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Hasan Jackson

dblp:197/3065 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computing education · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computing education
broadening participation in computing		 0.412020
Perspectives on Broadening Participation in STEM Careers across Academia, Government, and Industry · KDD 2020
Computing education › broadening participation in computing
diversity and inclusion in computing		 0.412020
Perspectives on Broadening Participation in STEM Careers across Academia, Government, and Industry · KDD 2020
Computing education
computing careers		 0.112020
Perspectives on Broadening Participation in STEM Careers across Academia, Government, and Industry · KDD 2020
YearPublicationVenuePosition
2020 Perspectives on Broadening Participation in STEM Careers across Academia, Government, and Industry
abstract
Bias, defined as prejudice for or against something/someone, is a central component of our understanding of everyday life. In particular, the technology that you interact with daily and the teams that you work with help to inform your biases. For minority populations in technology, often being the lone representative for diverging perspectives, the inclusion of potentially harmful bias in technology projects is easily discernable, even if it has proven near impossible to resist.
Hasan Jackson
 KDD1