Prof. Dr. Wolfgang Nejdl is a Professor at the Institute for Data Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. He serves as Executive Director of the L3S Research Centre and Leibniz Forschungszentrum Inclusive Citizenship. Web Science Information Retrieval Artificial Intelligence Deep Learning His recent research focuses on AI applications in medicine , multimodal data fusion , and ethical AI systems . Projects include CAIMed (AI in Causal Medicine) and DAISEC (AI & Cybersecurity). His publications span conferences like AAMAS, WWW, and SIGIR. Notable awards include membership in the National Academy of Science and Engineering (acatech) . Former students hold positions at institutions like Stanford, TU Dresden, and ETH Zürich. Current projects involve climate resilience AI , federated learning for healthcare , and quantum-inspired data science .
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱۶-۳۰ از ۸۶۳ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Mehrdad Salehiمشاهده پروفایل
پژوهشگر
Mehrdad Salehi is a researcher at the Chair of Computer Science Applications in Medicine at the Technical University of Munich (TUM) . His work focuses on the intersection of computer science and medical imaging, with expertise in ultrasound technology, deep learning, and surgical navigation systems. Key research areas include sonification of medical data, 3D ultrasound reconstruction, and machine learning-based segmentation. He has contributed to innovative projects like PRO-TIP calibration phantoms and ColibriDoc autonomous docking systems. His publications highlight trends in acoustic feedback mechanisms, neural radiance fields for medical imaging, and real-time image analysis. He can be reached at mehrdad.salehi@tum.de .
Burkhard Maessمشاهده پروفایل
استاد پژوهشی
- Neuroscience
- Auditory Processing
- Signal Analysis
- +۳ مورد دیگر
Dr. Burkhard Maess is a Research Professor and Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences, leading the Methods and Development Group Brain Networks. His research focuses on auditory and language processing, signal analysis, and dynamic modeling of neuronal networks. He holds a Diploma in Physics (University of Leipzig, 1987) and a PhD in Physics (University of Leipzig, 1990). His career includes postdoctoral positions at the Academy of Sciences of the GDR and the Free University of Berlin before joining the MPI in 1995. Since 2000, he has led research groups on MEG/EEG signal analysis and cortical network dynamics. His work integrates advanced neuroimaging techniques like MEG and EEG to study sensory processing, neural network dynamics, and the effects of aging on auditory attention. Key contributions include developing high-resolution BEM-FMM methods for source localization and analyzing cross-frequency coupling in neuroscience data. His group also explores spinal cord electrophysiology and the neural underpinnings of perceptual decision-making. Dr. Maess’ research spans cognitive neuroscience, biomedical engineering, and computational modeling, with a focus on bridging empirical findings with theoretical frameworks in neuroscience.
- Artificial Intelligence in Healthcare
- Biomedical Engineering
- Traditional Chinese Medicine Informatics
- +۳ مورد دیگر
Dr. Jing Wang is a Professor in the Department of Bioinformatics at Southern Medical University's School of Medicine, with extensive research at the intersection of artificial intelligence and biomedical applications. Her work demonstrates strong cross-disciplinary collaboration across medical institutions, engineering departments, and computer science research groups. Her primary research interests include Artificial Intelligence in Healthcare , Biomedical Engineering , and Traditional Chinese Medicine Informatics , with recent publications showing particular expertise in medical imaging analysis, diagnostic assistance systems, and clinical decision support. Her work spans both theoretical algorithm development and practical clinical implementations. Analysis of her 15 most recent publications (2025-2026) reveals a strong trend toward clinically applicable AI systems, with approximately 60% of publications focused on medical diagnostics and treatment support systems. The remaining publications demonstrate expertise in industrial applications of computer vision and fundamental AI research. Her work shows consistent collaboration with both domestic Chinese institutions and international research groups. Notable scientific contributions include: Development of 'Tianyi', a traditional Chinese medicine language model for clinical practice Innovations in bionic soft robotics for rehabilitation assistance Novel approaches to medical image analysis for cancer diagnostics Her research program appears well-funded with consistent publication output across high-impact journals in biomedical engineering, AI, and medical informatics. Current work suggests strong emphasis on translating AI research into clinical practice, particularly in diagnostic support systems and rehabilitation technology.
Julia Herzenمشاهده پروفایل
دانشیار
Prof. Julia Herzen holds the Associate Professorship of Physics in Biomedical Imaging at the Department of Physics , TUM School of Natural Sciences , Technical University of Munich . Her research focuses on advancing X-ray imaging techniques using synchrotron radiation and laboratory sources, with applications in medical diagnostics and tissue analysis. Position: Associate Professor Department: Physics School: TUM School of Natural Sciences University: Technical University of Munich Contact: julia.herzen@tum.de Her core research interests include: Quantitative multi-modal X-ray imaging (spectral & phase-contrast) 3D virtual histology of human tissue Breast cancer detection improvement Lung disease imaging (emphysema, pneumonia) X-ray phase-contrast tomography Dark-field imaging material decomposition Recent publications demonstrate expertise in dark-field imaging for lung pathology , phase-contrast CT for organoid visualization , and spectral X-ray applications in multi-material differentiation . Her team explores clinical translation of X-ray techniques for non-invasive diagnostics . She supervises PhD students and teaches Biomedical Engineering courses, including: Quantitative X-Ray Imaging (3 VI) Image Processing in Physics (2 VO) Biostatistics (2 VO) Advanced Lab Courses in X-ray Micro-CT
Hao Liuمشاهده پروفایل
پژوهشگر
Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols
- Machine Learning
- Computer Vision
- Signal Processing
- +۶ مورد دیگر
Dongwook Kim is affiliated with the Korea Advanced Institute of Science & Technology (KAIST) as a faculty member in the Department of Business and Technology Management under the College of Business. His research spans multiple domains including machine learning, robotics, signal processing, and biomedical engineering. Key contributions in Computer Vision (CNN-based semantic segmentation, 3D point cloud analysis) Significant work in Hardware Design (energy-efficient processors, neuromorphic computing) Interdisciplinary expertise in Medical Imaging (bone age assessment, retinal biomarkers) and Cybersecurity (attack detection, network analytics) Publications since 2015 demonstrate sustained innovation in AI applications , Signal Processing , and Smart City Governance . His work often integrates theoretical advances with practical implementations in real-world systems. No scientific awards or student mentorship details are explicitly documented in the provided records.
Matthias Kuhl is a Professor at the Institute of Microsystems Technology (IMTEK) at the University of Freiburg since April 2022. He leads research projects focused on neural probes, biomedical implants, and integrated microelectronic systems. His work includes developing low-power neural interfaces, stress sensors, and energy-efficient circuits for medical applications. Research Interests Neural probes with electronic depth control Implantable biomedical devices CMOS integrated sensors and actuators Energy harvesting for autonomous systems Microfabrication and 3D-printed electronics Key Projects Advanced EDC: Intracortical neural probes with electronic depth control ComBiNE: Bidirectional neural exchange components SEAM-WiT: Implantable neural probe transceivers Multi-material 3D-printed electronics His recent publications emphasize low-power neural front-ends, stress sensor integration, and biomedical system design. He advises numerous graduate students on topics ranging from CMOS circuit design to biohybrid systems. Labs & Teams He leads the Professur für Mikroelektronik lab, specializing in microelectronic systems for biomedical and industrial applications. Collaborates with orthodontic, neurobiology, and materials science groups.
- Microfluidics
- Lab-on-a-Chip
- Bio-MEMS
- +۶ مورد دیگر
Prof. Dr. Roland Zengerle serves as Full Professor for Application Development at the Institute of Microsystems Technology within the Faculty of Engineering at Albert Ludwigs University of Freiburg, concurrently holding the position of Director at Hahn-Schickard Institute for Microanalysis Systems in Freiburg. His academic leadership spans microsystems engineering with a focus on translational research bridging fundamental science and clinical applications. Zengerle's research expertise centers on Microfluidics, Lab-on-a-Chip systems, Bio-MEMS, Electrochemical Energy Systems, and Tomographic Reconstruction of Mesoporous Materials. He pioneers hybrid manufacturing techniques integrating molten metal printing with polymer processing to develop point-of-care diagnostic platforms and advanced energy systems. Current projects include UTI-Diag for urinary tract infection diagnosis and PhotonMed, a 32-million-euro medical technology initiative where his MEMS Applications Laboratory develops centrifugal microfluidic solutions. Analysis of his recent publications reveals a dominant trend toward multi-technology integration: centrifugal microfluidics combined with 3D bioprinting for organoid-based drug testing, molten metal printing for flexible electronics, and bead-based immunoassays for infectious disease detection. The work demonstrates strong clinical translation focus, particularly in cancer diagnostics (circulating tumor cell isolation), infectious disease testing (TB diagnostics), and regenerative medicine (spheroid/organoid handling). His laboratory has secured significant funding for high-impact projects including: UTI-Diag: Molecular diagnostics for urinary tract infections PhotonMed: Medical technology innovation consortium livMatS: Living, Adaptive and Energy-autonomous Materials Systems Zengerle actively mentors researchers through Freiburg's Master Lab program and Writer's Studio initiative while promoting young talent via Bootcamp training. His group maintains strategic alliances with Hahn-Schickard spin-offs and industry partners, leveraging university cleanroom facilities and specialized service centers for microfabrication. The MEMS Applications Laboratory operates as a hub for interdisciplinary innovation, combining microfabrication expertise with clinical insights to develop commercializable diagnostic solutions. Current infrastructure supports centrifugal microfluidic cartridge development, 3D-bioprinting of tissue models, and electrochemical sensor integration, with ongoing work focused on automating complex biological workflows for point-of-care applications.
Mikhail Gelfand is a Full Professor and Director of the Center for Molecular and Cellular Biology at Skolkovo Institute of Science and Technology (Skoltech), where he also serves as Vice President for Biomedical Research. His distinguished career spans multiple prestigious institutions including Lomonosov Moscow State University and the Higher School of Economics. His educational background includes: 1985: MSc in mathematics (functional analysis) 1993: PhD in physics-mathematics (biophysics) 1998: DSc in biology (molecular biology) 2007: full professor (bioinformatics) Professor Gelfand's research focuses on molecular evolution, comparative genomics, systems biology, and metagenomics. His work examines eukaryotic processes including alternative splicing, mRNA editing, and chromatin structure, as well as bacterial genome evolution and transcription regulation. His lab combines data on three-dimensional chromatin structure, epigenetic states, and gene expression to obtain an integrated view of genome functioning across diverse organisms from humans to amoebae. One major research direction focuses on the evolution of transcript splicing and editing, while comparative analysis of bacterial genomes yields functional annotations of novel enzymes, transporters, and transcription factors. His recent publications demonstrate a strong focus on RNA editing in cephalopods, bacterial genome analysis, and computational approaches to understanding chromatin structure. The work spans molecular biology, evolutionary biology, and bioinformatics, with particular emphasis on how RNA editing contributes to adaptation and molecular evolution across metazoans. His research shows how edited adenines are more frequently substituted with guanine in evolution than their unedited counterparts, suggesting RNA editing may enhance adaptation. His notable awards include: The President of Russian Federation's Award for Young Doctors of Science (2000) The "Best Scientist of the Russian Academy of Sciences" award (2004) A. A. Baev Prize in Genomics and Genoinformatics (2007) Member of Academia Europaea (2010) As Director of the Center for Molecular and Cellular Biology, Professor Gelfand leads a research group that combines computational and experimental approaches to study genome function and evolution. His lab's work has significant implications for understanding molecular mechanisms of evolution and adaptation across diverse biological systems, from bacteria to complex eukaryotes. His research on metagenomics extends to practical applications in areas including coral disease, aphids, and oil wells.
Irena Koprinska is a prominent researcher at the University of Sydney with over 150 publications from 1996 to 2025. Her work spans multiple interdisciplinary domains with significant contributions to machine learning applications in educational technology, time series forecasting, and health informatics. She maintains strong research collaborations, particularly with Kalina Yacef (38 joint publications), Mashud Rana (26 papers), and Bryn Jeffries (22 papers), indicating leadership in her research group. Her research interests focus on practical applications of machine learning across diverse domains. In educational data mining, she has pioneered methods for predicting student performance in programming courses, analyzing syntax errors, and developing automated hint generation systems. Her work in time series forecasting has made significant contributions to solar power prediction using advanced neural network architectures. Additionally, she has applied machine learning techniques to medical domains, particularly in sleep disorder detection and analysis. The analysis of her 15 most recent publications (2022-2025) reveals a continued focus on educational technology and time series analysis, with increasing attention to interpretable methods and health applications. Her work demonstrates a consistent trajectory of applying sophisticated machine learning techniques to solve real-world problems across multiple domains, with particular emphasis on creating practical tools for education and renewable energy management. Notable Research Contributions: Development of the HINTS framework for automated programming hint generation Innovative approaches to multistep-ahead time series forecasting Applications of deep learning to sleep disorder detection Methods for predicting student performance in programming education Her publication record in top venues including Machine Learning journal, AIED, EDM, and IJCNN demonstrates significant impact in both machine learning and educational technology communities. The consistent output of high-quality research over nearly three decades indicates sustained scholarly productivity and leadership in her fields of expertise.
Tsun-Ming Tseng is a Professor and principal investigator at the Chair of Electronic Design Automation at the Technical University of Munich (TUM). He leads the Emerging Technology Group and oversees multiple DFG/BMBF-funded research projects in the areas of microfluidic large-scale integration, optical network-on-chip design, and novel microfabrication techniques. Dr. Tseng's research focuses on design automation for emerging technologies, with particular expertise in three main areas: microfluidic large-scale integration, optical network-on-chip systems, and novel microfabrication processes. His work bridges the gap between electronic design automation and cutting-edge applications in bioengineering, photonics, and advanced manufacturing. His research group develops sophisticated algorithms and tools for optimizing design, reliability, and performance in these emerging domains. Analysis of Dr. Tseng's recent publications reveals a strong focus on practical implementation challenges in emerging technologies. His work spans both theoretical algorithm development and practical system implementation, with particular emphasis on reliability, performance optimization, and manufacturing considerations. The research shows increasing integration between different technology domains, particularly the convergence of microfluidics, optical networking, and electronic design automation. Dr. Tseng has been awarded multiple significant research grants including: "DE-TW-CloudWRONoC" (BMBF-NSTC project, PI, 2025-2028, EUR 797.7K) "DE-TW-PI3D" (BMBF-NSTC project, PI, 2024-2027, EUR 391.6K) "Physical Design for Microfluidic Large-Scale Integration" (DFG research grant, PI, 2024-2026, EUR 331.9K) Multiple other DFG and industrial projects totaling over EUR 3 million in funding He has successfully supervised numerous doctoral researchers and postdoctoral fellows, with current group members including Jiahui Peng, Debraj Kundu, Liaoyuan Cheng, and several others. Dr. Tseng leads the Emerging Technology Group at TUM, which focuses on developing design automation methodologies for next-generation technologies. The group maintains strong collaborations with international institutions, including partnerships with researchers in Taiwan and Hong Kong. The team operates state-of-the-art facilities for research in microfluidics, optical networking, and advanced microfabrication techniques.
- X-ray Imaging
- Computed Tomography
- Medical Imaging
- +۴ مورد دیگر
Nikolai Gustschin is a researcher affiliated with the Chair of Biomedical Physics at the Technical University of Munich (TUM) , associated with the Faculty of Medicine and the Department of Physics . His work focuses on developing advanced imaging techniques for clinical applications. Research Interests: X-ray grating interferometry, dark-field CT, phase contrast imaging, clinical translation of imaging technologies, grating fabrication quality assessment. Recent Publications highlight his contributions to dark-field CT algorithms, vibration modeling for interferometers, and grating fabrication methods. Collaborations with experts in biomedical physics and engineering are central to his work.
- MEMS Technology
- Microfluidics
- Acoustic Sensors
- +۳ مورد دیگر
Prof. Gabriele Schrag holds the Professorship of Microsensors and Actuators at the Technical University of Munich (TUM), within the TUM School of Computation, Information and Technology. Her research focuses on MEMS (Micro-Electro-Mechanical Systems), including microsensors, actuators, and their applications in acoustics, microfluidics, and bioengineering. She has pioneered work in virtual prototyping for system-level modeling to enhance device robustness and performance. Education: PhD (summa cum laude) from TUM on 'Modeling coupled effects in microsystems' Habilitation in sensor systems technology (2018) Acting head of the Chair of Technical Electrophysics (2018-2023) Research emphasizes acoustic MEMS transducers , electrohydrodynamic printing , and physics-based modeling . Notable projects include developing piezoelectric MEMS microphones with corrugated membranes and integrated micropump systems. Awards include the Bavarian Prize for Good Teaching (2021) and Eurosensors Fellow Award (2019). Her work bridges virtual prototyping with real-world applications , addressing challenges in miniaturization, energy efficiency, and sensor integration for medical and industrial systems.
Prof. Dr. Sebastian Schlücker is a full professor in the Department of Physical Chemistry at the University of Duisburg-Essen , where he leads the Molecular Biophotonics and Nanodiagnostics research group within the Faculty of Chemistry. He is actively engaged in research, teaching, and academic leadership, with a strong focus on advanced spectroscopic techniques for biomedical and analytical applications. His research interests lie at the intersection of nanophotonics, plasmonics, and bioanalytical chemistry . Key areas include surface-enhanced Raman spectroscopy (SERS) , single-particle spectroscopy , laser diagnostics , and the design of functionalized metal colloids for biosensing and tumor diagnostics. He emphasizes a theory-guided approach combining simulation and experiment to tailor nanoparticle properties. His recent publications (2023–2025) reflect a strong trend toward quantitative, label-free molecular diagnostics , point-of-care testing , and in situ monitoring of catalytic and biological processes . The work spans fundamental plasmonics to clinical applications, particularly in cancer detection and immunoassays using SERS nanotags. International Raman Innovation Prize He mentors students and researchers, supervises theses, and collaborates widely across disciplines. His group develops advanced instrumentation, including portable SERS readers , fs-laser laboratories , and automated nanoparticle synthesis systems (e.g., BONAPARTE robot). He teaches master’s courses such as NanoBioPhotonics and Optical Spectroscopy , and is involved in STEM outreach.
فقط ۷۵۰ نتیجه اول نمایش داده میشود. برای رسیدن به نتایج دقیقتر، جستوجو را با فیلترها محدودتر کنید.