I am the Associate Division Director for Research of the Intelligent Systems Division at ISI. The division is home to more than one hundred AI researchers and PhD students. If you would like to visit ISI, give a talk, or join our research group, please contact me!
I am also Research Professor in the Department of Computer Science at USC. I designed a new course for teaching data science to non-programmers, which I teach in the USC Informatics Program.
Before coming to ISI in 1992, I received my PhD in Computer Science from Carnegie Mellon University. My thesis focused on the acquisition of planning knowledge through the formulation of deliberate experiments with the environment. I have been fascinated ever since with the challenge of enabling computers to learn new knowledge both autonomously and from being taught.
Quick Links: short bio, CV, awards and grants, research projects, publications, recent invited talks, teaching, contact information.
I have become very active in a new area: the development of intelligent systems to support data analysis and scientific discovery.
Our work has focused on semantic workflows that describe the input data, computations in the workflow steps, and all results of the workflow execution using semantic web languages (OWL, RDF, SPARQL) which are W3C standards. We have developed expressive representations of workflows, as well as a variety of reasoning algorithms for workflow composition through interactive assistance, workflow validation, automated workflow completion, metadata propagation, and workflow retrieval. A major result from our work is the Wings workflow system. On the Wings site there are publications, a web-accessible installation of our workflow system with a tutorial, examples from different science domains, and open source software if you are interested in downloading it. See also the Pegasus project site. In recent work, we are developing software metadata ontologies and software registries based on them in the OntoSoft project.
Reproducibility of scientific results has also been a major area of interest. Our Scientific Paper of the Future Geoscience Paper of the Future Initiatives provide training to scientists on best practices of reproducible papers, open science, and digital scholarship. It is also generating exemplar papers that follow these best practices to report research in different geosciences disciplines as part of a special issue of a few selected journals. See also below the overview of our work on provenance.Read more.
Provenance refers to the origins of objects. Software systems should generate provenance records for their results, containing assertions about the entities and activities involved in producing and delivering or otherwise influencing that object. By knowing the provenance of an object, we can for example make assessment about its validity and whether it can be trusted, we can decide how to integrate it with others, and can validate that it was generated according to specifications.
We are collaborating with the broader provenance community to develop general representations of provenance records through our participation in the World Wide Web Consortium (W3C) and the Open Geospatial Consortium (OGC). The W3C is an international standards body for Web Architecture and promotes the establishment of community-driven activities that may lead to standardization efforts. OGC is a standards body for geospatial information. The W3C work started with the Provenance Incubator Group, with a Final Report released in December 2010, which put forward use cases for provenance on the web, outlined requirements, compared existing provenance vocabularies, and recommended the creation of a standard. The W3C Provenance Working Group was established to develop this standard, which was released as PROV on April 2013. We are working with the OGC community to understand the specific requirements of geospatial information, analyze how PROV can be used in a geospatial context, and align PROV with other metadata standards used in the OGC community such as ISO. Provenance standards could change how trust, licensing, and information integration are done on the Web. Read more.
I am President-Elect of the Association for the Advancement of Artificial Intelligence (AAAI). I was elected in July 2016, and will become president in July 2018. AAAI is the foremost international association of AI researchers. AAAI sponsors several conferences, including AAAI, IAAI, EAAI, AIIDE, and several workshops and symposia. It also organizes educational activities, competitions that test AI systems, and a range of other activities that support the AI community. One of the most fun things I do for AAAI is be a judge at the Intel International Science and Engineering Fair (ISEF) where students from many countries present science projects, and most computer science projects are actually in AI. These young researchers develop amazing projects and are incredibly inspiring!
I was elected Chair of the Special Interest Group in Artificial Intelligence (SIGAI) of the Association for Computing Machinery for two terms, which ended in July 2016. I still serve in its Executive Committee as Past Chair. Among other things, we started the AI Matters magazine and the Career Network and Conference for early career researchers in AI. SIGAI supports the AI community with activities ranging from conference support, student fellowships, research awards, and publications management in the ACM Digital Library. Join ACM SIGAI today! And please contact any of the officers if you would like to volunteer and get involved.
I am General Chair for the International Semantic Web Conference, which will be held in Kobe on October 17-21, 2016. We have amazing invited speakers, and lots of opportunities to present your work. I hope to see many of you in Japan this Fall!
I regularly review for AAAI (I was program co-chair in 2006), IAAI, IUI (I was program chair in 2002), ISWC (I was program co-chair in 2005), K-CAP (I was general chair in 2009), WWW (I was area chair in 2010), and EKAW. I have also been in the program committee, though less frequently, for ICAPS, ICML (I was area chair in 2002), and KR.
There are two excellent papers that I strongly recommend to reviewers of conferences: "The health of research conferences and the dearth of big idea papers", by David Patterson and "Reviewing the reviewers", by Ken Church.
I am a founding Editorial Board member of the new ACM Transactions on Intelligent Systems and Technology, Journal of Web Semantics, and Applied Ontology, and an Editorial Board member of the Artificial Intelligence journal. I was Associate Editor of the Cognitive Science journal from 2006 to 2008.
I was chair of the Incubator Group on Provenance, which is part of the Semantic Web Activity at the World Wide Web Consortium. Provenance refers to the sources, entities, and processes involved in creating or delivering an artifact. Provenance is a topic of great interest in a variety of contexts including eBusiness, eGovernment, eScience, copyright and licensing, and linked data in the semantic web. The wiki contains several reports produced by the group, including its Final Report. I was involved in the follow-on W3C Provenance Working Group that led to the PROV standard.
I was elected to the National Science Foundation's EarthCube founding Leadership Council as representative (and Co-Chair) of the EarthCube Technology and Architecture Committee (TAC) for the term 2014-2017. The EarthCube initiative is a partnership between the NSF Directorate of Geosciences and the NSF Directorate of Computer Science and Engineering to transform geosciences research through novel cyberinfrastructure that is driven by the needs of the science community and supports unprecedented sharing, exploration, and discovery. Its Leadership Council oversees the governance of the EarthCube initiative, and the TAC is responsible for technology development, architecture design, and fostering standards.
I served in the Advisory Committee of the NSF Computer and Information Science and Engineering (CISE) Directorate from 2006 to 2008.
I designed a new course to teach data science to non-programmers. I am teaching that class at the USC Informatics program as INF549. You can see the class syllabus and several papers about the design of the curriculum.
I taught USC CS541 on "Artificial Intelligence Planning" on several semesters.
Picture credits: Lupe Forrester, August 2016
Last updated: August 5, 2016