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Peter K Liaw

researcher
Person Human Q99363693

Facts

7 properties
Instance of
human
Sex or gender
male[3]
Country of citizenship
Taiwan[2]
Occupation
materials scientist
Official website
tickle.utk.edu[6]
Family name
Liao[4]
Given name
Peter[5]
🏷️ Also known as
en Peter K Liaw en Peter Liaw
🔖 Identifiers · 22
ISNI
0000000116388415
ORCID iD
0000-0003-0185-3411
VIAF cluster ID
49551578, 2764158369762501460000
Library of Congress Authorities ID
n88074643
ACM Digital Library citation ID
99660186554
BIBSYS ID
1065315
Bibliothèque nationale de France ID
15662529q
Canadiana Name Authority ID
ncf11465452
CiNii Research ID
1980304959791652546
Google Scholar author ID
AizJ-qUAAAAJ
IdRef ID
127493069
J9U entity ID
987007430795305171
Show all 22 identifiers +10
Libraries Australia ID
35721997
LinkedIn personal profile ID
peter-liaw-1051b917
NACSIS-CAT author ID
DA02802036
NLA Trove people ID
1058128
NUKAT ID
n2007012632
Research.com ID
peter-k-liaw
ResearchGate profile ID
Peter-Liaw
SciProfiles ID
232536
Scopus author ID
34668072500
Yale LUX ID
person/0f8d1636-e3ec-4a32-b39b-a749602811f4

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🔗 Connections
Author of 14
Accelerating the design of high-entropy alloys with high hardness by machine learning based on particle swarm optimization, A physics-based machine-learning approach for modeling the temperature-dependent yield strengths of medium- or high-entropy alloys, Data-driven investigation of microstructure and surface integrity in additively manufactured multi-principal-element alloys, Edge dislocation-induced high-temperature strengthening in the Ti37V15Nb22Hf23W3 refractory high-entropy alloys, Evolution of microstructure and residual stress for a lead-frame Cu-2.13Fe-0.026 P (wt%) alloy, Fatigue life prediction of the FCC-based multi-principal element alloys via domain knowledge-based machine learning, In situ monitoring of dislocation, twinning, and detwinning modes in an extruded magnesium alloy under cyclic loading conditions, Materials Fingerprinting Classification +6 more
← Authored by 14
Accelerating the design of high-entropy alloys with high hardness by machine learning based on particle swarm optimization, A physics-based machine-learning approach for modeling the temperature-dependent yield strengths of medium- or high-entropy alloys, Data-driven investigation of microstructure and surface integrity in additively manufactured multi-principal-element alloys, Edge dislocation-induced high-temperature strengthening in the Ti37V15Nb22Hf23W3 refractory high-entropy alloys, Evolution of microstructure and residual stress for a lead-frame Cu-2.13Fe-0.026 P (wt%) alloy, Fatigue life prediction of the FCC-based multi-principal element alloys via domain knowledge-based machine learning, In situ monitoring of dislocation, twinning, and detwinning modes in an extruded magnesium alloy under cyclic loading conditions, Materials Fingerprinting Classification +6 more
Affiliated with 2
University of Tennessee, Knoxville College
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Summary

Peter K Liaw has worked as a materials scientist[1].

FAQs

What did Peter K Liaw do for work?

Peter K Liaw worked as a materials scientist[1].

Related Entities

University of Tennessee

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [3] ↑ . wikidata.org.
  2. [2] ↑ . wikidata.org.
  3. [1] ↑ . wikidata.org.
  4. [4] ↑ . wikidata.org.
  5. [5] ↑ . wikidata.org.
  6. [6] ↑ . wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Peter K Liaw. Retrieved November 8, 2026, from https://4ort.xyz/entity/peter-k-liaw
MLA “Peter K Liaw.” 4ort.xyz Knowledge Graph, 4ort.xyz, 8 Nov. 2026, https://4ort.xyz/entity/peter-k-liaw.
BibTeX @misc{4ortxyz_peter-k-liaw_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Peter K Liaw}}, year = {2026}, url = {https://4ort.xyz/entity/peter-k-liaw}, note = {Accessed: 2026-11-08}}
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Edit History

Rolling log of changes to this entity's Wikidata record. Values shown reflect the current state of each edited property — follow the history link to see the precise diff for any edit.

  1. 26w ago · 本日晴天 · 2026-05-06 view diff on Wikidata ↗
    Library of Congress Authorities ID → n88074643
    ISNI → 0000000116388415
    Country of citizenship → Taiwan
    CiNii Research ID → 1980304959791652546
    + 26 other properties edited (see Wikidata diff for full list)
    "added some identifiers retrieved from CiNii Research (CiNii Research ID) or KAKEN (E-Rad researcher number) (…"
Live feed via Wikidata EventStreams. New edits appear within minutes of being made on Wikidata.