World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
101
Citations
50527
World Ranking
349
National Ranking
191

Research.com Recognitions

  • 2020 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2005 - ACM Fellow For contributions to planning algorithms.
  • 1999 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to development of qualitative reasoning methods, software agent technology, and plan synthesis algorithms.

Overview

Daniel S. Weld is affiliated with the University of Washington in the United States and has contributed to the field of computer science, with a strong focus on artificial intelligence and related subfields. Their research spans several areas including mobile crowdsensing and crowdsourcing, software engineering research, data stream mining techniques, auction theory and applications, artificial intelligence in games, AI-based problem solving and planning, and constraint satisfaction and optimization.

Their recent publications reflect a diverse range of topics within artificial intelligence and computer science applications. Notable papers include:

  • "Dynamically Switching between Synergistic Workows for Crowdsourcing" (2021), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "LRTDP Versus UCT for Online Probabilistic Planning" (2021), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Ontological Smoothing for Relation Extraction with Minimal Supervision" (2021), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • "Focused Topological Value Iteration" (2021), published in the Proceedings of the International Conference on Automated Planning and Scheduling
  • "Scim: Intelligent Skimming Support for Scientific Papers" (2022), published in arXiv (Cornell University)

Their collaborations include frequent coauthors such as Mausam Mausam, Eric Horvitz, Christopher H. Lin, Andrey Kolobov, and Congle Zhang.

Daniel S. Weld has published extensively in several venues, with the most common being:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the International Conference on Automated Planning and Scheduling

Their work covers multiple subfields including artificial intelligence, computer science applications, information systems, management science and operations research, and computer networks and communications.

Throughout their career, Daniel S. Weld has received recognition in the form of several awards. These include being named a Fellow of the American Association for the Advancement of Science (AAAS) in 2020, an ACM Fellow in 2005 for contributions to planning algorithms, and a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 1999 for contributions to qualitative reasoning methods, software agent technology, and plan synthesis algorithms.

Best Publications

  • Open information extraction from the web

    Oren Etzioni;Michele Banko;Stephen Soderland;Daniel S. Weld

  • SpanBERT: Improving Pre-training by Representing and Predicting Spans

    Mandar Joshi;Danqi Chen;Yinhan Liu;Daniel S. Weld

  • Wrapper induction for information extraction

    Nicholas Kushmerick;Daniel S. Weld

  • Unsupervised named-entity extraction from the Web: An experimental study

    Oren Etzioni;Michael Cafarella;Doug Downey;Ana-Maria Popescu

  • Guidelines for Human-AI Interaction

    Saleema Amershi;Dan Weld;Mihaela Vorvoreanu;Adam Fourney

  • TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

    Mandar Joshi;Eunsol Choi;Daniel S. Weld;Luke Zettlemoyer

  • Web-scale information extraction in knowitall: (preliminary results)

    Oren Etzioni;Michael Cafarella;Doug Downey;Stanley Kok

  • UCPOP: a sound, complete, partial order planner for ADL

    J. Scott Penberthy;Daniel S. Weld

  • Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations

    Raphael Hoffmann;Congle Zhang;Xiao Ling;Luke Zettlemoyer

  • A scalable comparison-shopping agent for the World-Wide Web

    Robert B. Doorenbos;Oren Etzioni;Daniel S. Weld

  • An Introduction to Least Commitment Planning

    Daniel S. Weld

  • Readings in qualitative reasoning about physical systems

    Daniel S. Weld;Johan de Kleer

  • A softbot-based interface to the Internet

    Oren Etzioni;Daniel Weld

  • Open Information Extraction Using Wikipedia

    Fei Wu;Daniel S. Weld

  • Scaling question answering to the Web

    Cody C. T. Kwok;Oren Etzioni;Daniel S. Weld

  • An adaptive query execution system for data integration

    Zachary G. Ives;Daniela Florescu;Marc Friedman;Alon Levy

  • CORD-19: The Covid-19 Open Research Dataset

    Lucy Lu Wang;Kyle Lo;Yoganand Chandrasekhar;Russell Reas

  • SUPPLE: automatically generating user interfaces

    Krzysztof Gajos;Daniel S. Weld

  • Intelligent agents on the Internet: Fact, fiction, and forecast

    O. Etzioni;D.S. Weld

  • Scaling question answering to the web

    Cody Kwok;Oren Etzioni;Daniel S. Weld

  • The psychology of everyday things: Donald A. Norman, (Basic Books, New York, 1988); 257 pages, $19.95

    Daniel S. Weld

Frequent Co-Authors

Oren Etzioni
Oren Etzioni University of Washington
Pedro Domingos
Pedro Domingos University of Washington
Stephen Soderland
Stephen Soderland University of Washington
Krzysztof Z. Gajos
Krzysztof Z. Gajos Harvard University
Luke Zettlemoyer
Luke Zettlemoyer University of Washington
Alon Halevy
Alon Halevy Facebook (United States)
Zachary G. Ives
Zachary G. Ives University of Pennsylvania
Eric Horvitz
Eric Horvitz Microsoft (United States)
Henry Kautz
Henry Kautz University of Virginia
Omer Levy
Omer Levy Deep Mind

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