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Roni Rosenfeld, Professor my-email-address-distorted

School of Computer Science (LTI, MLD, CSD, CompBio

Carnegie Mellon University

Office: Gates-Hillman Complex 8103.   Phone 412-268-7678.   Fax 412-268-5576.
Secretary: Pat Loring, GHC 8122, 412-268-5628.
Mailing address:  Carnegie Mellon / Computer Science,  5000 Forbes Ave.Pgh PA 15213

Hi! My research interests are in:

  • Forecasting Epidemics: The long term vision of our DELPHI research group is to make epidemiological forecasting as universally accepted and useful as weather forecasting is today. As was the case with weather forecasting, this will likely take several decades. In the shorter term, we select high value epidemiological forecasting targets (currently Influenza and Dengue); create baseline forecasting methods for them; establish metrics for measuring and tracking forecasting accuracy; estimate the limits of forecastability for each target; and identify new sources of data that could be helpful to the forecasting goal. We are part of the multi-university MIDAS research group.

  • Information and Communication Technologies for Development (ICT4D), and specifically Spoken Language Technologies for Development (SLT4D), which is the term we coined for our own subfield of ICT4D: finding ways to use spoken language technologies (like automatic speech recognition, speech synthesis, and human-machine dialog systems) to aid socio-economic development around the world.

  Our current project, Polly, uses telephone-based viral entertainment to reach low-literate people in Pakistan and India, familiarizing them with speech interfaces and then introducing them to development-related services. First deployed in Lahore in May 2012, Polly reached over 165,000 users all over Pakistan and fielded over 2.5 million phone calls in 8 months. In 2013 we launched Polly in Bangalore, India, and it ended up spreading virally to West Bengal, New Delhi and other areas of India. As of September 2014, we are reconfiguring Polly for immediate deployment in Liberia, Guinea and Sierra Leone, for person-to-person spreading of approved Public Health messages about Ebola in many languages. Try a live demonstration of our current prototype.

  A previous project, HealthLine, investigated the use of a telephone-based automated dialog system for access to healthcare information by low-literate community health workers in Pakistan.

  • Modeling the evolution of viral epidemics: As part of the multi-university MIDAS research program, we use machine learning, large scale simulations, network analysis and stochastic process theory to try to answer research questions such as:

    1. How, and to what extent, can the evolution of infectious diseases like Influenza be predicted?

    2. How, and to what extent, is the evolution of viral disease like Influenza affected by public health interventions such as vaccination, antiviral drug use, school closures, travel restrictions, etc.

We model the spread of epidemics in the population as well as the evolution of the virus itself, such as changes in its virulence, pathogenicity, drug resistance, or antigenicity (immune escape).

Publications (updated sporadically)

Teaching: 10-601 Machine Learning, 11-761/11-661 Language and Statistics.

Current Graduate Students:  David Farrow (CompBio, viral evolution), Ali Raza (LTI, ICT4D), Logan Brooks (CSD, Epi forecasting), Chuang Wu (Comp Bio, viral genotype-phenotype mapping).

Graduated PhD Students:  Jahanzeb Sherwani (CSD),   Yong Lu (CSD), Dan Bohus (CSD), Stefanie Tomko (LTI) Jerry (Xiaojin) Zhu (LTI, MLD),   Lin Chase (RI).

Past Post-docs:  Andy Walsh (computational virology), Xiaojin Wang (machine learning), Stan F. Chen (language modeling),  Pierre DuPont (language modeling).

 

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