جست‌وجوی استاد و پژوهشگر

• Business Mathematics
• Statistics
• Data Warehouse Systems
• +۳ مورد دیگر

Manfred Soeffky serves as a Professor at the Berlin School of Economics and Law within the School of Economics and Law and Department of Economics and Business Administration, actively affiliated with the Institute of Quantitative Methods and Business Information Systems in Berlin, Germany. His research specializes in Business Mathematics and Statistics with concentrated expertise in Data Warehouse System Management, Multidimensional Data Analysis, and Knowledge Discovery and Data Mining. He investigates quantitative methodologies for corporate data infrastructure, focusing on data quality assessment, system architecture optimization, and practical implementation of business intelligence frameworks. Analysis of his 1999-2001 publications reveals consistent emphasis on data warehouse process management, ETL development, and knowledge management systems. His work demonstrates strong technical focus on data preparation techniques, operational data quality challenges, and portal-based enterprise integration solutions within business information systems. No information regarding scientific awards was documented in source materials. Specific details about student advising, research grants, laboratory teams, or current projects remain unreported in available documentation.

Catherine Ludwigمشاهده پروفایل

استاد پژوهشی

• Healthy Aging
• Vulnerabilities
• Nursing Care
• +۵ مورد دیگر

Catherine Ludwig is a Research Professor at the Geneva School of Health (University of Applied Sciences and Arts Western Switzerland), specializing in Healthy Aging , Vulnerabilities , and Nursing Care . She contributes to evidence-based practice through applied research in home care complexity and frailty assessment. Her research focuses on: Developing tools like the COMID Index and VIeSA for healthy aging interventions Addressing multidimensional complexity in home care Studying frailty indicators via interRAI-HC Exploring brain aging via neuroimaging and cognitive studies Her recent publications span Gerontology , Nursing , and Public Health , emphasizing Swiss healthcare and community-dwelling seniors . She collaborates on projects involving caregiver support , home care adaptation , and health policy . Key affiliations include: Geneva School of Health Geneva School of Social Work Institute of Applied Research (IR-HEdS) LIVES - Swiss National Centre of Competence in Research

Sergey Vasilyevich Golubمشاهده پروفایل

استاد

• Agent programming
• Intelligent monitoring
• Medical informatics
• +۴ مورد دیگر

Sergey Vasilyevich Golub is a Professor at the Department of Software for Automated Systems at Cherkasy State Technological University. He holds a Doctor of Technical Sciences degree and has been part-time faculty since 2018. His career spans multiple roles, including dean at CHNU and head of departments in intelligent systems and software engineering. His research focuses on agent programming, intelligent monitoring, medical informatics, and machine learning. He has contributed to interdisciplinary projects linking software engineering with environmental monitoring and healthcare diagnostics. Recent publications emphasize multi-agent systems, social network analysis, and data-driven disease prediction. Key article trends include integrating satellite data for climate monitoring, authorship classification in social media, and agent-based modeling for pandemic forecasting. He collaborates with researchers in Ukraine and abroad, with works in Springer LNNS and CEUR-WS proceedings. Thanks and honorary diplomas from Cherkasy National University (2000, 2003, 2015) Honorary diplomas from Cherkasy Regional State Administration (2001, 2014) Honorary diploma from Ukraine's Ministry of Education and Science (2011) He has authored monographs on data analysis technologies and cross-platform decision support systems. His work bridges academic research and practical applications in intellectual monitoring across healthcare, ecology, and cybersecurity domains.

Patrick Kürschnerمشاهده پروفایل

دانشیار

• Numerical Linear Algebra
• Model Order Reduction
• Eigenvalue Problems
• +۸ مورد دیگر

Patrick Kürschner is an Associate Professor for Numerical Mathematics and Linear Algebra at Leipzig University of Applied Sciences (HTWK Leipzig) . He previously held postdoctoral positions at the Max Planck Institute for Dynamics of Complex Technical Systems and KU Leuven's Kulak Kortrijk Campus. His work focuses on computational methods in systems and control theory. PhD in Mathematics (Otto-von-Guericke University, 2015) MSc in Mathematics (Chemnitz University of Technology, 2010) BSc in Financial Mathematics (Chemnitz University of Technology, 2008) His research interests span numerical linear algebra, matrix equations and functions, eigenvalue problems, preconditioning, model order reduction, tensor methods, and numerical algorithms for digital signal processing. He develops efficient computational techniques for large-scale systems in control theory and data science applications. Recent publications include advancements in low-rank ADI iteration, time-limited balanced truncation, inexact linear solvers, and tensor decompositions for polynomial systems. His work addresses challenges in computational neuroscience, mechanical simulations, and optimal control.

Joon Yeon Choehمشاهده پروفایل

استاد

• Social Behavior Prediction
• Natural Language Processing (NLP)
• Text Classification
• +۶ مورد دیگر

Joon Yeon Choeh is a Professor in the Department of Software at Sejong University 's College of Artificial Intelligence Convergence. With a Ph.D. in Management Engineering from KAIST, he leads the Intelligent Contents Lab , focusing on predictive analytics through social media and user-generated content. Education: Ph.D. (2006), MS (1998), BS (1996) from KAIST Current: Professor at Sejong University (2008–present) Previous: SK Telecom (2003–2008), Communication Intelligence Division His research spans NLP for social media analysis , market trend prediction , and neural network applications . Recent work includes economic sentiment indexing , personality prediction , and COVID-19 behavioral analysis . Key publication trends (2020–2025) show expertise in: Electronic Word-of-Mouth (eWOM) modeling Bayesian networks and ensemble methods Time-aware microblog analysis Neuroticism and mental health prediction Consumer-generated content integration Speech spectrogram-based biometrics Contact: zoon@sejong.edu | Lab: Intelligent Contents Lab | Phone: 02-3408-3887

Albert A. Smith-Penzelمشاهده پروفایل

پژوهشگر

• Biomolecular Dynamics
• NMR Spectroscopy
• Molecular Dynamics Simulation
• +۳ مورد دیگر

Dr. Albert A. Smith-Penzel is a Principal Investigator at the Institute for Medical Physics and Biophysics , University of Leipzig Medical Faculty . He leads a DFG-funded project titled "Disentangling dynamics in biomolecules with experiment and simulation" since 2021, following his 2019-2020 Research Associate position at the same institution. B.Sc. in Physics, University of Mount Union (2007) Ph.D. in Chemistry, Massachusetts Institute of Technology (2012) Postdoctoral Researcher at ETH-Zürich (2012-2018) His research focuses on biomolecular dynamics characterization through advanced NMR relaxation techniques combined with molecular dynamics simulations. He pioneered detector analysis methods for correlating experimental and computational dynamics data, addressing challenges in motion amplitude quantification across multiple timescales. Recent publications highlight his work on: Dynamic landscapes of bio-membranes Energy landscapes of GPCRs Model-free analysis of protein fibrils Software development for NMR analysis (INFOS, DIFRATE) He actively develops open-source tools for dynamics analysis and contributes to understanding how distributed motions influence macromolecular function.

• Business Process Management
• Process Mining
• Workflow Systems
• +۳ مورد دیگر

Marian Lux is a researcher affiliated with the Faculty of Computer Science, specializing in workflow systems and business process management through the Research Group Workflow Systems and Technology. Her academic profile centers on the intersection of process modeling, user behavior analysis, and search algorithm development within information systems. Her research interests span business process management and process mining, with particular emphasis on: User behavior patterns in search process models Quality assessment of business process execution Pattern recognition in workflow systems Data-driven optimization of customer journey processes Digital transformation frameworks for smart communities Analysis of her publication history reveals a consistent trajectory from foundational work on search process modeling (2018-2019) toward broader applications in digital ecosystems (2023), demonstrating increasing scope from technical process analysis to societal-scale digital transformation projects. Her research bridges theoretical computer science with practical business process applications across tourism, e-commerce, and rural community development domains. Marian Lux actively contributes to the Research Group Workflow Systems and Technology, where she develops methodologies for analyzing process execution data and modeling common behavioral patterns. Her work frequently employs ontology-based approaches and leverages underlying data structures to identify optimization opportunities in complex workflow systems.

Bert Provanمشاهده پروفایل

پژوهشگر ارشد

• Housing and Homelessness
• Social Cost-Benefit Analysis
• French and European Regeneration Policies
• +۲ مورد دیگر

Bert Provan is a CASE Visiting Senior Policy Fellow at the London School of Economics, specializing in housing and homelessness, social cost-benefit analysis, and French/European regeneration policies. His work bridges academic research with senior policy management experience in UK central and local government. Research Focus: Housing policy, poverty mitigation, and cost-benefit frameworks. Key Collaborations: Projects with Kath Scanlon, Laura Lane, Anne Power, and the European Investment Bank. His recent research explores multidimensional approaches to housing challenges, including wheelchair accessibility, domestic abuse support, and urban overcrowding. Articles span policy evaluation, economic modeling, and third-sector housing solutions, emphasizing actionable insights for local governments and NGOs. Prior projects include European regional development fund analysis and welfare reform impacts on housing tenants. Bert’s methodology integrates cross-sector stakeholder engagement and longitudinal data analysis to address inequality in housing and social policy.

Robert Heyerمشاهده پروفایل

استاد

• Bioinformatics
• Multi-omics data integration
• Machine learning in bioinformatics
• +۵ مورد دیگر

Prof. Dr.-Ing. Robert Heyer is a full professor at Bielefeld University and leads the Multidimensional Omics Analyses Group within the Faculty of Engineering and the Center for Biotechnology (CeBiTec) . He is also affiliated with the Institute for Bioinformatics Infrastructure (BIBI) and collaborates with the Leibniz Institute for Analytical Science (ISAS) . His work focuses on developing cloud-based bioinformatics tools and integrating multi-omics data using machine learning and knowledge graphs. Research Interests: His group specializes in: Software development for omics data analysis Cloud-based web platforms for bioinformatics Knowledge graph integration of omics and clinical data Microbiome and metaproteomics research Machine learning applications in biomedical data His research bridges computational biology, clinical informatics, and systems medicine, aiming to translate complex omics data into actionable clinical insights. Recent Publications: His 2024–2025 publications emphasize the application of AI and graph-based models in sepsis prediction, IBD remission profiling, and microbial community analysis. These works highlight a consistent trend toward explainable AI, clinical translation, and integrative multi-omics frameworks. Teaching & Infrastructure: Prof. Heyer contributes to teaching in scientific informatics and oversees infrastructure development at the Institute for Bioinformatics Infrastructure (BIBI).

Micah Donorمشاهده پروفایل

استادیار

• Structural Biology
• Native Mass Spectrometry
• Ion Mobility-Mass Spectrometry
• +۳ مورد دیگر

Micah Donor serves as an Assistant Professor of Biochemistry in the Department of Biological and Molecular Sciences at George Fox University, a position he has held since 2022. Prior to this appointment, he was a postdoctoral research associate at the Pacific Northwest National Laboratory in Richland, Washington, specializing in ultra-high resolving power ion mobility-mass spectrometry. His academic credentials include: PhD in Chemistry from the University of Oregon (2020) BS in Chemistry from George Fox University (2014) Donor's research program centers on the development and application of native mass spectrometry methods for structural biology . He employs native ion mobility-mass spectrometry to investigate the structural dynamics of protein complexes, with particular emphasis on eye lens crystallins. This work bridges experimental mass spectrometry and computational modeling to elucidate protein-protein interactions and higher-order structures, with significant implications for understanding protein folding diseases. Analysis of his recent publications (2020-2024) reveals consistent innovation in mass spectrometry methodology, including the development of data conversion tools like MZA for AI-assisted analysis. His work demonstrates particular expertise in studying protein oligomerization through native mass spectrometry, with recurring themes in crystallin protein behavior, instrumental optimization for protein complexes, and computational integration of ion mobility data. While no specific awards are documented in available sources, his publication record in high-impact analytical chemistry journals indicates scholarly recognition. Donor's teaching background includes instrumental analysis, physical chemistry, and organic chemistry instruction during his graduate studies, suggesting strong pedagogical foundations for his current faculty role. He resides in Newberg, Oregon with his wife Tai and son Simeon, maintaining active interests in hiking, running, guitar, and disc golf.

Ben Bond-Lambertyمشاهده پروفایل

پژوهشگر

• Carbon cycling
• Disturbance effects
• Ecosystem respiration
• +۲ مورد دیگر

Ben Bond-Lamberty is a research scientist at the Joint Global Change Research Institute (JGCRI), a collaboration between Pacific Northwest National Laboratory and the University of Maryland in College Park. His work focuses on carbon and nutrient cycling in terrestrial ecosystems, particularly disturbances (e.g., wildfires), ecosystem respiration, and multiscale modeling to understand climate feedbacks. Education: PhD in Forest Ecosystem Ecology, University of Wisconsin—Madison, 2003 BA in History and Computer Science, Williams College, 1993 Research interests span forest ecology, carbon cycle dynamics, and climate change impacts. Bond-Lamberty investigates how disturbances alter forest carbon cycling, the response of soil respiration to warming, and the development of scalable ecological models. His interdisciplinary approach integrates field data, global databases, and computational tools to address ecosystem-climate interactions. Publications emphasize soil respiration, forest resilience, and carbon-climate feedbacks. Recent articles show a trend toward large-scale data synthesis (e.g., global soil respiration databases), model-data integration, and methodological innovations for measuring ecosystem processes. Studies frequently address disturbance legacies, moisture effects on carbon fluxes, and coastal ecosystem vulnerabilities. Scientific awards and recognition: Fellow, American Association for the Advancement of Science (AAAS) Bond-Lamberty leads collaborative projects at JGCRI, contributing to open-science initiatives and community data standards. He serves as an editor for Ecosystems and Global Biogeochemical Cycles and is a member of the American Geophysical Union and Ecological Society of America.

• Econometrics
• Statistics
• Food Security
• +۴ مورد دیگر

Ing. Jozef Palkovič, PhD. is an Assistant Professor at the Institute of Statistics, Operation Research and Mathematics within the Faculty of Economics and Management at Slovak University of Agriculture in Nitra. His academic career spans multiple research domains with a strong focus on quantitative methods applied to economic and agricultural challenges. Dr. Palkovič's research interests center on econometric modeling , statistical analysis , and food security assessment , particularly examining European countries in the context of climate change. His work integrates advanced analytical approaches with practical applications in regional development, risk assessment, and productivity evaluation. He has developed expertise in multidimensional evaluation frameworks for sustainable growth at both national and regional levels. As an active researcher, Dr. Palkovič serves as principal investigator for multiple significant projects including VEGA grants on food security in Europe and climate change impacts. His research portfolio demonstrates a consistent focus on applying statistical and econometric methods to pressing socioeconomic challenges, particularly within the Visegrad Group countries. He has led numerous KEGA educational innovation projects focused on modernizing econometrics teaching materials and developing statistical literacy. Dr. Palkovič actively supervises diploma theses and teaches a comprehensive range of quantitative courses including Econometrics, Statistics, Risk Modeling, and Econometric Modeling. His teaching responsibilities reflect his dual expertise in theoretical statistical methods and their practical applications in economic analysis. He maintains regular consulting hours for students and appears to be deeply engaged in curriculum development for quantitative subjects within his faculty.

• measure theory
• Gaussian measures
• measures on infinite-dimensional spaces
• +۴ مورد دیگر

Egor Dmitrievich Kosov is an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), where he has been working since 2016. He also serves as a Senior Research Fellow at the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis within HSE's Institute of Artificial Intelligence and Digital Sciences. Additionally, he holds positions as Senior Researcher at the Steklov Mathematical Institute's Department of Function Theory and Junior Researcher at the Laboratory of Multidimensional Approximation and Applications. Dr. Kosov earned his Candidate of Physical and Mathematical Sciences degree from Lomonosov Moscow State University in 2018, where he also completed postgraduate studies specializing in Mathematics and Mechanics with a qualification as Researcher. His research focuses on measure theory , particularly Gaussian measures , measures on infinite-dimensional spaces , logarithmically concave measures , and measurable polynomials . Kosov's work bridges theoretical mathematics with applications in stochastic analysis, exploring the regularity properties of distributions and developing discretization techniques for functional norms. His research has significant implications for understanding complex probabilistic structures in high-dimensional spaces. Analysis of Kosov's recent publications reveals a strong focus on polynomial mappings of random variables, particularly Gaussian and log-concave distributions. A significant portion of his research addresses discretization problems—developing methods to approximate continuous mathematical structures through discrete sampling. His publications demonstrate growing recognition in the mathematical community, with appearances in prestigious journals across multiple subfields of mathematical analysis. Letter of gratitude from the First Vice-Rector of HSE (March 2023) Letter of Gratitude from the Faculty of Computer Science at HSE (September 2019) Bonus for publication in List A journals (2023-2024) Multiple bonuses for international peer-reviewed publications (2019-2023) Best Teacher award (2018) Moscow Mathematical Society award (2021) At HSE, Kosov teaches Mathematical Analysis, Probability Theory, and Functional Analysis to undergraduate students in the Applied Mathematics and Computer Science program across both the Faculty of Computer Science and the Faculty of Economic Sciences. His teaching spans multiple academic years (2020-2023), demonstrating his commitment to education alongside research. Dr. Kosov is actively involved in research teams including the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis at HSE and the Laboratory of Multidimensional Approximation and Applications. His work connects with the broader mathematical community through collaborations with researchers such as V.I. Bogachev, V.N. Temlyakov, and others, contributing to Russia's strong tradition in mathematical analysis and probability theory.

Tomasz Kaczynskiمشاهده پروفایل

دانشیار

• Computational Topology
• Dynamical Systems
• Nonlinear Analysis
• +۱ مورد دیگر

Tomasz Kaczynski is an Associate Professor in the Department of Mathematics at the University of Sherbrooke, affiliated with the Research Group on Information Technologies (GRTCI) and the Research Team on Algebraic and Geometric Structures. Education: M.Sc. in Mathematics, University of Warsaw (1981) Ph.D. in Mathematics, McGill University (1986) Postdoctoral Fellowship, University of Waterloo (1986-1987) Research Focus: Dr. Kaczynski develops topological methods including homology, fixed point index, Conley index, and critical point theory to establish existence of solutions with specific properties in dynamical systems and differential equations. His work in computational topology bridges mathematics and computer science, with applications in computer vision and formal verification of chaotic systems observed in numerical experiments. Publication Trends: Recent work advances multidimensional persistence algorithms and formal connections between combinatorial and classical vector field dynamics. These contributions drive topological data analysis for complex systems, emphasizing algorithmic development for dynamical modeling and image analysis. Research Groups: He actively participates in the GRTCI and leads the Research Team on Algebraic and Geometric Structures, focusing on interdisciplinary applications of topological methods.

Ralph Ernstorferمشاهده پروفایل

استاد

• Ultrafast Spectroscopy
• Condensed Matter Physics
• 2D Materials
• +۷ مورد دیگر

Prof. Dr. Ralph Ernstorfer is a full professor at Technische Universität Berlin's Institute for Optics and Atomic Physics, where he leads the Ultrafast Nanoscience group. He simultaneously holds a Max Planck Fellowship at the Fritz Haber Institute's Department of Physical Chemistry, heading the Structural & Electronic Surface Dynamics research group. His dual affiliation enables cutting-edge research in ultrafast phenomena. Research Focus: Ernstorfer's group investigates out-of-equilibrium electronic and atomic structures in solids and heterostructures using advanced ultrafast techniques. Core methodologies include: Time- and angle-resolved photoelectron spectroscopy (trARPES) Femtosecond electron diffraction and microscopy Ultrafast optical spectroscopy Current research themes encompass exciton dynamics in 2D materials, topological properties of quantum materials, light-induced phase transitions, and machine learning applications in spectroscopy. Awards & Recognition: Max Planck Fellowship (2022-2027) for collaborative research on ultrafast electron dynamics in nanoscale materials Academic Leadership: Ernstorfer advises doctoral candidates including Tania Mukherjee and leads multiple funded projects: ERC project 'FLATLAND' studying electron-lattice-spin correlations in 2D semiconductors DFG projects within CRC 951 HIOS and SPP 2244 2D Materials consortium Coordination of TRR227 collaborative research network on ultrafast spin systems He oversees laboratories at both TU Berlin and FHI equipped with MHz XUV lasers, femtosecond electron diffractometers, and multidimensional ARPES systems.