Dixuan Yujing Chen and Fernanda Eliott Receive Harris Faculty Fellowships

Published:
March 13, 2023

Mattia Wells

Dixuan Yujing Chen, assistant professor of Religious Studies and Fernanda Eliott, assistant professor of Computer Science have won Harris Faculty Fellowships for the 2023-2024 academic year. 

A gift from the late John “Jack” Harris ’39 and Lucile (Hanson) Harris ’40 has endowed annual competitive fellowships for early career faculty members at Grinnell. The fellowships provide awardees with a leave at full salary for one academic year and up to $8,000 in research/travel funds.  

“It is my great pleasure to join in congratulating Dixuan and Fernanda who have received Harris Faculty Fellowships for the 2023–24 academic year, in recognition of their innovative research and outstanding accomplishments,” Dean Beronda Montgomery said. “Their work is reflective of Grinnell’s commitment to cultivating research as an effective pathway for discovery and enhancing collaboration.” 

Dixuan Yujing Chen’s Project   

Dixuan Yujing

Chen’s project, “How Meditation became Medicine: Construction of Healing Meditation in Chinese Buddhism,” will explore the transformation of Buddhist meditation by investigating how Buddhism integrated Chinese medical knowledge into religious practices. Her project focuses on a new type of “healing meditation” developed by the scholar-monk Zhiyi (538–597 C.E.), a major figure in the Tiantai tradition of Buddhism. This research project will not only contribute to the study of the interactions between religion and health, but also enable scholars and students to consider a variety of internal and external factors that shape health-seeking behaviors within and beyond religions.  

Chen will travel to Academia Sinica in Taiwan to study Buddhist scriptures and Chinese medical treatises, helping her to analyze how meditation was reconfigured as a therapeutic tool to improve physical health and how Buddhist views on health and the body changed during this evolution. The ultimate product of her project will be a monograph, and during the fellowship year she plans to draft chapters, produce journal articles, and work on a book proposal.   

Fernanda Eliott’s Project  

Fernanda Elliot

Eliott’s project, “Modeling and Assessing Emotional Processes in Utility-based Computational Approaches,” will use a variety of approaches to develop artificial intelligence systems that simulate empathy and moral behavior. A key hypothesis in her work is that biologically-inspired systems that model empathy and moral processes can enable AI agents to choose cooperative solutions, even when “selfish” solutions are highly rewarded, and the agents are given no explicit rules to enforce cooperation.  

Eliott shared, "I was honored to receive such a prestigious fellowship! That not only inspires me deeply but also enables me to extend such a distinction to my students.” 

With a team of undergraduate student researchers, Eliott will investigate the distinctions between relevant concepts (e.g. empathy and sympathy; intuitive knowledge, perspective-taking and common sense), examine how these concepts are embedded in existing computational approaches, and develop new architectures integrating concepts like cooperation, emotions, and empathy. This work also targets two crucial umbrellas to face today’s challenges given by technologies: AI literacy and AI explainability. Eliott and her students will also develop a variety of tools that can help both the general public and students in her classes better comprehend AI. By developing AI systems that model empathy and moral processes, Eliott’s project has the potential to create tools that can help people make better decisions and to help non-expert audiences understand artificial intelligence. 

We use cookies to enable essential services and functionality on our site, enhance your user experience, provide better service through personalized content, collect data on how visitors interact with our site, and enable advertising services.

To accept the use of cookies and continue on to the site, click "I Agree." For more information about our use of cookies and how to opt out, please refer to our website privacy policy.