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• Bioinformatics
• Transcriptomics
• Gene Expression Analysis
• +4 more

David Philip Kreil is an Associate Professor at the Institute of Molecular Biotechnology within the Department of Biotechnology and Food Science at the University of Natural Resources and Life Sciences, Vienna (BOKU) . He holds a joint appointment as Chair of Bioinformatics at the University of Warwick (2012-2014) and has held research positions at the European Bioinformatics Institute (EBI) and the University of Cambridge . His work bridges computational biology, transcriptomics, and plant-nematode interactions. 2012-2014: Chair of Bioinformatics, University of Warwick 2005: WWTF Vienna Science Chair at BOKU 2001-2004: MRC Research Fellow, University of Cambridge 1997-2001: EMBL PhD Programme, EBI Kreil's research focuses on transcriptomic analysis of plant-pathogen interactions (e.g., Fusarium resistance in wheat, nematode-induced syncytia) and computational methods for microarray calibration, data normalization, and statistical modeling. He has applied machine learning to weather forecasting and biomedical data. Scientific Awards : Research Fellow, Darwin College, University of Cambridge (2002-2005) His 15 most recent articles emphasize bioinformatics tools, plant immunity, and interdisciplinary applications of machine learning in biology and climate science. He has supervised theses on wheat transcriptomics and nematode-induced gene expression.

Thomas EiterView profile

Professor

• Answer Set Programming
• Knowledge Representation
• Logic Programming
• +7 more

Thomas Eiter is a Professor at TU Wien's Institute of Logic and Computation. His research focuses on declarative programming paradigms, knowledge representation, and artificial intelligence. He leads projects in neurosymbolic systems, answer set programming (ASP), and stream reasoning, with applications in visual question answering, scheduling optimization, and semantic scene generation. Eiter has contributed to foundational work in ASP semantics, computational complexity, and hybrid reasoning frameworks. His work bridges logical formalisms with practical AI challenges, emphasizing explainability and scalability. Projects like ALASPO and neurosymbolic integration showcase his focus on advancing both theoretical and applied aspects of AI. Projects: HumanE AI Network, WASP, REWERSE Research Themes: Neurosymbolic AI, Answer Set Programming, Stream Reasoning Notable achievements include pioneering work on semiring-based reasoning frameworks and developing efficient ASP solvers like Alpha. His contributions span over 471 publications, emphasizing interdisciplinary applications in computer vision, robotics, and automated planning.

• Computer Vision
• Explainable Machine Learning
• Statistical Models in AI
• +3 more

Siavash Arjomand Bigdeli serves as an Associate Professor of Computer Vision at the Technical University of Denmark, following prior employment as a scientist at the Swiss Center for Electronics and Microtechnologies (CSEM). His research focuses on: Ante-/Post-Hoc explainability of machine learning models Integration of statistical models in learning/inference processes Philosophical methodologies in artificial intelligence development Advanced computer vision techniques for visual understanding Recent publications reveal consistent specialization in image restoration and stereo vision, employing deep learning architectures and probabilistic graphical models to solve core challenges in visual data reconstruction and temporal coherence. His work demonstrates strong interdisciplinary connections between theoretical machine learning, practical computer vision applications, and epistemological considerations in AI systems.