World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
10396
World Ranking
5101
National Ranking
306

Research.com Recognitions

  • 1951 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Stephen Clark is affiliated with Cambridge Quantum Computing in the United Kingdom. Their research spans multiple fields within medicine, with a focus on hematology and public health as well as philosophy. This combination of disciplines reflects their engagement with both clinical medical topics and broader epistemological and ethical questions.

The primary areas of study for Stephen Clark include:

  • Medicine
  • Hematology
  • Public Health, Environmental and Occupational Health
  • Philosophy

The main research topics their work covers are:

  • Acute Myeloid Leukemia Research
  • Chronic Myeloid Leukemia Treatments
  • Acute Lymphoblastic Leukemia Research
  • Epistemology, Ethics, and Metaphysics

Stephen Clark's recent publications include these peer-reviewed papers:

  • "Humanity: Respecting What is Real" (2023) published in Etyka
  • "P526: REAL-WORLD COMPARISON OF DIFFERENT TREATMENT MODALITIES FOR FAVORABLE RISK ACUTE MYELOID LEUKEMIA: STANDARD DOSE ANTHRACYCLINE VS HIGH DOSE ANTHRACYCLINE VS ADDITION OF GEMTUZUMAB OZOGAMICIN" (2022) published in HemaSphere
  • "Values and facts and fancies" (2024) published in Religious Studies

The frequent co-authors involved in their research collaborations are:

  • J. Mort
  • B. Brewer
  • B. Mautner
  • S. Dibenedetto
  • E. Pierce

Stephen Clark has published in various academic venues, most notably:

  • Etyka
  • HemaSphere
  • Religious Studies

Among awards associated with the name Stephen Clark is the Fellow of the American Association for the Advancement of Science (AAAS), awarded in 1951.

Best Publications

  • Wide-coverage efficient statistical parsing with ccg and log-linear models

    Stephen Clark;Stephen Clark;James R. Curran;James R. Curran

  • Mathematical Foundations for a Compositional Distributional Model of Meaning

    Bob Coecke;Mehrnoosh Sadrzadeh;Stephen Clark

  • Example selection for bootstrapping statistical parsers

    Mark Steedman;Rebecca Hwa;Stephen Clark;Miles Osborne

  • Linguistically Motivated Large-Scale NLP with C&C and Boxer

    James Curran;Stephen Clark;Johan Bos

  • Parsing the WSJ Using CCG and Log-Linear Models

    Stephen Clark;James R. Curran

  • A Tale of Two Parsers: Investigating and Combining Graph-based and Transition-based Dependency Parsing

    Yue Zhang;Stephen Clark

  • Language independent NER using a maximum entropy tagger

    James R. Curran;Stephen Clark

  • Vector Space Models of Lexical Meaning

    Stephen Clark

  • Wide-coverage semantic representations from a CCG parser

    Johan Bos;Stephen Clark;Mark Steedman;James R. Curran

  • Syntactic processing using the generalized perceptron and beam search

    Yue Zhang;Stephen Clark

  • A tale of two parsers: investigating and combining graph-based and transition-based dependency parsing using beam-search

    Yue Zhang;Stephen Clark

  • A Systematic Study of Semantic Vector Space Model Parameters

    Douwe Kiela;Stephen Clark

  • Bootstrapping statistical parsers from small datasets

    Mark Steedman;Miles Osborne;Anoop Sarkar;Stephen Clark

  • Class-based probability estimation using a semantic hierarchy

    Stephen Clark;David Weir

  • The importance of supertagging for wide-coverage CCG parsing

    Stephen Clark;James R. Curran

  • Combining Symbolic and Distributional Models of Meaning

    Stephen Clark;Stephen Pulman

  • Bootstrapping POS taggers using unlabelled data

    Stephen Clark;James R. Curran;Miles Osborne

  • Specializing Word Embeddings for Similarity or Relatedness

    Douwe Kiela;Felix Hill;Stephen Clark

  • Joint Word Segmentation and POS Tagging Using a Single Perceptron

    Yue Zhang;Stephen Clark

  • Chinese Segmentation with a Word-Based Perceptron Algorithm

    Yue Zhang;Stephen Clark

  • What happens next? event prediction using a compositional neural network model

    Mark Granroth-Wilding;Stephen Clark

Frequent Co-Authors

Felix Hill
Felix Hill Google (United States)
Douwe Kiela
Douwe Kiela Stanford University
Yue Zhang
Yue Zhang Westlake University
Mark Steedman
Mark Steedman University of Edinburgh
Phil Blunsom
Phil Blunsom University of Oxford
Chris Dyer
Chris Dyer Google (United States)
Julia Hockenmaier
Julia Hockenmaier University of Illinois at Urbana-Champaign
Andreas Vlachos
Andreas Vlachos University of Cambridge
Matthew Botvinick
Matthew Botvinick Yale University
James L. McClelland
James L. McClelland Stanford University

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