Tim Althoff

I develop computational methods to improve human well-being, combining techniques from data science, social network analysis, and natural language processing.

My research leverages detailed behavioral data from smartphones, smartwatches, and social interactions at the scale of billions of actions taken by millions of people, to realize new types of scientific approaches that generate actionable insights about our lives, health, and happiness.

I am looking for PhD students, especially in but not limited to causal inference, deep learning, and data science. If you're interested please apply to UW Paul G. Allen School of Computer Science & Engineering. Go Dawgs!

Recent highlights

Leveraging Routine Behavior and Contextually-Filtered Features for Depression Detection among College Students
Xuhai Xu, Prerna Chikersal, Afsaneh Doryab, Daniella Villalba, Janine M. Dutcher, Michael J. Tumminia, Tim Althoff, Sheldon Cohen, Kasey Creswell, David Creswell, Jennifer Mankoff, Anind K. Dey
IMWUT/UbiComp 2019
Best Practices for Analyzing Large-scale Health Data from Wearables and Smartphone Apps
Jennifer L. Hicks, Tim Althoff, Rok Sosic, Peter Kuhar, Bojan Bostjancic, Abby C. King, Jure Leskovec, Scott L. Delp
NPJ Digital Medicine (2) 2019
Learning Individualized Cardiovascular Responses from Large-scale Wearable Sensors Data
Haraldur T. Hallgrímsson, Filip Jankovic, Tim Althoff, Luca Foschini
NIPS ML4H 2018
Data Science for Human Well-being
Tim Althoff
Ph.D. Thesis, Stanford University
SIGKDD Dissertation Award 2019
thesis   defense
Modeling Interdependent and Periodic Real-World Action Sequences
Takeshi Kurashima, Tim Althoff, Jure Leskovec
WWW 2018
Modeling Individual Cyclic Variation in Human Behavior
Emma Pierson, Tim Althoff, Jure Leskovec
WWW 2018
Psychomotor function measured via online activity predicts motor vehicle fatality risk
Tim Althoff, Eric Horvitz, Ryen W. White
NPJ Digital Medicine (1) 2018
pdf   suppl. inf.   method details
Large-scale physical activity data reveal worldwide activity inequality
Tim Althoff, Rok Sosic, Jennifer L. Hicks, Abby C. King, Scott L. Delp, Jure Leskovec
Nature (547.7663) 2017
pdf   suppl. inf.   Nature   project   press releases   dataset
Population-Scale Pervasive Health
Tim Althoff
IEEE Pervasive Computing 2017
Harnessing the Web for Population-Scale Physiological Sensing: A Case Study of Sleep and Performance
Tim Althoff, Eric Horvitz, Ryen W. White, Jamie Zeitzer
WWW 2017
pdf   appendix   slides  
Quantifying Dose Response Relationships Between Physical Activity and Health Using Propensity Scores
Tim Althoff, Rok Sosic, Jennifer L. Hicks, Abby C. King, Scott L. Delp, Jure Leskovec
NIPS Workshop on Machine Learning for Health 2016
TimeMachine: Timeline Generation for Knowledge-Base Entities
Tim Althoff, Xin Luna Dong, Kevin Murphy, Safa Alai, Van Dang, Wei Zhang
KDD 2015
pdf   full version   slides   poster   demo
How to Ask for a Favor: A Case Study on the Success of Altruistic Requests
Tim Althoff, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky
ICWSM 2014
pdf   slides   dataset
Analysis and Forecasting of Trending Topics in Online Media Streams
Tim Althoff, Damian Borth, Jörn Hees, Andreas Dengel
ACM Multimedia 2013
pdf   slides
Analysis and Forecasting of Trending Topics in Online Media
Tim Althoff
Master's Thesis, University of Kaiserslautern, Germany April 2013
pdf   slides
Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition
Tim Althoff, Hyun Oh Song, Trevor Darrell
ACM Multimedia 2012
pdf   poster
Sparselet Models for Efficient Multiclass Object Detection
Hyun Oh Song, Stefan Zickler, Tim Althoff, Ross Girshick, Mario Fritz, Christopher Geyer, Pedro Felzenszwalb, Trevor Darrell
ECCV 2012
pdf   project   demo video
Don't Look Back: Post-hoc Category Detection via Sparse Reconstruction
Hyun Oh Song, Mario Fritz, Tim Althoff, Trevor Darrell
UC Berkeley, Tech. Rep. UCB/EECS-2012-16 Jan. 2012
pdf   archive
Balanced Clustering for Content-based Image Browsing
Tim Althoff, Adrian Ulges, Andreas Dengel
German Computer Science Society, Informatiktage March 2011
pdf   project   demo
Scalable Clustering for Hierarchical Content-based Browsing of Large-scale Image Collections
Tim Althoff
Bachelor's Thesis, University of Kaiserslautern, Germany September 2010

Paul G. Allen School of Computer Science & Engineering at the University of Washington

Assistant Professor
Computer Science
University of Washington

Gates Center #313
3800 E Stevens Way NE
Box 352355
Seattle, WA 98195

Google Scholar

Many thanks to David Jurgens for the site template/inspiration