I am a Ph.D. student in Computational Communication at UCLA, supervised by Prof. Jungseock Joo and Prof. Rick Dale. My research interests lie in the realm of deep learning, cognitive science, and multimodal communication. I am proficient in developing multimodal deep learning networks that integrate auditory, visual, and semantic processing.
I previously worked as an NLP research intern at Testin to implement a Seq2Seq model for OCR misspelling correction. Several of my papers are published in the Communications in Computer and Information Science, Culture and Computing, Review of Communication, ICWSM and LREC workshop proceedings. I have won multiple top awards, including First Place Student Paper and Top Method Paper at the AEJMC conference.
I currently work as a PhD student researcher at the Computational Media Lab and Communicative Mind (Co-Mind) Lab. We develop a standardized end-to-end pipeline for multimodal analysis. Additionally, we propose statistical approaches for visualizing the learning trajectory of neural networks, contributing to model explainability using cognitive science theories.
As a rigorous computational social scientist and data science researcher from an interdisciplinary program, I enjoy developing and validating deep learning tools, answering impact-driven societal questions using machine learning, and bridging knowledge between fields.
In my free time, I like hiking, pilates, aerial yoga, Marathon, and true crime!
Access my Curriculum Vitae here.
Ph.D. Communication, 2026, University of California Los Angeles
M.A. Communication Management, 2019, University of Southern California
B.S. Business Administration & Cinematic Arts, 2018, University of Southern California
human-machine intelligence | multimodal communication
University of California Los Angeles
Department of Communication
yanrujiang AT g.ucla.edu