My research is driven by the goal to design
autonomous systems that can improve our quality of life by, for
instance, making it easier to collect information, make decisions, or
predictions. I design and utilize methods at the interface between computer science and economics, specifically around
the intersections among multi-agent, multi-robot and sensor systems, game theory and computational economics.
Underwater Robotic Unit with an Automated Sensing Technology for water quality testing
We build a prototype for an underwater robotic unit equipped with multiple sensors that are able to collect data autonomously and we are working on an enhanced analytics software that uses machine learning to analyze the collected data and predict trends related to water quality.
Distributed Prediction Markets based on Weighted Bayesian Graphical Games
We develop a framework to model a novel, yet practical setting of prediction markets called distributed prediction markets, where the aggregated price of a security of an event in one prediction market is affected dynamically by
the prices of securities of similar events in other, simultaneously running prediction markets.
We propose an ad-hoc collaboration framework where each agent strategically
selects capabilities to learn from other agents which would help
it to improve its expected future utility of performing tasks.
Pricebots: Dynamic Pricing
We propose dynamic pricing algorithms that sellers can use to update the prices of their products online automatically: