Heinz College’s Event and Pattern Detection Lab Launches Website
Mar 25, 2014
The Event and Pattern Detection Laboratory (EPD Lab), a research center affiliated with Carnegie Mellon University’s H. John Heinz III College, launched its website this week at epdlab.heinz.cmu.edu. The website will be an invaluable resource for news and information on the EPD Lab and their ongoing projects.
The EPD Lab’s research, directed by Heinz College faculty member Daniel Neill, focuses on the development of new statistical and computational methods for scalable and accurate detection of emerging events and other patterns in complex, massive, and high-dimensional datasets. Applications of the EPD Lab’s research range from public health and patient care, to law enforcement and urban analytics, to human rights and conflict.
The work done by the EPD Lab has advanced the state of the art in large-scale pattern detection in multiple ways. These contributions include the development of new statistical methods that enable more accurate detection of emerging events and patterns, new algorithms that make previously impossible detection tasks computationally feasible and fast, and new machine learning methods that enable systems to model and distinguish between relevant and irrelevant patterns. For example, the Lab’s technologies for “fast subset scanning” enable exact and efficient optimization over subsets of data elements, requiring only milliseconds to solve real-world detection problems that would otherwise have required years of computation time.
These novel methods are being applied to create, develop, and deploy systems that directly enhance the public good, for example, by detecting emerging outbreaks of disease, predicting violent crime hot-spots, and using 311 call data to predict and prevent rodent infestations in Chicago. “We are particularly excited about our ongoing collaborations with city leaders, public health and law enforcement agencies, and other organizations in the public sector,” noted EPD Lab director Daniel Neill. “These projects have given us outstanding opportunities not only to push forward the state of the art in pattern detection methodology, but to directly apply our methods to important real-world problems.” Other application areas addressed by the Lab’s work include conflict prediction, human rights, and international development, as well as security applications such as intrusion detection, customs monitoring, and infrastructure monitoring.
“Our primary focus as a lab,” stated Neill, “is to benefit the public good by developing and deploying novel detection methods, with the goals of improving public health, safety, and security. We are grateful for the funding support provided by the National Science Foundation, MacArthur Foundation, Bloomberg Philanthropies, and University of Pittsburgh Medical Center, which have provided us with the essential resources to pursue these goals.”
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