جست‌وجوی استاد و پژوهشگر

• Molecular Mycology
• Mycoparasitism and Biocontrol
• Fungal Signaling Pathways
• +۴ مورد دیگر

Susanne Zeilinger-Migsich is a Universitätsprofessorin (Full Professor) and Director of the Institute of Microbiology at the University of Innsbruck's Faculty of Biology. She leads the Molecular Mycology and Mycoparasitism research group, focusing on Trichoderma species as biocontrol agents against plant pathogens. Her work integrates molecular genetics, chemical ecology, and systems biology to dissect fungal interactions. Her research centers on molecular mycology with emphasis on: Mechanisms of mycoparasitism and fungal biocontrol Signal transduction in Trichoderma during host interaction Secondary metabolite biosynthesis (particularly 6-pentyl-α-pyrone) Fungal volatile organic compound communication Nutrient regulation and stress response pathways Current work leverages CRISPR-Cas9, metabolomics, and live-cell imaging to visualize molecular interactions in real-time. Analysis of her 15 most recent publications reveals strong thematic continuity in Trichoderma molecular mechanisms, with increasing methodological sophistication in genome editing (CRISPR), real-time VOC analysis (PTR-MS), and spatial metabolomics (MALDI imaging). Key research threads include TOR and MAPK signaling pathways, epigenetic regulation of mycoparasitism, and light-dependent metabolic reprogramming. Scientific recognition includes: Associate Editor for Frontiers in Fungal Biology Editorial Board Member for Biocontrol Science and Technology Editorial Board Member for Pathogens journal Leadership of the DK Bio-Interactions doctoral program Member of Faculty Council for Biology Her group actively mentors PhD students (including Baldin, Pierson, Flatschacher) who lead projects on CRISPR applications, antioxidant systems, and nanoparticle biosynthesis. Major funded projects include WWTF's 'BIOGEN: from genes to biocontrol' and FWF's 'TRICHO-TOR: TOR kinase signaling in Trichoderma atroviride', reflecting strong institutional support for her research program. Public engagement includes frequent media appearances in Der Standard, ORF, and Tiroler Tageszeitung discussing fungal applications in agriculture and biotechnology.

Francesco Profumoمشاهده پروفایل

استاد

• High power devices
• New electrical machines structures
• Integrated electronic/electromechanical design
• +۴ مورد دیگر

Francesco Profumo serves as Rector of Polytechnic University of Turin since 2005 and previously as Dean of the Faculty of Engineering (2003-2005). He holds a Professorship in Electrical Machines and Drives at the same institution since 1996, following a professorship at University of Bologna (1994-1996). His international experience includes Visiting Professorships at University of Nagasaki (1996-1997) and University of Wisconsin, Madison (1986-1988). Prof. Profumo's research focuses on advanced electrical machine systems and power electronics, specializing in high-power devices, novel electrical machine structures, integrated electromechanical design, and power conversion technologies. His work particularly addresses high-response servo drives, fuel cell power conditioning, and energy-saving applications in electrical plants. This research bridges theoretical innovation with industrial implementation in automotive traction, renewable energy systems, and industrial motor drives. His publication record from 2002-2008 demonstrates consistent contributions to dual three-phase motor drives, sensorless control techniques, and multiphase drive systems. Key thematic areas include thermal management in integrated drives, fault-tolerant control architectures, and energy-efficient electrical plant design, with publications predominantly appearing in IEEE Transactions journals. Major recognitions include multiple honorary doctorates from Technical University of Riga, Politechnica of Bucharest, and University of Miskolc, alongside IEEE-IAS paper prizes (1991, 1992, 1997) and IIEE-IPEC first prize (2005). Additional distinctions comprise honorary professorships at University of Cordoba and Jiao Tong University, and the Signum Aureum award from University of Miskolc. No information regarding student advising or research grants appears in the source materials. Similarly, laboratory affiliations or team leadership details beyond administrative roles are not documented.

Christian Vogelمشاهده پروفایل

مدرس ارشد

• Signal Processing
• Analog/Digital Conversion (ADCs)
• Mixed-Signal Systems
• +۵ مورد دیگر

Christian Vogel is a Senior Lecturer affiliated with the Institute for Signal Processing and Speech Communication at TU Graz. His work focuses on advanced signal processing techniques, analog/digital conversion systems, and mixed-signal architectures. Key research areas include time-interleaved ADC error correction, digital predistortion for RF systems, and EVM estimation methodologies. Education: Holds a Dr.techn. (Doctor of Engineering) and Dipl.-Ing. (Diploma in Engineering). His research emphasizes practical applications in mixed-signal systems, including calibration techniques for high-resolution ADCs, nonlinear system compensation, and energy-efficient transmitter design. Recent work explores optimization-based quantization, crest factor reduction in envelope tracking, and adaptive filtering for digital predistortion. Publications span over 15 years, addressing topics ranging from PWM-based RF transmission to all-digital phase-locked loops. His contributions bridge theoretical signal processing with hardware implementation challenges in modern electronic systems. Teaching expertise includes analog and digital signal processing, with authorization to teach at TU Graz. Active in industry-academia collaboration, his work aims to improve system performance in telecommunication and embedded electronics.

Philipp Bringmannمشاهده پروفایل

پژوهشگر

• Numerical solution of PDEs
• Least-squares finite element method
• Adaptive mesh refinement
• +۴ مورد دیگر

Philipp Bringmann is a Researcher at the Institute of Analysis and Scientific Computing (E 101) at TU Wien, Austria. His work focuses on numerical methods for partial differential equations (PDEs), with specializations in adaptive finite element methods (FEM), least-squares formulations, and discontinuous Petrov-Galerkin techniques. He holds a PhD in Mathematics from Humboldt-Universität zu Berlin (2020) and has held postdoctoral positions at both TU Wien and Humboldt-Universität. Research Interests : Numerical solution of PDEs Least-squares finite element methods Adaptive mesh refinement Iterative linearization techniques Applications in computational mechanics Teaching : Current: Least-Squares Finite Element Methods (Winter 2024/25) Past: Numerical methods for PDEs (Winter 2023/24) Software Contributions : octAFEM3D: 3D adaptive finite element software MooAFEM: MATLAB-based adaptive FEM toolkit Recent Talks : Presented work on adaptive FEM with inexact solvers at the Chemnitz Finite Element Symposium 2024 .

• Pharmaceutical Sciences
• Immunology
• Microbiology
• +۴ مورد دیگر

Simon Decker is a researcher in the Faculty of Life Sciences at an unspecified institution, specializing in the Department of Pharmaceutical Sciences. His work focuses on advanced drug delivery systems and molecular targeting strategies. Department: Pharmaceutical Sciences Research Areas: Nanocarrier design, gene therapy, immune modulation, and RNA-based therapeutics Decker's research explores innovative approaches to enhance therapeutic efficacy through targeted delivery mechanisms, including ligand engineering and endosomal escape optimization. His work intersects pharmacology, immunology, and biotechnology. Recent publications highlight trends in oligonucleotide delivery systems, viral vector retargeting, and peptide ligand design for receptor-specific therapies. Key subfields include epidermal growth factor receptor targeting, siRNA complexation, and macrophage interaction dynamics.

• Microglia
• Neuronal Circuits
• Neuropathological Disorders
• +۴ مورد دیگر

Sandra Siegert is a Professor in the Life Sciences Department at the Institute of Science and Technology Austria (ISTA). Her research focuses on understanding how microglia interact with neuronal networks in both healthy and diseased states, particularly in the context of neuropathological disorders. She integrates knowledge from virology, immunology, molecular biology, neuroscience, and applied mathematics to study microglia's role in brain maintenance and disease progression. Education Dr. phil. nat in Neurobiology from the University of Basel (2005-2010) Diploma in Biological Sciences from Goethe-Universität Frankfurt am Main (2000-2005) Research Interests Dr. Siegert's work emphasizes microglia's response to environmental cues, their epigenetic regulation, and their contribution to neurological disorders like schizophrenia and Alzheimer's disease. Key areas include: Microglia-neuron communication in retinal and cortical circuits Role of microRNAs (e.g., miR-137) in synaptic plasticity 60-Hz light entrainment effects on brain plasticity Applied topology for analyzing cellular networks Human iPSC-derived microglia modeling Publication Trends Her recent articles highlight interdisciplinary approaches to studying microglia in retinal organoids, mitochondrial dynamics in stress response, and chimeric GPCR tools for modulating neuroimmune activity. Collaborative work spans gene therapy vectors (AAV2/6), synaptic dysfunction in schizophrenia, and ketamine/light entrainment effects on perineuronal nets. Scientific Contributions EMBO short-term fellowship (2011) FWF Austrian Science Fund grant P 37131 (2023-2026) European Research Council grant 715571 (2017-2022) Human Frontiers Science Program grant (2012-2015) Multiple Swiss National Science Foundation grants (2011-2012)

Manfred Kaltenbacherمشاهده پروفایل

استاد

• Computational Electromagnetics
• Finite Element Analysis
• Aeroacoustics
• +۴ مورد دیگر

Manfred Kaltenbacher is a University Professor at Vienna University of Technology, specifically in the Institute of Fundamentals and Theory in Electrical Engineering. He holds multiple prestigious positions and has received significant recognition including a Doctor Honoris Causa from Budapest University of Technology and Economics and election to the Austrian Academy of Sciences. His research spans computational electromagnetics, acoustics, and materials science with over 200 publications and numerous active research projects. Professor Kaltenbacher's research interests focus on advanced computational methods for electromagnetic and acoustic phenomena. His work encompasses finite element analysis for magnetics and acoustics, hysteresis modeling, aeroacoustics, and computational physics. He has made significant contributions to the simulation of electromagnetic devices, noise propagation, and the development of numerical methods for multiphysics problems. His research bridges theoretical developments with practical engineering applications across multiple domains including Advanced Materials Science, Information and Communication, Mobility & Production, and Sustainable Systems. His recent publications show a strong trend toward integrating machine learning with traditional physics-based modeling, particularly in magnetics and acoustics. There's significant focus on developing advanced numerical methods like the Discontinuous Galerkin method for outdoor noise propagation and improving hysteresis models for electromagnetic devices. His work often addresses multiphysics challenges, combining electromagnetics with acoustics, fluid dynamics, and structural mechanics, with applications spanning from electric motors to noise barriers and energy systems. Professor Kaltenbacher has received notable scientific recognition: Doctor Honoris Causa (Dr. h.c.) from Budapest University of Technology and Economics (2020) Election to the Austrian Academy of Sciences (Österreichische Akademie der Wissenschaft) (2017) He actively leads multiple research projects including "Verlust E-Blech" (focusing on loss models for electrical sheets), "VAMM" (noise barriers), "ECHODA" (energy efficient cooling), and "eMotorWinding" (eMotor winding design). His research funding spans multiple domains including electromagnetics, acoustics, and energy efficiency applications. While the text mentions "Supervised Work (1)", specific student names aren't provided in the available information. Professor Kaltenbacher collaborates extensively across institutions, with recent activities showing collaboration with Budapest University of Technology and Economics and other international partners. His research group appears to focus on computational methods for electromagnetic and acoustic phenomena, with particular expertise in finite element methods and multiphysics simulations, as evidenced by his numerous publications and active projects through 2025.

• Bayesian Statistics
• Time Series Analysis
• Econometrics
• +۳ مورد دیگر

Gregor Kastner is Professor and Deputy Head of the Institute of Statistics at the University of Klagenfurt. His research focuses on Bayesian statistics, time series analysis, econometrics, and computational methods, with applications in finance, economics, and environmental modeling. He develops statistical software including packages for stochastic volatility modeling in R. Kastner's methodological work centers on Bayesian inference for high-dimensional problems, developing efficient computational algorithms for complex models. His applied research examines volatility dynamics in financial markets, macroeconomic forecasting, and spatial analysis of economic indicators. Recent projects include Bayesian nonparametric clustering for evaluating agricultural subsidies in Europe, sparse vector autoregressions for high-dimensional forecasting, and stochastic volatility models for commodity markets. He maintains active collaborations across economics, finance, and environmental science disciplines.

Birgit Rudloffمشاهده پروفایل

استاد

• Multivariate risks
• Set-valued risk measures
• Markets with transaction costs
• +۴ مورد دیگر

Birgit Rudloff is a Full Professor at the Institute for Statistics and Mathematics at Vienna University of Economics and Business. With a PhD in Financial Mathematics from Martin-Luther-University Halle-Wittenberg, her research focuses on multivariate risks, set-valued risk measures, optimization algorithms, and game theory applications in finance. She leads significant research projects in financial mathematics and vector optimization. Her research interests span dynamic set-valued risk measures, markets with transaction costs, systemic risk measurement, and algorithms for solving vector optimization problems. Recent work explores Nash equilibria computation and convex projections in unbounded spaces. Research outputs demonstrate strong focus on convex optimization techniques in financial mathematics, risk measurement methodologies, and game theory applications. Recent publications show growing interest in machine learning approaches for optimization problems. 2021 SIAM-FME Conference Paper Prize 2021 WU Star Journal Award Advises doctoral students and postdoctoral researchers in financial mathematics and optimization theory. Current research group includes postdocs and PhD students working on vector optimization and risk measures.

Andrea Wagnerمشاهده پروفایل

پژوهشگر

• Convex Optimization
• Vector Optimization
• DC Programming
• +۳ مورد دیگر

Dr. Andrea Wagner is a faculty member at the School of Statistics and Mathematics (Vienna University of Economics and Business, WU). Her research focuses on convex optimization , vector optimization , and DC programming , with applications in locational analysis and mathematical economics . Education: Dr.rer.nat. (PhD equivalent) in Statistics and Mathematics Research Interests: Andrea specializes in solving complex optimization problems, particularly unbounded convex vector optimization and semi-obnoxious facility location using Manhattan distances. Her work bridges theoretical mathematics with practical applications in economics and urban planning. Publication Trends: Recent articles emphasize computational methods for multi-objective optimization, duality theory applications, and algorithmic solutions for non-convex problems, reflecting her interdisciplinary approach. Scientific Awards: GOR Young Researchers Award (2020) Scholarship from Society of Friends and Patrons of Martin Luther University Halle-Wittenberg (2014) Ebert Beratung und Innovation GmbH Advancement Award (2010) Traveling Scholarship from General Endowment Fund of Theoretical Physics and Mathematics (2010)

• Real-Time Systems
• Embedded Systems
• Worst-Case Execution Time (WCET) Analysis
• +۵ مورد دیگر

Overview Peter Puschner is a full Professor at the Faculty of Informatics at TU Wien, specializing in Computer Engineering and Real-Time Systems. He serves as Faculty Representative for Research and Infrastructure, overseeing strategic initiatives in informatics research and infrastructure development. His academic role also includes leading the Service Unit Infrastructure (E199-02) and heading the Cyber-Physical Systems department (E191-01). Education and Roles Puschner holds a Diplom-Ingenieur (Dipl.-Ing.) and a Dr.techn. from TU Wien, alongside the title Ao.Univ.Prof. His roles include teaching and supervising students in advanced topics such as Operating Systems, Real-Time Systems, and Scientific Research methodologies. He has been actively involved in curriculum design for Computer Science and Business Informatics programs. Research Interests His research focuses on: Timing Analysis: WCET analysis for real-time systems, especially in multi-core and mixed-criticality environments. Embedded Systems: Designing time-predictable architectures for safety-critical applications. Communication Networks: Time-triggered protocols for automotive and industrial systems. Publications and Tools Puschner has authored over 160 publications, including seminal work on the Platin WCET analysis tool and the T-CREST multi-core architecture. His recent work emphasizes compiler-driven timing predictability and dual-path code paradigms. Grants and Awards Recipient of the Marie-Curie Fellowship (2003) and a founding member of the IFIP 10.2 WG on Embedded Systems. His projects have been funded by the EU (e.g., T-CREST, Multicores Partitioning), FWF, and industry collaborations. Students and Supervision He has supervised numerous PhD and Master’s students, including Elias Maroun (2024), Matthias Platzer (2022), and Bledar Cilku (2018). Key topics include WCET analysis, memory hierarchy design, and secure communication protocols. Labs and Teams Puschner leads the Real-Time Systems Lab, collaborating with industry partners (e.g., automotive, aerospace) to develop safety-critical embedded systems. His team contributes to open-source tools like Platin and the Patmos processor.

• Gene therapy
• Cell therapy
• Hematopoietic stem cells
• +۶ مورد دیگر

Luigi Naldini is a renowned Italian scientist and academic at San Raffaele Vita-Salute University , serving as Director of the San Raffaele Telethon Institute for Gene Therapy (SR-Tiget) since 2008. Over a 25-year career, he has revolutionized gene therapy through lentiviral vector development, impacting genetic disease treatment, cancer immunotherapy, and stem cell research.

• Bioprocess Engineering
• Molecular Biotechnology
• Cell Biology
• +۹ مورد دیگر

Georg Smesnik is a Researcher at the Institute of Bioprocess Science and Engineering , part of the Department of Biotechnology and Food Science at the University of Natural Resources and Life Sciences, Vienna (BOKU) . He works at the location Muthgasse 18, 1190 Wien, Austria, and his research focuses on bioprocess optimization for gene therapy vectors using mammalian cell systems. Research Interests His work intersects: Bioprocess Engineering Molecular Biotechnology Cell Biology Genetics and Epigenetics Gene Therapy Production Pharmaceutical Biotechnology Publication Trends Georg's 2023 publications analyze the cellular behavior of HEK293 cells under evolutionary pressures, focusing on genetic and epigenetic limitations for vector production in gene therapy applications. His research contributes to understanding how cellular engineering can enhance bioproduction efficiency.

Tirado Franciscoمشاهده پروفایل

استاد

• Power Aware Computing
• Heterogeneous Computing
• Applications optimization
• +۴ مورد دیگر

Francisco Tirado is a Full Professor of Computer Architecture at Complutense University of Madrid since 1986. He has held leadership roles including Vice-Chancellor for Research (2012-2015), Dean of the Faculty of Physics (1994-2002), and Director of the Complutense Supercomputing Center (2002-2007). He is a founding member of the Spanish Society for Computer Science (SCIE) and Spanish Society for Computer Architecture (SARTECO). His research focuses on power-aware computing, heterogeneous systems, bioinformatics, and hardware design automation. He has authored over 242 publications and supervised 15 PhD theses. His professional service includes chairing 138 international conferences and serving on numerous committees for EUROMICRO, IEEE, and national research agencies. Education: No explicit details provided, but has been active at Complutense University since 1978. Affiliations: Member of COSCE Executive Board (2012), IEEE Senior Member (2005), and EUROMICRO Board (1991-2004). Research Interests: - Optimizing energy efficiency in high-performance computing systems - Design of heterogeneous architectures and accelerators - Bioinformatics applications through hardware/software co-design - Parallel programming models for emerging architectures - Automation tools for FPGA and embedded systems development Conference Contributions: Played multiple roles (General Chair, Program Chair) for major events like ParCo, HPCA, and EUROMICRO PDP conferences. Delivered 64 keynote/plenary lectures globally. Scientific Awards: Doctor 'Honoris Causa' from universities in Spain, Paraguay, and Peru 2013 National Computer Science Award IEEE Senior Membership Advising: Supervised 15 PhD students. Active in technology transfer contracts with industry. Labs/Teams: Founder and leader of the ArTeCS research group at Complutense University, specializing in computer architecture and high-performance computing innovations.

Philipp Grohsمشاهده پروفایل

استاد

• Mathematical Data Science
• Deep Learning Algorithms
• High-Dimensional Partial Differential Equations
• +۷ مورد دیگر

Prof. Dr. Philipp Grohs is a full professor of Mathematical Data Science at the University of Vienna and head of the Mathematical Data Science group at RICAM (Austrian Academy of Sciences). He holds a MSc from TU Vienna (2006) and a PhD from the same institution (2007). After postdoc positions at TU Graz, KAUST, and ETH Zurich, he became an assistant professor at ETH Zurich in 2011 before moving to the University of Vienna in 2016. His research focuses on designing efficient algorithms for signal processing, computational sciences, and finance, with recent contributions to understanding deep learning algorithms and solving high-dimensional PDEs using machine learning. He has received the ETH Latsis Prize (2014) and was selected for an Alexander von Humboldt Professorship (2019). Research Interests: Mathematical foundations of deep learning High-dimensional PDEs and their numerical solutions Signal and image processing (phase retrieval, Gabor systems) Approximation theory and function spaces Computational finance and mathematical modeling Recent Research Trends: His work explores theoretical guarantees for neural network performance, particularly in overcoming dimensionality challenges. Notable contributions include phase retrieval algorithms, analysis of DNN expressivity, and applications of deep learning in quantum chemistry and epidemiology modeling. Awards: ETH Latsis Prize (2014) Alexander von Humboldt Professorship (2019) Advising & Projects: Leads research initiatives such as the 'Data Science' hub at Vienna, and has coordinated projects on hybrid computational sciences and explainable AI models. Active in supervising interdisciplinary research teams across mathematics and computer science. Labs/Teams: Directs the Mathematical Data Science group at RICAM and oversees computational research collaborations with institutions like KAUST and ETH Zurich. Engages in applied projects like group testing strategies for SARS-CoV-2 and neural network-based electronic structure calculations.