Industrial Math Modeling Center Seminar: Applications of Data-Driven NLP Models and Graph-Analytic Algorithms in Technical Chat Contexts
Industrial Math Modeling Center Seminar
Applications of Data-Driven NLP Models and Graph-Analytic Algorithms in Technical Chat Contexts
Dr. Juan Batista
In this seminar series, industrial mathematicians and scientists discuss their use and development of mathematical models. The talks, of which there are four each academic year, are intended to keep members of the RIT community apprised of current industrial modeling trends and challenges. All are welcome.
Data-driven natural language processing models and graph-analytic algorithms form the theoretical backbones of many of the digital recommendations we receive every day: from search engines like Google, from shopping sites Amazon, and from everyday personal digital assistants like Siri, Alexa, and Cortana. With the widespread adoption of hardware-accelerated deep learning over the past decade, the field of NLP has experienced an explosion of growth in model effectiveness and complexity and has become a hotbed of data-driven modeling research. In this talk, I will introduce some of the classical NLP and graph-theoretic problems we at MITRE tackle, and the models and techniques we use to deliver proof-of-concept solutions and actionable analytics to our sponsors.
Dr. Juan Batista took his BS from RIT and his Ph.D. from Penn State, both in applied mathematics. As a mathematical analyst at MITRE, he collaborates with computer scientists, engineers, and various technical specialists on projects to develop proof-of-concept models, prototypes, and other deliverables to provide clients with state-of-the-art solutions to cutting-edge problems.
Undergraduates, graduates, and experts. Those with interest in the topic.
When and Where
This is an RIT Only Event