One thing that surprised me was how often an idea that sounded intuitively strong turned out to be weak once we actually tested it. And sometimes the opposite happened, relatively simple ideas could become surprisingly useful after the right transformations, neutralisation or combination with other signals.

It made me much more skeptical of intuition on its own. In quant, an idea isn't really interesting because it sounds clever. It's interesting when the data keeps giving you a reason to believe it.

For the Global Finals, I'm focusing on two things: improving the research process and understanding why our strongest signals work rather than just optimising their performance. At this stage, robustness matters much more than finding one spectacular backtest.

And obviously, I'd love to win. But getting to represent India internationally has already been a pretty surreal outcome for something that started as a competition I was curious enough to try.

In five years, I'd like to be doing quantitative research professionally. That's definitely the direction I'm most serious about.

Filmmaking is something I picked up because I genuinely enjoy editing and making things. I don't see it as an alternative career I need to somehow combine with quant. I'd like to keep doing it on the side because it makes college more than just classes, competitions, and internships.

I think I'll be happier looking back and remembering that I actually did things I enjoyed in my free-willed years, rather than realising I spent all of them preparing to be "professional."