What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- World Wide Web
His primary scientific interests are in World Wide Web, Multimedia, Crowdsourcing, Human–computer interaction and Information retrieval.
His study in Web page, Web navigation, Web service, Web modeling and Web standards is carried out as part of his World Wide Web studies.
Jeffrey P. Bigham undertakes multidisciplinary investigations into Multimedia and Screen reader in his work.
His research integrates issues of Unpaid work, Crowds, End user, Set and Internet privacy in his study of Crowdsourcing.
His Human–computer interaction study combines topics in areas such as Mobile device, Interface and Human intelligence.
His work deals with themes such as Ranking and Visualization, which intersect with Information retrieval.
His most cited work include:
- VizWiz: nearly real-time answers to visual questions (536 citations)
- Slide rule: making mobile touch screens accessible to blind people using multi-touch interaction techniques (423 citations)
- VizWiz: nearly real-time answers to visual questions (349 citations)
What are the main themes of his work throughout his whole career to date?
Jeffrey P. Bigham spends much of his time researching Crowdsourcing, Human–computer interaction, World Wide Web, Multimedia and Artificial intelligence.
The concepts of his Crowdsourcing study are interwoven with issues in Task, Data science, Crowds, Set and Internet privacy.
His biological study spans a wide range of topics, including Mobile device, User interface, Interface and Conversation.
Jeffrey P. Bigham has researched Multimedia in several fields, including Readability, End user and Closed captioning.
His research in Artificial intelligence intersects with topics in Machine learning, Computer vision and Natural language processing.
His work carried out in the field of Web modeling brings together such families of science as Web standards, Information retrieval and Data Web.
He most often published in these fields:
- Crowdsourcing (33.58%)
- Human–computer interaction (27.92%)
- World Wide Web (23.77%)
What were the highlights of his more recent work (between 2017-2021)?
- Human–computer interaction (27.92%)
- Artificial intelligence (14.34%)
- Crowdsourcing (33.58%)
In recent papers he was focusing on the following fields of study:
Jeffrey P. Bigham mostly deals with Human–computer interaction, Artificial intelligence, Crowdsourcing, Social media and Conversation.
His study in Human–computer interaction focuses on Augmented reality in particular.
The Artificial intelligence study combines topics in areas such as Machine learning, Private information retrieval, Dyslexia and Natural language processing.
His research investigates the connection between Crowdsourcing and topics such as Demographic economics that intersect with issues in Unpaid work.
His Interface research incorporates elements of Wheelchair basketball, Multimedia, Content creation and Presentation.
His World Wide Web research includes elements of Ubiquitous computing and Hacker.
Between 2017 and 2021, his most popular works were:
- VizWiz Grand Challenge: Answering Visual Questions from Blind People (132 citations)
- A Data-Driven Analysis of Workers' Earnings on Amazon Mechanical Turk (129 citations)
- Evorus: A Crowd-powered Conversational Assistant Built to Automate Itself Over Time (34 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Microsoft Windows
His primary areas of study are Crowdsourcing, Artificial intelligence, Human–computer interaction, Quality and Machine learning.
He has included themes like Conversation and Demographic economics in his Crowdsourcing study.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Private information retrieval, Information retrieval and Internet privacy.
Jeffrey P. Bigham integrates Human–computer interaction and Dynamic programming in his research.
His studies deal with areas such as World Wide Web, Dialog box, Open domain and Optical character recognition as well as Quality.
His work in the fields of Machine learning, such as Statistical model, intersects with other areas such as Executive functions, Early detection, Working memory and Cognitive skill.
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