جست‌وجوی استاد و پژوهشگر

Michael Razenمشاهده پروفایل

استاد

• Behavioral Finance
• Market Efficiency
• Financial Literacy
• +۳ مورد دیگر

Michael Razen is a Professor and Department Head at MCI | Die Unternehmerische Hochschule® as well as an affiliated researcher at the Department of Banking and Finance at Universität Innsbruck. He holds a PhD in Economics from Universität Innsbruck (2017) and became a Privatdozent in 2023. His research focuses on Behavioral Finance, Market Efficiency, and Financial Literacy, employing experimental and econometric methods. He leads the 'Innsbruck Decision Sciences' research group and co-founded the FiT financial literacy program for youth. Razen has been recognized with awards including the Bates-White Prize and CFA Society Austria Prize. He teaches courses like Data Science and Decision-Making at MCI while maintaining active academic collaborations across institutions globally. His research team includes Sebastian Bachler, Sabine Ferdik, and others. Recent work explores domain-specific financial decision-making, computational reproducibility in finance, and family firm CSR dynamics. Over 20 peer-reviewed publications span journals like Science, Strategic Entrepreneurship Journal, and European Economic Review. He advises both academic and industry stakeholders, sits on the board of the Austrian Financial Literacy Foundation, and frequently presents at international finance conferences. Education: BSc in Economics, Universität Innsbruck (2011) MSc in Finance and Economics, London School of Economics (2012) PhD in Economics, Universität Innsbruck (2017) Privatdozent (Habilitation), Universität Innsbruck (2023) Grants & Awards: 2022: Bates-White Prize for Best Paper (Society for Financial Econometrics) 2018: CFA Society Austria Prize Multiple research stipends from Universität Innsbruck (2013–2015) Teaching Roles: Lead courses in Data Science, Decision Theory, and Financial Literacy Advises master's theses and entrepreneurship labs at MCI Labs/Teams: Core member of Innsbruck Decision Sciences, founder of FiT program, and collaborator in international financial research networks. Current projects include AI ethics in business decisions and stakeholder analysis for corporate sustainability.

• Agent-based Modeling
• Epidemiology
• Computational Statistics
• +۳ مورد دیگر

Nikolas Popper is a Senior Scientist in the Research Area of Computational Statistics at TU Wien. His work focuses on agent-based modeling, epidemiological simulations, and computational methods for decision support systems. He has contributed to pandemic response strategies through predictive modeling and multi-model frameworks. Popper has co-supervised numerous theses on topics including agent-based influenza models, maintenance analysis in aviation networks, and obesity prevalence modeling in Austria. His research integrates diverse methodologies like Bayesian networks, Monte Carlo simulations, and co-simulation techniques to address complex systems challenges. Notable contributions include a multi-model warning system for public health policies and vaccination strategy optimization frameworks. Popper's work emphasizes interdisciplinary approaches to healthcare, transportation systems, and environmental impact analysis. Key Projects: Multi-criteria decision support for pandemic management, train delay analysis using Bayesian networks Grants and Funding: Not explicitly listed in provided texts Labs/Teams: Part of the Network Lab and collaborative initiatives involving computational statistics and epidemiology.

Thorsten Rheinländerمشاهده پروفایل

استاد

• Stochastic Finance
• Actuarial Mathematics
• Derivative Pricing
• +۳ مورد دیگر

Thorsten Rheinländer is a Full Professor at the Department of Financial & Actuarial Mathematics at Vienna University of Technology. His research focuses on stochastic finance, actuarial mathematics, and the application of advanced mathematical techniques to financial markets and risk management. Research Interests: Stochastic finance and insurance hedging Valuation and hedging of derivatives Liquidity risk and market microstructure Neural networks in financial modeling Self-duality in stochastic processes His recent work includes applications of machine learning to financial data classification and the analysis of Hawkes processes in market dynamics. Notable contributions include studies on barrier options, large trader impact, and longevity bonds. Current projects explore Brownian trading excursions and stochastic heat equations with multiplicative noise. Publications: Over 20 peer-reviewed articles in top journals like Finance and Stochastics , Mathematical Finance , and Stochastic Processes and their Applications . Key themes include computational methods for derivatives pricing, risk-minimization techniques, and the development of consistent factor models. Books: Authored/co-authored Hedging Derivatives (World Scientific, 2011) and contributed to the Encyclopedia for Quantitative Finance (Wiley, 2010).

• Cyber-Physical Systems
• Runtime Monitoring
• Software Engineering
• +۳ مورد دیگر

Dr. Michael Vierhauser is an Assistant Professor in the Department of Computer Science at the University of Innsbruck. His research focuses on Cyber-Physical Systems (CPS), runtime monitoring, autonomous systems, and software engineering methodologies. He specializes in safety-critical systems, human-machine interaction, and innovative educational technologies for programming and software development. Key research areas include: Runtime monitoring frameworks for CPS and UAVs Development of adaptive systems and self-protective IoT devices Integration of AI into software engineering education Agile methodologies for sustainability assessment His recent publications emphasize field-testing of drone missions, automated simulation testing for aerial systems, and frameworks like FORTE for scalable environmental monitoring. He leads projects like Dronology, an incubator for CPS research, and contributed to tools such as ReMinds and GRuM for runtime monitoring. Dr. Vierhauser collaborates on digital transformation initiatives in underground construction and has designed learning analytics dashboards to improve programming education outcomes. His work bridges theory and practice through real-world applications in emergency response systems and industrial 4.0 contexts.

• Aeroacoustics
• Computational Fluid Dynamics
• Acoustic Resonance
• +۳ مورد دیگر

Stefan Schoder is an Associate Professor at the Institute of Fundamentals and Theory in Electrical Engineering, Graz University of Technology. His research focuses on aeroacoustics, fluid dynamics, acoustic resonance, and noise control, with applications in aerospace, automotive, and biomedical engineering. He employs advanced computational methods like Finite Element Analysis and the Discontinuous Galerkin method to model complex fluid-acoustic interactions. Schoder's work spans experimental and theoretical investigations of sound generation, turbulence, and vibroacoustic phenomena. Key projects include optimizing low-pressure axial fans, analyzing wind noise in medical devices, and developing digital twins for prosthetics. His publications emphasize predictive modeling of acoustics in industrial and environmental contexts. He has received multiple scientific awards, including the Weihnachtspreisaufgabe (Christmas Prize Competition) in 2015, 2016, 2018, and 2020. Schoder collaborates internationally, contributing to projects like bioCOMP4acoustics (recyclable sound-absorbing composites) and ECHODA (energy-efficient cooling).

• Signal Processing
• Audio Technology
• Speech Processing
• +۵ مورد دیگر

Martin Hagmueller is a researcher at the Institute of Signal Processing and Speech Communication at Graz University of Technology. His work focuses on signal processing, audio technology, and biomedical applications such as vocal fatigue monitoring and speech data analysis. He has contributed to projects involving acoustic sensing, speech corpora management, and bionics. Key research areas include: Acoustic feature extraction for voice analysis Development of speech corpora version control systems Real-time intrusion detection via distributed acoustic sensing Hagmueller has received prestigious awards including the ATC Maastricht Innovation Award (2004) and the 2020 Final Pitch competition recognition. He actively engages in public outreach through events like the Graz Electrical Engineering Days (GEED) exhibitions. Current projects involve acoustic fiber sensing for gas pipelines, high-efficiency refrigeration systems, and clinical applications for dysphonic speakers. He collaborates internationally, evidenced by his involvement in Antarctic research expeditions and interdisciplinary teams.

Thomas Fahringerمشاهده پروفایل

استاد

• Parallel Computing
• Distributed Systems
• High-Performance Computing (HPC)
• +۴ مورد دیگر

Thomas Fahringer is a full Professor and Head of the Distributed and Parallel Systems Group at the University of Innsbruck's Institute of Computer Science. His research focuses on parallel computing, distributed systems, and high-performance computing (HPC), with particular emphasis on GPU acceleration, cloud/edge computing, and serverless architectures. He leads interdisciplinary projects involving scientific workflows, resource management systems, and exascale computing solutions. Key research areas include: Design of high-level APIs for accelerator clusters (e.g., Celerity-RSim) Optimization of IoT and LoRa networks using machine learning Scalable key-value stores for geo-distributed systems Workflow scheduling in edge-cloud continuum environments Recent work emphasizes automation of deployments, energy-efficient transmission policies, and fault-tolerant orchestration of serverless functions. He actively participates in community initiatives like the Workflows Community Summit, driving advancements in scientific workflows and HPC ecosystems. His lab develops frameworks such as Apollo and AllScale, targeting exascale computing and distributed runtime systems.

• Human-Centered Computing
• Digital Thinking Pedagogy
• Crowdsourcing Mechanics
• +۴ مورد دیگر

Lisa Posch, a Research Fellow at the Institute of Human-Centred Computing at Graz University of Technology, focuses on digital thinking pedagogy, crowdsourcing mechanics, and social media analytics. Her work bridges computational methods with sociotechnical systems. Education: Dipl.-Ing. (Master of Science), Dr.techn. (Doctorate in Technical Sciences), BSc Her research spans Human-Centered Computing , Natural Language Processing , and Digital Humanities , with publications on crowdworker motivation, social media monitoring, and metadata modeling. She has contributed to advancements in probabilistic ontology mapping and multilingual topic modeling. Her recent publications (2013-2023) demonstrate expertise in social media analytics , digital labor dynamics , and semantic data systems . She actively engages in educational initiatives through the Teaching Digital Thinking Project (TDT).

• Sound Generation
• Knee Prosthesis
• Simulation Model
• +۴ مورد دیگر

Andreas Wurzinger is a researcher at the Institute of Fundamentals and Theory in Electrical Engineering at Graz University of Technology. His work spans acoustics, biomedical engineering, and computational methods. PhD Student, Graz University of Technology (current) Research focuses on sound generation , knee prosthesis acoustics , and physics-informed neural networks . He develops digital twins for noise analysis in mechanical and medical systems, including refrigerant compressors and hydraulic prostheses. Recent publications highlight applications of computational aeroacoustics , flow-induced sound modeling , and data-driven frameworks like pyCFS-data. Collaborations span automotive and medical device industries . He actively participates in conferences like NOVEM 2025, Forum Acusticum 2025, and DAS/DAGA 2025, presenting on vibro-acoustic emissions and digital twin applications .

Dan Alistarhمشاهده پروفایل

استاد

• Machine Learning
• Distributed Computing
• Optimization
• +۴ مورد دیگر

Dan Alistarh is a Professor at the Institute of Science and Technology Austria (IST Austria) and leads the Deep Algorithms and Systems Lab (DASLab). His research focuses on efficient algorithms and systems for machine learning, including distributed optimization, sparse and quantized neural networks, and scalable training/inference techniques. He holds a PhD from École Polytechnique Fédérale de Lausanne (EPFL) and has held positions at MIT, Microsoft Research, and ETH Zurich. Research interests: Optimization for data analysis, parallel and distributed optimization, efficient machine learning algorithms, and distributed systems. Collaborations include work on optimization under uncertainty with Immanuel Bomze, Radu Bot, and others. Publications span top venues like NeurIPS, ICML, and DISC, with notable contributions in model compression (e.g., GPTQ, SparseGPT), communication-efficient distributed training, and concurrency algorithms. Awards include ERC grants and best paper awards. He advises a team of PhD students and postdocs, and his lab's tools are widely used (e.g., GitHub repositories). His work has been adopted in industry (e.g., OpenAI, Neural Magic).

Andreas Läuchliمشاهده پروفایل

استاد

• Quantum Science
• Condensed Matter Physics
• Atomic, Molecular, and Optical (AMO) Physics
• +۳ مورد دیگر

Andreas Läuchli is a Professor at the University of Innsbruck and a member of the Erwin Schrödinger Center for Quantum Science & Technology (ESQ). He currently heads the Institute of Theoretical Physics at the University of Innsbruck. His research focuses on the theoretical and computational exploration of correlated quantum matter in condensed matter and AMO systems. Key interests include novel phases of matter, quantum critical phenomena, and non-equilibrium quantum systems, leveraging concepts from condensed matter theory, statistical mechanics, quantum field theory, and quantum information science. He develops innovative computational algorithms for large-scale simulations on high-performance computers. Research Areas: Quantum Phase Transitions Quantum Criticality Many-Body Localization Tensor Network Methods Quantum Simulation Techniques Notable Contributions: His work bridges foundational quantum theory with advanced computational methods, advancing understanding of complex quantum systems. Currently leads a research group at the University of Innsbruck, contributing to Austria's quantum science initiatives through ESQ collaborations.

• Stellar Astrophysics
• Galactic Astrophysics
• Quantitative Spectroscopy
• +۷ مورد دیگر

Norbert Przybilla is a Full Professor in the Institute for Astro- and Particle Physics at the University of Innsbruck, Austria, where he leads the Galactic Astrophysics research group. He holds a permanent faculty position and is actively engaged in research, teaching, and instrument development for next-generation telescopes. His primary research interests include stellar astrophysics , with a focus on quantitative spectroscopy of massive stars , chemical abundances , non-LTE atmospheric modeling , stellar evolution , and the diffuse interstellar medium . He applies high-resolution spectroscopic data to understand the life cycles of massive stars and their role in galactic chemical evolution. Przybilla’s recent publications reveal a strong focus on OB-type and supergiant stars , Be stars , and diffuse interstellar bands (DIBs) . His work often involves non-LTE spectral analysis , abundance determination , and the use of advanced instrumentation like MUSE , CRIRES , and future ELT instruments such as MICADO and METIS . He is also involved in major observational surveys such as the EDIBLES and Gaia-ESO projects. Presentations: He regularly delivers invited talks at international conferences on topics such as stellar abundances, blue supergiants, and instrumentation for the ELT. Instrumentation: He is a key contributor to the development of spectroscopic pipelines for MICADO and METIS, indicating deep involvement in future observational capabilities. Public Outreach: He actively participates in public lectures and events such as the 'Lange Nacht der Forschung' and 'Astronacht' at the University of Innsbruck, discussing exoplanets and astronomical observations. He mentors several early-career researchers and PhD students, including David Weßmayer, Patrick Aschenbrenner, and Alexander Ebenbichler, who frequently appear as co-authors on his publications. His collaborative network is extensive, involving institutions across Europe and beyond.

Markus Oppelمشاهده پروفایل

پژوهشگر

• Theoretical Chemistry
• Quantum Chemistry
• Computational Chemistry
• +۵ مورد دیگر

Markus Oppel is a researcher in the Department of Theoretical Chemistry at the Faculty of Chemistry, University of Vienna. With a PhD in Theoretical Chemistry completed in 1998 and a Diploma in Chemistry from Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) completed in 1995, he has established himself as an active contributor to computational and theoretical chemistry with 46 publications spanning nearly three decades. Education: Theoretical Chemistry, PhD (January 1996 - April 1998) Chemistry, Diploma, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) (1990 - 1995) Dr. Oppel's research focuses on quantum dynamics, excited state calculations, and computational method development. His fingerprint analysis reveals significant contributions to Laser Pulse Physics (100%), Infrared Laser Physics (75%), Excited State Chemistry (61%), and Electronic State Chemistry (48%). He has made substantial contributions to major computational chemistry software packages including COLUMBUS for ground and excited state computations and SHARC for non-adiabatic dynamics simulations. His recent work shows a strategic evolution toward quantum computing applications in chemistry, particularly in drug design, where his 2024 Nature Physics paper has garnered significant attention with 160 reader captures and 8 news mentions. This represents a bridge between traditional quantum chemistry methods and emerging computational paradigms. Dr. Oppel maintains an active presence in the scientific community with 25 recorded activities, including recent invited talks such as "Artifizielle Photosynthese" (May 14, 2025) and "Heterogeneous Computing in Quantum Chemistry" (November 18, 2024), demonstrating his recognition as an expert in computational chemistry and quantum dynamics.

Ya Chenمشاهده پروفایل

پژوهشگر

• Virtual Screening
• Drug Discovery
• Cheminformatics
• +۳ مورد دیگر

Ya Chen is affiliated with the Department of Pharmaceutical Sciences at the Faculty of Life Sciences. Their research focuses on computational approaches in drug discovery, including virtual screening, metabolic pathway analysis, and machine learning applications. Key areas include natural product-based drug design, receptor modulation, and enzyme inhibition mechanisms. Notable contributions involve developing predictive models for drug metabolism and exploring chemical spaces for therapeutic targets like the glucocorticoid receptor. Ya Chen has presented work at international conferences and contributed to interdisciplinary projects combining cheminformatics and biological systems. Research interests emphasize the intersection of artificial intelligence with pharmaceutical sciences, particularly in optimizing drug design workflows and understanding metabolic processes. Their work spans enzyme inhibition studies (e.g., CYP19A1, InsP3Kinase), nuclear receptor ligand discovery (RORγ, LXR), and the development of open-source tools for cheminformatics (e.g., Scikit-Mol). Collaborative efforts involve international teams and focus on advancing methodologies for natural product screening, site-of-metabolism prediction, and chemical library design. Ya Chen’s activities highlight a commitment to bridging computational techniques with experimental pharmacology to address challenges in drug development and toxicology.

• Neuroscience
• Sensorimotor Integration
• Behavioral Neuroscience
• +۳ مورد دیگر

Charles Fieseler is a Research Fellow at the Department of Neuroscience and Developmental Biology, Faculty of Life Sciences at the University of Vienna. He holds MSc and PhD degrees and has been affiliated with the institution since at least 2020. His primary research focuses on understanding neural control mechanisms in Caenorhabditis elegans, with a particular emphasis on sensorimotor integration, neuronal signaling pathways, and the application of advanced imaging and machine learning techniques to study neural activity. He has contributed to groundbreaking work on tyraminergic corollary discharge mechanisms and unsupervised learning of control signals in C. elegans. His research integrates experimental neuroscience with computational methods, including calcium imaging and dynamic mode decomposition. Fieseler is currently supported by the Vienna International Postdoctoral Program VIP2 Fellowship (2021–2024), which funds his project on neuro-sensory integration mechanisms. His publications span topics such as neuronal manifold organization, dopaminergic system modeling, and acoustic signal analysis in materials science. Notable contributions include pioneering work on C. elegans behavior control structures and the first observation of parity-odd asymmetries in neutron capture experiments (2018).