World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
84
Citations
29174
World Ranking
850
National Ranking
465

Overview

Kevin Knight is affiliated with the University of Southern California in the United States. Their research spans interdisciplinary fields including Computer Science, Medicine, and Psychology, with a significant focus on artificial intelligence and health-related topics.

The principal fields of study in their work are:

  • Computer Science
  • Medicine
  • Psychology

The scientist's subfields of expertise include:

  • Artificial Intelligence
  • General Health Professions
  • Clinical Psychology
  • Epidemiology
  • Sociology and Political Science

Kevin Knight's research topics cover a range of social and health-related issues. These include:

  • HIV, Drug Use, Sexual Risk
  • Criminal Justice and Corrections Analysis
  • Natural Language Processing Techniques
  • HIV/AIDS Research and Interventions
  • Homelessness and Social Issues
  • Topic Modeling
  • Child and Adolescent Psychosocial and Emotional Development

The scientist has published frequently in the following venues:

  • arXiv (Cornell University)
  • Substance Use & Misuse
  • Journal of Substance Abuse Treatment
  • Journal of Offender Rehabilitation
  • Frontiers in Psychology

Recent papers from Kevin Knight include:

  • "Linking criminal justice-involved individuals to HIV, Hepatitis C, and opioid use disorder prevention and treatment services upon release to the community: Progress, gaps, and future directions" (2021) published in International Journal of Drug Policy
  • "Preventing opioid use among justice-involved youth as they transition to adulthood: leveraging safe adults (LeSA)" (2021) published in BMC Public Health
  • "Study protocol of a randomized controlled trial comparing two linkage models for HIV prevention and treatment in justice-involved persons" (2022) published in BMC Infectious Diseases
  • "Justice community opioid innovation network (JCOIN): The TCU research hub" (2021) published in Journal of Substance Abuse Treatment
  • "The Role of Personality Functioning on Early Drop out in Outpatient Substance Misuse Treatment" (2021) published in Substance Use & Misuse

Frequent co-authors working alongside Kevin Knight include:

  • Thomas B. Sease
  • Amanda L. Wiese
  • Wayne E. K. Lehman
  • Jennifer E. Becan
  • Jennifer Pankow

Best Publications

  • Machine transliteration

    Kevin Knight;Jonathan Graehl

  • Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

    Kevin Knight;Ani Nenkova;Owen Rambow

  • Abstract Meaning Representation for Sembanking

    Laura Banarescu;Claire Bonial;Shu Cai;Madalina Georgescu

  • A Syntax-based Statistical Translation Model

    Kenji Yamada;Kevin Knight

  • Transfer Learning for Low-Resource Neural Machine Translation

    Barret Zoph;Deniz Yuret;Jonathan May;Kevin Knight

  • Summarization beyond sentence extraction: a probabilistic approach to sentence compression

    Kevin Knight;Daniel Marcu

  • What’s in a translation rule?

    Michel Galley;Mark Hopkins;Kevin Knight;Daniel Marcu

  • Generation that Exploits Corpus-Based Statistical Knowledge

    Irene Langkilde;Kevin Knight

  • Statistics-Based Summarization - Step One: Sentence Compression

    Kevin Knight;Daniel Marcu

  • Scalable Inference and Training of Context-Rich Syntactic Translation Models

    Michel Galley;Jonathan Graehl;Kevin Knight;Daniel Marcu

  • Building a large-scale knowledge base for machine translation

    Kevin Knight;Steve K. Luk

  • Unification: a multidisciplinary survey

    Kevin Knight

  • Statistical machine translation

    Kevin Knight;Philipp Koehn

  • Decoding complexity in word-replacement translation models

    Kevin Knight

  • Empirical methods for compound splitting

    Philipp Koehn;Kevin Knight

  • Cross-lingual Name Tagging and Linking for 282 Languages

    Xiaoman Pan;Boliang Zhang;Jonathan May;Joel Nothman

  • Fast and optimal decoding for machine translation

    Ulrich Germann;Michael Jahr;Kevin Knight;Daniel Marcu

  • Plan-And-Write: Towards Better Automatic Storytelling

    Lili Yao;Nanyun Peng;Ralph M. Weischedel;Kevin Knight

  • Does String-Based Neural MT Learn Source Syntax?

    Xing Shi;Inkit Padhi;Kevin Knight

  • Fast Decoding and Optimal Decoding for Machine Translation

    Ulrich Germann;Michael Jahr;Kevin Knight;Daniel Marcu

  • Smatch: an Evaluation Metric for Semantic Feature Structures

    Shu Cai;Kevin Knight

Frequent Co-Authors

Daniel Marcu
Daniel Marcu University of Southern California
Heng Ji
Heng Ji University of Illinois at Urbana-Champaign
Philipp Koehn
Philipp Koehn Johns Hopkins University
Ashish Vaswani
Ashish Vaswani Google (United States)
Vasileios Hatzivassiloglou
Vasileios Hatzivassiloglou Columbia University
David Chiang
David Chiang University of Notre Dame
Barret Zoph
Barret Zoph Google (United States)
Eduard Hovy
Eduard Hovy Carnegie Mellon University
Liang Huang
Liang Huang Oregon State University
Panayiotis G. Georgiou
Panayiotis G. Georgiou University of Southern California

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science opens doors to a variety of online degrees and fast-tracked career options. Many students expand their expertise by branching into allied engineering fields. For example, those interested in applied technology often discover rewarding online electrical engineering career outcomes. These include roles in robotics, automation, and emerging tech sectors, where job prospects remain strong.

Not every career move requires a full degree. Ambitious professionals are also pursuing 3-month certificate programs that pay well to quickly boost earning power. Certificates in areas like cybersecurity, data analytics, and cloud computing provide practical skills sought by employers—often with minimal time and financial investment.

For those seeking advanced credentials, earning the quickest masters degree online is an efficient route to career advancement. Many accredited U.S. universities now offer flexible, accelerated online master's in Computer Science, AI, and engineering management.

If you want to maximize your future opportunities, consider enrolling in one of the most in demand masters degrees. These programs align with tech industry trends and employer needs, making them valuable stepping stones to leadership roles and higher salaries.

Best Scientists Citing Kevin Knight

Trending Scientists

Recently Published Articles