جستجوی استاد راهنمای دانشگاهی

• Selective Sampling
• Text Classification and Web Mining
• Data Mining in the Social Sciences
• +۶ مورد دیگر

Johannes Fürnkranz serves as a Professor at the Faculty of Informatics, TU Wien, affiliated with the Distributed Systems research group (Institute E194-02). His institutional presence is evidenced by current contact details and recent scholarly output. His research spans critical machine learning domains including Selective Sampling, Text Classification and Web Mining, Data Mining in the Social Sciences, Inductive Logic Programming, and Noise Handling. Specialized interests cover Machine Learning in Game Playing, Pairwise Classification and Preference Learning, alongside Meta-Learning and Ensemble Classifiers, reflecting both theoretical depth and applied versatility in artificial intelligence. Current publication trends indicate active work in change point detection for heterogeneous data systems, combining predictive modeling with anomaly detection in time series. This aligns with broader themes in statistical learning and non-parametric methods for complex data structures. No scientific awards were documented in the source material. Advising activities and research funding details remain unspecified in available information. Laboratory affiliations center on the Distributed Systems group within TU Wien's Faculty of Informatics infrastructure.

Thomas Bäckمشاهده پروفایل

استاد

• Artificial Intelligence
• Evolutionary Computation
• Machine Learning
• +۶ مورد دیگر

Thomas Bäck is a Full Professor at the Leiden Institute of Advanced Computer Science (LIACS), Leiden University, and Chief Scientist at NORCE Norwegian Research Center, Norway. His career spans roles as Director of the Center for Applied Systems Analysis (Germany) and Vice Scientific Director at LIACS (since 2017). He holds additional positions like Adjunct Professor at the University of Calgary and Visiting Professor at Xi'an Jiaotong University. Bäck's research focuses on evolutionary computation, machine learning, and their applications in sustainable smart industry and health. He leads interdisciplinary initiatives like the Society, Artificial Intelligence, and Life Sciences (SAILS) program, with expertise in natural computing, data-driven optimization, and quantum computing challenges. IEEE Fellow (2022) Member of KNAW (2021) IEEE CIS Pioneer Award (2015) Fellow of International Society of Genetic and Evolutionary Computation (2003) Best PhD Thesis Award from German Society of Computer Science (1995) Bäck has graduated 22 PhD students and currently supervises 14, with 62 MSc students mentored. His editorial roles include Editor-in-Chief of the Evolutionary Computation Journal and Associate Editor for multiple journals. He has secured grants from the Dutch Research Council and The Research Council of Norway for projects like ECOLE and CIMPLO.

Thomas Grafمشاهده پروفایل

استاد پژوهش

• Macrophage
• Cancer biology
• Reprogramming
• +۱۶ مورد دیگر

Thomas Graf is a Research Professor at the Centre for Genomic Regulation (CRG) in Barcelona, Spain, and an ICREA Research Professor since 2006. His academic career spans multiple prestigious institutions including Albert Einstein College of Medicine, European Molecular Biology Laboratory, and Max Planck Institute. Research focus: Cancer biology, Reprogramming, Genetic engineering, Molecular biology Key contributions: Hematopoietic stem cells, Transdifferentiation, Computational biology His recent publications demonstrate expertise in inverse imaging problems, diffusion models, and biomedical applications spanning cardiology and protein structure analysis. Scientific accolades include the Paul Ehrlich Prize and membership in Academia Europaea. 1989: Paul Ehrlich and Ludwig Darmstaedter Prize 1983: Wilhelm Warner Foundation Prize Other: Leukemia Research Award, German Society for Microbiology and Hygiene Prize, Academia Europaea membership

Seth Grantمشاهده پروفایل

استاد

• Neuroscience
• Behaviour
• Synaptic biology
• +۳ مورد دیگر

Professor Seth Grant is a distinguished Professor of Molecular Neuroscience at the University of Edinburgh, holding a Personal Chair in the Department of Neuroscience within the College of Medicine & Veterinary Medicine. He serves as Director of the Centre for Clinical Brain Sciences and leads the internationally renowned Genes to Cognition (G2C) Programme. His academic career spans multiple prestigious institutions including the Wellcome Trust Sanger Institute, University of Cambridge, and Florey Institute for Neuroscience and Mental Health in Melbourne. Professor Grant's research focuses on understanding the fundamental mechanisms of behavior through studying the genes and proteins that control synapses - the connections between nerve cells. His work has revealed that multiprotein machines comprising synapse proteins are responsible for innate and learned behaviors, with their dysfunction underlying numerous brain diseases including Alzheimer's disease, schizophrenia, autism, depression, addiction and intellectual disability. Current research in his laboratory is centered on uncovering the scope and functional impacts of synapse diversity throughout the brain, developing methods for brain-wide mapping of protein composition at single-synapse resolution ('synaptome' maps). His laboratory has characterized how the synaptome architecture changes throughout the lifespan and how mutations causing cognitive disorders reorganize synaptome maps. These findings have significant implications for understanding how information is stored and recalled in the brain. Recent publications demonstrate his team's work on evolutionary aspects of cognitive function, human-mouse proteome comparisons, and the molecular basis of brain diseases. IBANGS Distinguished Investigator Award (2019) FENS EJN Award (2020) Wesley College Foundation Medal (2017) Elected Fellow of the Academy of Medical Sciences (2015) Kenneth B. Myer Award (2014) Elected Fellow of the Royal Society of Edinburgh (2011) Professor Grant actively supervises PhD students including Wen Chyi Quah, Aisha Belhadi, and Candace Adams, and has received substantial research funding from the Wellcome Trust, European Research Council, Medical Research Council, Simons Initiative for the Developing Brain, Chan Zuckerberg Initiative, and Medical Research Scotland. His laboratory comprises a multidisciplinary team of senior researchers, postdoctoral fellows, research technicians, and students working at the forefront of synaptic neuroscience.

Andreas Holzingerمشاهده پروفایل

دانشیار

• Explainable AI
• Interpretable machine learning
• Health informatics
• +۳ مورد دیگر

Andreas Holzinger leads the Holzinger Group (HCAI, Human-Centered AI Lab) at the Institute for Medical Informatics/Statistics, Medical University Graz, and holds a venia docendi at TU Graz. He serves as consultant for multiple governments and scientific organizations and participates in the advisory boards of national AI strategies. PhD in Cognitive Science (Graz University, 1998) Habilitation in Applied Computer Science (TU Graz, 2003) His research focuses on Explainable AI , Interactive Machine Learning , and Human-in-the-Loop approaches within Health Informatics , combining Human-Computer Interaction and Knowledge Discovery . He founded the Expert Network HCI-KDD and organizes the IFIP Cross-Domain Conference CD-MAKE . His recent publications emphasize human-centric AI , medical data visualization , and interactive knowledge discovery , particularly in biomedical and clinical domains. He has contributed to gamification approaches in education technology and virtual patient applications. 2018 - Top 10 AI expert in Austria (IFIP WCC) 2018 - Elected Austrian Representative to IFIP TC 12 2017 - Invited Keynote at DATA 2017 2016 - Invited Keynote at KES Conference Andreas has participated in 30+ multinational R&D projects (€6M+ budget), published 300+ works (11k+ citations, h-index 48), and actively promotes cross-domain collaboration between AI and biomedical research.

Urbashi Mitraمشاهده پروفایل

استاد

• Sensor networks
• Wireless communication systems
• Machine learning
• +۶ مورد دیگر

Urbashi Mitra is the Gordon S. Marshall Chair Professor in Electrical & Computer Engineering at the University of Southern California (USC) . She has held visiting professor positions at King’s College London, Imperial College London, and Delft University of Technology. Her academic career began at The Ohio State University as Assistant Professor (1994–2000) and briefly as Associate Professor (2000). She was a Visiting Associate Professor at Stanford and Rice Universities earlier in her career. Education : B.S. and M.S. from University of California, Berkeley; Ph.D. from Princeton University. Research interests include wireless communication systems (4G/5G/6G), machine learning , sensor networks , molecular communications , underwater networking , and signal processing . She has pioneered interdisciplinary work at the intersection of communication theory, biological systems, and multi-scale signal processing. Scientific awards reflect her leadership and innovation: 2024 Distinguished Lecturer, IEEE Signal Processing Society 2021 USC Viterbi Senior Research Award 2017 IEEE Women in Communications Engineering Technical Achievement Award 2016 Fulbright US Scholar and Royal Academy of Engineering Distinguished Visiting Fellowship She served as the inaugural Editor-in-Chief of the IEEE Transactions on Molecular, Biological, and Multi-Scale Communications and held associate editor roles across five IEEE journals. Her career spans academia, international collaborations, and industry advisory roles.

Jean-Luc Starckمشاهده پروفایل

استاد پژوهش

• Large Scale Structures
• Cosmology
• Astrophysics
• +۵ مورد دیگر

Dr. Jean-Luc Starck is a Research Professor and Director of Research at the French Alternative Energies and Atomic Energy Commission (CEA), leading the CosmoStat laboratory since 2010. He specializes in astrophysics, cosmology, and interdisciplinary research at the intersection of statistics and machine learning. His work supports major space missions like ESA's Euclid and Planck, where he coordinates teams developing scientific algorithms for billion-euro missions. Affiliations: CEA Astrophysics Department, CosmoStat Lab (20 researchers). Education: PhD from Nice Observatory (1992), Habilitation from University Paris XI. Research Interests: Focuses on cosmological large-scale structures, weak lensing analysis, sparsity techniques, and machine learning applications in astrophysics. His group develops cutting-edge methodologies for space mission data analysis and industry-academia collaborations. Awards: Recipient of the Gruber Cosmology Prize (2018, ESA Planck team), Tycho Brahe Medal (2022), and 2024 Space Achievement Award. Elected to Academia Europaea in 2021. Grants & Advising: Secured over €8M in competitive funding, including an Advanced ERC Grant. Oversees Euclid's 250-member algorithm team for end-user scientific products. Labs/Teams: Heads CosmoStat Lab, collaborating with institutions like Stanford, UCLA, and FORTH. Involved in Euclid's 1500-member international collaboration across 18 countries.

Wojciech Szpankowskiمشاهده پروفایل

استاد

• Analysis of Algorithms
• Information Theory
• Analytic Combinatorics
• +۶ مورد دیگر

Wojciech Szpankowski is the Saul Rosen Distinguished Professor of Computer Science at Purdue University. He holds concurrent positions as a Guest Professor at ETH Zurich and a Professor at Jagiellonian University, Krakow. His research focuses on analysis of algorithms, information theory, analytic combinatorics, and random structures. He has directed major initiatives like the NSF Science & Technology Center on Science of Information (CSoI), a $50M 10-year project. Szpankowski is a Fellow of the IEEE and has received prestigious awards including the Flajolet Prize (2020) and Humboldt Research Award (2010). He has held visiting roles at institutions worldwide, including Stanford University and the Newton Institute, Cambridge. His academic journey includes tenure as Full Professor at Purdue (since 1992), Assistant Professorships at McGill University (1984–1992) and Technical University of Gdańsk (1980–1984). His scholarly contributions span monographs like "Average Case Analysis of Algorithms on Sequences" (2001) and "Analytic Pattern Matching" (2015), with a forthcoming work on Analytic Information Theory (2022). He actively contributes to scientific boards, including HIIT Helsinki and NeuroMat Brazil. Szpankowski’s publications emphasize interdisciplinary research at the intersection of computer science, mathematics, and biology. His work on privacy-preserving data analysis, dynamic network inference, and protein superfamily evolution showcases his broad impact. Keynote talks at major conferences (e.g., SODA 2019, AofA 2016) reflect his leadership in theoretical computer science. His grants and recognitions underscore institutional trust: the NSF Science & Technology Center (2010) and Arden L. Bement Jr. Award (2015) highlight his pioneering role in redefining information science. Collaborations span academia and industry, with affiliations at Hewlett-Packard and INRIA.

• Deep learning
• Multimedia
• Applied statistics and mathematics
• +۸ مورد دیگر

Dacheng Tao is a Professor of Computer Science at the University of Technology Sydney (UTS), where he has been employed since 2010 and holds an ARC Future Fellowship since 2013. His work bridges statistics, mathematics, and advanced data analytics, with a focus on machine learning, computer vision, and multimedia technologies. Research Interests : Deep learning, computer vision, image processing, data mining, pattern recognition, geoinformatics, and video surveillance. Academic Contributions : Author of one monograph and over 400 publications in prestigious journals and conferences, with multiple best paper awards, including the 2014 ICDM 10 Year Highest Impact Paper Award. Honors and Recognition : 2015 ESI Highly Cited Researchers in Engineering and Computer Science. 2015 Australian Scopus-Eureka Prize, ACS Digital Disruptors Award (Gold Disruptor), and UTS Vice-Chancellor’s Medal for Exceptional Research. Fellowships in IEEE, IAPR, SPIE, OSA, IET, and BCS. Leadership and Service : Guest editor for 10+ special issues, editor for 10+ journals (including 7 IEEE Transactions), 4 conference keynote speeches, 60+ conference chairmanships, and service on 150+ major conferences and 60+ international journals.

Jerzy Tiurynمشاهده پروفایل

استاد

• Bioinformatics
• Computational Biology
• Sequence Analysis
• +۹ مورد دیگر

Jerzy Tiuryn is a Full Professor at the Faculty of Mathematics, Informatics and Mechanics, University of Warsaw (since 1992), with a PhD in Mathematics from the same university (1975). He served as Vice Dean for Scientific Matters and International Relations (2005-2012) and is actively engaged in editorial roles for journals like Theoretical Computer Science , Information and Computation , and BioMed Research International . Education: PhD in Mathematics (University of Warsaw, 1975). Research Interests: His work spans past contributions in program verification, semantics, typed lambda calculus, and type theory, with current focus on bioinformatics and computational biology. Specific areas include sequence analysis, gene family evolution, protein-protein interaction networks, gene regulatory regions, gene mutations in bacterial drug resistance, and comparative genomics. Trends in Publications: His recent articles emphasize computational methods in bacterial genomics (CAMBerVis, CAMBer), regulatory element prediction (Bi-Billboard), protein interaction mapping via phylogeny, and Bayesian network modeling for gene expression. Themes center on genomic data analysis, evolutionary conservation, and algorithm development for biological systems. Scientific Contributions: Awards and memberships highlight leadership in European and Polish academic networks: Board Member, European Research Consortium for Informatics and Mathematics (ERCIM) (2011) First President, Polish Bioinformatics Society (2008-2010) Founding Member/President, PLERCIM (2007-2012) Member, Academia Europaea (since 1996)

Alessandro Trevesمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Neural Networks
• Hippocampus Function
• +۴ مورد دیگر

Alessandro Treves is a Full Professor of Cognitive Neuroscience at SISSA (International School for Advanced Studies), where he has held this position since 2006. His academic career includes roles as Associate Professor (2000–2006) and Research Fellow (1992–2000) at SISSA. He also serves as a long-term visiting professor at NTNU’s Centre for Neural Computation (2003–present) and has held leadership roles, including Coordinator of the Neuroscience Area at SISSA (2016–2018) and Director of the Master in Complex Actions (2013–2015). From 2011–2013, he was a Counsellor for Scientific Affairs at the Italian Embassy in Tel Aviv. His research focuses on cognitive neuroscience, particularly the hippocampus, spatial cognition, and statistical physics approaches to brain function. Key areas include attractor neural networks, evolutionary neuroscience, and the theoretical underpinnings of neural systems. He has mentored numerous successful PhD students, many of whom now lead institutions globally. Dr. Treves was elected to the Royal Norwegian Society of Sciences and Letters (2008) and actively contributes to academic governance, including roles in the Federation of European Neuroscience Societies (2005–2007) and the Jewish Community of Trieste (2002–2018). His work bridges theoretical physics and neuroscience, with notable contributions to understanding grid cells and spatial navigation systems. His academic journey began with a postdoctoral fellowship at the University of Oxford (1989–1992) under Prof. E.T. Rolls, followed by research at SISSA’s Biophysics and Cognitive Neuroscience sectors.

• Bayesian Probability Theory
• Uncertainty Quantification
• Machine Learning
• +۶ مورد دیگر

Sascha Ranftl is an Erwin Schrödinger Fellow at the Courant Institute of Mathematical Sciences, New York University. Their research spans interdisciplinary domains including Bayesian probability theory, uncertainty quantification, computational engineering, and biomedical applications. Affiliation: Courant Institute, NYU Former Affiliation: Graz University of Technology (Institute of Theoretical Physics & Computational Physics, Graz Center of Computational Engineering) Research Interests: Ranftl's work focuses on integrating Bayesian inference with machine learning and physics-informed modeling to address uncertainty quantification in biomedical simulations, particularly for aortic dissection and impedance cardiography . Their approach harmonizes statistical rigor with engineering pragmatism, emphasizing surrogate models and computational fluid dynamics. Recent Publications: Analyze geometric uncertainties in patient-specific blood vessels, develop physics-consistent neural networks, and apply Bayesian frameworks to biomedical diagnostics and elastoplastic material modeling. Scientific Awards: Erwin Schrödinger Fellowship Contact: ranftl@tugraz.at sranf@duck.com

Zhu Xiaoxiangمشاهده پروفایل

استاد

• Synthetic Aperture Radar
• Remote Sensing
• Global Urban Mapping
• +۴ مورد دیگر

Xiaoxiang Zhu is a Full Professor for Data Science in Earth Observation at Technical University of Munich (TUM) and Director of the International AI Future Lab (AI4EO). She leads interdisciplinary research on signal processing and machine learning applied to Earth observation (EO) data, addressing global challenges like urbanization and climate change. Her work focuses on extracting geoinformation from big EO datasets using innovative AI techniques. Education & Positions: Professor (W3) since 2019, TUM Former Head of EO Data Science Department at German Aerospace Center (DLR) Adjunct Teaching Professor (2013–2015) Research Interests: Deep learning in SAR and multispectral imagery Global urban morphology mapping Uncertainty quantification in AI models EO data fusion and big data analytics Climate change monitoring via satellite data Articles Trends: Her publications emphasize AI-driven solutions for EO challenges, including SAR tomography, benchmark datasets (e.g., So2Sat LCZ42), and uncertainty estimation in neural networks. Over 220 journal papers and 173 conference papers highlight her contributions to geosciences and remote sensing. Awards: IEEE Fellow (2021) ERC Grants (Starting & Proof of Concept) Heinz Maier-Leibnitz-Preis (2015) Member of German and Bavarian Academies of Sciences Advising & Grants: Supervised PhD students (e.g., Mou) Secured €10M+ in research funding Co-led Helmholtz AI Research Field MASTr (2019–2022) Labs & Teams: Founder of AI4EO Lab Co-leader of Munich Data Science Research School (MUDS) Member of ELLIS Society and IEEE committees

• Causal Inference
• Machine Learning
• Statistical Modeling
• +۴ مورد دیگر

Dr. Lucas Kook is a Researcher at the Department of Statistics and Mathematics, WU Vienna University of Economics and Business. His research focuses on causal inference, machine learning, and statistical modeling, with applications in sports analytics, medical data analysis, and healthcare outcomes. He actively develops R packages such as deeptrafo for neural network-based statistical inference. His work bridges theoretical advancements in distributional regression and practical implementations in healthcare and sports domains. Key research areas include algorithm development for significance testing in supervised learning, causal feature selection, and nonparametric methods for conditional independence. Recent studies explore the efficacy of thrombolytic therapies in retinal artery occlusion and the predictive power of deep learning models in stroke patient outcomes. Collaborations span interdisciplinary fields, emphasizing reproducibility and methodological rigor in simulation studies.

Monika Dörflerمشاهده پروفایل

استاد

• Applied Harmonic Analysis
• Audio Signal Processing
• Machine Learning
• +۳ مورد دیگر

Monika Dörfler is a Professor in the Department of Mathematics at the University of Vienna. Her research focuses on applied harmonic analysis, audio signal processing, and the mathematics of machine learning. She specializes in time-frequency analysis, nonstationary Gabor frames, and deep learning applications in audio processing. Dörfler has contributed significantly to methods like the invertible constant-Q transform and has explored the intersection of convolutional neural networks with signal representation theory. Affiliations: Department of Mathematics, University of Vienna Roles: Professor, Privatdozent, Principal Investigator (PI) in grants including WWTF Hertha Firnberg and SALSA projects Teaching: Courses such as Applied Analysis and Bachelor seminar Her research interests emphasize both theoretical foundations and practical applications of signal processing techniques. Notable contributions include work on Gabor frames in deep scattering networks and orthogonal projections for dimension reduction in learning problems. Dörfler has received awards for her papers, including Best Paper Awards at ISMIR19 and DAFx-11, and has organized international conferences like SAMPTA19 and DAFx2020. Awards: Best Paper Gold (DAFx-11), ISMIR19 Award, WWTF Grant Leadership Grants: Co-PI in aMOBY (Acoustic Monitoring of Biodiversity), PI in Audio-Miner and Hertha Firnberg grant Her work addresses challenges in audio denoising, music information retrieval, and algorithmic biases in recommendation systems. Ongoing projects include "Filter them all! Gabor theory for image quality assessment" submitted to FWF in 2023.