I gave a research talk at Sungkyunkwan University’s Human Affective Neuroscience Lab (PI: Dr. Justin Minue Kim). I presented my first PhD project, Differentiable Intersample Modeling (DIM), discussing how it complements the Anna Karenina (AnnaK) framework widely used in social and affective neuroscience. Specifically, using the lab's dataset (Kim & Kim, 2022 PNAS), we explored how the representational geometry of affective traits can align with that of emotional processing neural circuit morphologies.
Biography
I am the 2nd-year PhD student in UCSD SciMinds (PI: Dr. Eshin Jolly). I study the paradoxical nature of human emotion: its idiosyncrasy and commonality. Specifically, I investigate (1) which and how psychological profiles shape individual differences in emotion-related neural representations and subjective feelings, and (2) how people nevertheless come to share and align emotions. To this end, I am also developing new computational tools. Ultimately, I aim to explore implications of affective science across related fields such as mental health, aesthetics, and social robotics.
I grew up in South Korea, and received my B.A. in Psychology and Aesthetics and M.S. in Brain and Cognitive Sciences from SNU Connectome Lab (PI: Dr. Jiook Cha), Seoul National University.
News
I’m excited to share that my first PhD project, Differentiable Intersample Modeling (DIM), has been selected for a Trainee Blitz Talk at SANS2026, and I’ve also received a Travel Award! DIM is a new toolkit that expands RSA (representational similarity analysis), enabling a flexible learning of intersample geometry so that the resultant representation can be maximally aligned to the target representation.
I’d love to connect and chat at SANS2026! Feel free to reach out. See you in San Diego!
In the previous quarter, I worked as a TA for PSYC137: Social Cognition (taught by Dr. Piotr Winkielman), where I also had the chance to give a guest lecture to about 200 undergrad students. In the lecture, I introduced the ongoing debates in psychology around mixed emotions and shared some critical perspectives on why mixed emotions haven’t been widely studied as a distinct affective experience in experimental psychology so far.
I have explored some tools that can better analyze individual differences and their underlying factors. About four years ago, I began studying the principles and applications of causal machine learning, exploring its potential to address these questions. As part of this effort, I contributed as the second author to this new paper, Individual differences in effects of stressful life events on childhood ADHD: genetic, neural, and familial contributions.
Through this work, we were able not only to predict ‘individualized' exposure effects of early-life stress on children’s ADHD symptoms but also to identify key moderators such as parental psychiatric history, the child’s genetic vulnerability, and white matter connectivity within cognitive control networks. These findings allowed us to discuss the possibility of early identification and prevention among vulnerable groups. I believe that psychological/psychiatric works could move from an average treatment–effect paradigm toward a more individual-centered framework.
I’m excited to announce that I start my PhD in UCSD Psychology! Since UCSD Psych has long been my dream program because of its research-intensive and interdisciplinary environment, I’m deeply thrilled to have the opportunity to pursue my PhD at this institution.
I will pursue my PhD under the supervision of Dr. Eshin Jolly, whose research focuses on identifying neural representations of social relationships and affective experiences. He explores how these representations function in naturalistic settings through the development and application of innovative tools, which is highly aligned to my theoretical and methodological interests. I hope to make powerful synergy through productive collaboration!
Research Highlight
During my master's studies, I investigated how subjective feelings in daily life intertwine over time and shift across contexts, as well as what these complex dynamics reveal about an individual's traits and resultant emotional experience. To this end, I combined naturalistic neuroimaging with computational approaches (e.g., representational geometry and dynamics, predictive modeling). Stay tuned for my upcoming PhD work!
Awe is characterized as an ambivalent affect in the human behavior and cortex
Communications Psychology, 3(1), 123 (2025)