VLDB 2026 Research / reviewers in the wild / expert
William R. Swartout
dblp:97/3882
· DBLP profile ↗
30ranked-venue papers
11as first author
1since 2021 · last 2023
0000-0002-7436-6940ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 18 · 8 first-authorArtificial intelligence and machine learning · 17 · 8 first-authorHuman-computer interaction and ubiquitous computing · 13 · 2 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 4 · 1 since 2021Software engineering, systems software and programming languages · 2 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
12 papers |
Multi-agent systems · 77% Knowledge representation and reasoning · 15% Question answering and dialogue systems · 4% | |
| Computer graphics and multimedia
3 papers |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
4 papers |
Human-AI interaction · 86% Games and playful interaction · 10% Usability and user experience research · 4% | |
| Software engineering, system software, and programming languages
5 papers |
Software maintenance and evolution · 87% Requirements engineering and software design · 5% Program synthesis and code generation · 4% |
Topics — the 20 heaviest of 26, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction › virtual agents
virtual human |
0.1 | 1 | 2007 | The More the Merrier: Multi-Party Negotiation with Virtual Humans · AAAI 2007 |
Virtual and augmented reality
virtual humans |
0.1 | 1 | 2006 | Virtual Humans · AAAI 2006 |
Virtual and augmented reality › virtual environment
immersive training |
0.0 | 1 | 2003 | Hollywood Meets Simulation: Creating Immersive Training Environments at the ICT · VR 2003 |
Virtual and augmented reality › virtual reality
virtual reality applications |
0.0 | 1 | 2001 | Tutorial 5: Virtual Reality for Fun and Profit · VR 2001 |
Software maintenance and evolution
software integration |
0.0 | 1 | 2005 | Virtual humans: lessons learned in integrating a large-scale AI project · ASE 2005 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
expert systems |
0.0 | 4 | 1986 | Towards Explicit Integration of Knowledge in Expert Systems: An Analysis of MYCIN's Therapy Selection Algorithm · AAAI 1986 Enhanced Maintenance and Explanation of Expert Systems Through Explicit Models of Their Development · IEEE Trans. Software Eng. 1985 Explainable (and Maintainable) Expert Systems · IJCAI 1985 |
Virtual and augmented reality
immersive audio |
0.0 | 1 | 2003 | Hollywood Meets Simulation: Creating Immersive Training Environments at the ICT · VR 2003 |
Virtual and augmented reality › virtual environment
virtual environment design |
0.0 | 1 | 2003 | Hollywood Meets Simulation: Creating Immersive Training Environments at the ICT · VR 2003 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
explanation generation |
0.0 | 3 | 1989 | A Reactive Approach to Explanation · IJCAI 1989 XPLAIN: A System for Creating and Explaining Expert Consulting Programs · Artif. Intell. 1983 A Digitalis Therapy Advisor with Explanations · IJCAI 1977 |
Games and playful interaction › extended reality games
virtual reality games |
0.0 | 1 | 2001 | Tutorial 5: Virtual Reality for Fun and Profit · VR 2001 |
Human-AI interaction › explainable AI
explanation generation |
0.0 | 1 | 1990 | Pointing: A Way Toward Explanation Dialogue · AAAI 1990 |
Software maintenance and evolution › software evolution
software evolvability |
0.0 | 1 | 1986 | The Shifting Terminological Space: An Impediment to Evolvability · AAAI 1986 |
Usability and user experience research
user modeling |
0.0 | 1 | 1985 | User Modelling · IJCAI 1985 |
Machine learning › Trustworthy machine learning
interpretability |
0.0 | 1 | 1983 | The GIST Behavior Explainer · AAAI 1983 |
Medical and health informatics
clinical decision support |
0.0 | 2 | 1986 | Towards Explicit Integration of Knowledge in Expert Systems: An Analysis of MYCIN's Therapy Selection Algorithm · AAAI 1986 A Digitalis Therapy Advisor with Explanations · IJCAI 1977 |
Natural language and speech › Language models and text generation
text generation |
0.0 | 1 | 1982 | GIST English Generator · AAAI 1982 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
reactive planning |
0.0 | 1 | 1989 | A Reactive Approach to Explanation · IJCAI 1989 |
Requirements engineering and software design
software architecture |
0.0 | 1 | 1986 | The Shifting Terminological Space: An Impediment to Evolvability · AAAI 1986 |
Program synthesis and code generation
programming by example |
0.0 | 1 | 1975 | Inferring LISP Programs From Examples · IJCAI 1975 |
Programming languages and type systems › functional programming
lisp |
0.0 | 1 | 1975 | Inferring LISP Programs From Examples · IJCAI 1975 |
Methods — techniques the papers use, named apart from their topics
speech synthesis · 0.1natural language processing · 0.1emotion modeling · 0.1pointing · 0.0knowledge capture · 0.0explanation generation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Can Virtual Agents Scale Up Mentoring?: Insights from College Students' Experiences Using the CareerFair.ai Platform at an American Hispanic-Serving Institution
Yuko Okado, Benjamin Nye, Angelica Aguirre, William R. Swartout |
AIED | 4 |
| 2018 | Mitigating Knowledge Decay from Instruction with Voluntary Use of an Adaptive Learning System
Andrew J. Hampton, Benjamin Nye, Philip I. Pavlik Jr., William R. Swartout, Arthur C. Graesser, Joseph Gunderson |
AIED (2) | 4 |
| 2015 | New Dimensions in Testimony: Digitally Preserving a Holocaust Survivor's Interactive Storytelling
David R. Traum, Val Jones 0002, Kia Hays, Heather Maio, Oleg Alexander, Ron Artstein, Paul E. Debevec, Alesia Gainer, Kallirroi Georgila, Kathleen Haase, Karen Jungblut, Anton Leuski, William R. Swartout |
ICIDS | 14 |
| 2014 | Time-offset interaction with a holocaust survivorabstractTime-offset interaction is a new technology that allows for two-way communication with a person who is not available for conversation in real time: a large set of statements are prepared in advance, and users access these statements through natural conversation that mimics face-to-face interaction. Conversational reactions to user questions are retrieved through a statistical classifier, using technology that is similar to previous interactive systems with synthetic characters; however, all of the retrieved utterances are genuine statements by a real person. Recordings of answers, listening and idle behaviors, and blending techniques are used to create a persistent visual image of the person throughout the interaction. A proof-of-concept has been implemented using the likeness of Pinchas Gutter, a Holocaust survivor, enabling short conversations about his family, his religious views, and resistance. This proof-of-concept has been shown to dozens of people, from school children to Holocaust scholars, with many commenting on the impact of the experience and potential for this kind of interface. Ron Artstein, David R. Traum, Oleg Alexander, Anton Leuski, Val Jones 0002, Kallirroi Georgila, Paul E. Debevec, William R. Swartout, Heather Maio |
IUI | 8 |
| 2013 | The Effects of a Pedagogical Agent for Informal Science Education on Learner Behaviors and Self-efficacy
H. Chad Lane, Clara Cahill, Susan Foutz, Daniel Auerbach, Dan Noren, Catherine Lussenhop, William R. Swartout |
AIED | 7 |
| 2012 | Ada and Grace: Direct Interaction with Museum Visitors
David R. Traum, Priti Aggarwal, Ron Artstein, Susan Foutz, Jillian Gerten, Athanasios Katsamanis, Anton Leuski, Dan Noren, William R. Swartout |
IVA | 9 |
| 2011 | Intelligent Tutoring Goes to the Museum in the Big City: A Pedagogical Agent for Informal Science Education
H. Chad Lane, Dan Noren, Daniel Auerbach, Mike Birch, William R. Swartout |
AIED | 5 |
| 2010 | Ada and Grace: Toward Realistic and Engaging Virtual Museum Guides
William R. Swartout, David R. Traum, Ron Artstein, Dan Noren, Paul E. Debevec, Kerry Bronnenkant, Josh Williams, Anton Leuski, Shri Narayanan, Diane Piepol |
IVA | 1 |
| 2010 | Virtual Museum Guides demonstrationabstractThe Virtual Museum Guides are two virtual humans set in an exhibit at the Museum of Science, Boston, designed to promote interest in Science, Technology, Engineering and Mathematics (STEM). The primary audience is children between ages 7 to 14, in particular females and other groups under-represented in STEM.The Guides are based on and extend the approach used in the SGT Star character and the Gunslinger project. To interact with the characters, an operator presses a push-totalk button and speaks into a microphone. An audio acquisition client then sends audio to the automatic speech recognizer (ASR), which creates hypotheses of the words that were said, and then sends this text to the Language Understanding (LU) module. William R. Swartout, David R. Traum, Ron Artstein, Dan Noren, Paul E. Debevec, Kerry Bronnenkant, Josh Williams, Anton Leuski, Shri Narayanan, Diane Piepol, H. Chad Lane, Jacquelyn Ford Morie, Priti Aggarwal, Matt Liewer, Jen-Yuan Chiang, Jillian Gerten, Selina Chu, Kyle White |
SLT | 1 |
| 2007 | The More the Merrier: Multi-Party Negotiation with Virtual Humans
Patrick G. Kenny, Arno Hartholt, Jonathan Gratch, David R. Traum, Stacy Marsella, William R. Swartout |
AAAI | 6 |
| 2006 | Virtual Humans
William R. Swartout |
AAAI | 1 |
| 2005 | Fight, Flight, or Negotiate: Believable Strategies for Conversing Under Crisis
David R. Traum, William R. Swartout, Stacy Marsella, Jonathan Gratch |
IVA | 2 |
| 2005 | Virtual humans: lessons learned in integrating a large-scale AI projectabstractVirtual humans are computer generated characters that can populate games or simulations. The behaviors of virtual humans are not scripted, but instead they use sophisticated AI techniques to reason about their environment and events as they unfold. Based on that reasoning, the virtual humans respond in believable ways. Virtual humans can interact in natural language, understanding speech and responding with synthesized speech. In addition to verbal communication, virtual humans can use non-verbal communication means such as gestures. In addition to rational behavior, virtual humans also have the ability to model and mimic human emotions.At the USC Institute for Creative Technologies, we have been engaged in the construction of virtual humans for the past six years. This project is not only a significant AI research effort, but it is also a significant software engineering task because a number of research projects must be integrated and work together to realize the virtual human. In this talk I will outline the virtual human effort, describe some of the synergies that have emerged from the software integration effort, and report on the lessons we have learned in this large-scale integration effort. William R. Swartout |
ASE | 1 |
| 2004 | Building Better Systems for Learning and Training: Bringing the Entertainment Industry and Simulation Technology Together
William R. Swartout |
ICEC | 1 |
| 2003 | Hollywood Meets Simulation: Creating Immersive Training Environments at the ICTabstractThe Institute for Creative Technologies is a federally funded research center set up three years ago at the University of Southern California to advance the state of the art in immersive training. Teaming researchers in artificial intelligence, graphics, animation and immersive audio with Hollywood writers, directors and special effect artists, the ICT brings a unique mix of high-technology and professional storytelling esthetic to the problem of creating compelling immersive environments. This afternoon tutorial will consist of a panel presentation by top ICT affiliated researchers to discuss this wide range of technologies and skills and how they relate to the design of virtual environments. The panel will be followed by a tour of the ICT facilities and demonstrations of several virtual training systems. Jonathan Gratch, Paul E. Debevec, Dick Lindheim, Frédéric H. Pighin, Jeff Rickel, William R. Swartout, David R. Traum, Jacquelyn Ford Morie |
VR | 6 |
| 2001 | Tutorial 5: Virtual Reality for Fun and Profit
Carolina Cruz-Neira, William R. Swartout, Michael R. Macedonia |
VR | 2 |
| 1999 | Bridging Science and Applications (Panel)abstractNo abstract available. Jude W. Shavlik, Lawrence Birnbaum, William R. Swartout, Eric Horvitz, Barbara Hayes-Roth |
IUI | 3 |
| 1990 | Pointing: A Way Toward Explanation Dialogue
Johanna D. Moore, William R. Swartout |
AAAI | 2 |
| 1989 | A Reactive Approach to Explanation
Johanna D. Moore, William R. Swartout |
IJCAI | 2 |
| 1986 | Towards Explicit Integration of Knowledge in Expert Systems: An Analysis of MYCIN's Therapy Selection Algorithm
Jack Mostow, William R. Swartout |
AAAI | 2 |
| 1986 | The Shifting Terminological Space: An Impediment to Evolvability
William R. Swartout, Robert Neches |
AAAI | 1 |
| 1985 | Explainable (and Maintainable) Expert Systems
Robert Neches, William R. Swartout, Johanna D. Moore |
IJCAI | 2 |
| 1985 | User Modelling
Derek H. Sleeman, Douglas E. Appelt, Kurt Konolige, Elaine Rich, William R. Swartout |
IJCAI | 6 |
| 1985 | Enhanced Maintenance and Explanation of Expert Systems Through Explicit Models of Their DevelopmentabstractPrincipled development techniques could greatly enhance the understandability of expert systems for both users and system developers. Current systems have limited explanatory capabilities and present maintenance problems because of a failure to explicitly represent the knowledge and reasoning that went into their design. This paper describes a paradigm for constructing expert systems which attempts to identify that tacit knowledge, provide means for capturing it in the knowledge bases of expert systems, and, apply it towards more perspicuous machine-generated explanations and more consistent and maintainable system organization. Robert Neches, William R. Swartout, Johanna D. Moore |
IEEE Trans. Software Eng. | 2 |
| 1983 | The GIST Behavior Explainer
William R. Swartout |
AAAI | 1 |
| 1983 | XPLAIN: A System for Creating and Explaining Expert Consulting Programs
William R. Swartout |
Artif. Intell. | 1 |
| 1982 | GIST English Generator
William R. Swartout |
AAAI | 1 |
| 1981 | Explaining and Justifying Expert Consulting Programs
William R. Swartout |
IJCAI | 1 |
| 1977 | A Digitalis Therapy Advisor with Explanations
William R. Swartout |
IJCAI | 1 |
| 1975 | Inferring LISP Programs From Examples
David E. Shaw, William R. Swartout, Cordell Green |
IJCAI | 2 |