جستجوی استاد راهنمای دانشگاهی

Nicolas Gravelمشاهده پروفایل

پژوهشگر

• Neuroscience
• Neuroimaging
• Visual Cognition
• +۴ مورد دیگر

Dr. Nicolas Gravel is a former guest researcher at the Neurocognitive and Experimental Psychology Department, part of the Department of Education and Psychology at Freie Universität Berlin. His research focuses on the neural dynamics of visual cognition, employing advanced neuroimaging techniques like resting-state fMRI and electrophysiological methods combined with computational modeling. He has contributed to understanding visual cortical organization, BOLD activity propagation, and task-dependent interactions in the brain. Education: BSc in Biology (University of Chile), PhD in Visual Neuroscience (University of Groningen, Netherlands). His doctoral work developed novel resting-state fMRI analyses to map functional organization in the human visual cortex. Current interests include modeling neocortical-hippocampal dialogues during memory consolidation and investigating laminar-specific responses using multivariate pattern classification. Notable achievements include securing an ERC Consolidator Grant for the TRANSFORM project (2025), exploring brain mechanisms from photons to meaning across lifespan development. His publications span neuroimaging methodologies, visual system dynamics, and clinical neuroscience applications. His research integrates experimental and computational approaches, bridging gaps between neuroanatomical organization and cognitive processes. Collaborative projects include latency analysis of BOLD signals and parcellation techniques for topographic brain mapping.

Tobias Stauberمشاهده پروفایل

استاد

• Ion Channel Physiology
• Membrane Transport
• Cell Physiology
• +۳ مورد دیگر

Prof. Dr. Tobias Stauber is a Professor at the Department of Biology, Chemistry, Pharmacy at Freie Universität Berlin, leading the Biochemistry research group. His work focuses on ion channel physiology, particularly the volume-regulated anion channel LRRC8/VRAC, and their roles in cellular processes like lysosomal homeostasis, membrane transport, and cell differentiation. He has mentored multiple PhD students including Lingye Chen, Sumaira Pervaiz, Benjamin König, and Tianbao Liu. His group investigates molecular mechanisms of ion transport using techniques like fluorescence microscopy and mathematical modeling. Key contributions include identifying LRRC8 heteromers as essential components of VRAC and elucidating their roles in disease contexts such as hereditary spastic paraplegia. Stauber collaborates across disciplines, publishing in high-impact journals like Science and EMBO Journal . His lab is located at Thielallee 63, Berlin.

Jacopo Di Russoمشاهده پروفایل

پژوهشگر

• Mechanobiology
• Cell-Extracellular Matrix Interactions
• Stem Cell Engineering
• +۳ مورد دیگر

Jacopo Di Russo is an Associated Scientist and independent group leader at the Medical Faculty of RWTH Aachen University. His research integrates cell biology, chemistry, and physics to investigate mechanobiological processes, focusing on cell-extracellular matrix interactions and their role in tissue function. Collaborating with DWI, he develops hydrogel substrates for stem-cell-based models to study tissue plasticity and cell-material interfaces. He holds a cell biology background from the University of Florence, followed by a Marie Curie Fellowship at the University of Münster and postdoctoral work at the Max Planck Institute for Medical Research in Heidelberg. His work emphasizes how mechanical forces regulate cellular behavior in physiological and pathological contexts, particularly in retinal and vascular systems. Key research areas include mechanobiology of epithelial tissues, hydrogel engineering for regenerative medicine, and the role of extracellular matrix heterogeneity in disease progression. His group explores applications in retinal aging models and biomaterial-driven tissue regeneration.

Eckehard Steinbachمشاهده پروفایل

استاد

• Haptic Communication
• Tactile Internet
• Multimedia Systems
• +۴ مورد دیگر

Prof. Dr.-Ing. Eckehard Steinbach is a Full Professor of Media Technology at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology. His research focuses on haptic communication, the Tactile Internet, multimedia systems, and machine learning-driven analysis of sensory data. He holds an IEEE Fellowship (2015) for contributions to visual and haptic communications and has led projects like the Centre for Tactile Internet with Human-in-the-Loop (CeTI). Education: Studied Electrical Engineering at the University of Karlsruhe, University of Essex, and ESIEE Paris. Earned a Ph.D. from Friedrich-Alexander University of Erlangen-Nuremberg (1999). Postdoc at Stanford University (2000–2002). Research Interests: Haptic data compression, teleoperation, networked multimedia systems, and applications of machine learning in sensory data analysis. Key projects include the IEEE 1918.1.1-2024 standard for haptic codecs and 5G-based teleoperation systems. Awards: ERC Starting Grant (2011–2015), Alcatel-Lucent Research Award (2011), VDE-ITG Publication Award (2009). Grants and Projects: Led initiatives in tactile internet, 5G testbeds for eHealth, and radar-based human activity monitoring. Collaborates on robotics and remote collaboration systems via platforms like the Munich 5G Research Hub. Labs/Teams: Chair of Media Technology at TUM, contributing to TUM-IAS and the Munich Institute of Robotics and Machine Intelligence (MIRMI).

Hanna Veselovskaمشاهده پروفایل

پژوهشگر

• Phase Retrieval
• Super-Resolution
• Sigma-Delta Modulation
• +۴ مورد دیگر

Hanna Veselovska is a researcher in the Data Science Group at the Technical University of Munich (TUM), part of the Faculty of Mathematics and the TUM School of Computation, Information and Technology. Her research focuses on Quantization Theory, Mathematical Perspectives of Machine Learning, Image Processing, and Graph Signal Processing. She holds a PhD from the Institute of Mathematics of the National Academy of Sciences of Ukraine (NASU) under Anatoly Holub and has held postdoctoral positions at TU Braunschweig (Germany) and the University of Lübeck (Germany as a DAAD fellow). Current Position: Researcher at TUM Data Science Group PhD: Institute of Mathematics of NASU (2017) Postdoc: TU Braunschweig (2018–2020), University of Lübeck (DAAD fellowship) Her research interests span Phase Retrieval, Super-Resolution, and Sigma-Delta Modulation, with contributions to numerical analysis and signal processing. She has published extensively on topics such as regularized sampling formulas, graph signal quantization, and non-intrusive surrogate modeling. Her work bridges theoretical mathematics with applied data science, with applications in image processing and crashworthiness analysis. Teaching includes courses on Modelling and Simulation with Differential Equations, Random Matrix Theory, and Foundations in Data Analysis at TUM, as well as engineering mathematics courses at TU Braunschweig. Key contributions include advancements in digital halftoning via sigma-delta modulation and recovery of atomic measures on spheres. Her research emphasizes interdisciplinary approaches to solving complex signal processing challenges.

Daniel Cremersمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Deep Learning
• +۱۰ مورد دیگر

Prof. Daniel Cremers is a Professor of Informatics and Mathematics at the Technical University of Munich (TUM), leading the Chair of Computer Vision & Artificial Intelligence within the TUM School of Computation, Information and Technology. His work spans computer vision, machine learning, and mathematical image analysis, with contributions to autonomous systems, SLAM, and self-driving cars. Affiliations: Chair of Computer Vision & AI, TUM School of Computation, TUM. Education: Bachelor's in Mathematics and Physics (University of Heidelberg), Master's in Theoretical Physics (University of Heidelberg), PhD in Computer Science (University of Mannheim). Research Interests: Focuses on computer vision fundamentals, deep learning, variational methods, and real-world applications like autonomous systems. Key areas include 3D reconstruction, SLAM, and geometric processing. Recent Contributions: Over 12 papers accepted to CVPR 2025, including work on probabilistic bundle adjustment and dynamic scene reconstruction. Notable achievements include the ECCV 2024 Koenderink Award for LSD SLAM and the Leibniz Prize (2016). Awards: Leibniz Prize, ERC grants (Starting, Consolidator, Advanced), multiple best paper awards. Teaching: Offers courses like Computer Vision II: Multiple View Geometry and Introduction to Deep Learning. Supervises practical courses on deep learning methods and autonomous systems. Labs/Teams: Leads the Computer Vision Group, actively organizing conferences (e.g., GCPR/VMV 2024) and contributing to open datasets like DeepScenario. Engages in industry through startups and advisory roles.

Andreas Paulمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Real-Time Visualization
• Computational Geometry
• +۳ مورد دیگر

Andreas Paul is a Researcher affiliated with the Department of Computer Science (Informatik V) at the Technische Universität München (TUM), part of the TUM School of Computation, Information and Technology. His research focuses on real-time visualization, computational geometry, and flight simulation systems. He contributed to the FORTWIHR project, developing synthetic vision systems for aircraft, demonstrating expertise in adaptive algorithms and terrain triangulation. Collaborations include work with the TU Braunschweig and ESG, highlighting interdisciplinary engagement. His academic background includes a Master's thesis (1995) and a PhD dissertation (2000) on hierarchical data structures and terrain modeling. Professional activities include conference participation and contributions to visualization technology for aviation applications. Education: PhD in Computer Science, TU Munich, 2000 Master's Thesis: 'Compression of image sequences with hierarchical bases', 1995 Research interests emphasize practical applications of computational methods in aviation and geospatial systems, with a strong focus on real-time performance and algorithmic efficiency. His work bridges computer graphics, geographic information systems, and aerospace engineering, addressing challenges in synthetic vision and terrain data representation.

• Glaciology
• Climate Science
• Environmental Science
• +۵ مورد دیگر

Johannes Freitag is a glaciologist affiliated with the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). He leads the X-Ray-ICE-CT-Lab and AWI-ICE-STORAGE initiatives, focusing on advanced imaging and data management in polar research. His work integrates field experiments, microstructure analysis, and computational modeling to study snow and ice evolution. Freitag holds a PhD from the Alfred Wegener Institute, completing his thesis on Arctic sea ice hydrology in 1999. His research emphasizes polar snow/firn properties, densification processes, microstructure dynamics, and the role of ice cores as climate archives. Key areas include air bubble trapping mechanisms, impurity effects on firn, and CT-based image processing for environmental insights. His studies span Antarctic and Greenland ice sheets, with contributions to improving ice core interpretation through innovative sampling techniques like the dual-tube method and portable LISA box. He collaborates on international projects such as EPICA and IPICS, addressing issues like Holocene melt events, preindustrial biomass burning impacts, and Southern Ocean bioproductivity changes. Freitag’s research also intersects with remote sensing (e.g., Sentinel-3 applications) and interdisciplinary topics like crystal fabric analysis and semantic data management systems (CaosDB). Despite no explicitly listed awards or advisees, his work significantly advances understanding of polar climate archives and cryospheric processes.

• Computational Neuroscience
• Network Anatomy
• Decision Making
• +۱ مورد دیگر

Dr. Marcel Oberländer leads the In-Silico Brain Sciences research group at the Max Planck Institute for Neurobiology of Behavior - caesar and is affiliated with the University of Bonn's Transdisciplinary Research Area: Life and Health. His research integrates network anatomy, cellular physiology, and computational modeling to understand neural mechanisms underlying perception and decision-making. Using the rodent whisker system as a model, his team develops anatomically constrained network simulations to study sensory-guided behaviors like texture discrimination. Recent work reveals how horizontal projections in cortical deep layers gate output signals and how structural heterogeneity maintains excitation-inhibition balance in neural circuits. Oberländer employs multidisciplinary approaches including in vivo electrophysiology, neural tracing, and biologically realistic simulations to establish structure-function relationships in cortical microcircuits.

• Genetics
• Molecular Genetics
• Human Genetics
• +۷ مورد دیگر

Prof. Nilima Prakash is a Professor in the Department of Applied Genetics and Stem Cell Biology at Hamm-Lippstadt University of Applied Sciences. Her research focuses on regenerative medicine for Parkinson’s Disease, stem cell-based therapies, and developmental neurobiology. She leads the Human Stem Cell Research Group, developing protocols for midbrain dopaminergic neuron generation and studying ion channel roles in neurodegeneration. She holds certifications in genetic engineering safety and is an approved animal experimentation researcher. Her expertise spans molecular genetics, forensic genetics, and genetic engineering. She mentors in the TUM Mentoring Program and serves as a journal reviewer and co-editor for Frontiers in Neuroanatomy . Research interests include stem cell differentiation pathways, Wnt signaling, and neurodevelopmental mechanisms in neuropsychiatric disorders. Her work bridges basic science and translational medicine, with recent articles exploring calcium homeostasis in Parkinson’s models and CRISPR-based neuronal reprogramming. She collaborates on projects like the IDGenes database for mouse brain genetic interactions. Grants and funding support her studies on dopaminergic neuron survival and disease modeling. Prof. Prakash is affiliated with the ISSCR, German Genetics Society, and Stem Cell Network NRW. Her lab integrates cutting-edge techniques like live cell imaging and CRISPR-Cas9 engineering for stem cell analysis.

• Medical Physics
• Radiation Therapy
• Medical Imaging
• +۵ مورد دیگر

Dr. Marco Pinto is a Researcher at the Chair of Experimental Physics and Medical Physics, Ludwig-Maximilians-Universität München under Prof. Dr. Katia Parodi. His work focuses on advancing radiation therapy techniques, particularly in proton and carbon ion therapy, with emphasis on range verification using prompt gamma detection and positron emission tomography (PET). He contributes to space missions such as JUICE and BepiColombo, analyzing radiation environments in planetary systems and developing instrumentation for in-situ measurements. Research interests include medical physics applications in proton beam monitoring, small animal irradiation platforms (SIRMIO project), and radiation effects in space exploration. His expertise spans detector design, computational modeling, and experimental validation of therapeutic and space radiation systems. Collaborations extend to missions exploring Mercury and Jupiter's icy moons, addressing challenges in radiation dosimetry and particle physics. Key projects include developing spherical in-beam PET systems for real-time range monitoring and optimizing treatment plans using prompt gamma imaging. His work bridges clinical oncology with space science, advancing technologies for both medical and planetary research domains. Advising focuses on interdisciplinary projects combining medical imaging and radiation physics. He collaborates with international teams on missions like BepiColombo and JUICE, contributing to radiation monitoring systems and environmental analyses. His lab, part of the SIRMIO initiative, pioneers preclinical proton therapy tools for small animal studies.

• Medical Image Segmentation
• Deep Learning
• Computer-Aided Diagnosis
• +۳ مورد دیگر

Zhe Liu is a researcher at Jiangsu University , School of Computer Science and Telecommunication Engineering, China. He has extensive collaborations across institutions including University of Edinburgh , IBM Almaden Research Center , and Nanyang Technological University . His research focuses on medical image segmentation , deep learning , and multimodal learning . Key areas include liver vessel segmentation , pancreas segmentation , lesion detection , and healthcare AI . He has developed frameworks like MMMViT and HI-Net to address challenges in missing modality handling and feature fusion . Recent publications highlight trends in 3D convolutional networks (RC-3DUNet with SOM), semi-supervised learning for segmentation, and anomaly detection in time-series medical data. His work often combines computer vision with clinical applications , emphasizing robustness and data efficiency . He has co-authored over 60 publications (2012-2025), frequently collaborating with Kai Han , Yuqing Song , and Victor S. Sheng on topics like medical imaging , deep learning , and biomedical signal processing .

• Optical Fiber Sensing
• Wireless Communication Networks
• Internet of Things
• +۷ مورد دیگر

Huan Wu is an accomplished academic researcher with a substantial publication record spanning nearly three decades (1996-2025), comprising 63 indexed publications in the dblp database. Their scholarly work demonstrates expertise across multiple technical domains with significant contributions to optical communication systems, wireless networking, and artificial intelligence applications. Research interests focus on the intersection of electrical engineering and computer science, particularly in developing advanced sensing technologies using optical fibers, creating efficient communication protocols for IoT systems, and applying machine learning techniques to environmental monitoring and biomedical applications. Recent work shows a strong trend toward AI integration for infrastructure monitoring systems, including water pipe leak detection and hydrological modeling, as well as healthcare applications like non-invasive glucose monitoring and medical image analysis. The publication portfolio reveals a clear evolution from foundational work in signal processing and communication systems toward increasingly interdisciplinary research that bridges engineering with environmental science and healthcare. Recent publications (2023-2025) demonstrate particular strength in graph neural networks, distributed sensing systems, and AI-driven solutions for critical infrastructure monitoring. Based on publication patterns including consistent first-author contributions, supervisory roles evident in student collaborations, and extensive research output, Huan Wu appears to hold a senior academic position with significant research leadership. The collaborative nature of the work, involving multiple institutions across China and internationally, suggests active participation in major research initiatives and substantial grant funding, though specific details are not provided in the publication records.

• Machine Learning
• Remote Sensing
• Signal Processing
• +۳ مورد دیگر

Jianbo Liu is a prolific researcher with a focus on interdisciplinary fields spanning machine learning, remote sensing, signal processing, and computer vision. His work emphasizes developing advanced algorithms for applications in environmental monitoring, telecommunications, and data-driven decision-making. Liu collaborates frequently with institutions and researchers in China and internationally, contributing to journals like IEEE Transactions on Wireless Communications , Remote Sensing , and Pattern Recognition . Research Interests: Machine learning frameworks for computer vision tasks, remote sensing data analysis, signal processing in communication systems, and optimization of industrial processes. Key Collaborators: Fu Chen, Jimmy S. J. Ren, Ningyuan Cao, Hongsheng Li, and Boyang Cheng. Publications: Over 138 papers across venues such as CVPR, ICCV, and IEEE journals, demonstrating expertise in neural networks, sensor fusion, and spatiotemporal data analysis. His recent work highlights contributions to physics-informed machine learning, gesture recognition via hierarchical attention networks, and secure communication protocols for satellite systems. Liu’s research bridges theoretical advancements with practical applications in environmental science, healthcare, and smart infrastructure.

• VLSI Design
• Integrated Circuits
• Computer Architecture
• +۶ مورد دیگر

Xiaoyang Zeng is a Professor at Tsinghua University's School of Information Science and Technology, Institute of Microelectronics, with an extensive research portfolio in VLSI design, integrated circuits, and hardware acceleration systems. With over 429 publications spanning from 2005 to 2025, Professor Zeng maintains an exceptionally active research program, particularly evident in the high publication volume in recent years (45 papers in 2024 and 28 projected for 2025). His collaborative network includes prominent researchers such as Yibo Fan, Jun Han, Xu Cheng, and Xiaoyong Xue. Professor Zeng's research focuses on cutting-edge areas including Compute-in-Memory architectures, neuromorphic computing, low-power circuit design, and hardware acceleration for AI applications. His work bridges theoretical innovation with practical implementation, as evidenced by numerous publications in top-tier IEEE journals including the Journal of Solid-State Circuits, Transactions on Circuits and Systems, and Transactions on VLSI Systems. Recent work demonstrates particular strength in RRAM-based CIM accelerators, energy-efficient converters, and advanced signal processing techniques. The publication trends show a strategic evolution from traditional circuit design toward emerging computing paradigms, with increasing focus on AI hardware acceleration, neuromorphic systems, and energy-efficient computing solutions. His research group has developed innovative approaches to address challenges in memory-centric computing, analog circuit design, and hardware implementation of machine learning algorithms, with applications spanning consumer electronics, medical devices, and edge computing systems. Selected Scientific Awards: IEEE Journal of Solid-State Circuits Best Paper Award (2022) National Natural Science Award of China (Second Class, 2020) IEEE Asian Solid-State Circuits Conference Best Paper Award (2019) Professor Zeng has successfully advised numerous graduate students who have become active contributors in the field, with several now leading their own research projects. His research has been supported by multiple national-level grants from the National Natural Science Foundation of China and the Ministry of Science and Technology, focusing on next-generation computing architectures and advanced circuit design methodologies. The research group maintains strong industry connections with leading semiconductor companies for technology transfer and practical implementation of research outcomes.