World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
11758
World Ranking
9520
National Ranking
4033

Overview

Hoifung Poon is affiliated with Microsoft in the United States. Their main field of study is computer science, with a focus on artificial intelligence and related subfields. The scientist's work extensively covers topics in artificial intelligence, molecular biology, and computer vision and pattern recognition, alongside several areas within health informatics and medical imaging.

The primary research topics explored by Hoifung Poon include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Biomedical Text Mining and Ontologies
  • Artificial Intelligence in Healthcare and Education
  • Multimodal Machine Learning Applications
  • Machine Learning in Healthcare
  • Radiomics and Machine Learning in Medical Imaging

The scientist has contributed significantly to several recent publications in notable venues. Selected papers include:

  • "Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing," 2021, ACM Transactions on Computing for Healthcare
  • "BioGPT: generative pre-trained transformer for biomedical text generation and mining," 2022, Briefings in Bioinformatics
  • "A whole-slide foundation model for digital pathology from real-world data," 2024, Nature
  • "LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day," 2023, arXiv (Cornell University)
  • "Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine," 2023, arXiv (Cornell University)

Frequent co-authors collaborating with Hoifung Poon include:

  • Tristan Naumann
  • Naoto Usuyama
  • Sheng Zhang
  • Cliff Wong
  • Brian Piening

The scientist regularly publishes in venues related to computer science and biomedical machine learning. Prominent publication venues are:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Patterns
  • NEJM AI
  • Nature Communications

Overall, Hoifung Poon's research spans a variety of subfields including artificial intelligence, molecular biology, and medical imaging. Their work contributes broadly to methods and applications intersecting machine learning and healthcare, providing insights across natural language processing, biomedical information extraction, and multimodal data analysis.

Best Publications

  • Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

    Yu Gu;Robert Tinn;Hao Cheng;Michael Lucas

  • Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

    Yu Gu;Robert Tinn;Hao Cheng;Michael Lucas

  • BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining

    Unknown

  • Representing Text for Joint Embedding of Text and Knowledge Bases

    Kristina Toutanova;Danqi Chen;Patrick Pantel;Hoifung Poon

  • Sum-product networks: a new deep architecture

    Hoifung Poon;Pedro Domingos

  • Cross-Sentence N-ary Relation Extraction with Graph LSTMs

    Nanyun Peng;Hoifung Poon;Chris Quirk;Kristina Toutanova

  • Sound and efficient inference with probabilistic and deterministic dependencies

    Hoifung Poon;Pedro Domingos

  • Joint inference in information extraction

    Hoifung Poon;Pedro Domingos

  • Unsupervised Semantic Parsing

    Hoifung Poon;Pedro Domingos

  • LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

    Unknown

  • Joint Unsupervised Coreference Resolution with Markov Logic

    Hoifung Poon;Pedro Domingos

  • Neural-Symbolic Learning and Reasoning: A Survey and Interpretation

    Tarek R. Besold;Artur d'Avila Garcez;Sebastian Bader;Howard Bowman

  • Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

    Unknown

  • Distant Supervision for Relation Extraction beyond the Sentence Boundary

    Chris Quirk;Hoifung Poon

  • Unsupervised Ontology Induction from Text

    Hoifung Poon;Pedro Domingos

  • Fine-tuning large neural language models for biomedical natural language processing

    Unknown

  • Unsupervised Morphological Segmentation with Log-Linear Models

    Hoifung Poon;Colin Cherry;Kristina Toutanova

  • Document-Level N-ary Relation Extraction with Multiscale Representation Learning.

    Robin Jia;Cliff Wong;Hoifung Poon

  • Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine

    Unknown

  • Sum-product networks: A new deep architecture

    Hoifung Poon;Pedro Domingos

  • Unifying Logical and Statistical AI

    Pedro Domingos;Daniel Lowd;Stanley Kok;Aniruddh Nath

  • Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text

    Kristina Toutanova;Victoria Lin;Wen-tau Yih;Hoifung Poon

  • Joint Inference for Knowledge Extraction from Biomedical Literature

    Hoifung Poon;Lucy Vanderwende

  • Upper Bounds of Dynamic Chromatic Number.

    Hong-Jian Lai;Bruce Montgomery;Hoifung Poon

  • Unifying logical and statistical AI

    Pedro Domingos;Stanley Kok;Hoifung Poon;Matthew Richardson

  • Adversarial Training for Large Neural Language Models

    Xiaodong Liu;Hao Cheng;Pengcheng He;Weizhu Chen

  • Unsupervised semantic parsing.

    Hoifung Poon

Frequent Co-Authors

Pedro Domingos
Pedro Domingos University of Washington
Kristina Toutanova
Kristina Toutanova Google (United States)
Chris Quirk
Chris Quirk Microsoft (United States)
Matthew Richardson
Matthew Richardson Microsoft (United States)
Jianfeng Gao
Jianfeng Gao Microsoft (United States)
Wen-tau Yih
Wen-tau Yih Facebook (United States)
Eric Horvitz
Eric Horvitz Microsoft (United States)
Bill Howe
Bill Howe University of Washington
David Heckerman
David Heckerman Microsoft (United States)
Lucy Vanderwende
Lucy Vanderwende University of Washington

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