Siddhant Mukherjee

What’ve you enjoyed most about your area of study? Was there a particular discovery, new skill or way of thinking, or insight that you found especially valuable? Please share an example from your favorite class or experience.

I enjoyed learning about rationality and decision-making over the course of my minor in Economics. In Strategy and Information, I learned how asymmetric information and differing incentives induce interaction dynamics between agents. I was taught to recognize the pervasive influence of game theory across diverse settings such as the job market, political negotiation, and geopolitics.

How does the knowledge from this field, or your interest in it, combine with your other major or minor studies at MIT?

Game theory and decision-making combine well with my experience in computer science and mathematics to form more complete models of the world and human behavior. The mathematical rigor of computer science complements the strategic analysis of economics, allowing me to build more accurate, data-driven models of decision-making in complex systems.

An MIT education includes study in the scientific, technical, social science, arts, and humanities fields. How do you think that wide range of knowledge and perspectives will be valuable to you – for your career success and for your enjoyment of life?

I think that a broad understanding of economics and the incentives that drive human actions will allow me to look at real-world scenarios from multiple points of view. By anticipating interpersonal dynamics and understanding diverse perspectives, I will be better equipped to navigate the complexities of both professional and personal situations. This wide range of knowledge will be invaluable in my career, where the ability to think critically across disciplines is essential for solving complex, multi-faceted problems.

What are your plans for the future?

I will be joining Citadel for a career in quantitative research. I am excited to apply the knowledge I gained at MIT to real-world financial markets and solve challenging problems in data-analysis and algorithmic decision-making.