PhD Candidate in Computer Science
Hi! I'm a PhD candidate in the Computer Science Department at Stanford University
where I work with Jure Leskovec and am part of SNAP, the InfoLab, and the Mobilize Center.
I enjoy analyzing large-scale traces of human activity to learn more about human behavior.
Most recently, I have been working on computational linguistic methods to analyze counseling and conversation strategies and data mining and social network analysis techniques to better understand exercise and health behaviors and their relation to health outcomes.
August 2016: Our TACL paper on a large-scale analysis of crisis counseling conversations got featured in
May 2016: Kevin Clark and I published a blog post on the Stanford NLP blog highlighting some of the main results of our recent large-scale analysis of crisis counseling conversations.
May 2016: Our
on natural language processing for mental health analyzing a large annotated corpus of counseling conversations got accepted for publication at TACL.
More information on the project can be found here.
April 2016: I gave an invited talk at the "Wearable Devices & the 24-hour Activity Cycle" conference about "Consumer Mobile Tracking Devices as a Sensor for Physical Activity from Personal to Planetary Scale" organized by William Haskell,
Mary Rosenberger, and
March 2016: Hima Lakkaraju and I gave a lecture on submodular optimization in CS246 at Stanford. You can find the slides here. The featured paper on automatic timeline generation can be found here.
February 2016: I am honored to receive an Outstanding Reviewer award at WSDM 2016.
February 2016: I am excited to be working with Eric Horvitz and Ryen White at Microsoft Research this summer.
January 2016: My proposal on "Empowering Users Through Supportive Social Networks" was selected as a finalist for the Facebook fellowship.
August 2015: I am presenting our work on
automatic timeline generation
Check out the
slides, or our
May 2015: Our work on donor retention was featured on
and I wrote a guest post about it on the DonorsChoose Data Science Blog.
May 2015: I am honored and deeply grateful to be awarded a three-year
Stanford Graduate Fellowship (SGF).
March 2015: My proposal on "Healthier lives through supportive social networks" was selected as a finalist for the Facebook fellowship.
September 2014: I am now a fellow at DERP, an alliance of platforms supporting the academic exploration of communities online. Our work on helping behavior in reddit has been featured in The Guardian and The Economist.
June - September 2013: I interned in Google's machine intelligence group in Mountain View working on automatic timeline generation for entities with rich history together with
and Wei Zhang.
June 2014: My thesis on trending topics in online media has been awarded an university-wide thesis award from the Kreissparkassen-Foundation (awarded across all disciplines).
June 2014: Our work on trending topics in online media has been featured on Technology.org.
May 2014: Our work on how to ask for a favor has been featured across a number of news sites and media outlets including the
Slate's Future Tense blog,
International Business Times,
May - August 2013: I interned at Google Research in Mountain View again working on music recommendation for YouTube with David Ross, Huazhong Ning, and Mohamad Tarifi.
January 2013: Our work on trending topics in online media has been awarded with a PiCloud Academic Research Program Grant.
April 2013: After completing my classes at UC Berkeley and completing my thesis at the German Research Center for Artificial Intelligence I graduated with honors from University of Kaiserslautern (MS).
May - September 2012: I interned at Google Research in Mountain View working on YouTube Music with David Ross, Douglas Eck, and Hrishikesh Aradhye.
August 2011 - May 2012: I visited Trevor Darrell's vision group at UC Berkeley and ICSI working on object detection and multimedia event recognition.
Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition
Tim Althoff, Hyun Oh Song, Trevor Darrell
ACM Multimedia 2012
Sparselet Models for Efficient Multiclass Object Detection
Hyun Oh Song, Stefan Zickler, Tim Althoff, Ross Girshick, Mario Fritz, Christopher Geyer, Pedro Felzenszwalb, Trevor Darrell
Proceedings of ECCV 2012
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
Authorship Attribution in Multi-author Documents
Tim Althoff, Denny Britz, Zifei Shan
CS224U Natural Language Understanding (Chris Potts and Bill MacCartney) and
CS341 Project in Mining Massive Data Sets (Jure Leskovec, Jeff Ullman, Anand Rajaraman), Spring 2013/2014
Recommending CouchSurfers: Machine Learning for Social Travel
Ron Sun, Tobi Baumgartner, Tim Althoff, Sergey Karayev
CS281B Scalable Machine Learning (Alex Smola), Spring 2012
University of California, Berkeley
Iterative Learning: Leveraging the Computer as an On-Demand Expert Artist
Tim Althoff, Armin Samii
CS281A Statistical Learning Theory (Michael Jordan and Martin Wainwright) and
CS294-69 Image Manipulation and Computational Photography (Maneesh Agrawala), Fall 2011
University of California, Berkeley
Social Media Driven Concept Detection (survey)
Seminar on Collaborative Intelligence (Andreas Dengel), Summer 2011
University of Kaiserslautern
Jam-or-Fold: Eine spieltheoretische Betrachtung des Heads-Up Poker (English: Jam-or-Fold: A Game-theoretic Treatment of Heads-up Poker)
Freshman paper (Hausarbeit), September 2008
Eine mathematische Betrachtung des RSA-Verfahrens (English: A Mathematical Treatment of the RSA algorithm)
High School paper (Facharbeit), May 2006
email: [my last name] @stanford.edu
CV/references available upon request