{
 "type": "researcher",
 "question": "Who collaborates with Nabeel Seedat?",
 "id": "A5067213867",
 "name": "Nabeel Seedat",
 "url": "https://researcher-atlas.com/researcher/nabeel-seedat-a5067213867/",
 "total_coauthors": 29,
 "displayed_coauthors": 20,
 "display_limit": 20,
 "data_version": "2026.07-r1",
 "updated": "2026-07-28",
 "source": "OpenAlex (CC0)",
 "answer": "Atlas records 29 co-authors for Nabeel Seedat, who works on Explainable Artificial Intelligence (XAI); the 20 strongest connections are shown. The strongest collaboration is with Mihaela van der Schaar (33 joint papers).",
 "metrics": {
  "cited_by_count": 248,
  "works_count": 62
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 "affiliation_latest": "University of Cambridge",
 "co_authors": [
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   "url": "https://researcher-atlas.com/researcher/mihaela-van-der-schaar-a5012339002/"
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  {
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   "url": "https://researcher-atlas.com/researcher/fergus-imrie-a5017415803/"
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  {
   "name": "Boris van Breugel",
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   "url": "https://researcher-atlas.com/researcher/boris-van-breugel-a5018684838/"
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  {
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   "cited_by_count": 543,
   "url": "https://researcher-atlas.com/researcher/jonathan-crabbe-a5113266713/"
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  {
   "name": "Nicolás Astorga",
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   "url": "https://researcher-atlas.com/researcher/nicolas-astorga-a5052369244/"
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   "name": "Tennison Liu",
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   "url": "https://researcher-atlas.com/researcher/tennison-liu-a5048553903/"
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  {
   "name": "Jiashuo Liu",
   "openalex_id": "A5004072676",
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   "url": "https://researcher-atlas.com/researcher/jiashuo-liu-a5004072676/"
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  {
   "name": "Thomas Pouplin",
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   "name": "Alan Jeffares",
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   "url": "https://researcher-atlas.com/researcher/alan-jeffares-a5067437313/"
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   "name": "Max Ruiz Luyten",
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   "url": "https://researcher-atlas.com/researcher/max-ruiz-luyten-a5056082346/"
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  {
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   "name": "Nicolas Huynh",
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   "url": "https://researcher-atlas.com/researcher/nicolas-huynh-a5109681954/"
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   "name": "Jeroen Berrevoets",
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   "url": "https://researcher-atlas.com/researcher/jeroen-berrevoets-a5079318903/"
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   "name": "Lasse Hansen",
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   "cited_by_count": 389,
   "url": "https://researcher-atlas.com/researcher/lasse-hansen-a5039129186/"
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  {
   "name": "Andrija Petrovic",
   "openalex_id": "A5073856473",
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   "url": "https://researcher-atlas.com/researcher/andrija-petrovic-a5073856473/"
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  {
   "name": "Zhaozhi Qian",
   "openalex_id": "A5031571500",
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   "cited_by_count": 496,
   "url": "https://researcher-atlas.com/researcher/zhaozhi-qian-a5031571500/"
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  {
   "name": "Yinpeng Dong",
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   "joint_papers": 1,
   "cited_by_count": 8650,
   "url": "https://researcher-atlas.com/researcher/yinpeng-dong-a5068755794/"
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  {
   "name": "Evgeny S. Saveliev",
   "openalex_id": "A5050007929",
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   "cited_by_count": 26,
   "url": "https://researcher-atlas.com/researcher/evgeny-s-saveliev-a5050007929/"
  },
  {
   "name": "Jim Weatherall",
   "openalex_id": "A5060506150",
   "joint_papers": 1,
   "cited_by_count": 168,
   "url": "https://researcher-atlas.com/researcher/jim-weatherall-a5060506150/"
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  {
   "name": "Ioana Bica",
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   "url": "https://researcher-atlas.com/researcher/ioana-bica-a5006610847/"
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 ],
 "topics": [
  {
   "id": "T12026",
   "name": "Explainable Artificial Intelligence (XAI)",
   "works_count": 14,
   "subfield": "Artificial Intelligence",
   "field": "Computer Science"
  },
  {
   "id": "T13702",
   "name": "Machine Learning in Healthcare",
   "works_count": 13,
   "subfield": "Artificial Intelligence",
   "field": "Computer Science"
  },
  {
   "id": "T10028",
   "name": "Topic Modeling",
   "works_count": 10,
   "subfield": "Artificial Intelligence",
   "field": "Computer Science"
  },
  {
   "id": "T12535",
   "name": "Machine Learning and Data Classification",
   "works_count": 9,
   "subfield": "Artificial Intelligence",
   "field": "Computer Science"
  },
  {
   "id": "T11689",
   "name": "Adversarial Robustness in Machine Learning",
   "works_count": 8,
   "subfield": "Artificial Intelligence",
   "field": "Computer Science"
  }
 ],
 "topics_note": "OpenAlex exposes only this author's top 5 topics.",
 "papers": [
  {
   "title": "Generalization—a key challenge for responsible AI in patient-facing clinical applications",
   "year": 2024,
   "cited_by_count": 103
  },
  {
   "title": "Navigating Data-Centric Artificial Intelligence With DC-Check: Advances, Challenges, and Opportunities",
   "year": 2023,
   "cited_by_count": 15
  },
  {
   "title": "U-PASS: An uncertainty-guided deep learning pipeline for automated sleep staging",
   "year": 2024,
   "cited_by_count": 14
  },
  {
   "title": "Large Language Models to Enhance Bayesian Optimization",
   "year": 2024,
   "cited_by_count": 13
  },
  {
   "title": "DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems",
   "year": 2022,
   "cited_by_count": 11
  },
  {
   "title": "Towards calibrated and scalable uncertainty representations for neural networks",
   "year": 2019,
   "cited_by_count": 11
  },
  {
   "title": "Automated and interpretable m-health discrimination of vocal cord pathology enabled by machine learning",
   "year": 2020,
   "cited_by_count": 10
  },
  {
   "title": "Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark",
   "year": 2023,
   "cited_by_count": 8
  }
 ]
}