Curriculum vitae
Mu-Jung “MJ” Cho|卓牧融
Scientist with over 10 years of data-science research experience, specializing in behavioral and psychological analytics and human–computer interaction. Led a cloud infrastructure housing 100TB+ of digital-trace data from 500+ participants. Peer-reviewed publications on knowledge discovery from digital screen records.
Academic Positions
Dec 2023 –
Assistant Research Fellow
Center for Survey Research, RCHSS, Academia Sinica, Taipei
2020 – 2023
Postdoctoral Research Fellow
Solutions Science Lab, Department of Pediatrics, Stanford University School of Medicine
Education
Aug 2020
Ph.D. in Communication
Stanford University
Jun 2014
M.A. in East Asian Studies
Stanford University
Jun 2009
B.A. in Economics, minor in Political Science
National Taiwan University
Grants
2019 – 2020
Magic Grant, Brown Institute for Media Innovation — US$100,000
Co-PI. Screenomics Interactive Dashboard.
2018
Summer Research Grant — US$3,500
Center for East Asian Studies, Stanford University
2016
Summer Research Grant — US$5,000
Center for East Asian Studies, Stanford University
Honors & Fellowships
2021
Nathan Maccoby Dissertation Award
Department of Communication, Stanford University — awarded only in years with a truly outstanding dissertation
2019 – 2020
The March Fong Eu Fellowship
Stanford University
2019
Dissertation Fellowship
Institute for Research in the Social Sciences, Stanford University
2018 – 2019
The May Chandler Goodan Fellowship
Stanford University
2017
Computational Social Science Fellowship
Institute for Research in the Social Sciences, Stanford University
2014 – 2016
National Scholarship for Overseas Study
Ministry of Education, Taiwan (R.O.C.)
2014 – 2015
The Melville J. Jacoby Fellowship
Stanford University
2012 – 2014
Academic-Year Fellowship
Center for East Asian Studies, Stanford University
Teaching
Stanford
Teaching Assistant
COMM 121S — Audience 2.0: Changing Practices and Experiences of Audiencing in the Digital Age · COMM 154/254 — The Politics of Algorithms · COMM 108/208 — Media Processes and Effects · COMM 172/272 — Media Psychology · COMM 121 — Behavior and Social Media
Technical Skills
Digital-trace measurement
Screenomics capture and pipeline design (Android, 5 s sampling) · GCP at scale — BigQuery, GCS, Compute Engine, Vertex AI · Spark · 250M+ screenshots, 100TB+ corpus
Vision & multimodal
OCR and text extraction from screens · object and face detection · vision transformers and multimodal LLMs for content labelling (Media Content Atlas) · PyTorch · CLIP-style embeddings
Language & LLM methods
NLP on screen text · LLM structured labelling with agreement checks · embeddings, UMAP + HDBSCAN clustering with Optuna sweeps · topic and sentiment models
Statistical modelling
Intensive-longitudinal and multilevel time-series models · person-specific (idiographic) models · survey-weighted multilevel models · causal inference · R and Python (statsmodels, lme4/brms)
Survey & measurement
Probability vs nonprobability sample accuracy · resampling and post-stratification estimators · scale development and validation (the informational-threat battery) · questionnaire design
Languages & tooling
Python · R · SQL · JavaScript/TypeScript · C/C++ · git · Quarto, Typst, LaTeX · reproducible pipelines; agentic research workflows with LLM tooling
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