September 1, 2020
With support from the Robust Intelligence program in the Division of Intelligent and Information Systems (IIS) and the NSF 2026 Fund Program in the Office of Integrated Activities, investigators at Boston College and Professor James Pustejovsky's team at Brandeis University are addressing the challenge of creating Artificial General Intelligence by synthesizing symbolic or logical reasoning, learning through interaction with the environment, as well as state-of-the-art neural networks. Inspired by the structure of natural (e.g., human) intelligence, the resulting mental architecture deploys each of these strategies for the problems they excel at (the "Best of All Worlds?, or BAW, approach). Successful completion of this project will facilitate a range of research projects in AI and psychology/neuroscience. Long-term, the development of AGI is expected to have significant benefits to society, by enabling computers to develop abstract concepts grounded in experience with the world, and to generate novel ideas and inventions. This project will also help broaden student training and participation of women and underrepresented minorities.
This project aims to prototype a new architecture and test it against an open-ended task that is difficult for artificial intelligence but mastered by human toddlers everywhere: uncovering the affordances of blocks, containers, and other small objects. The primary aims are to build a virtual world that a simulated infant can explore, manipulate, and learn from; build a working prototype of a simulated infant incorporating key aspects of the BAW mental architecture; and evaluate the performance of the agent on several difficult, open-ended tasks. This architecture facilitates incorporation of key concepts from the study of natural intelligence that are infrequently used in artificial intelligence: mental models, exploratory play, and chunking.
April 1, 2020
Computer science and linguistics professor James Pustejovsky is leading a Brandeis team in creating an artificial intelligence platform called Semantic Visualization of Scientific Data — or SemViz — that can sort through the growing mass of published work on coronavirus and help biologists who study the disease gain insights and notice patterns and trends across research that could lead to a treatment or cure. Read the full article in BrandeisNow as well as a feature story in the Brandeis Magazine.
September 1, 2019
WGBH announced today The Andrew W. Mellon Foundation’s renewed support for WGBH with a two-year, $750,000 grant, which will enhance usability of the American Archive of Public Broadcasting (AAPB). The AAPB is a collaboration between WGBH and the Library of Congress that aims to digitize and preserve thousands of hours of broadcasts and previously inaccessible programs from the more than 60-year legacy of public radio and public television. Over the next two years, the grant will support a two-pronged effort to make the AAPB an even more valuable resource for researchers, educators, academics and the public. The AAPB will work with Brandeis University’s Lab for Linguistics and Computation, headed by Professor James Pustejovsky, which uses machine learning and artificial intelligence to develop open-source tools and workflows, to capture detailed metadata from AAPB radio and television programs. This metadata, descriptive information about the people, places, dates and conversations in the archive, is a powerful way to improve access and discoverability of content. Read more here.
August 1, 2019
Brandeis University received a major grant to enhance the Language Application (LAPPS) Grid Project and EU’s CLARIN Platform to provide access to NLP-enabled tools to quickly analyze huge amounts of language for digital humanities to create Smart Archives. Brandeis was awarded a 16-month $673,000 grant from the Andrew W. Mellon Foundation to expand and deploy the LAPPS Grid Project which connects open-source computer programs to analyze texts from diverse sources and genres. The programs analyze any language content, determine the overall meaning, and help uncover hidden relationships embedded in the data. According to James Pustejovsky, the Project Director, the Mellon Foundation support will allow Brandeis and its collaborators from around the world to extend the range of the LAPPS Grid platform by linking it to a similarly broad and extensive one known as the European Common Language Resources and Technology Infrastructure (CLARIN). Read more here.
July 1, 2019
July 1, 2018
Professor Nianwen Xue and Professor James Pustejovsky (CO-PI) were awarded a $399,000 grant from the National Science Foundation to develop a uniform meaning representation for natural language processing. This is a collaborative project with University of Colorado and University of New Mexico. Detailed information can be found on the NSF website: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1763926&HistoricalAwards=false
April 1, 2017
The Dean of Arts and Sciences Mentoring Award is an annual award of $2,500 for "outstanding ability as a mentor" by a member of the faculty involved in the supervision of graduate students enrolled in the Graduate School of Arts and Sciences. We are delighted to announce that Professor Lotus Goldberg, Associate Professor of Language and Linguistics and Computational Linguistics Advising Chair received this year's Dean of Arts and Sciences Mentoring Award.
November 8, 2016
Brandeis announced that James Pustejovsky, the TJX/Feldberg Chair of Computer Science, has been awarded a two-year $390,000 grant from the Andrew W. Mellon Foundation to expand and deploy the LAPPS Grid Project that seamlessly connects open-source computer programs to quickly analyze huge amounts of language from diverse sources and genres.Read the full story on BrandeisNow