March 6, 2023
By Patricia Waldron
The National Science Foundation (NSF) has selected Immanuel Trummer and Cheng Zhang, both from the Cornell Ann S. Bowers College of Computing and Information Science, to receive Faculty Early Career Development (CAREER) Awards. They join two other Cornell Bowers CIS faculty who recently received NSF CAREER Awards: Sumanta Basu, assistant professor of statistics and data science, and Tapomayukh Bhattacharjee, assistant professor of computer science.
Trummer, assistant professor of computer science, and Zhang, assistant professor of information science, will each receive approximately $600,000 over the next five years to support their research. NSF provides these sustaining grants to early-career scientists who they believe will advance their fields and serve as role models within their institutions.
Trummer’s work focuses on improving database performance through tuning, a series of decisions about how a database processes information internally. Specifically, he leverages large language models to support automated database performance tuning. The performance of database management systems depends on various tuning decisions, including settings for internal configuration parameters as well as the creation of auxiliary data structures. Making such decisions by hand is difficult, which has motivated the development of automated tuning tools. However, crucial information for database tuning is often contained in text documents, such as the database manual or text describing specific data sets and their properties. The current generation of tuning tools cannot exploit such information, making them inefficient. However, the latest generation of text processing methods – large language models based on the Transformer architecture – is often able to extract information from text with little to no task-specific training data. Trummer plans to exploit such methods to parse relevant text for database tuning, extracting information that helps to guide automated tuning efforts.
As the director of the Smart Computer Interfaces for Future Interactions (SciFi) lab, Zhang designs intelligent, privacy-sensitive, and minimally obtrusive wearables that can predict and understand human behavior and intentions in daily activities. Currently, computers struggle to recognize everyday activities due to the lack of high-quality behavioral data, such as body postures. Zhang's team addresses this through wearables endowed with artificial intelligence (AI)-powered active acoustic sensing that track and interpret human body postures of the hands, limbs, face, eyes, and tongue. The research aims to bridge the gap using cutting-edge AI techniques to enable applications in human activity recognition, telemedicine, and improving computer accessibility for individuals with hearing or speech impairments. Ultimately, the SciFi Lab seeks to create systems that function efficiently in real-world settings while protecting user privacy.
Patricia Waldron is a writer for the Cornell Ann S. Bowers College of Computing and Information Science.