Yun Bao
Doctoral Researcher at New York University
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolYun Bao is a doctoral researcher and behavioral scientist blending psychology, data science, and political science to design scalable interventions that shift emotion and behavior around societal challenges like polarization, misinformation, and climate change. With 11 years of research and engineering experience, Yun combines rigorous RCT design and longitudinal studies with advanced computational methods—NLP, network analysis, and large-scale modeling—to analyze millions of texts and develop targeted emotion-regulation strategies that boost mental health and civic engagement. They have optimized GPU-accelerated topic models on HPC clusters and contributed engineering improvements to high-profile open-source AI projects such as ParlAI, NeMo, and Megatron-LM, linking computational rigor to applied social science. At NYU, Harvard, and Stanford they led large datasets and pipelines (e.g., a 1,188-participant diary study during the 2024 US election and 60M+ Reddit comment analyses) and mentored 100+ students in research methods. Yun translates complex behavioral insights into actionable recommendations for industry and is actively seeking a Summer 2026 internship in computational social science, data science, people analytics, or UX research. A less obvious strength is their full-stack product experience from undergrad work—building web apps and intervention modules—giving them rare end-to-end fluency from experiment design to production systems.
11 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of Southern CaliforniaDoctor of Philosophy - PhD, Social Psychology, Doctor of Philosophy - PhD, Social Psychology at New York University
English, Chinese
Github Skills (27)
transformers10
pytorch10
python10
model-driven10
machine-learning10
text-normalization10
large-language-models10
reinforcement-learning10
data-preprocessing10
model-building10
dialogue-systems10
deep-learning10
trainings10
ai10
question-answering10
Programming languages (2)
Github contributions (5)
NVIDIA/NeMo
Sep 2019 - Jan 2023
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:695 reviews, 653 commits, 588 PRs in 3 years 4 months
Contributions summary:Yun appears to be primarily focused on the development and maintenance of the back-end functionality within the NeMo toolkit. They were involved in fixing an issue in a named entity recognition file and adding support for the new T5 tokenizer. Furthermore, the user was responsible for extending the text normalization grammars with additional components, and contributing to the support for more parameters.
asrspeech-recognitionnatural-language-processingttsspeaker-diarization
NVIDIA/Megatron-LM
Apr 2020 - Oct 2020
Ongoing research training transformer models at scale
Role in this project:ML Engineer
ML EngineerContributions:16 commits in 5 months
Contributions summary:Yun primarily contributed to the project by updating and modifying the `setup.py` and `megatron/package_info.py` files, which are essential for packaging and distributing the Megatron-LM library. They added and updated support for pip, adjusted the versioning, and modified package information, indicating a focus on improving the usability and distribution of the project. These changes are crucial for making the large language model training framework accessible and maintainable for others to use and contribute to.
pytorchnlplanguage-modeltransformer-modelsbert
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