D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 38 Citations 13,652 75 World Ranking 6236 National Ranking 3002

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Margaret Mitchell spends much of her time researching Artificial intelligence, Context, Natural language processing, Image and Question answering. Her research integrates issues of Machine learning and Event structure in her study of Artificial intelligence. Her Machine learning research includes themes of Debiasing, Generative grammar, Dialog box and Machine translation.

As a part of the same scientific study, she usually deals with the Context, concentrating on Visualization and frequently concerns with Proxy, Object, Composition and Visual reasoning. Her studies in Natural language processing integrate themes in fields like Expression and Literal and figurative language. The concepts of her Question answering study are interwoven with issues in Natural language and Mirroring.

Her most cited work include:

  • VQA: Visual Question Answering (1720 citations)
  • VQA: Visual Question Answering (1041 citations)
  • From captions to visual concepts and back (934 citations)

What are the main themes of her work throughout her whole career to date?

Her primary areas of study are Artificial intelligence, Natural language processing, Machine learning, Image and Context. Her Closed captioning, Training set and Range study, which is part of a larger body of work in Artificial intelligence, is frequently linked to Set and Population, bridging the gap between disciplines. Her work on Sentiment analysis, Noun phrase and Phrase as part of general Natural language processing research is frequently linked to Metric and Structure, bridging the gap between disciplines.

Her study in Machine learning is interdisciplinary in nature, drawing from both Classifier and Generative grammar. Margaret Mitchell regularly links together related areas like Question answering in her Image studies. Her research investigates the connection between Context and topics such as Natural language that intersect with problems in Information retrieval.

She most often published in these fields:

  • Artificial intelligence (64.44%)
  • Natural language processing (36.67%)
  • Machine learning (27.78%)

What were the highlights of her more recent work (between 2017-2021)?

  • Artificial intelligence (64.44%)
  • Machine learning (27.78%)
  • Focus (6.67%)

In recent papers she was focusing on the following fields of study:

Margaret Mitchell mostly deals with Artificial intelligence, Machine learning, Focus, Accountability and Set. The study of Artificial intelligence is intertwined with the study of Counterfactual thinking in a number of ways. The study incorporates disciplines such as Range and Generative grammar, Generative model in addition to Machine learning.

Her Focus research covers fields of interest such as Key, Population, Human–computer interaction, Variety and Context. Margaret Mitchell interconnects Face and Internet privacy in the investigation of issues within Set. Her Leverage research integrates issues from Sentiment analysis, Phrase and Natural language processing.

Between 2017 and 2021, her most popular works were:

  • Mitigating Unwanted Biases with Adversarial Learning (352 citations)
  • Model Cards for Model Reporting (258 citations)
  • 50 Years of Test (Un)fairness: Lessons for Machine Learning (71 citations)

In her most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Her main research concerns Artificial intelligence, Machine learning, TRACE, Leverage and Harm. Her research in Artificial intelligence intersects with topics in Analogy and Debiasing. Her work in the fields of Machine learning, such as Classifier, overlaps with other areas such as Adversary.

You can notice a mix of various disciplines of study, such as Social environment, Test, Process management, Auditor's report and Accountability, in her TRACE studies. The Leverage study combines topics in areas such as Sentiment analysis, Phrase, Natural language processing and Generative grammar, Generative model. Her work deals with themes such as Face, Internet privacy and Set, which intersect with Harm.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

VQA: Visual Question Answering

Stanislaw Antol;Aishwarya Agrawal;Jiasen Lu;Margaret Mitchell.
international conference on computer vision (2015)

3384 Citations

VQA: Visual Question Answering

Aishwarya Agrawal;Jiasen Lu;Stanislaw Antol;Margaret Mitchell.
arXiv: Computation and Language (2015)

1920 Citations

From captions to visual concepts and back

Hao Fang;Saurabh Gupta;Forrest Iandola;Rupesh K. Srivastava.
computer vision and pattern recognition (2015)

1221 Citations

A Neural Network Approach to Context-Sensitive Generation of Conversational Responses

Alessandro Sordoni;Michel Galley;Michael Auli;Chris Brockett.
north american chapter of the association for computational linguistics (2015)

879 Citations

Model Cards for Model Reporting

Margaret Mitchell;Simone Wu;Andrew Zaldivar;Parker Barnes.
Proceedings of the Conference on Fairness, Accountability, and Transparency (2019)

610 Citations

Mitigating Unwanted Biases with Adversarial Learning

Brian Hu Zhang;Blake Lemoine;Margaret Mitchell.
national conference on artificial intelligence (2018)

604 Citations

Midge: Generating Image Descriptions From Computer Vision Detections

Margaret Mitchell;Jesse Dodge;Amit Goyal;Kota Yamaguchi.
conference of the european chapter of the association for computational linguistics (2012)

425 Citations

Spoken Language Derived Measures for Detecting Mild Cognitive Impairment

B. Roark;M. Mitchell;J. Hosom;K. Hollingshead.
IEEE Transactions on Audio, Speech, and Language Processing (2011)

293 Citations

Visual Storytelling

Ting-Hao Kenneth Huang;Francis Ferraro;Nasrin Mostafazadeh;Ishan Misra.
north american chapter of the association for computational linguistics (2016)

285 Citations

Generating Natural Questions About an Image

Nasrin Mostafazadeh;Ishan Misra;Jacob Devlin;Margaret Mitchell.
meeting of the association for computational linguistics (2016)

284 Citations

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

Contact us

Best Scientists Citing Margaret Mitchell

Devi Parikh

Devi Parikh

Facebook (United States)

Publications: 117

Dhruv Batra

Dhruv Batra

Georgia Institute of Technology

Publications: 87

Jianfeng Gao

Jianfeng Gao

Microsoft (United States)

Publications: 71

Marcus Rohrbach

Marcus Rohrbach

Facebook (United States)

Publications: 60

Hanwang Zhang

Hanwang Zhang

Nanyang Technological University

Publications: 52

Anton van den Hengel

Anton van den Hengel

University of Adelaide

Publications: 49

Mohit Bansal

Mohit Bansal

University of North Carolina at Chapel Hill

Publications: 47

Zhe Gan

Zhe Gan

Microsoft (United States)

Publications: 43

Yejin Choi

Yejin Choi

University of Washington

Publications: 42

Li Fei-Fei

Li Fei-Fei

Stanford University

Publications: 42

Kate Saenko

Kate Saenko

Boston University

Publications: 39

Trevor Darrell

Trevor Darrell

University of California, Berkeley

Publications: 36

Alexander G. Schwing

Alexander G. Schwing

University of Illinois at Urbana-Champaign

Publications: 36

Ali Farhadi

Ali Farhadi

University of Washington

Publications: 35

Jingjing Liu

Jingjing Liu

MIT

Publications: 34

Yi Yang

Yi Yang

Zhejiang University

Publications: 32

Trending Scientists

Xiaohua Hu

Xiaohua Hu

Drexel University

Tadeusz Kaczorek

Tadeusz Kaczorek

Bialystok University of Technology

Danail Stoyanov

Danail Stoyanov

University College London

Daniele Dini

Daniele Dini

Imperial College London

Michael R. Bailey

Michael R. Bailey

University of Washington

Kenneth Hedberg

Kenneth Hedberg

Oregon State University

Alphons G. J. Voragen

Alphons G. J. Voragen

Wageningen University & Research

Wei Xu

Wei Xu

Northeastern University

Alysson R. Muotri

Alysson R. Muotri

University of California, San Diego

Matthew H. Godfrey

Matthew H. Godfrey

North Carolina Wildlife Resources Commission

Gregory J. Frost

Gregory J. Frost

National Oceanic and Atmospheric Administration

Andrew Forge

Andrew Forge

University College London

Kerri N. Boutelle

Kerri N. Boutelle

University of California, San Diego

Gilbert Gottlieb

Gilbert Gottlieb

University of North Carolina at Chapel Hill

Paul Peter Rosen

Paul Peter Rosen

Cornell University

Rüdiger Schmitt-Beck

Rüdiger Schmitt-Beck

University of Mannheim

Something went wrong. Please try again later.