جست‌وجوی استاد و پژوهشگر

Roman Kernمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Data Science
• +۷ مورد دیگر

Assoc. Prof. Roman Kern is affiliated with the Institute of Machine Learning and Neural Computation at Graz University of Technology and serves as Chief Scientific Officer at Know-Center Research GmbH , a competence center for Big Data analytics. His research bridges natural language processing, data science, and machine learning with a focus on causal inference and discovery, applied to scientific publication mining, intelligent transportation systems, and smart production. Research Interests : Causal inference, NLP, data science, trustworthy AI, knowledge discovery, and interdisciplinary applications. Projects : VanillaFlow (sustainable electrolytes for batteries), REWAI (causal discovery in textile manufacturing), and EPN-2024-RI (planetary science infrastructure). Teaching : Courses include Knowledge Discovery, Natural Language Processing, and Introduction to Scientific Working at TU Graz. His recent publications analyze causal relationships in semiconductor manufacturing, differential privacy, and LLM applications in healthcare and environmental monitoring. Roman Kern actively mentors students through thesis topics on causality, LLMs, and data privacy frameworks, while leading applied research projects with industry partners.

Emanuel Gasteigerمشاهده پروفایل

دانشیار

• Macroeconomics
• Behavioral Macroeconomics
• Monetary Policy
• +۴ مورد دیگر

Emanuel Gasteiger is an Associate Professor in Economics at the Institute of Statistics and Mathematical Methods in Economics at Technische Universität Wien . He is affiliated with the Economics Research Group at BRU-IUL (Lisbon), the Centre for Dynamic Macroeconomic Analysis (CDMA, University of St Andrews), and is an alumnus of the Berlin Economics Research Associates (BERA) Program. His research focuses on macroeconomic policy design, heterogeneous expectations, and their implications for inflation dynamics, fiscal multipliers, and automation impacts. He has organized numerous workshops, including the Behavioral Macroeconomics Workshop series, and has been funded through projects like the OeNB Anniversary Fund and EU initiatives. Key contributions include work on Ricardian/non-Ricardian belief equilibria, Euro Area fiscal multipliers, and time-varying price-setting behavior. He received the Best Paper Award 2020 from TU Wien's Faculty of Mathematics and Geoinformation for research on automation-induced stagnation and robot tax policies. His teaching responsibilities include courses at TU Wien's School of Business and Economics. Recent grants include funding for projects analyzing optimal tax-transfer policies and inflation targeting frameworks under bounded rationality. He collaborates extensively with institutions like Narodowy Bank Polski and the University of California, Irvine, and has advised doctoral students in macroeconomic policy research.

• Molecular Biotechnology
• Recombinant Protein Expression
• Baculovirus Expression Systems
• +۷ مورد دیگر

Dipl.-Ing. Dr. Wolfgang Ernst is a researcher at the Institute of Molecular Biotechnology, part of the Department of Biotechnology and Food Sciences at the University of Natural Resources and Life Sciences, Vienna (BOKU). His research focuses on molecular biotechnology, particularly in the areas of baculovirus expression systems, recombinant protein production, and gene delivery in mammalian and insect cells. His research interests span recombinant protein expression , CHO cell biotechnology , transcriptome analysis , virus-like particles , and genetic engineering of viral vectors . He has extensively studied the use of baculoviruses for gene delivery and surface display, optimizing their transduction efficiency in mammalian cells through genetic modifications of the gp64 envelope protein. His work also includes comparative studies of protein secretion in CHO cells and Pichia pastoris, transcriptomic analyses of high- and low-producing cell lines, and the development of novel vaccine platforms using virus-like particles. The 15 most recent publications reflect a consistent focus on molecular and cellular biotechnology, with recurring themes in gene expression optimization , cell line development , and viral vector engineering . The research combines systems biology approaches like transcriptomics with practical bioprocessing challenges, aiming to improve yields and efficiency in recombinant protein production. Dr. Ernst led the research project Baculoviren als Transportvehikel für tierische Zellen (2000–2002), demonstrating his leadership in the field. He has collaborated with key figures in biotechnology, including Rudolf Grabherr and Diethard Mattanovich. Although no formal awards are listed, his sustained publication record and project leadership indicate significant scientific contributions. He has contributed to numerous international conferences, presenting on topics ranging from cell line development using FACS to redox regulation in recombinant CHO cells. His work supports both academic knowledge advancement and industrial bioprocess applications, particularly in vaccine and therapeutic protein production.

• Ontology
• Automotive Industry
• Data Mining Techniques
• +۶ مورد دیگر

Christina Feilmayr is a Professor at the University of Applied Sciences Steyr, affiliated with the Research Center Steyr. Her work focuses on digital transformation and support for clinical core processes. Research Interests: She specializes in ontology engineering, data mining applications in automotive quality management, and accessible visual data representation through scalable vector graphics. Her research intersects computer science with industrial optimization and accessibility standards. Publication Trends: Her academic output spans Ontology frameworks for business applications (2016) Automotive process optimization using data mining (2014) Accessible SVG standards for tactile displays (2010) .

• Real-Time Systems
• Worst-Case Execution Time (WCET) Analysis
• Single-Path Code Optimization
• +۳ مورد دیگر

Peter Puschner is an Associate Professor at Vienna University of Technology (TU Wien), affiliated with the Cyber-Physical Systems Research Area. His work focuses on real-time systems, worst-case execution time (WCET) analysis, and time-predictable code execution. Key research areas: Real-Time Systems, Single-Path Code, Time-Triggered Networks, Cache Architectures Advisor to multiple thesis students including Michael Platzer and Bekim Cilku Co-developer of tools like the platin Toolkit for WCET analysis Recipient of Best Paper Award at ECRTS 2015 for Requirement Semi-formalization Methodology for SoC Design

Jürgen Zanghelliniمشاهده پروفایل

استاد

• Metabolic Engineering
• Bioprocess Optimization
• Proteomics
• +۳ مورد دیگر

Jürgen Zanghellini is a Professor at the Faculty of Chemistry, Institute of Analytical Chemistry. His work spans metabolic engineering, bioprocess optimization, and proteomics, with a focus on industrial microorganisms like Escherichia coli and Komagataella phaffii. Key Projects : Circular Bioengineering (2024-2029) Prokaryote Proteomics at High Temperatures (2024-2027) Morphometabolic Fingerprint of Ovarian Cancer (2022-2026) Research Themes : Metabolic modeling, crosslinking mass spectrometry, and data-driven bioprocess control dominate his recent work. He integrates multi-omics approaches to enhance viral vector yields and optimize fed-batch fermentation processes. Collaborations : He works extensively with researchers like Köllensperger, Gerner, and Mattanovich, and is involved in organizing scientific events such as 'The Metabolic Guide to Space Survival' (2025).

Peter Kritzerمشاهده پروفایل

پژوهشگر

• High-dimensional algorithms
• Information-based complexity
• Quasi-Monte Carlo methods
• +۳ مورد دیگر

Peter Kritzer is a Senior Scientist and Scientific Coordinator at the Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences in Linz, Austria. He holds a Master's degree (2003) and a Doctoral degree (2005, 'Sub Auspiciis Praesidentis') from the University of Salzburg, followed by a Habilitation in Mathematics (2012) from Johannes Kepler University Linz. His research focuses on high-dimensional algorithms, quasi-Monte Carlo methods, discrepancy theory, and information-based complexity. Affiliations: RICAM, Austrian Academy of Sciences (since 2015); previously at University of Salzburg, UNSW Australia, and Johannes Kepler University Linz. His work emphasizes numerical integration, tractability analysis, and algorithm design for high-dimensional problems. Notable contributions include advancements in lattice rules, digital nets, and hybrid function spaces. He has received awards such as the Information-Based Complexity Young Researcher Award (2011) and the Kardinal Innitzer Förderungspreis (2013). His recent articles explore topics like reduced digital nets, QMC matrix-vector products, and tractability in Hilbert spaces. He actively contributes to Monte Carlo and quasi-Monte Carlo research communities, editing volumes like Monte Carlo and Quasi-Monte Carlo Methods 2022 .

Martin Schälerمشاهده پروفایل

دانشیار

• Database Systems
• Scientific Data Management
• Hardware-sensitive Database Tuning
• +۵ مورد دیگر

Associate Professor Martin Schäler is part of the Database Research Group at the Department of Computer Science, University of Salzburg. His research focuses on Scientific Data Management, Hardware-sensitive Database Tuning, Time Series Analytics, and Data Provenance. He holds a Dr.-Ing. (PhD) from Otto-von-Guericke University Magdeburg (2014), where he also completed his Master's degree in 2010. Prior to his current position, he was a post-doctoral researcher at the Karlsruhe Institute of Technology's DBIS group (2015-2020). His work emphasizes optimizing database systems through hardware-aware techniques and efficient query processing. Notable contributions include studies on main-memory storage structures, semantic change analysis in text data, and encryption methods preserving distance metrics. He has published in top venues such as IEEE TKDE, VLDB, and ICDE. His academic trajectory includes roles as a research assistant, scientific coordinator, and postdoc researcher before securing his tenure-track position at Salzburg University in 2020. Current research trends show a focus on bridging theoretical database advancements with real-world hardware constraints.

Stefan Ohrhallingerمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Geometry Processing
• Surface Reconstruction
• +۳ مورد دیگر

Stefan Ohrhallinger is a Senior Researcher at TU Wien's Institute of Visual Computing and Human-Centered Technology. He holds a PhD from Concordia University (2013) and a Master's in Business Informatics from Johannes Kepler University Linz (1997). His research focuses on surface reconstruction, point-based graphics, and geometry processing with applications in computer graphics and virtual/augmented reality. Education: PhD in Computer Science, Concordia University (2013) Master of Business Informatics, Johannes Kepler University Linz (1997) Affiliations: Principal Investigator for grants totaling €1.7M+ (e.g., WWTF Modeling the World at Scale, FWF Superhumans) Teaching: 'Modeling in Computer Graphics' and 'Scientific Writing' courses His work emphasizes robust algorithms for reconstructing curves/surfaces from sparse/noisy data, with contributions to occlusion-aware processing and large-scale point cloud handling. Notable achievements include the Best Poster Award at Eurographics 2012 and over 30 peer-reviewed publications. Grants & Projects: WWTF 'Modeling the World at Scale' (2020–2026, €578k) FWF 'Superhumans: Walking Through Walls' (2019–2023, €333k) IPA 'Photogrammetry made easy' (2020–2022, €50k)

• Databases
• Artificial Intelligence
• Text Mining
• +۲ مورد دیگر

Ingo Feinerer serves as an Associate Professor at Vienna University of Technology's Faculty of Informatics, specifically within the Institute of Information Systems Engineering (E192-02). His research bridges theoretical computer science and practical applications in database systems, artificial intelligence, and text mining, with significant contributions to configuration management and formal methods. His educational background includes: PhD Dissertation (2007): A formal treatment of UML class diagrams as an efficient method for configuration management Diploma Thesis (2005): Formal program verification: a comparison of selected tools and their theoretical foundations Feinerer's research focuses on database theory (particularly schema mapping and dependencies), AI-driven configuration systems using integer linear programming, and text mining infrastructure development in R. His work combines theoretical rigor with practical tool development, notably through the textcat and tm packages. The integration of formal methods in software engineering remains a consistent thread throughout his publications. Analysis of his 15 most recent publications reveals strong specialization in database constraints (40%), text mining applications (30%), and software configuration systems (30%), with increasing interdisciplinary work connecting computer science to digital humanities. His notable recognition includes: INiTS Award (2007) for technology commercialization potential Feinerer has supervised doctoral research including F. I. Chertes' work on schema mapping languages and diploma theses on UML semantics and probabilistic databases. He led major research projects HINT (2012-2017) and SEE (2012-2016) focusing on database technologies and information systems. His work demonstrates consistent funding through Austrian national research programs. As a core member of the Databases and Artificial Intelligence research group, he collaborates extensively on R package development for text analysis and contributes to international workshops on theoretical aspects of software engineering.

• Signal Processing
• Machine Learning
• Bioinformatics
• +۴ مورد دیگر

Asoke Nandi is a Professor at Brunel University London's Electronic and Computer Engineering department since 2013, with prior roles at University of Liverpool (David Jardine Professor, 1999-2010), University of Strathclyde (1995-1998 Reader, 1991-1995 Senior Lecturer), and Imperial College London (1987-1991 Lecturer). He holds Distinguished Visiting Professor roles at Xi’an Jiaotong University (China) and Jyväskylä University (Finland), where he was Finland Distinguished Professor (2010-2014). Ph.D. in Physics, University of Cambridge Over 600 technical publications (280 journal papers, 6 books) Google Scholar: 32,035 citations, h-index 83, i10-index 300 Research Focus: Signal processing and machine learning innovations in: Big and Heterogeneous Data Modulation Classification Fault Diagnosis Blind Source Separation Biomedical Signal Processing Clustering Algorithms Publication Trends: His work spans physics (Z-boson detection, 1983), telecommunications (modulation recognition, 1988-2015), biomedical engineering (fetal ECG extraction, 2001), mechanical systems (fault detection, 2002), and machine learning (FRFCM clustering, 2018). Key methodologies include artificial neural networks, genetic algorithms, and higher-order statistics. Scientific Honors: 10+ Fellowships (Royal Academy of Engineering, IEEE, IET, etc.) Heinrich Hertz Award (IEEE, 2012) Glory of Bengal Award (2010) Mountbatten Premium (IEE, 1998)

Shi Pengمشاهده پروفایل

استاد

• Automation and control systems
• Cyber-physical systems
• Hybrid systems
• +۷ مورد دیگر

Peng Shi is a distinguished academic holding dual professorial positions: Distinguished Professor at Obuda University, Hungary, and Professor leading the Systems and Control Group at the School of Electrical and Electronic Engineering, The University of Adelaide, Australia. His career spans over three decades, with prior roles including Professorships at Victoria University and the University of Glamorgan, and senior research roles at the Defence Science and Technology Organisation (Australia). Education: He earned a BSc in Applied Mathematics (Harbin Institute of Technology, 1982), MSc in Systems Engineering (Harbin Engineering University, 1985), PhD in Electrical Engineering (University of Newcastle, 1994), and second PhD in Mathematics (University of South Australia, 1998). He also holds two higher doctorates: Doctor of Science (University of Glamorgan, 2006) and Doctor of Engineering (University of Adelaide, 2015). Research focuses on systems and control theory, with applications to autonomous systems, robotics, cyber-physical systems, and network security. Key areas include multi-agent systems, hybrid systems, and fuzzy logic. He directs labs in Advanced Unmanned Systems and Cyber-Physics-Human Systems at the University of Adelaide. Notable awards include the 2024 Nobert Wiener Award, 2023 Meritorious Service Award (IEEE SMC Society), and consecutive Highly Cited Researcher recognition (2014–2020). He serves as Editor-in-Chief of IEEE Transactions on Cybernetics and holds fellowships from IEEE, IET, and Engineers Australia. Over 100 invited talks and editorial leadership across top journals like Automatica and IEEE Transactions underscore his global influence. Labs/Teams: Leads the Laboratory of Advanced Unmanned Systems and Laboratory of Cyber-Physics-Human Systems at the University of Adelaide. Active in IEEE SMC Society governance, serving as Vice President and Distinguished Lecturer.

Joseph Vandewalleمشاهده پروفایل

استاد

• Mathematical System Theory
• Signal Processing
• Neural Networks
• +۵ مورد دیگر

Joos Vandewalle is a Full Professor at the Department of Electrical Engineering (ESAT), KU Leuven, Belgium, since 1986. He has held leadership roles including Chairman of the Department of Electrical Engineering (1996-1999, 2003-2005), Vice-Dean of the Faculty of Engineering (1999-2002), and Coordinator of the Center of Excellence on Optimization in Engineering since 2005. His academic career spans over four decades, with prior positions as a Visiting Assistant Professor at UC Berkeley (1978-1979) and Research Associate at KU Leuven (1976-1978). Education : Electrical Engineering degree (1971), Doctorate in Applied Sciences (1976), both from KU Leuven. His research focuses on the intersection of mathematical system theory and its applications in circuit theory, control systems, signal processing, cryptography, and neural networks. Recent work emphasizes nonlinear methods like support vector machines and multilinear algebra for data processing and optimization. He has taught courses in linear algebra , system and circuit theory , and neural networks , influencing large cohorts of students. Vandewalle’s accolades include IEEE Fellows , EURASIP Fellow , and IEE (UK) Fellow distinctions. He received the IEEE Gustav Robert Kirchhoff Award (2022) and honorary doctorate in 2023. His editorial contributions include roles at the IEEE Transactions on Circuits and Systems and advisory boards for journals like Neurocomputing and Neural Networks . He has supervised approximately 30 PhD students, many of whom became successful researchers or managers in fields such as biomedical signal processing, telecommunications, and applied mathematics. Vandewalle has also participated in international research evaluations and panels, including the ERC Advanced Grants (2008) and the German DFG for Centers of Excellence (2006) . Labs/Teams : Head of the SCD division (over 150 researchers) and Coordinator of the Center of Excellence on Optimization in Engineering at KU Leuven.

Franz Pernkopfمشاهده پروفایل

استاد

• Machine Learning
• Probabilistic Graphical Models
• Signal Processing
• +۴ مورد دیگر

Franz Pernkopf is a Professor at the Signal Processing and Speech Communication Laboratory, Graz University of Technology, Austria. He holds a MSc from Graz University of Technology (1999) and a PhD from the University of Leoben (2002). His research focuses on machine learning, probabilistic graphical models, and signal processing applications in speech recognition, medical data analysis, and radar technology. He has led the Christian Doppler Laboratory for Dependable Intelligent Systems and contributed to national research networks in signal processing. His work emphasizes resource-efficient deep learning, Bayesian networks, and time-series analysis. Notable contributions include interference mitigation in radar systems and acoustic event detection. Awards include the Erwin Schrödinger Fellowship (2002) and Young Investigator Award (2010). He advises on projects ranging from lung sound analysis to embedded system optimizations. His lab hosts courses on signal processing and machine learning.

Robert Machمشاهده پروفایل

استاد

• Biotechnology
• Microbiology
• Genetic Regulation
• +۵ مورد دیگر

Prof. Robert Mach is a faculty member at TU Wien's Institut für Verfahrenstechnik, Umwelttechnik und technische Biowissenschaften. His research focuses on microbial biotechnology, genetic regulation in fungi, and applications in bioindustrial processes. He leads studies on Trichoderma reesei for enzyme production and biorefinery strategies, as well as radiation-based pest control methods for tsetse flies. His work integrates molecular biology, bioinformatics, and environmental engineering to address challenges in sustainable bioprocessing and vector-borne disease management. Key areas of research include strain optimization in fungi, detoxification of lignocellulosic hydrolysates, and development of the Sterile Insect Technique using X-ray irradiation. Collaborations span entomology, microbiology, and computational biology, with contributions to genomic tools like FunOrder 2.0 for analyzing fungal biosynthetic pathways. Prof. Mach also investigates symbiotic relationships between insects and microbes, advancing understanding of tsetse fly microbiota and their impact on disease transmission.