I am a Ph.D. candidate in Cognitive and Computational Communication and an M.S. student in Statistics at UCLA, supervised by Prof. Jungseock Joo, Prof. Rick Dale, Prof. Hongjing Lu and Prof. Elisa Kreiss. 

​

ABOUT MY RESEARCH

​

My dissertation, titled “From Language Models to Multimodal Intelligence,” aims to map human and computational models into the framework of symbolic vs. embodied cognition, leveraging deep learning simulations and human-AI interaction studies. As a highly interdisciplinary researcher, I’m passionate about answering the fundamental question: How can multimodal AI (such as LLMs and language-vision models) enhance communication, problem-solving, and collaboration with human users?

​

My research lies in the intersection of deep learning, cognitive science, and multimodal communication. I am proficient in developing deep neural networks that process and integrate various forms of data, such as language (BERT, GPT) and image-text (CLIP) embeddings, behavioral (OpenFace, OpenPose), auditory (mel spectrogram or MFCC), and neuroimaging signals (fNIRS, fMRI).

​​

I currently work as a PhD student researcher at the Communicative Mind (Co-Mind) Lab and the Computation and Language for Society (Coalas) Lab. At Co-Mind, I develop end-to-end pipelines for processing multimodal conversational data. At Coalas, I collaborate on multi-agent LLM simulation and analyze neural and multimodal responses from human-AI vs. human-human interactions.

​

Several of my papers are published in Cognitive Systems Research, Computational Communication Research, Culture and Computing, CogSci, CHI, ICWSM and LREC conference and workshop proceedings. I am also a finalist for the 2023-2024 Meta PhD Fellowship and the recipient of the UCLA Graduate Council Diversity Fellowship, which includes full tuition and stipend coverage.