Scholars have long employed a divisive lens to view science and humanities, with the former rapidly
developing to replace human labor while the latter ultimately oriented around human interpretations.
Such division in perspective also manifests itself in the division of scholarly communities that
perceive themselves as having little to do with each other.
However, my experience researching at the intersection of the two revealed that this made us miss
out on an enormous potential for the two domains to co-evolute and recursively augment each other. This
motivates me to pursue an integrated approach to research that combines both.
I believe that it is the questions we ask, not the methods we employ, that can positively impact the
I am interested in exploring the relationship between the human mind and machines, and how their differing perspectives can help us better understand the world. To grasp these connections, an interdisciplinary approach is needed to merge computational methods with humanistic inquiries, which can be approached from two directions:
[☾˚.] In the information age where words so often give way to number crunching, how to cogitate the humanistic meaning of data science?
I am particularly interested in understanding representation and interpretability/explanatory models in both human minds and modern Deep Learning models (such as Large Language Models), and their connections with each other.
What does it mean to represent or understand something? Can computers think?
I believe that we are better positioned to answer these questions through not only empirical studies but also through philosophical and historical explorations of computation and science.
[✭] How can computational methods be used to expand and contextualize humanities research, empowering large-scale cultural analytics and historical investigations?
This line of research is commonly referred to as digital/computational humanities. (I am currently supported by the Digital Humanities Graduate Fellowship from the Center for Spatial and Textual Analysis (CESTA).)
While being open to the myriad unexploited benefits that scientific inquiries may offer, I wish to clarify that none of these approaches represent a technocratic method aiming to replace traditional humanities techniques such as close reading, or claim to be powerful enough to assume the crucial role of deep thinking.
Instead, my goal is for these methods to assist thinkers in discovering new connections and perspectives, which could be better illuminated with the latest analytical tools.
[☾⋆⁺₊] These two directions may ultimately converge.
My aspiration is to develop both a theoretical framework and empirical methods that transcend simple imitation of traditional humanities methodologies and mere application of computational tools as a “technological upgrade”. Instead, I intend to propose new modes of inquiry that combine computational capabilities with humanistic interpretation.
I aim for such approaches to encourage researchers to rethink and pose new questions about the mind and machine.
Visit my research page and blog
for more details!
✧ My parents and friends have complained for years that I try to turn every conversation into a
philosophical debate. I am now trying very hard to master small talks (please lend a hand if you catch me struggling).
✧ Essentials for me: quality books, VSCode, and COFFEE. With this in mind, You may spot me hiding in a cafe's cozy corner or blending into the bookshelves. My favorite place is the
Library of Babel.
Besides reading and writing, I enjoy
playing the Chinese zither (I am currently in the Stanford Baipu Chinese Music Ensemble),
and trying every ice cream flavor.
I am always energized by inspiring conversations and meaningful connections. Drop me an email to say hello anytime!