VLDB 2026 Research / reviewers in the wild / expert
William H. Smith
dblp:49/10818
· DBLP profile ↗
3ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
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
1 paper |
Trustworthy machine learning · 50% Language models and text generation · 50% | |
| Network and information security
1 paper |
Systems and software security · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Trustworthy machine learning
AI safety |
0.9 | 1 | 2025 | To Err Is AI: A Case Study Informing LLM Flaw Reporting Practices · AAAI 2025 |
Natural language and speech › Language models and text generation
large language model safety |
0.9 | 1 | 2025 | To Err Is AI: A Case Study Informing LLM Flaw Reporting Practices · AAAI 2025 |
Systems and software security › vulnerability management
bug bounty programs |
0.3 | 1 | 2025 | To Err Is AI: A Case Study Informing LLM Flaw Reporting Practices · AAAI 2025 |
Systems and software security › vulnerability management
vulnerability disclosure |
0.3 | 1 | 2025 | To Err Is AI: A Case Study Informing LLM Flaw Reporting Practices · AAAI 2025 |
Methods — techniques the papers use, named apart from their topics
bug bounty · 1.7red-teaming · 0.9red teaming · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | To Err Is AI: A Case Study Informing LLM Flaw Reporting PracticesabstractIn August of 2024, 495 hackers generated evaluations in an open-ended bug bounty targeting the Open Language Model (OLMo) from The Allen Institute for AI. A vendor panel staffed by representatives of OLMo's safety program adjudicated changes to OLMo's documentation and awarded cash bounties to participants who successfully demonstrated a need for public disclosure clarifying the intent, capacities, and hazards of model deployment. This paper presents a collection of lessons learned, illustrative of flaw reporting best practices intended to reduce the likelihood of incidents and produce safer large language models (LLMs). These include best practices for safety reporting processes, their artifacts, and safety program staffing. Sean McGregor, Allyson Ettinger, Nick Judd, Paul Albee, Kavel Rao, William H. Smith, Shayne Longpre, Avijit Ghosh, Christopher Fiorelli, Michelle Hoang, Sven Cattell, Nouha Dziri |
AAAI | 7 |
| 2001 | Surface reflectance mapping using interferometric spectral imagery from a remotely piloted aircraftabstractDuring October 1997, a prototype sensor was flown on an experimental remotely piloted aircraft over the island of Kauai as part of a terrestrial remote sensing technology feasibility study. The authors describe the deployment, testing, and evaluation of the compact lightweight sensor design based on two-beam interferometry for acquiring visible and near-infrared spectral images. The resulting images of agricultural fields and an air base facility are presented and evaluated. Surface albedo measurements obtained from a ground based spectrometer and an atmospheric profile measured from a radiosonde were used to establish ground-truth and to evaluate the spectral imager's performance. Quantitative intercomparisons between ground-based and airborne-based measurements were made using an atmospheric model based on MODTRAN together with algorithms to account for the sensors' differences in instrumental line shape and spectral sampling grids. The future potential of this alternative sensor technology is discussed in the light of current and predicted sensor performance. Philip D. Hammer, Lee F. Johnson, Anthony W. Strawa, Stephen E. Dunagan, Robert G. Higgins, James A. Brass, Robert E. Slye, Don V. Sullivan, William H. Smith, Brad M. Lobitz, David L. Peterson |
IEEE Trans. Geosci. Remote. Sens. | 9 |
| 1996 | Experimental techniques for investigating cardiac electrical activity and response to electrical stimuliabstractOne of the goals of experimental research in the areas of cardiac electrical activity and effects of stimulation has been to understand basic physiological responses of the heart to electrical stimulation. It is thought that electrical stimulation produces a distribution of current or an electric field in the heart that alters the transmembrane voltages of heart cells. This leads to changes in states of transmembrane voltage-dependent ionic currents, altered electrophysiological behavior of cells, and finally alteration of the electrophysiological behavior of the heart. The research has employed standard electrophysiological measurement techniques and new techniques that have been developed to study specific effects. This paper discusses some of the techniques. Stephen B. Knisley, William H. Smith |
Proc. IEEE | 2 |