Demo Data from VLDB 2026 / reviewers in the wild / expert
Ramesh S. Patil
dblp:56/2410
· DBLP profile ↗
8ranked-venue papers
3as first author
0since 2021 · last 1997
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 7 · 3 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-authorApplied, interdisciplinary, general and emerging computing · 2Theory of computation · 1 · 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
4 papers |
Knowledge representation and reasoning · 100% | |
| Theoretical computer science
2 papers |
Logic in computer science · 64% Automated reasoning and model checking · 18% Algorithmic game theory and mechanism design · 18% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% |
Topics — the 8 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning › knowledge management
knowledge sharing |
0.0 | 1 | 1992 | The DARPA Knowledge Sharing Effort: A Progress Report · KR 1992 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
description logic |
0.0 | 1 | 1991 | Two Theses of Knowledge Representation: Language Restrictions, Taxonomic Classification, and the Utility of Representation Services · Artif. Intell. 1991 |
Logic in computer science › knowledge representation and reasoning
knowledge representation |
0.0 | 1 | 1991 | Two Theses of Knowledge Representation: Language Restrictions, Taxonomic Classification, and the Utility of Representation Services · Artif. Intell. 1991 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
knowledge acquisition |
0.0 | 1 | 1986 | Panel: Knowledge Representation Meets Knowledge Acquisition: What Are the Needs and Where Is the Leverage? · AAAI 1986 |
Automated reasoning and model checking
diagnosis |
0.0 | 1 | 1982 | Information Acquisition in Diagnosis · AAAI 1982 |
Algorithmic game theory and mechanism design › decision theory
information acquisition |
0.0 | 1 | 1982 | Information Acquisition in Diagnosis · AAAI 1982 |
Medical and health informatics
clinical diagnosis |
0.0 | 1 | 1981 | Causal Understanding of Patient Illness in Medical Diagnosis · IJCAI 1981 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
causal reasoning |
0.0 | 1 | 1981 | Causal Understanding of Patient Illness in Medical Diagnosis · IJCAI 1981 |
Methods — techniques the papers use, named apart from their topics
taxonomic classification · 0.0representation services · 0.0causal inference · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Critical Care Decision Support System
Jafar Adibi, Ramesh S. Patil, William C. Shoemaker |
AMIA | 2 |
| 1992 | The DARPA Knowledge Sharing Effort: A Progress Report
Ramesh S. Patil, Richard Fikes, Peter F. Patel-Schneider, Donald P. McKay, Tim Finin, Thomas R. Gruber, Robert Neches |
KR | 1 |
| 1991 | Two Theses of Knowledge Representation: Language Restrictions, Taxonomic Classification, and the Utility of Representation Services
Jon Doyle, Ramesh S. Patil |
Artif. Intell. | 2 |
| 1987 | An Expert System for Screening Employee Pension Plans for the Internal Revenue ServiceabstractThis paper describes the development of an expert system demonstration prototype for identifying legal issues within the domain of employee pension plans. Pension plans are submitted by employers to the Internal Revenue Service for approval as to content, and obtain subsequent tax advantages. The prototype is able to identify and analyze legal issues, reach conclusions about a plan's conformity with the issues identified, and provide an explanation of the conclusions reached by the system. Success in the program's ability to identify and explain legal issues was determined by comparing the system's conclusions with those of an expert in the field. G. Grdy, Ramesh S. Patil |
ICAIL | 2 |
| 1986 | Panel: Knowledge Representation Meets Knowledge Acquisition: What Are the Needs and Where Is the Leverage?
Robert Neches, Richard Fikes, Casimir A. Kulikowski, John P. McDermott, Ramesh S. Patil |
AAAI | 5 |
| 1982 | Information Acquisition in Diagnosis
Ramesh S. Patil, Peter Szolovits, William B. Schwartz |
AAAI | 1 |
| 1982 | Coping with Syntactic Ambiguity or How to Put the Block in the Box on the Table
Kenneth Church 0001, Ramesh S. Patil |
Am. J. Comput. Linguistics | 2 |
| 1981 | Causal Understanding of Patient Illness in Medical Diagnosis
Ramesh S. Patil, Peter Szolovits, William B. Schwartz |
IJCAI | 1 |