Distinguished professors from Carnegie Mellon University in Pittsburgh present public lectures on cutting-edge research
Questions such as, ‘How can a firm measure the effectiveness of celebrity endorsements?’ and ‘How does the human brain use neural activity to represent meanings of words and pictures?’ are to be discussed on Monday and Tuesday as part of the Distinguished Lecture Series held by Carnegie Mellon University in Qatar.
Renowned researchers from Carnegie Mellon University in Pittsburgh will be presenting to faculty, staff, students and members of the wider community. The speakers include Professors Kannan Srinivasan, the Rohet Tolani Distinguished Professor of International Business and H.J. Heinz II Professor of Management, Marketing and Business Technologies at the Tepper School of Business, and Tom M. Mitchell, the E. Fredkin University Professor and Department Head, Machine Learning Department. The lectures will be held in the Moot Board Room at Carnegie Mellon Qatar.
Srinivasan’s lecture, part of the Richard M. Cyert Distinguished Lecture Series in Business Management, is titled, “Business Insights from Big-Data.” It will address the rapid growth in data that helps answer business questions in new ways. Srinivasan will present his recent research that demonstrates improved forecasting power based on data collected from Google and Twitter.
“Data available to us now enables us to analyze and answer questions relating to business that would be difficult to imagine a decade ago,” Srinivasan said. “For example, can we measure the positive effective of celebrity endorsements for business?” The second part of the lecture will look at forecasting methods for television viewership ratings for prime-time shows and sports events. This examines data, including Google keyword search data and unstructured data of a staggering 1.7 billion tweets.
Professor Mitchell’s lecture, “How the Brain Represents Word Meanings,” is part of the A. Nico Habermann Distinguished Lecture Series in Computer Science. It will examine how the human brain uses neural activity to represent meanings of words and pictures.
“One way to study this question is to show people words and pictures while scanning their brain,” Mitchell said. “We have been doing experiments with brain imaging and, as a result, we have learned answers to questions such as, ‘are the neural encodings of word meaning the same in your brain and mine?’ and ‘what sequence of neurally encoded information flows through the brain during the half-second in which the brain comprehends a word?'”
Mitchell’s talk will summarize some of what has been learned and ask, “are neural encodings of word meaning built out of recognizable subcomponents, or are they randomly different for each word?” There will be a drinks reception before each lecture at 3:30 p.m., with the lectures taking place between 4-5 p.m. followed by a light dinner.
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