جستجوی استاد راهنمای دانشگاهی

Larissa Schlegel-Papeمشاهده پروفایل

پژوهشگر

• Poultry Science
• Animal Welfare
• Stress Assessment in Chickens
• +۴ مورد دیگر

Larissa Schlegel-Pape serves as a Scientific Associate at the Department for Ornamental and Pedigree Poultry within the Farm Animal Clinic of Freie Universität Berlin's Faculty of Veterinary Medicine. Her work focuses on developing innovative methods for assessing chicken welfare through the creation of the "Stressed Chicken Scale," which aims to systematically identify stress indicators in poultry. Her research interests center on animal welfare science, specifically stress assessment in chickens using both behavioral observation and computer vision technology. She investigates how body posture, movement patterns, and other visual indicators can reliably signal discomfort or stress in poultry, with the goal of creating practical assessment tools for veterinarians and poultry farmers. Her work bridges veterinary medicine, ethology, and technological innovation, contributing to refinement research (one of the 3Rs principles) in animal husbandry. Analysis of her publications reveals a strong focus on developing and validating the Stressed Chicken Scale across multiple contexts. Her work spans methodological development, practical implementation studies, and technological integration with computer vision systems. The research demonstrates progression from conceptual framework to validation studies and practical application, with increasing sophistication in assessment techniques and broader implications for animal welfare standards in poultry farming. Schlegel-Pape actively collaborates with the Federal Institute for Risk Assessment (BfR) and participates in interdisciplinary projects involving artificial intelligence applications in agriculture. She presents her findings regularly at major German veterinary conferences including the DVG (Deutsche Veterinärmedizinische Gesellschaft) events, DACh Epidemiology conferences, and specialized poultry medicine gatherings. Her work contributes significantly to advancing animal welfare assessment methodologies and promoting refinement in poultry husbandry practices.

Vincent Fortuinمشاهده پروفایل

استادیار

• Bayesian Deep Learning
• Uncertainty Quantification
• Probabilistic Inference
• +۵ مورد دیگر

Dr. Vincent Fortuin is a tenure-track Assistant Professor at the Technical University of Munich (TUM) and a research group leader at Helmholtz AI in Munich. He leads the Efficient Learning and Probabilistic Inference for Science (ELPIS) group and holds multiple prestigious fellowships including the Branco Weiss Fellowship. His academic affiliations include the TUM School of Computation, Information and Technology, the Konrad Zuse School of Excellence in Reliable AI, and the Munich Center for Machine Learning. Dr. Fortuin earned his BSc in Molecular Life Sciences from the University of Hamburg (2012-2015), followed by an MSc in Computational Biology and Bioinformatics from ETH Zürich (2015-2017), where he received the ETH Excellence Scholarship and the Willi Studer Prize. He completed his PhD in Machine Learning at ETH Zürich (2017-2021) under the supervision of Gunnar Rätsch and Andreas Krause, supported by a Swiss Data Science Center PhD Fellowship. Prior to joining TUM, he was a Research Fellow at St. John's College, University of Cambridge (2022-2023). His research focuses on the intersection of Bayesian statistics and deep learning, specifically developing methods for more robust, data-efficient AI systems with reliable uncertainty estimates. His work addresses critical limitations in standard deep learning approaches, particularly their tendency to be overconfident in predictions and require large datasets for training. He investigates better priors and more efficient inference techniques for Bayesian deep learning, deep generative modeling, meta-learning, and PAC-Bayesian theory, with applications in scientific and biomedical domains. Dr. Fortuin's recent publications demonstrate a consistent focus on improving uncertainty quantification in deep learning systems, with increasing emphasis on practical applications in scientific contexts. His work spans from theoretical foundations of Bayesian deep learning to practical implementations in protein design, materials science, and medical applications. A notable trend is his exploration of how to make Bayesian methods more scalable and applicable to modern large-scale AI systems while maintaining theoretical guarantees. Branco Weiss Fellowship (2023) St John's College Research Fellowship (2022) Swiss National Science Foundation Postdoc.Mobility Fellowship (2022) Swiss Data Science Center PhD Fellowship (2018) ETH Excellence Scholarship (2015) Willi Studer Award (2018) Dr. Fortuin actively supervises PhD and Master's students through his ELPIS research group at Helmholtz AI. He serves as a regular reviewer and area chair for major machine learning conferences and is an action editor for TMLR. He co-organizes the Symposium on Advances in Approximate Bayesian Inference (AABI) and the ICBINB initiative, demonstrating his commitment to advancing the field through community building. His research group receives funding from multiple sources including Helmholtz AI, the Branco Weiss Fellowship, and collaborations with international institutions. Dr. Fortuin leads the Efficient Learning and Probabilistic Inference for Science (ELPIS) group at Helmholtz AI, which focuses on fundamental machine learning research motivated by real-world scientific problems. The group collaborates extensively with researchers across Helmholtz centers and international institutions, particularly in biomedical applications where reliable uncertainty estimates are crucial.

André Fiebigمشاهده پروفایل

پژوهشگر

• Psychoacoustics
• Soundscape Research
• Noise Effects
• +۷ مورد دیگر

Dr. phil. André Fiebig is a Permanent Research Associate and PostDoc at the Institute of Fluid Mechanics and Technical Acoustics (ISTA) within Faculty V - Transportation and Mechanical Systems at Technical University of Berlin. From January 2019 to December 2024, he served as a Visiting Professor responsible for the field of psychoacoustics, funded by the HEAD Genuit Foundation. Since January 2025, he has been leading the 'Psychoacoustics and Noise Effects' working group at the Department of Technical Acoustics. His research spans multiple areas within psychoacoustics and soundscape studies, including fundamentals and modeling of psychoacoustic sensation variables, binaural psychoacoustics, assessment of ambient noise and soundscapes, and psychoacoustic evaluation of sound insulation measures. His work also addresses cognitive stimulus integration of auditory sensations, auditory recreation, acoustic quality of stay, characterization of quiet areas, and measuring sound-induced emotions. Analysis of his recent publications reveals a strong focus on urban soundscapes, noise-conscious behavior in transportation, and the development of methodological frameworks for soundscape assessment. His work often integrates psychoacoustic principles with environmental considerations, particularly examining the relationship between sound environments and human health. Recent research shows increasing emphasis on cross-cultural studies of noise perception and the development of standardized assessment methodologies. Dr. Fiebig is involved in the EARS (Education and Applied Research on Soundscapes) initiative and has contributed to numerous collaborative research projects examining the intersection of urban planning, environmental acoustics, and human perception. His work frequently appears in major acoustics conferences and journals, demonstrating his active role in advancing the field of psychoacoustics and soundscape research. His laboratory work focuses on psychoacoustic testing methodologies, soundscape assessment techniques, and the development of evaluation instruments for noise protection measures. The 'Psychoacoustics and Noise Effects' working group under his leadership conducts research on both theoretical aspects of sound perception and practical applications for urban noise management.

• Power Systems
• Smart Grids
• Energy Infrastructure
• +۱ مورد دیگر

Antonello Monti is a Professor and Director of the Institute for Automation of Complex Power Systems at RWTH Aachen University. His research focuses on modern power systems, including smart grid technologies, hybrid AC-DC grids, and quantum computing applications in energy systems. Recent publications demonstrate innovations in grid resilience, EV charging optimization, quantum-assisted power system planning, and advanced simulation techniques. His team develops open-source tools like JuliaGrid for power system analysis and validates concepts through real-time testing platforms. Research addresses energy transition challenges including renewable integration, grid modernization, cyber-physical security, and next-generation optimization methods combining quantum computing with traditional power engineering approaches.

• Gravitational Wave Data Analysis
• Cosmological Parameter Estimation
• LISA Data Analysis
• +۳ مورد دیگر

Dr. Jonathan Gair is a Group Leader in the Astrophysical and Cosmological Relativity Division at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute) in Potsdam, Germany. Previously, he served as Professor of Astrostatistics at the University of Edinburgh (2018-2019) and as Reader (Associate Professor) in Statistics at the same institution (2015-2018). Dr. Gair's research focuses on gravitational wave data analysis and its applications to cosmology and fundamental physics. His work spans multiple areas of gravitational wave astronomy, with particular emphasis on: Developing and applying new methodologies for gravitational wave data analysis Using gravitational wave observations to derive cosmological parameters, particularly the Hubble constant Developing data analysis tools for the LISA space-based gravitational wave detector Exploring the scientific potential of gravitational wave observations for testing general relativity Creating computationally efficient techniques for parameter inference in gravitational wave astronomy Dr. Gair plays a leading role within the LIGO/Virgo collaboration in deriving cosmological constraints from gravitational wave observations. He currently chairs the LISA Science Group, overseeing the development of data analysis tools for the planned ESA-led LISA mission. His research has significantly contributed to our understanding of how gravitational wave observations can serve as "standard sirens" for measuring cosmic distances and probing the expansion history of the universe. Dr. Gair's work involves both theoretical development and practical application of data analysis techniques. He has developed methods for handling selection effects in rate estimation of gravitational wave events, techniques for mapping gravitational wave backgrounds using methods adapted from cosmic microwave background analysis, and approaches for incorporating model uncertainties into gravitational wave parameter estimation.

• World Englishes
• Corpus Linguistics
• Gender and Language
• +۷ مورد دیگر

Prof. Robert Fuchs holds the Frommann Professorship of Applied English Linguistics at the University of Bonn, leading the Chair of Bonn Applied English Linguistics (BAEL) within the Department of English, American and Celtic Studies. His research focuses on World Englishes, corpus linguistics, sociolinguistics, and the impact of artificial intelligence on linguistic analysis. He actively supervises PhD students in topics aligned with his research group's interests, emphasizing empirical work and data science. Recent research explores language change in varieties like Hong Kong English, Trinidadian prosody, and intensifier usage across cultures. Fuchs frequently presents at international conferences, including ISLE, ICAME, and Sociolinguistics Symposium, and publishes extensively in journals like World Englishes and Language and Speech . His teaching includes advanced courses on corpus linguistics and language in culture, with a focus on climate change discourse analysis. He maintains an active academic presence through ResearchGate, Academia.edu, and LinkedIn. Research Interests: Fuchs investigates sociolinguistic variation, AI applications in linguistics, and the structural features of postcolonial Englishes. His work addresses topics such as vowel mergers in Hong Kong English, lexical stress perception in Indian English, and the role of gender in language use. He also explores diachronic changes in aspects like stative progressives and the perfect-past alternation across Asian Englishes. Advising & Grants: Fuchs oversees PhD student recruitment through research associate positions and self-funded scholarships, prioritizing applicants with strong empirical and analytical skills. His funded projects include studies on pandemic discourse (DisCOVIndUK) and linguistic trends in Caribbean English. His lab, BAEL, collaborates internationally, with ongoing work on Trinidadian prosody and Northeast Indian linguistic ecology. Labs/Teams: The Bonn Applied English Linguistics (BAEL) group, part of the University of Bonn's IAAK institute, focuses on cutting-edge research in global Englishes and computational linguistics, hosting international workshops and fostering interdisciplinary collaboration.

Volker J Schmidمشاهده پروفایل

استاد

• Bayesian Statistics
• Spatial Statistics
• Medical Imaging
• +۷ مورد دیگر

Volker J Schmid is a Professor of Bayesian Imaging and Spatial Statistics at the Department of Statistics, Ludwig Maximilian University of Munich. He leads the Bayesian Imaging and Spatial Statistics group and contributes to interdisciplinary initiatives like the Munich Center of Machine Learning. His work bridges statistical theory with applications in medical imaging and biology. PhD in Statistics (2004), LMU Munich Diploma in Statistics (2000), LMU Munich Abitur, Joseph-von-Fraunhofer-Gymnasium Cham (1993) His research focuses on Bayesian computational methods for high-dimensional data, particularly in medical imaging (MRI, DCE-MRI) and biological microscopy (e.g., 3D nuclear architecture analysis via super-resolution microscopy). Key applications include disease mapping , image segmentation , and spatio-temporal modeling . His software tools (e.g., nucim , bioimagetools , BAMP ) enable quantitative analysis in nuclear imaging and age-period-cohort modeling. His 15 most recent publications span Bayesian modeling for medical imaging , spatio-temporal epidemiology , and computational biology . Topics include co-localization metrics in fluorescence microscopy, nuclear architecture analysis, and dynamic Bayesian frameworks for MRI data. Collaborations extend to neuroimaging, oncology, and nuclear biology.

• Steel Bridge Construction
• Buckling Analysis
• Composite Structures
• +۵ مورد دیگر

Dr. Joseph Ndogmo is a Senior Academic Councillor in civil service for life at the Chair of Metal Construction at the Technical University of Munich (TUM), working under Prof. Martin Mensinger. He has been with the Chair since December 2005, initially as a Research Assistant, then as an Academic Councillor on probationary civil service status from November 2007 to June 2009, and as an Academic Councillor in civil service for life from July 2009 to June 2014, before being promoted to his current position as Senior Academic Councillor in July 2014. Dr. Ndogmo's educational background includes: Primary school in Yaoundé, Cameroon (1972-1978) High school in Batouri and Mbouda, Cameroon (1978-1985) Studies in Mathematics/Computer Science at the University of Yaoundé, Cameroon (1985-1986) Language course at the Herder Institute in Leipzig (1986-1987) Diploma in Engineering (Dipl.-Ing.) from the Friedrich List University of Transport in Dresden, majoring in road construction with specialization in bridge construction (1987-1992) Doctorate (Dr.-Ing.) from Technical University of Munich with thesis on "On the safety and economic reinforcement of bulging web plates of solid-wall girder bridges taking fatigue into account" (awarded November 27, 1997) Training as an international welding engineer at SLV Munich (January-April 2008) Dr. Ndogmo's research focuses on structural engineering with particular expertise in steel and composite bridge construction. His primary research interests include: Overall stability of steel composite bridges Plate and shell buckling phenomena External reinforcement elements for composite bridges Buckling verification according to Eurocode 3 standards Welding technology applications in structural engineering His work bridges theoretical structural mechanics with practical engineering applications, particularly in the context of bridge construction and maintenance. Dr. Ndogmo has made significant contributions to the understanding of buckling behavior in stiffened plates under various loading conditions, with numerous publications addressing both theoretical aspects and practical implementation of Eurocode standards. Dr. Ndogmo's recent publications (2016-2024) demonstrate a consistent focus on buckling analysis of steel structures, particularly in bridge applications. His work shows increasing sophistication in analyzing complex loading scenarios including biaxial stresses and eccentric load introduction. He has made notable contributions to the implementation of Eurocode 3 standards, particularly Part 1-5 on plate buckling. His research combines experimental testing with numerical analysis, providing practical insights for structural engineers. Professional memberships include: VSVI (Association of Road Construction and Traffic Engineers in Bavaria) DVS (The Connection Specialists) Technical Working Group 8.3 (Plate buckling) Working Group EN 1993-1-5 Working Group EN 1993-1-14 CEN / TC 250 / SC 3 / WG22 Dr. Ndogmo is actively involved in teaching at TUM, with courses including Assessment and preservation of historic steel structures, Welding Technology, Composite building and bridge construction, and Plate buckling and steel bridge construction. He also serves as a municipal councilor in Erdweg since 2014 and previously ran as a mayoral candidate in 2017 (finishing second with 32.4% of the vote).

Matthias Steinhauserمشاهده پروفایل

استاد

• Higgs boson production at the LHC
• Rare B meson decays
• Non-relativistic QCD and QED
• +۴ مورد دیگر

Prof. Dr. Matthias Steinhauser is a faculty member at the Karlsruhe Institute of Technology (KIT), affiliated with the Institute for Theoretical Particle Physics (TTP) since October 2004. His research focuses on precision calculations in particle physics, particularly in Higgs boson production, rare B meson decays, non-relativistic QCD, and multi-loop corrections. Research Interests: Higgs boson production at the LHC Rare B meson decays as probes for physics beyond the Standard Model Non-relativistic QCD and QED Massive and massless form factors Automation of multi-loop calculations Prof. Steinhauser’s recent publications (2025–2024) emphasize next-to-leading and next-to-next-to-leading order QCD corrections for Higgs boson production, B meson mixing, and decay rates. His work includes advanced computational techniques and high-order quantum corrections. Contact Information: Room: 11/11 Phone: +49 (0)721 608 - 47149 Email: Matthias.Steinhauser@kit.edu Office hours: Tuesday 13:30–14:30 and by request

Gaël Kermarrecمشاهده پروفایل

پژوهشگر

• Boundary Layer Meteorology
• Atmospheric Turbulence
• GNSS Applications
• +۳ مورد دیگر

Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections

• Control Theory
• Distributed Parameter Systems
• Model Predictive Control
• +۳ مورد دیگر

Lorenz Dörschel is an Adjunct Professor (Lehrbeauftragter) at the Institute of Automatic Control at RWTH Aachen University. He holds the academic title PD Dr.-Ing. habil, signifying post-doctoral research qualifications. His position is part-time, focusing on advanced control theory and applications. His primary research interests include: Control of distributed parameter systems (e.g., fluid dynamics, thermal processes) Model predictive control for industrial and automotive systems Parameter space methods for robust controller design Model reduction techniques for complex nonlinear systems Dörschel's recent publications (2018-2024) demonstrate broad applications across biomedical engineering, renewable energy, automotive systems, and industrial automation. His work consistently integrates mathematical rigor with practical implementations, emphasizing advanced control methodologies like nonlinear MPC, Lyapunov-based design, and Bayesian optimization. A recurring theme is the development of computationally efficient control strategies for distributed parameter systems. No scientific awards, student advising relationships, or research grants are documented in the available information.

Leandro Milhomens da Fonsecaمشاهده پروفایل

پژوهشگر

• Nuclear Physics
• Hypernuclei
• Neutron-rich Nuclei
• +۴ مورد دیگر

Dr. Leandro Milhomens da Fonseca is a researcher at the Technische Universität Darmstadt, affiliated with the Institute of Nuclear Physics (IKP). His work focuses on nuclear physics, particularly in hypernuclei and neutron-rich nuclei studies. Primary research areas: Nuclear Scattering, Neutron-skin Thickness, Radioactivity, and Gamma-ray Spectrometry. Contributions to detector development, including the Time-of-flight system for R3B experiments. Published extensively on nuclear interaction cross sections and radiation safety in Brazilian building materials. His recent publications highlight expertise in both experimental nuclear physics and environmental radiation assessment. While no formal awards are listed, his involvement in international collaborations like HYDRA/R3B suggests significant contributions to the field.

• Honeybee Genetics
• Animal Breeding
• Disease Resistance
• +۳ مورد دیگر

Prof. Dr. agr. Kaspar Bienefeld is an Honorary Professor at the Humboldt University of Berlin within the Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences. His research focuses on honeybee genetics, breeding optimization, and disease resistance mechanisms. Research Interests: Honeybee population genetics, Varroa mite resistance, genomic selection, and behavioral ethology. Key Contributions: Development of SNP assays for resistance traits, simulation studies for breeding schemes, and conservation strategies like Europe’s first honeybee gene bank. Publications: Over 40 peer-reviewed articles spanning honeybee breeding, genetic parameter estimation, and stress biomarker analysis.

Jörg Müssigمشاهده پروفایل

استاد

• Composite Materials
• Natural Fiber Composites
• Sustainable Materials
• +۴ مورد دیگر

Prof. Dr.-Ing. Jörg Müssig serves as a Professor at Bremen University of Applied Sciences within Faculty 5 (Department 2), focusing on sustainable composite materials development. His research bridges engineering and environmental science through innovation in natural fiber applications for industrial use. His primary research domains encompass natural fiber composites, biobased materials, and sustainable material systems, with specialized expertise in flax, hemp, and nettle fiber reinforcement. He investigates mechanical properties, interfacial adhesion mechanisms, flame retardancy solutions, and processing techniques like injection molding and filament winding, emphasizing sustainability metrics and biomimetic design principles. Analysis of his 2024-2025 publications reveals dominant themes in natural fiber composite optimization, particularly regenerated cellulose systems and coupling agent-free interfaces. Emerging trends include consumer perception studies of biobased materials and integration of ecological parameters into industrial design processes, reflecting expanding interdisciplinary approaches. Prof. Müssig leads extensive grant-funded projects including edible mushroom mycelium composites (2024-2026), sulfur-based flame retardants (2024-2026), natural fiber sector market analysis across Europe (2024-2025), and marine durability studies (2024-2025), demonstrating sustained research leadership with significant industry and cross-institutional collaborations. His work operates within a robust research ecosystem at Bremen University of Applied Sciences, where his project portfolio indicates leadership of a specialized team focused on sustainable material innovation, though specific lab infrastructure details remain unmentioned in source materials.

Anne Seidlitzمشاهده پروفایل

استاد

• Pharmaceutical Technology
• Biopharmaceutics
• 3D Printing in Drug Delivery
• +۳ مورد دیگر

Anne Seidlitz is a Professor of Pharmaceutical Technology at the Free University of Berlin since October 2024, previously holding the same position at Heinrich Heine University Düsseldorf (2021-2024). Affiliated with the Institute of Pharmacy , she leads the Seidlitz Pharmaceutical Technology Group , focusing on solid dosage forms and biorelevant drug release studies using 3D printing and hydrogel compartments . Doctorate in Pharmaceutical Technology (Greifswald, 2009) Habilitation in Natural Sciences (Greifswald, 2015) Qualified Person under German Medicines Act (AMG) Visiting Professorships: Hamburg, Jena Research Interests: Formulation development for implants , intravitreal injections , and subcutaneous delivery systems , with emphasis on biorelevant dissolution testing under physiological flow/movement conditions. Her group pioneers 3D-printed drug delivery devices and custom hydrogel models for vitreal , ear canal , and vascular implants . Publication Trends: Recent articles focus on thermal stability of steroids during extrusion, individualized implant design , and hydrogel compartments for non-oral dissolution testing . Key collaborations include EUFEPS Network and APV (Association for Pharmaceutical Process Engineering). Scientific Involvement: Member of EUFEPS Network on Bioavailability Scientific Council, German Federal Chamber of Pharmacists Active in APV (Arbeitsgemeinschaft für Pharmazeutische Verfahrenstechnik) Student Supervision: Mentored 24+ theses including 3D-printed tablets , implant coatings , and vitreal drug distribution . Collaborates with institutions in Düsseldorf , Jena , and Hamburg .