Filippo Menczer, Ph.D. Associate Professor of Informatics Associate Professor of Computer Science Core Faculty, Cognitive Science Adjunct Associate Professor of Physics

Background
Ph.D. in Computer Science and Cognitive Science from the University of California, San Diego, 1998
Laurea in Physics from the University of Rome, 1991

Research Interests

Agent based algorithms and models for complex ecological, social, and virtual environments. Methodologies include intelligent agents, evolutionary computation, machine learning, and neural networks. Applications include scalable Web, text, and data mining, Web intelligence, Web IR, and distributed peer information systems.

Research statement

I have been interested in complex dynamical systems since working with Miguel Virasoro and Domenico Parisi on the statistical mechanics of evolutionary models simulating ecological environments. At UCSD I worked with an interdisciplinary group of computer scientists, cognitive scientists, and biologists. My dissertation focused on interactions between individual reinforcement learning and evolutionary computation based on local selection schemes. These distributed algorithms have been employed to study cognitive models of adaptive behavior in complex environments, including both ecological simulations and Web crawling applications. An artificial life model called Latent Energy Environments was developed as a simulation tool, distributed as open source with Linux, and used in experimental and instructional settings. At the University of Iowa, and as a fellow-at-large of the Santa Fe Institute, my research has addressed the scalability limitations on Web applications, and ways to overcome them by exploring both content and structure of the Web graph. An example application is the MySpiders search system, which allows users to launch personal adaptive agents who crawl the Web on their behalf. More recently I have undertaken a systematic study of the correlations between the various topologies of the Web (lexical, link, and semantic) to gain a better understanding of the emergence of the Web's critical network structure. This research is funded by a Career Award from the NSF. I believe that what we learn from this exploration of artificial environments can give us new insight into the many critical networks that we find in nature, from the metabolic to the social and economic scale.

More Information
Home Page