Dr.  Lora Aroyo Digital Library

Based in New York City, NY, United States
Lora Aroyo


Lora Aroyo is a Full Professor in Computer Science. Currently, she is a visiting professor at the Data Science Institute at Columbia University (https://datascience.columbia.edu/). She is also Chief of Science for a NY-based startup Tagasauris (http://tagasauris.com), and the president of the User Modeling community (UM Inc) which serves as a steering committee for the ACM Conference Series “User Modeling, Adaptation and Personalization” (UMAP) part of both SIGCHI and SIGWEB (http://www.um.org/). She is also member of the ACM SIGCHI conferences board, in her role as the UMAP steering committee chair. She headed the User-centric Data Science group (http://ucds.cs.vu.nl/) at the Department of Computer Science, Vrije Universiteit Amsterdam, The Netherlands, and was member of the Amsterdam Data Science (http://amsterdamdatascience.nl) and the Network Institute (http://www.networkinstitute.org).

She is involved in a number of research projects and in the organization of conferences, workshops and tutorials focussing on crowdsourcing and human computation, collecting data, data quality assessment, and especially hybrid human-AI systems for understand text, image and video. She has led major research projects in semantic search, recommendation systems, event-driven access to online multimedia collections, and through these has become a recognized leader in human computation techniques for specific domains, such as digital humanities, cultural heritage, and interactive TV.

Three notable current projects are: (1) CrowdTruth project “Harnessing Disagreement in Crowdsourcing for Ambiguity-aware Gold Standards”: http://crowdtruth.org/, (2) ReTV project “Re-inventing the TV for the Digital Age”: http://retv-project.eu/ and (3) CaptureBias project: “Diversity-aware Analysis of Bias in News Videos“ https://capturebias.wordpress.com/.

She is an ACM member, and a four times holder of IBM Faculty Award for her work on CrowdTruth (http://crowdtruth.org/): Crowdsourcing ground truth data for adapting IBM Watson system to the medical domain & applying Crowdtruth for capturing ambiguity for the purpose of understanding misinformation. Check also her website: http://lora-aroyo.org, her Twitter stream at @laroyo and also her slideshare presentations at http://www.slideshare.net/laroyo.

Available Lectures

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  • Data Science for Smart Culture: Harnessing Human Semantics at Scale

    Software systems are becoming ever more intelligent and more useful, but the way we interact with these machines too often reveals that they don’t actually understand people. Knowledge...

  • Dial "E" for Events

    Objects, like people, locations, and various other types of named entities, are often easy to detect in language and present on the semantic web.  Without events, however, they lack...

  • Disrupting the Semantic Comfort Zone
    Ambiguity in interpreting signs is not a new idea, yet the vast majority of research in machine interpretation of signals such as speech, language, images, video, audio, etc., tend to...
  • StorySourcing: Telling Stories with Humans & Machines

    Stories connect us with other people, guide us in exploring unfamiliar places, bring us to discover new things. They are all around us - in our daily lives, in museum exhibitions, in movies...

  • To be AND not to be: quantum intelligence?
    Lora Aroyo and Chris Welty propose a radical new approach to modeling human behavior for the next generation of Personal Digital Assistants: use quantum math instead of probability theory....
  • Truth is Lie: Rules & Semantics from a Crowd Perspectives

    Processing real-world data with the crowd leaves one thing absolutely clear - there is no single notion of truth, but rather a spectrum that has to account for context, opinions, perspectives...

  • Truth is a Lie
    In this talk we discuss two messages: (1) There is no single notion of truth, but rather a spectrum that has to account for context, opinions, perspectives and shades of grey. This is critical...

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