Personal Information
Organization / Workplace
Greater Seattle Area, WA United States
Industry
Education
About
Data acquisition is outpacing data analysis in every scientific discipline. As a result, the process of *doing* science is fundamentally changing: Discoveries are increasingly made by querying large public databases rather than conducting primary experiments (consider GenBank and SDSS, for example). This shift mandates collaborations with computer scientists and technology experts, especially those in the database community.
As part of that community, my group builds systems that facilitate this new kind of data-intensive science. Our recent work focuses on a database-as-a-service systems targeting scientists (SQLShare and Myria). In the past, I've worked on a query language for "gr.
Tags
data science
databases
escience
big data
data-intensive
database
sql
disc
hadoop
fairness
urban science
mooc
cloud
science
oceanography
cloud computing
mapreduce
mining
nlp
workload
data science for social good
transparency
accountability
responsible data science
algorithmic bias
policy
teradata
query optimization
polystores
isim2017
simulation
social science
justice
polystore
ethics
reproducibility
data curation
human-data interaction
hpc
university of washington
relational algebra
research
education
workforce
analytics
uw
pnnl
graphs
clustering
uwescience
hpts2013
hpts
relational algorithmics
curriculum
bigdata
longtail
higher education
sqlshare
azure
sqlazure
long tail
gridfields
regridding
numerical methods
computer science
reproducible research
escience mashups databases mesh gridfields
haloop
visualization
moore
dataspace database sql escience sqlshare
dataspace database sql hiv escience
See more
- Presentations
- Documents
- Infographics