جست‌وجوی استاد و پژوهشگر

• State-society relations
• Anthropology of markets and trade
• Religious belief and ritual practice
• +۶ مورد دیگر

Kirsten Endres serves as Head of Research Group at the Max Planck Institute for the Science of Human History and holds an adjunct professorship at the University of Halle-Wittenberg. Her work focuses on Vietnamese society, state-society dynamics, ritual practices, and infrastructural development. She earned her PhD in Anthropology from the University of Munich (2000) and habilitation from the University of Halle-Wittenberg (2010). Education: Doctorate in Anthropology, University of Munich (2000) Habilitation in Anthropology, University of Halle-Wittenberg (2010) Research Interests: Kirsten’s research examines ritual transformation, urban renewal in Southeast Asia, bureaucratic documentation practices, and the sociopolitical impacts of electrification. She combines historical anthropology with ethnographic fieldwork, particularly in Vietnam, to analyze how state policies intertwine with local cultural frameworks. Grants & Labs: Leads a research group investigating state-making processes and societal interactions. Formerly a postdoctoral fellow at the MPI (2009–2010) before transitioning to her current leadership role.

• Climate Modeling
• Atmospheric Physics
• Numerical Weather Prediction
• +۵ مورد دیگر

Monika Esch is a Researcher in the Department of Climate Physics at the Max Planck Institute for Meteorology in Hamburg, Germany, where she has been employed since 1991. She works in the Wave Driven Circulations research group, focusing on climate modeling and atmospheric physics. Her career began with a Diploma in Physics from the University of Hamburg in March 1988, followed by positions as a Scientist at the MPIfM (1988-1990) and GKSS Forschungszentrum (1990-1991) before transitioning to her current role as Scientific Programmer. Esch's research interests span climate modeling, atmospheric physics, numerical weather prediction, climate dynamics, tropical cyclone simulation, Earth system modeling, climate variability, and cloud physics. Her work primarily involves developing and implementing climate models, particularly focusing on the ICON (Icosahedral Nonhydrostatic) modeling framework. She has made significant contributions to understanding how microphysical processes affect tropical condensate, the simulation of Earth System components at high resolution, and the representation of quasi-biennial oscillation in climate models. Her publication record demonstrates consistent research activity from the late 1980s through 2025, with recent work focusing on high-resolution climate modeling, Earth system interactions, and the atmospheric response to increasing CO2. Her research shows a clear evolution from early work on ice sheet modeling and tropical cyclones toward more complex Earth system modeling at increasingly higher resolutions. While no specific scientific awards are mentioned in the available information, her extensive publication record in high-impact journals and consistent involvement in major climate modeling projects suggests recognition within the climate science community. Her collaborative work extends across multiple international research teams focused on advancing climate modeling capabilities. Esch has been instrumental in the development of the ICON modeling system and its various components, contributing to both the theoretical foundations and practical implementation of these models. Her technical expertise in scientific programming has enabled significant advances in climate simulation capabilities at the Max Planck Institute for Meteorology.

• Land-Atmosphere Interactions
• Storm-Resolving Earth System Models
• Climate Modeling
• +۳ مورد دیگر

Junhong Lee is a Research Fellow at the Max Planck Institute for Meteorology (MPI-M) in Hamburg, Germany, specializing in land-atmosphere interactions within storm-resolving Earth System Models. His work investigates how soil moisture conditions influence precipitation triggering and carbon cycle dynamics in high-resolution climate simulations. His academic background includes: Ph.D. and M.S. in Atmospheric Sciences from Yonsei University, Korea (2012-2019), with thesis on "The Representations of Vegetation for Surface Wind in the WRF Model" B.S. in Atmospheric Sciences and B.S. in Earth Science Education from Kongju National University, Korea (2008-2012), with thesis on "Analysis of Arctic and Antarctic Sea-Ice Concentration Variation Retrieved from Aqua/AMSER-E" Lee's research centers on improving boundary-layer processes and land-surface representations in climate models. He has implemented critical model components including the 3D Smagorinsky turbulence scheme in ICON's Sapphire configuration and the roughness sublayer scheme in WRF. His work bridges observational data with high-resolution modeling to advance understanding of land-atmosphere feedback mechanisms, particularly in storm-resolving frameworks where traditional parameterizations break down. Analysis of his 12 publications (2015-2023) reveals consistent focus on boundary-layer meteorology, model development, and land-surface interactions. His recent work emphasizes kilometer-scale Earth System Modeling (ICON-Sapphire), vegetation-atmosphere coupling, and innovative parameterizations for surface-layer processes. Key trends include integration of observational data into models, evaluation of model physics across scales, and exploration of land-surface feedbacks in extreme weather contexts. Lee actively contributes to MPI-M's modeling infrastructure including the ICON Earth System Model and participates in collaborative projects like nextGEMS and WarmWorld. His research leverages the institute's observational assets such as the Barbados Cloud Observatory and HALO research aircraft, though no specific lab leadership or student advising is documented. The institute's structure—particularly the Climate Physics and Climate Dynamics departments—provides the framework for his storm-resolving model development work.

• Transatlantic History
• Jewish Intellectual History
• Gender Studies
• +۴ مورد دیگر

Vera Kallenberg is a postdoctoral scholar and research associate at the Interdisciplinary Center for Gender Studies (IZG) within Bielefeld University’s Faculty of Sociology. Her work bridges transatlantic history, gender studies, and Jewish intellectual history, with a focus on migrant knowledge and critical race theories. Ph.D. in History (summa cum laude), TU Darmstadt/EHESS Paris State Examination in History and German, Free University Berlin Her research explores: Transnational gender experiences 20th-century Jewish émigré networks Intersectional historiography Memory studies in legal contexts Recent publications examine Gerda Lerner’s foundational feminist scholarship and postwar Holocaust testimony. Her article trends emphasize transdisciplinary methodologies and critical analysis of historical trauma. Scientific Awards: Fulbright Visiting Scholar (2023) Gerda Henkel Fellow (2019-2019) DAAD Fellow (2018-2019) She has held visiting positions at Harvard, Dartmouth, and Vanderbilt universities, with grants supporting her work on migrant intellectuals and gendered historiography.

• Blockchain Technology
• Cybersecurity
• Cloud Computing
• +۳ مورد دیگر

Wei-Tek Tsai is a Professor affiliated with Arizona State University's School of Computing, Informatics, and Decision Systems Engineering, and previously with Beihang University and the University of Minnesota. His research focuses on blockchain technology, cybersecurity, cloud computing, and software engineering. He has contributed significantly to areas such as blockchain-based systems, smart contract development, distributed testing methodologies, and crowdsourcing in software development. His work emphasizes practical applications like fraud detection, supply chain supervision, and decentralized financial systems. Research interests include permissioned blockchains, anomaly detection in cryptocurrency transactions, and optimizing consensus mechanisms. He has published extensively in top-tier journals and conferences, including IEEE Transactions and international workshops on software engineering and security. His work bridges theoretical advancements with real-world challenges in distributed systems and cybersecurity.

• High Performance Computing
• Network Simulation
• Parallel Discrete Event Simulation
• +۵ مورد دیگر

Kevin A. Brown is an active researcher in the field of High Performance Computing with a strong publication record spanning over a decade. His work primarily focuses on HPC network simulation, performance analysis, and optimization of parallel computing systems. He has collaborated extensively with researchers including Christopher D. Carothers, Robert B. Ross, and Satoshi Matsuoka across multiple institutions. Dr. Brown's research interests center around network simulation techniques, particularly Parallel Discrete Event Simulation (PDES) for modeling HPC networks. His recent work explores multi-fidelity network simulation frameworks, surrogate modeling for performance prediction, and machine learning applications for network traffic forecasting. He has made significant contributions to understanding network congestion, quality-of-service mechanisms, and the interference between different types of traffic in HPC environments. His publication record shows consistent output with 19 publications documented between 2014 and 2025, with increased productivity in recent years. The 2023-2025 period shows particularly strong activity with 12 publications, indicating ongoing research momentum. His work appears primarily in top HPC conferences including SIGSIM-PADS, CLUSTER, and ICPP. Notable recent contributions include the development of MFNetSim for multi-traffic modeling of Dragonfly systems, research on zombie packet techniques for hybrid PDES simulation, and work on steady-state fluid models for HPC networks. His research demonstrates a clear trajectory from fundamental network performance analysis toward more sophisticated simulation frameworks incorporating machine learning techniques.

Lars Blunckمشاهده پروفایل

استاد

• Art History
• 20th Century Art
• Photography Studies
• +۳ مورد دیگر

Prof. Lars Blunck is a Professor of Art History at the Academy of Fine Arts Nuremberg (AdBK) since 2013. He studied in Braunschweig and Kiel, earning his doctorate in 2001 with a dissertation on performative assemblages of the 1950s–60s. His habilitation (2007) focused on Marcel Duchamp's precision optics. He held a visiting professorship and was a fellow at the Terra Foundation for American Art (2011). His research emphasizes 20th-century art, participatory practices, and photography studies. Key achievements include the Deubner Prize (2005) and the 2025 Preis für gute Lehre. He co-edits the series Contact Zones: Studies in Global Art and has curated exhibitions at institutions like the Hamburger Bahnhof. His publications span Marcel Duchamp, Fluxus, and photographic theory, with notable works like Duchamps Readymade (2017) and essays on Duchamp's Prière de toucher . Blunck's research explores intersections of visual culture, performance, and art historiography, with a focus on 20th-century avant-garde movements. His recent articles address idleness in art, staged photography, and memorial aesthetics, reflecting his commitment to interdisciplinary analysis.

Manuela Bünzowمشاهده پروفایل

پژوهشگر ارشد

• Art History
• Media Studies
• Photography
• +۳ مورد دیگر

Manuela Bünzow is a Research Fellow at the Academy of Fine Arts Nuremberg, affiliated with the Department of Transmedia Spaces. She holds a doctoral degree from the Karlsruhe University of Art and Design (2020–present) under Prof. Dr. Matthias Bruhn and Prof. Dr. Lars Blunck. Her research focuses on intermedia studies, art history, and media aesthetics, with notable work on contemporary photography and art education. Education: 2013–2014: Art History and Education at Friedrich-Alexander University Erlangen-Nuremberg 2014–2019: Art Education at Academy of Fine Arts Nuremberg (Class of Fine Arts and Sculpture) 2019: First State Examination (Teacher Certification) Research Interests: Bünzow explores the intersections of art, media, and pedagogy. Her work critiques contemporary photographic practices, analyzes historical photographic archives (e.g., August Sander), and develops emancipatory approaches to media education. She emphasizes intermedia relationships and the theoretical frameworks shaping visual communication. Awards: Young Leaders Academy (2011) Oskar Karl Forster Scholarship (2013) German Academic Scholarship Foundation Fellowship (2014–2019) Equal Opportunities Scholarship (2021–2022) Advising & Grants: Since 2019, she has served as a Research Assistant at the Chair of Art History. Her publications span art criticism, pedagogical theory, and curatorial practices. She has taught at the Christian-Ernst-Gymnasium Erlangen (2015–2017) and contributed to curriculum development for art education programs. Labs/Teams: Associated with the LEONARDO - Center for Creativity and Innovation and the Transmedia Spaces research group.

• Neural Oscillations
• Transient Neural Activity
• Magnetoencephalography (MEG)
• +۳ مورد دیگر

Kamil KILIC is a Doctoral Researcher at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, since 2024, affiliated with the Department of Neurology and the International Max Planck Research School on Cognitive NeuroImaging (IMPRS CoNI). His work spans the Neural interactions and dynamics and Somatosensory research groups, focusing on advanced neuroimaging methodologies. His academic qualifications include: Doctoral Researcher (2024–present) at IMPRS CoNI under supervisors Prof. Dr. Arno Villringer and Dr. Vadim Nikulin, with advisory support from Prof. Dr. Karsten Mueller, Dr. Burkhard Maess, and Dr. Maria Herrojo Ruiz M.Sc. in Integrative Neuroscience (2021–2024) from Otto von Guericke University of Magdeburg B.Sc. in Psychology (2017–2021) from Dokuz Eylul University, Turkey His research centers on neural oscillations and transient activity patterns using MEG and structural MRI, with emphasis on somatosensory processing and neural dynamics. Prior research experience includes investigations into sensory learning at the Leibniz Institute for Neurobiology (2023–2024), motor control physiology (2023), and neural cybernetics (2022) at Otto von Guericke University. No scientific awards are documented in available records. As an early-career doctoral researcher, he does not currently supervise students. His work operates within the infrastructure of the Max Planck Society through institutional collaborations. He actively contributes to the Neural interactions and dynamics and Somatosensory research groups within the Department of Neurology, leveraging the institute's specialized neuroimaging facilities for cognitive neuroscience investigations.

Kyesam Jungمشاهده پروفایل

پژوهشگر

• Computational Neuroscience
• Whole-brain simulation
• Diffusion-weighted MRI
• +۱ مورد دیگر

Kyesam Jung is a Researcher at Forschungszentrum Jülich, affiliated with the Institute of Neuroscience and Medicine (INM) in the Brain and Behavior department (INM-7). His work centers on computational modeling of human brain networks using structural and functional neuroimaging data. Dr. Jung's primary research areas include Computational Neuroscience, Whole-brain simulation, and Diffusion-weighted MRI analysis. He reconstructs anatomical connectivity from T1-weighted and diffusion MRI data to develop whole-brain models that simulate blood-oxygen-level-dependent (BOLD) signals. These models are validated against empirical data and applied to investigate clinical and cognitive brain dynamics, with emphasis on neural information processing mechanisms. No scientific awards or fellowships are documented in the available information. Dr. Jung has no listed advisees or students. His research is conducted within the Brain and Behavior department at Forschungszentrum Jülich, contributing to the institution's neuroscience initiatives through computational modeling of brain structure-function relationships.

• Internet of Things
• Software Engineering
• Machine Learning
• +۵ مورد دیگر

Jorge Eduardo Ibarra Esquer is an Associate Professor in the Department of Computer Science at the School of Engineering, Universidad de Sonora, Mexico. With a publication record spanning nearly two decades from 2006 to 2023, he has established himself as an active researcher in multiple domains of computer science. His work demonstrates consistent collaboration with colleagues Brenda Leticia Flores Ríos, María Angélica Astorga Vargas, and Félix Fernando González-Navarro across numerous publications. His research interests focus on the Internet of Things , Software Engineering , Machine Learning , and Educational Technology . Recent work has explored IoT object categorization, user engagement analysis on social media for scientific dissemination, and software development education during the pandemic. Earlier research examined biosensor modeling, game playing preferences, and driving safety through gamification. His publications appear in reputable venues including IEEE Access, Sensors, and the Colombian Journal of Computing, as well as at national conferences like ENC (Encuentro Nacional de Computación). Analysis of his recent publications (2020-2023) reveals a strategic focus on applying machine learning to practical problems in IoT, educational technology, and social media analytics. His work bridges theoretical computer science with real-world applications, particularly in the Mexican higher education context as evidenced by studies on Facebook engagement at a higher education institution. The interdisciplinary nature of his research spans from healthcare applications (biosensors, physiological monitoring) to educational technology and software engineering practices. While no specific scientific awards are documented in the available publication records, his consistent publication output across multiple high-quality venues demonstrates recognition within his academic community. His research has practical implications for software development education, IoT applications, and human-computer interaction design. Dr. Ibarra Esquer's work shows strong collaborative patterns, particularly with researchers from his home institution. His recent publications suggest active involvement in research teams focusing on educational technology applications during the pandemic, social media analytics for scientific communication, and IoT applications. The continuity of his research program since 2006 indicates sustained scholarly productivity and relevance in evolving technological domains.

• Video Coding
• Image Compression
• Machine Learning for Video Processing
• +۵ مورد دیگر

Seyoon Jeong is a Professor in the Department of Computer Science and Engineering at Korea University's College of Engineering, with an extensive research career spanning over two decades in video coding, image compression, and computer vision. His scholarly contributions demonstrate consistent engagement with cutting-edge research topics in multimedia processing. Jeong's research primarily focuses on video and image compression technologies, with recent emphasis on Video Coding for Machines (VCM), High Efficiency Video Coding (HEVC), and machine learning applications for visual data processing. His work bridges traditional signal processing with modern AI techniques, particularly in optimizing compression algorithms for both human perception and machine vision tasks. Over the past five years, his research has increasingly concentrated on feature map compression, multi-scale processing, and the development of specialized coding techniques for machine-oriented applications. Analysis of his recent publications (2020-2024) reveals a clear research trajectory toward optimizing video coding specifically for machine vision systems rather than traditional human viewing. This emerging field addresses the challenge of efficiently transmitting visual data to AI systems that process video for tasks like object detection and scene understanding, where conventional perceptual quality metrics are less relevant. His work often involves collaboration with researchers from Korean institutions and international partners, reflecting the global nature of multimedia research. While specific awards aren't documented in the provided materials, his consistent publication record in top-tier journals and conferences (IEEE Transactions, CVPR, NeurIPS) indicates significant recognition within the multimedia research community. His research has practical applications in areas including 5G video transmission, machine vision systems, and efficient visual data processing for AI applications.

• Optical Communication
• Free Space Optics
• Wireless Communication
• +۵ مورد دیگر

Hemani Kaushal is an active researcher specializing in optical communication systems with a publication record spanning over a decade from 2013 to 2025. Her scholarly output demonstrates consistent contributions to the field of communications engineering, particularly in Free Space Optics (FSO) and related wireless technologies. With 19 documented publications in reputable venues including IEEE journals and conferences, she has established herself as a significant contributor to optical communication research. Dr. Kaushal's research interests center around optical communication systems, with particular expertise in Free Space Optics, underwater optical communication, space-based optical networks, and UAV communication systems. Her work demonstrates a progression from fundamental optical communication principles to increasingly applied systems, with recent publications exploring machine learning applications in healthcare management. The research trajectory shows consistent innovation in addressing challenges like atmospheric turbulence, signal degradation, and system optimization in optical communication channels. Analysis of her 15 most recent publications reveals a clear evolution from foundational optical communication work (2015-2017) toward more complex integrated systems (2018-2021) and recently toward interdisciplinary applications (2022-2025). While early work focused on theoretical aspects of FSO and underwater communication, more recent publications incorporate machine learning techniques and address practical implementation challenges in UAV networks and healthcare systems. The publications span multiple IEEE transactions and journals, indicating recognition within the communications engineering community. Dr. Kaushal maintains active collaborations with researchers worldwide, most notably with Georges Kaddoum across multiple publications, as well as with Mona Aggarwal, Swaran Ahuja, Ghanishtha Narang, and Zornitza Genova Prodanoff. These collaborations span various aspects of optical and wireless communication research, resulting in comprehensive investigations of system performance, security, and optimization techniques.

• Computer Science
• Quantum Computing
• Machine Learning
• +۲ مورد دیگر

Atul Kumar is a Researcher in computer science with publications spanning quantum computing, machine learning, and cybersecurity. His work appears in journals including IEEE Transactions on Visualization and Computer Graphics, Knowledge-Based Systems, and IEEE Access. His research focuses on quantum machine learning algorithms, medical image analysis, hardware security, and chaotic encryption systems. Recent investigations explore quantum support vector machines, hardware Trojan attacks, and uncertainty-aware neural representations for scientific visualization. Analysis of his publication portfolio reveals consistent methodological innovation in applying quantum computing principles to traditional computing problems, particularly in image processing and classification tasks. His security-focused research examines vulnerabilities in hardware systems and develops cryptographic solutions using chaotic maps.

• Neural Networks
• Medical Image Analysis
• Computer Vision
• +۵ مورد دیگر

Zhigang Li is a Professor in the Department of Computer Science at South China University of Technology's School of Computer Science and Engineering. His research spans multiple technical domains with significant contributions to neural networks, medical imaging, computer vision, and sensor technologies. Recent collaborations include work with Northwestern Polytechnical University, Hong Kong University of Science and Technology, and various medical research institutions. Dr. Li's research interests focus on neural network architectures, particularly small-world and feedforward networks for system modeling and medical applications. His work bridges computer science with practical applications in healthcare (EEG analysis, schizophrenia detection, liver transplant allocation), environmental monitoring (wastewater treatment), and engineering systems (CMOS image sensors, UAV networks). His research demonstrates strong interdisciplinary connections between theoretical computer science and real-world problem solving. Analysis of his recent publication trends shows increasing focus on medical applications of AI, with significant work in brain functional network analysis, depression recognition, and schizophrenia detection. His technical contributions include novel neural network architectures, efficient sensor systems, and advanced signal processing techniques. The publications reveal a consistent pattern of high-quality output in top-tier journals across multiple disciplines. Dr. Li has received recognition through publications in prestigious venues including IEEE Transactions, Medical Image Analysis, and Expert Systems with Applications, though specific awards aren't documented in the provided bibliography. His work demonstrates significant impact across multiple fields, particularly in applying computational methods to healthcare challenges. His research program includes collaborations with medical researchers for brain imaging applications, electrical engineers for sensor development, and computer scientists for network architecture design. Current projects appear focused on multi-view brain network analysis, energy-efficient sensor systems, and medical AI applications with potential clinical impact.