World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
6396
World Ranking
9775
National Ranking
24

Overview

Mark Gahegan is affiliated with the University of Auckland in New Zealand. Their research spans multiple domains, with a primary focus on computer science and social sciences, involving 15 and 9 publications respectively in these fields. The subfields of their work include molecular biology, geography, planning and development, artificial intelligence, signal processing, and information systems.

The scientist's research topics cover various areas such as geographic information systems studies, data management and algorithms, RNA and protein synthesis mechanisms, RNA research and splicing, RNA modifications and cancer, scientific computing and data management, and semantic web and ontologies.

Mark Gahegan has published papers in a range of venues, notably in arXiv (Cornell University) with three publications, Transactions in GIS with two, and one publication respectively in BMC Bioinformatics, Annals of GIS, and Sensors.

Frequent collaborators include Benjamin Adams, Jidong Zhang, Бо Лю, Zhihan Wang, and Klaus Lehnert, indicating a collaborative research network involving multiple co-authors over successive projects.

The following are some of the recent papers attributed to Mark Gahegan, detailing their titles, publication years, and publication venues:

  • Spatially explicit models for exploring COVID-19 lockdown strategies, 2020, Transactions in GIS
  • DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites, 2022, BMC Bioinformatics
  • Coastal Image Classification and Pattern Recognition: Tairua Beach, New Zealand, 2021, Sensors
  • GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS, 2025, Annals of GIS
  • A gastric cancer recognition algorithm on gastric pathological sections based on multistage attention-DenseNet, 2021, Concurrency and Computation Practice and Experience

Best Publications

  • Visualizing Geospatial Information Uncertainty: What We Know and What We Need to Know

    Alan M. MacEachren;Anthony Robinson;Susan Hopper;Steven Gardner

  • Geospatial Cyberinfrastructure: Past, present and future

    Chaowei Phil Yang;Robert Raskin;Michael F. Goodchild;Mark Gahegan

  • Geovisualization for knowledge construction and decision support

    A.M. MacEachren;M. Gahegan;W. Pike;I. Brewer

  • Visual Semiotics a Uncertainty Visualization: An Empirical Study

    A. M. MacEachren;R. E. Roth;J. O'Brien;B. Li

  • A Typology for Visualizing Uncertainty

    Judi R. Thomson;Elizabeth G. Hetzler;Alan MacEachren;Mark N. Gahegan

  • Biodiversity data should be published, cited, and peer reviewed

    Mark J. Costello;William K. Michener;Mark Gahegan;Zhi-Qiang Zhang

  • GeoVISTA studio: a codeless visual programming environment for geoscientific data analysis and visualization

    Masahiro Takatsuka;Mark Gahegan

  • Multivariate Analysis and Geovisualization with an Integrated Geographic Knowledge Discovery Approach

    Diansheng Guo;Mark Gahegan;Alan M. MacEachren;Biliang Zhou

  • The Integration of Geographic Visualization with Knowledge Discovery in Databases and Geocomputation

    Mark Gahegan;Monica Wachowicz;Mark Harrower;Theresa-Marie Rhyne

  • Introducing GeoVISTA Studio: an integrated suite of visualization and computational methods for exploration and knowledge construction in geography

    Mark Gahegan;Masahiro Takatsuka;Mike Wheeler;Frank Hardisty

  • A framework for the modelling of uncertainty between remote sensing and geographic information systems

    Mark Gahegan;Manfred Ehlers

  • Proximity operators for qualitative spatial reasoning

    Mark Gahegan

  • On the Application of Inductive Machine Learning Tools to Geographical Analysis

    Mark Gahegan

  • Cybertools and archaeology

    Dean R. Snow;Mark Gahegan;C. Lee Giles;Kenneth G. Hirth

  • ICEAGE: Interactive Clustering and Exploration of Large and High-Dimensional Geodata

    Diansheng Guo;Donna J. Peuquet;Mark Gahegan

  • Four barriers to the development of effective exploratory visualisation tools for the geosciences

    Mark Gahegan

  • Is inductive machine learning just another wild goose (or might it lay the golden egg)

    Mark Gahegan

  • Data structures and algorithms to support interactive spatial analysis using dynamic Voronoi diagrams

    Mark Gahegan;I Lee

  • Beyond ontologies: Toward situated representations of scientific knowledge

    William Pike;Mark Gahegan

  • Beyond Tools: Visual Support for the Entire Process of GIScience

    Mark Gahegan

  • Geospatial Data Mining and Knowledge Discovery

    May Yuan;Barbara P. Buttenfield;M. N. Gahegan;Harvey Miller

Frequent Co-Authors

Alan M. MacEachren
Alan M. MacEachren Pennsylvania State University
Geoff West
Geoff West Curtin University
Stefanie Vandevijvere
Stefanie Vandevijvere University of Auckland
Jan M. Lindsay
Jan M. Lindsay University of Auckland
Brendon A. Bradley
Brendon A. Bradley University of Canterbury
Brent Yarnal
Brent Yarnal Pennsylvania State University
Dirk Hölscher
Dirk Hölscher University of Göttingen
Kerry O'Donnell
Kerry O'Donnell National Center for Agricultural Utilization Research
Niklaus J. Grünwald
Niklaus J. Grünwald Oregon State University
Yong-Hwan Lee
Yong-Hwan Lee Seoul National University

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