A combination of biased data and decontextualized models has led to a host of  “intelligent” algorithms that are capable of reflecting and exacerbating human biases. As the use of such algorithms in societal contexts proliferates, the question arises: How can we redesign them to mitigate bias?

Nisheeth Vishnoi's research spans several areas of theoretical computer science: from approximability of NP-hard problems, to combinatorial, convex and non-convex optimization, to tackling algorithmic questions involving dynamical systems, stochastic processes, and polynomials.

He is also broadly interested in understanding and addressing some of the key questions that arise in nature and society from the viewpoint of theoretical computer science. Here, his current focus is on natural algorithms, emergence of intelligence, and questions at the interface of AI, Ethics, and Society

Sponsoring Organization(s): ISP, Justice Collaboratory