Surangi Punyasena

Associate Professor and Associate Head

University of Illinois at Urbana-Champaign

United States

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Surangi Punyasena is an Associate Professor and Associate Head at the University of Illinois, USA. Her research focuses on palynology, encompassing areas such as pollen morphology, deep learning applications in phylogenetics, and environmental adaptations. She has contributed to significant studies related to detecting and segmenting pollen using deep learning, as well as digitizing palynological collections to enhance research accessibility.

Articles (13)

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2025

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2025

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2025

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2025

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2024

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2023

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2023

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2022

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2022

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2021

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2020

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2020

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2020

Collaborators (7)

Aletta Bonn

GERMANY

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Stephanie Bohlmann

Finnish Meteorological Institute

FINLAND

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Luke Mander

Open University

UNITED KINGDOM

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Shu Kong

Assistant Professor

Texas A&M University

UNITED STATES

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Christopher W. Dick

UNITED STATES

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Bernd Heinold

Deputy Head, Senior Scientist

Leibniz Institute for Tropospheric Research

GERMANY

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Ellen Currano

Professor

University of Wyoming

UNITED STATES

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Surangi Punyasena

Research Interests

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About

Articles (13)

Addressing the “open world”: detecting and segmenting pollen on palynological slides with deep learning

Digitizing collections to unlock the full potential of palynology: A case study with the Smithsonian palynology collection

Pollen morphology, deep learning, phylogenetics, and the evolution of environmental adaptations in Podocarpus

The evolutionary history evident in grass pollen morphology

CuticleTrace: A toolkit for capturing cell outlines from leaf cuticle with implications for paleoecology and paleoclimatology

Deep learning approaches to the phylogenetic placement of extinct pollen morphotypes

Review of the cellulose acetate peel method and the physical and digital curation of coal balls

An integrative environmental pollen diversity assessment and its importance for the Sustainable Development Goals

Automated identification of diverse Neotropical pollen samples using convolutional neural networks

Phylogenetic and ecological correlates of pollen morphological diversity in a Neotropical rainforest

Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy

Assessing the influence of vegetation structure and phenological variability on pollen‐vegetation relationships using a 15‐year Neotropical pollen rain record

Airyscan superresolution microscopy: A high-throughput alternative to electron microscopy for the visualization and analysis of fossil pollen

Collaborators (7)

Aletta Bonn

Stephanie Bohlmann

Luke Mander

Shu Kong

Christopher W. Dick

Bernd Heinold

Ellen Currano

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