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Ovidiu PaunView profile

Associate Professor

• Evolutionary Biology
• Genomics
• Plant Ecology
• +7 more

Assoc. Prof. Ovidiu Paun is an Associate Professor at the Department of Botany and Biodiversity Research within the Faculty of Life Sciences at the University of Vienna, Austria, where he has served since 2019 following a tenure-track Assistant Professor position (2015-2019). He leads the Plant Ecological Genomics research group, focusing on understanding why and how organisms diversify through fundamental evolutionary processes of adaptation and divergence. Paun earned his PhD in Evolutionary Biology from the University of Vienna (2005), with a dissertation on "Evolution of apomixis in the Ranunculus cassubicus group," supervised by Elvira Hörandl and Tod Stuessy. Prior to this, he completed a degree in Horticulture from the University of Agronomical Sciences in Bucharest, Romania (2000). His postdoctoral training included prestigious Marie Curie and Erwin Schrödinger Fellowships at Royal Botanic Gardens Kew (2006-2010). His research integrates molecular data with environmental context to investigate natural populations of both model and non-model organisms, exploring the origin of biodiversity and its dynamics. With particular interest in understanding the role of the environment in evolutionary processes, Paun has made significant contributions to the exploration of epigenetic variation in evolution. His integrative approaches, built upon a genomics core, aim to understand how lineages speciate and spread across niches, including novel environments. Analysis of Paun's recent publications reveals a strong focus on polyploidy, adaptation mechanisms, and speciation processes across diverse plant systems. His work spans from orchids (Dactylorhiza) to bromeliads (Tillandsia), examining parallel adaptation, epigenetic contributions to evolution, and the genomic basis of ecological divergence. A recurring theme is the investigation of how environmental factors shape evolutionary trajectories through both genetic and epigenetic mechanisms. 2013 START Prize from the Austrian Science Fund (FWF) 2009 Elected fellow of the Linnean Society, London 2007 Marie Curie Fellowship from the EU Commission 2006 Erwin Schrödinger Fellowship from the Austrian Science Fund (FWF) 2006 Best Presentation Award from the Systematics Association 2002 IAPT Award for young investigators in Plant Systematics Paun has secured substantial research funding including an FWF Stand-alone grant (P35275-B, 2022-2026, €600K), multiple Marie Curie Intra-European Grants (2022-2024, €359K total), and a prestigious START grant (Y661, 2013-2022, €1.2M). He serves as a reviewer for numerous funding agencies including ERC, NSF, and DFG, and has organized international symposia on evolutionary epigenetics and speciation genomics. His laboratory employs integrative genomic approaches to investigate adaptation mechanisms and speciation processes, with particular emphasis on how organisms respond to environmental challenges and how this shapes biodiversity patterns.

• Machine Learning
• Data Mining
• Artificial Intelligence
• +3 more

Van Quoc Huynh is a Researcher at the Institute for Application-oriented Knowledge Processing, Johannes Kepler University Linz (JKU), Austria. His work focuses on advancing machine learning and data mining techniques with emphasis on rule-based systems and symbolic artificial intelligence. His primary research interests include Machine Learning , Data Mining , and Symbolic AI , specializing in rule extraction algorithms, classification systems, and knowledge representation. He develops novel approaches for efficient pattern mining and interpretable model construction, bridging neural and symbolic paradigms. Recent publications demonstrate a clear trajectory toward hybrid neural-symbolic models for classification tasks and memory-efficient rule mining architectures. His work addresses critical challenges in scalability, parallel processing, and interpretability within knowledge discovery systems, with strong emphasis on practical implementations for complex datasets. Dr. Huynh actively contributes to FFG-funded research projects including the ongoing Automated Rule Extraction and Interpretation from Symbolic Regression Trees (2025-2026) and completed PreMoBAF (2021-2025). He engages with the academic community through conference organization (e.g., 20th International Conference on Foundations of Digital Games, 2025) and technical presentations on frequent itemsets mining. He operates within JKU's Institute for Application-oriented Knowledge Processing, which provides interdisciplinary infrastructure for applied AI research focusing on practical knowledge processing solutions.