Bill Howe

Associate Professor, Information School
Adjunct Associate Professor, Computer Science & Engineering
Associate Director and Senior Data Science Fellow, UW eScience Institute
Program Director and Faculty Chair, UW Data Science Masters Degree
University of Washington
Short Bio | Curriculum Vitae | NSF-style biosketch | NIH-style biosketch
billhowe at cs.washington.edu | 206-221-9261 | Office: C610B in the WRF Data Science Studio

I am an Associate Professor in the Information School, Adjunct Associate Professor in Computer Science & Engineering, and Associate Director and Senior Data Science Fellow at the UW eScience Institute. I am a co-founder of Urban@UW, and with support from the MacArthur Foundation and Microsoft, I lead UW's participation in the MetroLab Network. I created a first MOOC on Data Science through Coursera, and I led the creation of the UW Data Science Masters Degree, where I serve as its first Program Director and Faculty Chair. I serve on the Steering Committee of the Center for Statistics in the Social Sciences.

My group's research aims to make the techniques and technologies of data science dramatically more accessible, particularly at scale. Our methods are rooted in database models and languages, though we sometimes work in machine learning, visualization, HCI, and high-performance computing. We are an applied, systems-oriented group, frequently sourcing projects through collaborations in the physical, life, and social sciences.


Data Science for Social Good
Building on our data science incubator program and the University of Chicago's Data Science for Social Good program, we ran an interdisciplinary summer program for...
Viziometrics
Machine vision, machine learning, and bibliometric analysis to understand how visualization is used to convey ideas in the scientific literature.
Myria Middleware for Polystores
Part of the Myria project, RACO (the Relational Algebra COmpiler) is a polystore middleware system that provides query translation, optimization, and orchestration across complex multi-system...
Clustering Billion-Edge Graphs
Working at the intersection of network science, databases, and high-performance computing, we developed a series of novel parallel algorithms based on Infomap serial graph clustering...
Scalable Flow Cytometry
We have developed algorithms, methods, systems, and applications in support of the Seaflow project in the Armbrust Lab in the UW department of Oceanography.
SQLShare: DB-as-a-Service
SQLShare aims to increase uptake of databases in data science and shed light on how data scientists work with data
VizDeck: Visualization Recommendation
VizDeck recommends visualizations based on the statistical properties of the data tempered by perception heuristics. Dashboards are assembled through a card-game UI.
Data Pricing
We developed theory and systems related to buying and selling data online.
Horizon: Big Data Analytics for Science
The Horizon project was one of the early efforts to study the limits of Hadoop for complex analytics. We developed Hadoop algorithms for visualization, machine...

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