Bill Howe

Associate Professor, Information School
Adjunct Associate Professor, Computer Science & Engineering
Adjunct Associate Professor, Electrical Engineering
Co-Founding Faculty Director, Center for Responsible AI Systems and Experiences
Director, Urbanalytics Lab
Founding Program Director and Faculty Chair, UW Data Science Masters Degree
Founding Associate Director and Senior Data Science Fellow, UW eScience Institute
University of Washington
Short Bio | Curriculum Vitae | NSF-style biosketch | NIH-style biosketch
billhowe at uw.edu | Office: MGH 310 in the iSchool DataLab

I am an Associate Professor in the Information School, Adjunct Associate Professor in Computer Science & Engineering and Electrical Engineering. I was Founding Associate Director of the UW eScience Institute where I remain a Senior Data Science Fellow. I currently serve as Faculty Director and Co-Founder of the Center for Responsible AI Systems and Experiences and Director of the Urbanalytics group. I am a co-founder of Urban@UW. 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 current research is in the epistemological foundations of AI, where we apply empirical methods and develop new algorithms to make AI safer for use in applications underserved by market forces, especially in the public sector and in the physical, life, and social sciences. My prior research was in developing systems and algorithms to make the techniques and technologies of data science broadly accessible especially in contexts where issues of equity, privacy, and compliance are paramount. Our methods and publications span three communities: AI, data management, and visualization, and my students have achieved recognition in all three fields. We are an applied, systems-oriented group, frequently sourcing projects through collaborations across campus and with local and state governments.


News

Projects

EZLearn+Automatic Claim Validation
We are developing an end-to-end system for validating scientific claims against open data repositories using NLP, machine learning, and data integration techniques.
Privacy-Preserving Synthetic Data
We are developing usable, general tools to generate shareable synthetic datasets with strong privacy guarantees from any input dataset.
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 Recommenders
VizDeck recommends visualizations based on the statistical properties of the data tempered by perception heuristics. Dashboards are assembled through a card-game UI.

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