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Tariq Masood
640 Points

Contributions by role

Editor 640

Contributions by subject area

Human-Computer Interaction
Emerging Technologies
Graphics
Social Computing
Computer Vision
Data Mining and Machine Learning
Data Science
Spatial and Geographic Information Systems
Artificial Intelligence
Bioinformatics
Multimedia
Algorithms and Analysis of Algorithms
Robotics
Natural Language and Speech

Tariq Masood


Summary

Reader in Design, Manufacturing and Engineering Management, University of Strathclyde, Glasgow.

Interested in robotics, human-machine interaction, artificial intelligence, machine learning, computer vision, visual analytics and Industry 4.0.

Additive Manufacturing Artificial Intelligence Autonomous Systems Computer Aided Design Computer Vision Data Mining & Machine Learning Human-Computer Interaction Robotics Science Policy Visual Analytics

Past or current institution affiliations

University of Cambridge
University of Strathclyde

Work details

Reader

University of Strathclyde
October 2020
Design, Manufacturing and Engineering Management
Dr Tariq Masood is interested in human-machine interaction, computer vision, computer aided design, and adoption, operations and management of technology in the context of smart/intelligent factories, and Industry 4.0. He is also interested in topics interfacing use of technology for disaster management, e.g. COVID-19, ICT4D and addressing UN Sustainable Development Goals.

Senior Research Associate

University of Cambridge
October 2012 - September 2020
Department of Engineering

Identities

@dtmasood

Websites

  • Google Scholar

PeerJ Contributions

  • Edited 2

Academic Editor on

June 1, 2021
Connecting virtual reality and ecology: a new tool to run seamless immersive experiments in R
Julie Vercelloni, Jon Peppinck, Edgar Santos-Fernandez, Miles McBain, Grace Heron, Tanya Dodgen, Erin E. Peterson, Kerrie Mengersen
https://doi.org/10.7717/peerj-cs.544
May 19, 2021
Gray level co-occurrence matrix (GLCM) texture based crop classification using low altitude remote sensing platforms
Naveed Iqbal, Rafia Mumtaz, Uferah Shafi, Syed Mohammad Hassan Zaidi
https://doi.org/10.7717/peerj-cs.536