Associate Professor, Information School
Adjunct Associate Professor, Computer Science & Engineering
Adjunct Associate Professor, Electrical Engineering
Co-Founding 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 |
billhowe at uw.edu | Office: MGH 310 in the iSchool DataLab
My group's research aims to make the techniques and technologies of data science broadly accessible, especially in the public sector where issues of equity, privacy, and compliance are paramount. Our methods are rooted in database models and languages, though we also study 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. Our current interests are in algorithmic fairness, machine learning for heterogeneous data, and urban computing.
June, 2019: Our paper on algorithmic fairness (with Babak Salimi, Luke Rodriguez, and Dan Suciu) received the Best paper award at SIGMOD 2019!
May, 2019: My student Dominik Moritz's (now at CMU!) paper on Falcon, demonstrating in-browser, interactive speeds for cross-linked visualizations on billion-tuple datasets received the Best paper award at VIs 2019!
July 26, 2018: I'm giving an invited talk at NSF on our work on algorithmic curation of science data repositories.
July 21, 2018: Best paper award Our paper on DRACO using answer set programming to model visualization recommendation rules won best paper at InfoVis 2018! Congratulations to Dominik and the whole team!
July 18, 2018: I presented our paper on EZLearn at IJCAI 2018 in Stockholm. EZLearn combines distant supervision and co-learning to avoid the need for training data in applications that have access to noisy free-text descriptions of data, especially in science.
July 10, 2018: Congratulation to Kanit (Ham) Wongsuphasawat for defending his thesis on visualization recommendation systems! Ham is joining Apple as a Research Scientist.