Le, Xiong Bearfield Receive 2023 NSF CAREER Awards

Two Manning College of Information and Computer Sciences (CICS) faculty members--Assistant Professor Hung Le and Assistant Professor Cindy Xiong Bearfield --have recently received CAREER grants from the National Science Foundation (NSF), among the most prestigious grants that the NSF offers. 

The NSF's CAREER program is intended to provide early career scholars identified as having the potential to serve as role models, both in their research and teaching activities, with significant funding. The ultimate goal of the grant program is to help cement the foundation for a lifetime of integrating research and teaching activities.  

Assistant Professor Hung Le has received $655,466 for his project to advance the theoretical understanding of topological graphs, which appear in many practical applications, including logistics and planning, very large-scale integration design, image processing, and robot navigation. 

According to Le, research on the structures of topological graphs has produced powerful algorithmic techniques over the past two decades, but current techniques are reaching their limits. His goal is to develop a new class of techniques inspired by geometry counterparts that will break through the limits of the existing ones. These geometrical techniques, according to Le, may provide breakthroughs for algorithms attempting to solve problems that are currently considered to be among the most difficult--such as the k-center problem, used to optimize the placement of network nodes or facilities, or the vehicle routing problem used in ride-sharing and logistic applications. Le's project also outlines plans to disseminate these new state-of-the-art algorithm design techniques, and to train graduate and undergraduate students on them. He has previously introduced graph algorithms to high school students from underserved communities through the Massenberg Summer STEM Institute, hosted at UMass Amherst. 

Assistant Professor Cindy Xiong Bearfield has received $631,846 to develop a formalized model to measure trust in human-data interaction and enhance critical thinking between humans and data in visual data communications. 

Using a multidisciplined approach, Bearfield's project will work to formally define, understand, and model trust in visual data communication. First, using theories and research methods from the social sciences, Bearfield's team will work to produce a collection of methods that reliably measure user trust in data visualizations. Using these methods, the team will then conduct studies that identify which visualization design factors--including perceived visualization clarity, complexity, data accuracy, and the amount of data--can encourage critical thinking and calibrated trust in users while identifying which of those elements can be applied generally and which may be tied to a specific use case. Finally, Bearfield and her team will develop prototype visualizations and visualization systems designed to facilitate calibrated trust, examine the effectiveness of trust guidelines, and identify ethical practices for trustworthy visual data communication. The team will also develop interdisciplinary coursework and initiatives that mobilize concepts from computer science, public policy, psychology, and behavioral economics to advance practice and education around visual data communication.