Daniel S. Weld

Daniel S. Weld

A photo of Daniel S. Weld

Daniel S. Weld

General Manager & Chief Scientist for Semantic Scholar

Dan is General Manager & Chief Scientist of Semantic Scholar at AI2 and Professor Emeritus at the Paul G. Allen School of Computer Science & Engineering. After formative education at Phillips Academy, he received bachelor’s degrees in both Computer Science and Biochemistry at Yale University in 1982. He landed a Ph.D. from the MIT Artificial Intelligence Lab in 1988, received a Presidential Young Investigator’s award in 1989, an Office of Naval Research Young Investigator’s award in 1990, was named AAAI Fellow in 1999, deemed ACM Fellow in 2005, and selected to be an AAAS Fellow in 2020. Dan was a founding editor for the Journal of AI Research, was area editor for the Journal of the ACM, guest editor for Computational Intelligence and Artificial Intelligence, and was Program Chair for AAAI-96. Dan has published two books and scads of technical papers.

Dan is an active entrepreneur with several patents and technology licenses. He co-founded Netbot Incorporated, creator of Jango Shopping Search (acquired by Excite), AdRelevance, a monitoring service for internet advertising (acquired by Nielsen NetRatings), and data integration company Nimble Technology (acquired by Actuate). Dan is a Venture Partner at the Madrona Venture Group and on the Scientific Advisory Boards of Madrona and AI2.

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Current Ph.D. Students:

Graduated Ph.D. Students and Postdocs:

  • Tongshuang (Sherry) Wu Interactive AI Model Debugging and Correction (2022) (Co-advised with Jeff Heer) Carnegie Mellon University (Pittsburgh, PA)
  • Lucy Lu Wang Postdoc (2022) University of Washington (Seattle, WA)
  • Mandar Joshi How to train your self-supervised NLP model: Investigating pre-training objectives, data, and scale (2022) (Co-advised with Luke Zettlemoyer) Google Brain (Seattle, WA)
  • Tom Hope Postdoc (2022) Hebrew University (Jerusalem, Israel).
  • Gagan Bansal Three Maxims for Developing Human-Centered AI for Decision Making (2021) Microsoft Research (Redmond, WA).
  • Jonathan Bragg Self-Improving Crowdsourcing: Near-Effortless Design of Adaptive Distributed Work (Co-advised with Mausam) (2018) Allen Institute for Artificial Intelligence (Seattle, WA).
  • Chris Lin The Intelligent Management of Crowd-Powered Machine Learning (Co-advised with Mausam) (2017) Microsoft (Redmond, WA)
  • Lydia Chilton Adaptive Crowd Algorithms for Open-Ended Problems (Co-advised with James Landay)(2016) Columbia University (NYC, NY)
  • Xiao Ling Entity Analysis with Weak Supervision: Typing, Linking, and Attribute Extraction (2015) Lattice (Palo Alto, CA)
  • Congle Zhang Exploiting Parallel News Streams for Event Extraction (2015) Facebook (Seattle, WA)
  • Andrey Kolobov (2013) Scalable Methods and Expressive Models for Planning Under Uncertainty (Co-advised with Mausam) Honorable Mention: 2014 ICAPS Dissertation Award. Microsoft Research (Redmond, WA)
  • Raphael Hoffmann (2012) Interactive Learning of Relation Extractors with Weak Supervision (Co-advised with Luke Zettlemoyer). Lattice (Palo Alto, CA).
  • Peng Dai (2011) Decision Making under Uncertainty: Scalability and Applications (Co-advised with Mausam). Honorable Mention: 2012 ICAPS Dissertation Award. Google (Mountain View, CA).
  • Stefan Schoenmackers (2011) Inference over the Web (Co-advised with Oren Etzioni), Decide.com (Seattle, WA).
  • Fei Wu (2010) Machine Reading: from Wikipedia to the Web, Google (Mountain View, CA).
  • Eytan Adar (2009) Temporal Informatics of the WWW, Associate Professor, University of Michigan (Ann Arbor, MIT).
  • Krzysztof Gajos (2008) Automatically Generating Personalized User Interfaces (Co-advised with Jacob Wobbrock). Associate Professor, Harvard University (Cambridge, MA).
  • Mausam (2007) Stochastic Planning with Concurrent, Durative Actions Honorable Mention: 2008 ICAPS Dissertation Award.. Associate Professor, Indian Institute of Technology Delhi (New Delhi, India).
  • Zack Ives (2002) An Adaptive Query Execution System for Data Integration (Co-advised with Alon Halevy) Assistant Professor, University of Pennsylvania (Philadelphia, PA).
  • Corin Anderson (2002) A Machine Learning Approach to Web Personalization (Co-advised with Pedro Domingos) Research Staff, Google (Mountain View, CA).
  • Tessa Lau (2001) Programming by Demonstration using Version Space Algebra (Co-advised with Pedro Domingos) Research Staff, IBM T.J. Watson Research Center (Yorktown Heights, NY).
  • Marc Friedman (1999) Representation and Optimization for Data Integration (Co-advised with Alon Halevy) Software Engineer, Microsoft Corporation.
  • Nick Kushmerick (1997) _Wrapper Induction for Information Extraction_College Lecturer, Department of Computer Science, University College Dublin, Ireland
  • Keith Golden (1997) Planning with Incomplete Information Research Staff, NASA Ames Research Labs.
  • Anthony Barrett (1997) _Hierarchical Task Network Planning with an Expressive Action Language_Research Staff, JPL.
  • Franz Amador (1994) Self-Explanatory Simulation for an Electronic Encyclopedia Senior Software Architect, Equator Inc.
  • J. Scott Penberthy (1993) Planning with Continuous Change Technical Advisor to the Chairman, IBM.

Graduated M.S. Students

  • Kyle Xiao Contrastive Sentence-Level Data Augmentation for BioNLP Relation Extraction (2022) Jump Crypto (New York, NY)
  • Joyce Zhou, An Interactive UI to Support Sensemaking over Collections of Parallel Texts (2021) Cornell University (Ithaca, NY)
  • Daniel Gorrie, Argumentation Improvement Techniques for the MicroTalk Workflow (2017) Pioneer Square Labs (Seattle, WA)
  • Ryan Drapeau, MicroTalk: Using Argumentation to Improve Crowdsourcing Accuracy (2016). Facebook, Inc. (Seattle, WA)
  • Angli LiuCrowd Supervision for Relation Extraction (2015)
  • Shih-Wen Huang Toward Automatic Bootstrapping of Online Communities Using Decision-Theoretic Techniques (2015)
  • Mitchell Koch, Type-Aware Distantly Supervised Relation Extraction with Linked Arguments (2014)
  • Stephen Jonany, Crowdsourcing the Creation of Expert-Annotated Named Entity Datasets (2014)
  • Jiun-Hung Chen, Naive-Bayes POMDPs (2005).
  • Karthik Gopalratnam, Extending Continuous-Time Bayesian Networks (2005). (Co-advised with Henry Kautz) Google, Inc. (Mountain View, CA)
  • Tal Shaked, Named-Entity Extraction and Statistical Classification From the Web (2004). Google, Inc. (Mountain View, CA)
  • Igor Tatarinov, Updating XML (2001). (Co-advised with Alon Halevy; subsequently received a Ph.D. with Alon Halevy) Amazon.com. (Seattle, WA)
  • Steve Wolfman, The LPSAT Engine (1998). Subsequently received a Ph.D. with Richard Anderson. Instructor, University of British Columbia.
  • Cody Kwok, Planning to Gather Information (1996). Subsequently received a Ph.D. with Dieter Fox. Google (Mountain View, CA).
  • Dave Christianson, Graphical Plan Debugging(1996). Senior Software Engineer, Farecast, Inc.
  • Ying Sun, Beyond Simple Observation: Planning to Diagnose(1992). Senior Software Engineer, Go2Net.com.
  • Adam Finkelstein, Pika, the Evolution of a Simulator (1992). Subsequently received a Ph.D. with David Salesin. Associate Professor, Princeton University.
  • Dorothy Neville, Analyzing Mechanisms(1991).