Philip Laird

2.6k total citations
21 papers, 1.5k citations indexed

About

Philip Laird is a scholar working on Artificial Intelligence, Computer Networks and Communications and Management Science and Operations Research. According to data from OpenAlex, Philip Laird has authored 21 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 5 papers in Management Science and Operations Research. Recurrent topics in Philip Laird's work include Machine Learning and Algorithms (9 papers), Scheduling and Optimization Algorithms (5 papers) and Scheduling and Timetabling Solutions (5 papers). Philip Laird is often cited by papers focused on Machine Learning and Algorithms (9 papers), Scheduling and Optimization Algorithms (5 papers) and Scheduling and Timetabling Solutions (5 papers). Philip Laird collaborates with scholars based in United States and France. Philip Laird's co-authors include Dana Angluin, Andrew B. Philips, Steven Minton and Mark Johnston and has published in prestigious journals such as Artificial Intelligence, Machine Learning and The MIT Press eBooks.

In The Last Decade

Philip Laird

19 papers receiving 1.4k citations

Peers

Philip Laird
Comparison fields: 5 of 94
  • Artificial Intelligence 1.0k
  • Computer Networks and Communications 618
  • Management Science and Operations Research 270
  • Computational Theory and Mathematics 237
  • Industrial and Manufacturing Engineering 228
Replace Paul Morris with:
Paul Morris United States
Christian Bessière France
Youssef Hamadi United Kingdom
Justin A. Boyan United States
Solomon Eyal Shimony Israel
Fabrizio Luccio Italy
Nicola Muscettola United States
Kenneth Bacławski United States
Konstantinos G. Margaritis Greece
César Rego United States
Paul Morris United States View profile →
Citations per field, relative to Philip Laird
Philip Laird · 1×
Citations per year, relative to Philip Laird
Philip Laird · 1×

Countries citing papers authored by Philip Laird

Since Specialization
Citations

This map shows the geographic impact of Philip Laird's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Philip Laird with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip Laird more than expected).

Fields of papers citing papers by Philip Laird

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philip Laird. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Philip Laird. The network helps show where Philip Laird may publish in the future.

Co-authorship network of co-authors of Philip Laird

This figure shows the co-authorship network connecting the top 25 collaborators of Philip Laird. A scholar is included among the top collaborators of Philip Laird based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Philip Laird. Philip Laird is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 2
2 36
3 30
4
Weighing Hypotheses: Incremental Learning from Noisy Data
0
5 466
6
An Extended Abstract: A Heuristic Repair Method for Constraint-Satisfaction and Scheduling Problems
2
7
Predictive Caching Using the TDAG Algorithm
1
8 6
9
The min-conflicts heuristic: Experimental and theoretical results
1
10 1
11 1
12
EBG and Term-Rewriting Systems.
1
13
Extending EBG to term-rewriting systems
3
14
Solving large-scale constraint satisfaction and scheduling problems using a heuristic repair method
190
15 6
16 376
17 296
18 62
19
Learning from good data and bad
14
20
Inductive inference by refinement
11

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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