Kevin Zeng Hu (kzh)
Accessible Data Analysis
PhD Candidate at the MIT Media Lab | Twitter | LinkedIn | Goodreads

We should all be able to ask questions of our data. Towards this end, I build data visualization and analysis tools that are accessible to the many, not just the few. My approach is to combine human-centered interface design, recommender systems, and machine learning — though the "how?" is secondary to the "why?"

I'm currently a graduate student with the Collective Learning Group at the MIT Media Lab. Previously, I studied Physics at MIT and interned at several tech companies. My past projects have been published in top academic journals and covered in diverse media outlets, though I'm proudest of having reached the front page of Reddit.

Selected Projects:
VizML (2019)
Machine learning for visualization recommendation
Info: Preprint, Paper (forthcoming in CHI 2019)
VizNet (2019)
Large-scale visualization learning and benchmarking repository
Info: Paper (forthcoming in CHI 2019)
DIVE (2018)
Semi-automated data exploration system
Info: Video, Paper
Clinton Circle (2016)
Visualize WikiLeaks e-mails as network of connections
Press: Univision
Global Language Network (2014)
Understand the connection between languages
Info: Video, Paper
Pantheon (2014)
Explore historical cultural production
Info: Video, Paper
GIFGIF (2014)
Measure the emotional content of animated GIFs
FOLD (2014)
Read and write non-linear, contextual stories


Last Updated on Feb 2019