Adish Singla is a PhD student in the Learning and Adaptive Systems group at ETH Zurich, working with Prof. Andreas Krause. Earlier, he was a Senior Development Lead in Bing Search for four years. Adish’s current research focuses on problems at the interplay of learning and incentives arising in crowdsourcing and human powered computing systems. The goal is to improve the effectiveness of such systems by developing new techniques that are both theoretically well-founded and practically applicable.

Research Summary

The success of crowdsourcing and human powered computing systems heavily depends on the active and effective participation of the users. How can we simultaneously learn about users’ preferences (i.e.,desired incentives) as well as their abilities and skills, while using the obtained information in order to maximize effectiveness? How can we design incentive-compatible mechanisms for learning and optimal information gathering? I.e., how should we recruit users to solve complex sensing and computation tasks? Adish’s research addresses these fundamental questions by building on state of the art results in machine learning, probabilistic modeling and game theory. His research spans various application domains, including optimizing bike sharing systems by steering the behavior of the users, incentivizing users for privacy-tradeoff in community sensing, teaching and training the crowd, exploring social aspects of crowdsourcing, and learning optimal pricing policies for online crowdsourcing marketplaces.