Peng Ye

electrical engineer and machine learning researcher
Person human Q135785022
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Peng Ye

Summary

Peng Ye is a human[1]. They worked as a software engineer[2].

Key Facts

  • Peng Ye worked as a software engineer[2].
  • Peng Ye's field of work was computer vision[3].
  • Peng Ye's field of work was machine learning[4].
  • Peng Ye's field of work was software as a service[5].
  • Peng Ye was employed by Q780442[6].
  • Peng Ye was educated at University of Maryland[7].
  • Peng Ye was educated at University of Delaware[8].
  • Peng Ye was educated at Tsinghua University[9].
  • Peng Ye's instance of is recorded as human[10].
  • Peng Ye's languages spoken, written or signed is recorded as English[11].
  • Peng Ye's languages spoken, written or signed is recorded as Chinese[12].
  • Peng Ye's affiliation is recorded as The TWIML AI Podcast[13].
  • Peng Ye's Google Scholar author ID is recorded as Q-GJEysAAAAJ[14].
  • Peng Ye's ResearchGate profile ID is recorded as Peng-Ye-28[15].
  • Peng Ye's IEEE Xplore author ID is recorded as 38242386400[16].

Body

Education

Educated at University of Maryland[7], a public research university[17], in United States[18], founded in 1858[19], headquartered in College Park[20]; University of Delaware[8], a land-grant university[21], in United States[22], founded in 1743[23], headquartered in Newark[24]; and Tsinghua University[9], a public university[25], in People's Republic of China[26], founded in 1911[27], headquartered in Beijing[28].

Career and Affiliations

Peng Ye's professions included software engineer[2]. Fields of work include computer vision[3], an academic discipline[29]; machine learning[4], an academic discipline[30]; and software as a service[5], a business model[31]. Among their employers was Q780442[6].

FAQs

What did Peng Ye do for work?

Peng Ye worked as software engineer[2].

Where did Peng Ye go to school?

Peng Ye was educated at University of Maryland[7], University of Delaware[8], and Tsinghua University[9].

References

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

Direct Wikidata claims

  1. [10] . wikidata.org.
  2. [7] . linkedin.com. Retrieved . linkedin.com. Provenance: wikidata.org.
  3. [8] . linkedin.com. Retrieved . linkedin.com. Provenance: wikidata.org.
  4. [9] . linkedin.com. Retrieved . linkedin.com. Provenance: wikidata.org.
  5. [3] . linkedin.com. Retrieved . linkedin.com. Provenance: wikidata.org.
  6. [4] . linkedin.com. Retrieved . linkedin.com. Provenance: wikidata.org.
  7. [5] . linkedin.com. Retrieved . linkedin.com. Provenance: wikidata.org.
  8. [2] . linkedin.com. Retrieved . linkedin.com. Provenance: wikidata.org.
  9. [6] . linkedin.com. Retrieved . linkedin.com. Provenance: wikidata.org.
  10. [11] . wikidata.org.
  11. [12] . wikidata.org.
  12. [13] . twimlai.com. Retrieved . twimlai.com. Provenance: wikidata.org.
  13. [14] . wikidata.org.
  14. [15] . wikidata.org.
  15. [16] . wikidata.org.

Inline context (facts about related entities)

  1. [17] . Wikidata. wikidata.org. → on this site
  2. [18] . Wikidata. wikidata.org. → on this site
  3. [19] . Wikidata. wikidata.org. → on this site
  4. [20] . Wikidata. wikidata.org. → on this site
  5. [21] . Wikidata. wikidata.org. → on this site
  6. [22] . Wikidata. wikidata.org. → on this site
  7. [23] . Wikidata. wikidata.org. → on this site
  8. [24] . Wikidata. wikidata.org. → on this site
  9. [25] . Wikidata. wikidata.org. → on this site
  10. [26] . Wikidata. wikidata.org. → on this site
  11. [27] . Wikidata. wikidata.org. → on this site
  12. [28] . Wikidata. wikidata.org. → on this site
  13. [29] . Wikidata. wikidata.org. → on this site
  14. [30] . Wikidata. wikidata.org. → on this site
  15. [31] . Wikidata. wikidata.org. → on this site

Class ancestry

  1. [1] . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Peng Ye. Retrieved March 11, 2026, from https://4ort.xyz/entity/peng-ye
MLA “Peng Ye.” 4ort.xyz Knowledge Graph, 4ort.xyz, 11 Mar. 2026, https://4ort.xyz/entity/peng-ye.
BibTeX @misc{4ortxyz_peng-ye_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Peng Ye}}, year = {2026}, url = {https://4ort.xyz/entity/peng-ye}, note = {Accessed: 2026-03-11}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Peng Ye — https://4ort.xyz/entity/peng-ye (retrieved 2026-03-11)

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