جست‌وجوی استاد و پژوهشگر

• Composite Materials
• Materials Science
• Lightweight Construction
• +۳ مورد دیگر

Prof. Dr.-Ing. Kay Weidenmann serves as Chair holder of Hybrid Composite Materials at the Institute of Materials Resource Management within the Faculty of Mathematics, Natural Sciences, and Materials Engineering at Augsburg University. His research focuses on developing innovative composite material systems with particular emphasis on hybrid metal-ceramic structures and lightweight construction solutions. Previously, he held positions at the Karlsruhe Institute of Technology (KIT) where he was nominated as associate professor in 2015 and completed his habilitation in Materials Science in 2012. Doctorate (Dr.-Ing.) in Mechanical Engineering, Universität Karlsruhe (TH), 2006 Habilitation in Materials Science, Faculty of Mechanical Engineering, 2012 Study of materials science at University of Stuttgart, 1998-2003 Weidenmann's research spans the development of process routes for hybrid materials (particularly fiber-reinforced polymer-metal hybrids), materials science evaluation of lightweight construction concepts, microstructure-mechanical property relationships in composites, and novel in-situ test methods for damage characterization. His work bridges fundamental materials science with practical engineering applications, particularly in automotive and aerospace sectors where weight reduction is critical. Analysis of his recent publications reveals strong focus on interpenetrating metal-ceramic composites, advanced characterization techniques using X-ray CT, and innovative manufacturing approaches including additive manufacturing of metallic glass structures. His work increasingly incorporates computational methods, machine learning for microstructure analysis, and sustainability considerations through composite recycling research. KIT Certificate "Academic Leadership" (2014) Baden-Wuerttemberg certificate in university didactics (2009) Prof. Weidenmann leads an active research group comprising postdoctoral researchers and graduate students working across multiple research areas including processes, materials and mechanics, condition monitoring, and robotics. His group maintains strong industry collaborations and pursues both fundamental research and applied projects addressing real-world engineering challenges in composite materials. Current work focuses on self-healing composites, sustainable recycling methods, and advanced characterization of hybrid material systems.

Ciarán Doneganمشاهده پروفایل

پژوهشگر ارشد

• Regulatory Genomics
• Explainable AI
• Geometric Deep Learning
• +۱ مورد دیگر

Ciarán Donegan is a Research Fellow in the Machine Learning group at the Technical University of Berlin and BIFOLD (Berlin Institute for the Foundations of Learning and Data), with a concurrent guest researcher position in the Ohler Lab at the Max Delbrück Center for Molecular Medicine. His primary research focuses on applying deep learning methodologies to elucidate gene regulation mechanisms within molecular biology. Education: M.A.I. in Electronic & Computer Engineering from Trinity College Dublin (2021) B.A.I. in Electronic & Computer Engineering from Trinity College Dublin (2020) His research program integrates Regulatory Genomics with cutting-edge machine learning techniques, emphasizing Explainable AI frameworks and Geometric Deep Learning architectures. This interdisciplinary approach targets complex biological systems, particularly in modeling transcriptional regulation and epigenetic modifications through neural network interpretability. Applications extend to disease mechanism analysis and therapeutic target identification in life sciences contexts. Publication trends reveal dual-domain expertise: the 2022 sports broadcasting paper demonstrates real-time computer vision capabilities for automated production systems, while the 2021 VPU-specific CNN research pioneers hardware-aware neural architecture search. These works collectively underscore a methodological thread in optimizing deep learning for constrained environments—whether computational (edge devices) or operational (live sports)—while maintaining biological research as his core focus area. No scientific awards were documented in the source materials. Advisory activities and grant funding details remain unspecified in available records. He operates within collaborative research ecosystems spanning TU Berlin's Machine Learning group, BIFOLD's interdisciplinary data science initiatives, and the Ohler Lab's genomic regulatory studies at the Max Delbrück Center, facilitating cross-institutional innovation in AI-driven life sciences.

• Wireless Communications
• Signal Processing
• Embedded Systems
• +۴ مورد دیگر

Ali Dziri is a permanent researcher at CentraleSupélec's Cedric Laboratory , focusing on wireless communications, signal processing, and embedded systems. His work spans 2004–2023 with key contributions in UWB communication, IoT networks, video/image transmission, and real-time tracking algorithms. His research interests include: Wireless Communications Signal Processing Embedded Systems Machine Learning IoT Networks Video/Image Compression Recent publications highlight trends in neural networks for channel equalization, MIMO relays for WSNs, and 5G D2D communication protocols. He has no listed scientific awards or advisees.

Ofer Kfirمشاهده پروفایل

پژوهشگر

• Quantum Optics
• Electron-Photon Coupling
• THz Spectroscopy
• +۴ مورد دیگر

Dr. Ofer Kfir is a Senior Academic Staff member at the Iby and Aladar Fleischman Faculty of Engineering , Tel Aviv University , where he leads the Quantum Nano Spectroscopy Lab in the School of Electrical Engineering. His research bridges ultrafast photonics and electron nanoscale spectroscopy to explore quantum phenomena. University: Tel Aviv University School: Iby and Aladar Fleischman Faculty of Engineering Department: School of Electrical Engineering Email: kfir@tauex.tau.ac.il Research Interests : The lab focuses on coherence in quantum systems, particularly: electron-photon entanglement, optical microresonator coupling, wavefunction control, THz-driven quantum materials, and magnetic imaging with femtosecond resolution. Projects include national quantum e-microscopy initiatives and high-harmonic lensless microscopy . Team : Ph.D. Students : Hadar Aharon, Gilad Pollack M.Sc. Students : Eitan Kazakevich, Isaac Reichman, Amer Sajrawi, Itamar Shaked

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Cem Eteke is a doctoral candidate at the Chair of Media Technology within the Munich Institute of Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich (TUM). His research focuses on semantic image and video synthesis, with an emphasis on explainable generative models, diffusion models, and their applications to semantic communication systems. Education: B.Sc. in Computer Engineering and Electrical & Electronics Engineering (2017), M.Sc. in same field (2019) from Koc University, Istanbul. Professional Experience: Former Data Scientist and AI Engineer, with brief research on high-dimensional non-convex optimization algorithms. Research Trends: His recent publications (2022-2025) highlight advancements in real-time semantic communication, diffusion models for video synthesis, and neural rendering techniques for indoor scene segmentation. Key themes include lossy coding strategies, spatially adaptive conditioning, and temporally consistent generative modeling. Projects: Involved in research initiatives like the Centre for Tactile Internet with Human-in-the-Loop (CeTI) , 5G Testbed Bayern , and KMU-Innovativ: KIMaps , focusing on haptic communication, indoor navigation, and semantic scene understanding.

Kapil Ahujaمشاهده پروفایل

استاد

• Machine Learning
• Network Science
• Computational Optimization
• +۴ مورد دیگر

Prof. Kapil Ahuja is a Full Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Indore (IIT Indore), where he heads the Mathematics of Data Science and Simulation (MODSS) research lab. After completing dual Master's degrees and a Ph.D. from Virginia Tech (USA) followed by postdoctoral work at the Max Planck Institute in Germany, he has held visiting positions at UT Austin, IMT Atlantique, Sandia National Labs, TU Dresden, and TU Braunschweig. His administrative roles include founding Dean of International Affairs and former Head of Computer Science & Engineering at IIT Indore. Education: Ph.D. in Mathematics, Virginia Tech (2011) M.S. in Mathematics, Virginia Tech (2009) M.S. in Computer Science, Virginia Tech (2007) B.Tech. in Mechanical Engineering, IIT (BHU) Varanasi (2001) Research Focus: Prof. Ahuja's work bridges theoretical advances with real-world applications, emphasizing machine learning algorithms for plant/cancer studies, game-theoretic poverty reduction models, exascale climate modeling solvers, and drone trajectory optimization. His interdisciplinary approach integrates numerical linear algebra with network science to solve complex systems problems across healthcare, agriculture, and climate science, supported by 4.85 Crores INR in external funding. Publication Trends: Recent work demonstrates growing emphasis on AI-driven optimization for physical systems (drones, climate models) and biomedical applications (cancer classification). His publications increasingly feature cross-disciplinary collaborations between computer science, biology, and economics, with notable contributions in explainable AI for healthcare and resource allocation algorithms for social networks. Scientific Recognition: National Teacher's Award (2024) from the President of India Five-time recipient of IIT Indore's Best Teacher Award (2013-2023) Best Poster Award at International Workshop on Game Theory & Networks (2019) Steeneck Graduate Research Fellowship (Virginia Tech, 2011) Multiple SIAM travel awards for international conferences Mentorship & Service: Prof. Ahuja has graduated 5 Ph.D. and 4 M.S. (Research) students while mentoring 75 B.Tech. projects. He serves as Associate Editor for Applied Intelligence Journal (Springer Nature) and Knowledge and Information Systems, organizes international conferences, and reviews for 35+ academic sources. His administrative leadership significantly expanded IIT Indore's global partnerships through the Research Park initiative. Research Infrastructure: The MODSS lab maintains active collaborations with Oak Ridge National Lab, Sandia National Labs, and European institutions. Current projects include AI-optimized drone swarms for agricultural monitoring and game-theoretic models for poverty intervention, utilizing high-performance computing resources for large-scale simulations.

• Machine Learning
• Computer Vision
• Autonomous Driving
• +۴ مورد دیگر

Ross Greer is an Assistant Professor in the Department of Computer Science & Engineering at the University of California Merced. He leads the Mi³ Lab, focusing on machine intelligence, human-agent interaction, and safe autonomous systems. Education : B.S. and B.A. in EECS, Engineering Physics, and Music from UC Berkeley (2015), M.S. in Electrical & Computer Engineering from UC San Diego (2018), Ph.D. in Electrical & Computer Engineering at UC San Diego (2021) under Mohan Trivedi and Shlomo Dubnov. His research explores computational intelligence for open-world adaptability, robustness to rare events, and safety in chaotic environments. Key applications include autonomous driving, driver state analysis, trajectory prediction, and AI-assisted musical creativity. Recent publications emphasize vision-language models, active learning for 3D object detection, and safety metrics. Awards include the 2024 Interdisciplinary Research Award, Henry Booker Award for Ethical Engineering, and multiple best poster/grand prizes. Scientific Awards : 2024 Interdisciplinary Research Award 2024 Henry Booker Award for Exemplary Ethical Engineering Postdoctoral Networking Fellowship (Germany's Academic Exchange Service) Grand Prize (AWS Automotive Day competition at IEEE Intelligent Vehicles Symposium, 2023) Best Poster Awards (2021/2023 Jacobs Research Expo) He also co-authored the textbook Deep and Shallow: Machine Learning in Music and Audio (Chapman & Hall, 2023) and serves as a music director for UCSD's Symphonic Student Association and UC Merced's marching band.

• Virtual Reality
• Augmented Reality
• Computer Vision
• +۴ مورد دیگر

Prof. Dr. Didier Stricker is a leading academic in computer science, serving as Scientific Director at the German Research Center for Artificial Intelligence (DFKI) and Professor at the University of Kaiserslautern-Landau (RPTU). His career spans over two decades, including leadership roles at Fraunhofer IGD and founding the Augmented Vision research unit at DFKI/RPTU, which now includes ~30 researchers. Education: Electrical Engineering (Technical University of Grenoble, Karlsruhe) PhD: Computer Vision-based Calibration and Tracking Methods for Augmented Reality (2002, TU Darmstadt) His research focuses on virtual and augmented reality , computer vision , human-computer interaction , and on-body sensor networks . He leads major EU/national projects like LUMINOUS (Language-Augmented XR) and SHARESPACE (Ethical Hybrid Shared Spaces), with industrial partnerships including Sony, Google, and John Deere. Recent publications emphasize 3D reconstruction , neural network optimization , and XR systems . Key trends include event camera processing , scene flow estimation , and multimodal AI for industrial applications . He holds patents in AR tracking and has received the 2006 Innovation Prize from the German Society of Computer Science. Scientific Awards : Innovation Prize (2006) Best Paper/Demonstration Awards at ISMAR, EUSIPCO, CVPR, and ICRA As a reviewer for journals and conferences in VR/AR and computer vision, he contributes to shaping research standards. His lab ( AG Augmented Vision ) combines academic and industrial collaborations to advance cognitive interfaces and extended reality systems.

Benedikt Wirthمشاهده پروفایل

استاد

• Optimisation and calculus of variations
• image processing
• scientific computing
• +۹ مورد دیگر

Prof. Dr. Benedikt Wirth is a Professor of Mathematics at the University of Münster, Germany, affiliated with the Institute for Analysis and Numerics within the Department of Mathematics and Computer Science. He is an active researcher and educator specializing in optimization and calculus of variations, with significant contributions to mathematical imaging and shape analysis. His research interests include image processing, scientific computing, numerical analysis, optimization, shape spaces, geodesics in shape space, variational methods, elastic deformation, and optimal transport. Wirth has developed innovative mathematical frameworks for shape analysis, particularly focusing on Riemannian metrics for shape spaces and variational approaches to shape comparison and optimization. His recent publications (2023-2025) demonstrate continued leadership in mathematical optimization, with particular focus on PET reconstruction, dimension reduction techniques, manifold embeddings, and branched transport theory. His work bridges theoretical mathematics with practical applications in medical imaging and computer vision, showing particular strength in connecting geometric analysis with computational methods. CRC 1450 - A05: Targeting immune cell dynamics by longitudinal whole-body imaging and mathematical modelling CRC 1450 - A06: Improving intravital microscopy of inflammatory cell response by active motion compensation EXC 2044 - C1: Evolution and asymptotics EXC 2044 - C2: Multi-scale phenomena and macroscopic structures EXC 2044 - C3: Interacting particle systems and phase transitions EXC 2044 - C4: Geometry-based modelling, approximation, and reduction Prof. Wirth actively supervises numerous bachelor's and master's students, with over 40 theses completed under his guidance since 2015. His teaching portfolio includes courses on inverse problems, numerical methods for partial differential equations, shape spaces, optimization, and optimal transport. He has consistently maintained an active research program while contributing significantly to the education of the next generation of mathematicians.

• Knowledge Representation and Reasoning
• Geometry Processing
• Machine Learning
• +۱ مورد دیگر

Dr. Stavros Nousias is a researcher at the Chair of Computing in Civil and Building Engineering at the Technical University of Munich , focusing on applications of Artificial Intelligence in the Built Environment . His work bridges Knowledge Representation and Reasoning , Geometry Processing , and Machine Learning to advance construction informatics and digital twinning. Research Interests: AI for building evacuation prediction, technical drawing segmentation, BIM optimization, and respiratory disease modeling. Publications: 15+ peer-reviewed articles on topics including graph neural networks for construction simulations, pulmonary airflow analysis, and heritage site monitoring. Supervised Theses: Guided projects on AI-based BIM command prediction and robotized construction simulation . Labs: Active in the BIM-Lab and Robotic Fabrication Lab . Teaching: Co-instructor for courses like Artificial Intelligence in Engineering and Computation in Engineering 1 .

• Synthetic Aperture Radar (SAR)
• Microwave Remote Sensing
• Digital Beamforming
• +۶ مورد دیگر

Prof. Dr.-Ing. Alberto Moreira is the Director of the Microwaves and Radar Institute at the German Aerospace Center (DLR) and a Full Professor in Microwave Remote Sensing at Karlsruhe Institute of Technology (KIT) . He leads pioneering work in synthetic aperture radar (SAR) systems, including the TanDEM-X and TerraSAR-X missions. Born in São José dos Campos, Brazil B.Sc./M.Sc. in Electrical Engineering (Aeronautical Technological Institute, 1984/1986) Ph.D. (summa cum laude, Technical University of Munich, 1993) Research Focus : Innovative SAR system design (polarimetric interferometry, tomography) Digital beamforming and multi-static radar architectures Global Earth observation through TanDEM-X and Tandem-L missions Quantum annealing applications in SAR processing Planetary radar systems for Venus exploration (EnVision, VERITAS) Scientific Impact : Author/co-author of >500 peer-reviewed publications H-index: 66 (Google Scholar) Holder of >40 patents in radar and antenna technology Awards & Leadership : IEEE Dennis J. Picard Medal (2023) IEEE GRSS Distinguished Achievement Award (2014) President of IEEE GRSS (2010) Founding Chair of IEEE GRSS German Chapter Principal Investigator for Helmholtz Alliance Earth System Dynamics (2012-2018) Collaborations : Works with ETH Zurich, TU Delft, and ESA on missions like Sentinel-1, BIOMASS, Harmony, and VERITAS. His institute develops cutting-edge technologies for spaceborne SAR systems.

Clara Saracenoمشاهده پروفایل

استاد پژوهشی

• Ultrafast Laser Physics
• Terahertz Photonics
• Mid-IR Photonics
• +۵ مورد دیگر

Professor Clara Saraceno is a Research Professor at Ruhr University Bochum's Faculty of Electrical Engineering, where she leads the PULS research group. Her work focuses on cutting-edge laser technology with applications spanning from fundamental physics to practical implementations in terahertz science. Her research interests center on ultrafast laser physics and terahertz photonics, with particular expertise in high-power thin-disk laser systems, mid-IR sources, and terahertz generation techniques. Professor Saraceno's work bridges fundamental laser physics with practical applications, developing increasingly powerful laser systems capable of driving advanced terahertz sources. Professor Saraceno maintains an exceptionally productive research program, with numerous publications each year in top optics and photonics journals. Her recent work (2024-2025) shows particular strength in high-repetition-rate terahertz generation, nonlinear pulse compression techniques, and advancing the performance boundaries of mid-IR laser systems operating around 2 µm. She actively contributes to the scientific community through conference participation and leadership in her field, with regular presentations at major international venues including CLEO, IRMMW-THz, and Ultrafast Optics conferences. Professor Saraceno teaches courses in Ultrafast Laser Physics and Technology (winter semester), Mid-IR and Terahertz Photonics (summer semester), and the Laser Colloquium throughout the academic year, providing students with direct access to her expertise in advanced laser systems. Her research group appears well-funded and productive, with consistent publication output demonstrating technical innovation in laser development and terahertz applications, positioning her as a significant contributor to advancing high-power ultrafast laser technology.

• Endocrine Surgery
• Thyroid Cancer
• Parathyroid Disorders
• +۶ مورد دیگر

Jennifer Braemar Ogilvie, MD, is Associate Professor of Surgery and Chief of the Section of Endocrine Surgery at Yale School of Medicine. She is affiliated with the Yale Cancer Center and Smilow Cancer Hospital, where she leads the Endocrine Cancers Program. Her clinical practice focuses on thyroid, parathyroid, and adrenal tumors, with particular expertise in complex endocrine surgical procedures. Dr. Ogilvie completed her medical training at Harvard University, followed by surgical residency and endocrine surgery fellowship at the University of California, San Francisco. Prior to Yale, she held faculty positions at the University of Pittsburgh Medical Center and New York University Langone Health, where she served as Director of Endocrine Surgery at Bellevue Hospital. Her research interests span health systems research, clinical outcomes in endocrine surgery, healthcare disparities, and surgical education. She leads a research team investigating Enhanced Recovery after Surgery protocols, oncocytic thyroid cancer biomarkers, and secondary hyperparathyroidism outcomes. Her work often examines how socioeconomic factors affect cancer presentation and treatment outcomes. Dr. Ogilvie's publication record demonstrates consistent contributions to endocrine surgery literature, with recent work focusing on environmental risk factors for thyroid cancer, diagnostic approaches to parathyroid disorders, and innovations in surgical education. Her research often addresses critical questions about appropriate surgical indications and the movement toward less aggressive interventions for low-risk conditions. As an educator, Dr. Ogilvie is committed to training the next generation of surgeons and has published on assessment methods for medical student clinical reasoning and the impact of curriculum changes on surgical education. She believes in the importance of shared decision making with patients and tailoring surgical approaches to individual patient needs while maintaining excellent oncologic outcomes.

Jan Fröhlichمشاهده پروفایل

استاد

• High Dynamic Range (HDR)
• Wide Color Gamut (WCG)
• Image Encoding
• +۵ مورد دیگر

Prof. Dr. Jan Fröhlich is a Professor for Motion Picture Engineering at Stuttgart Media University (HdM), specializing in advanced imaging technologies. His research focuses on high dynamic range (HDR) and wide color gamut (WCG) image encoding, color rendering, camera metrology, and HDR workflows. Prior to his academic appointment, he held key industry positions including Senior Image Scientist at ARRI Munich where he contributed to professional cinema camera systems, and Dolby Laboratories where he helped develop the ITU Rec.2100 ICtCp color space and Dolby Vision platform. He also served as Technical Director at CinePostproduction GmbH. His core research areas include: HDR/WCG encoding and color science Virtual production workflows Camera metrology and image sensor technology Perceptual aspects of high frame rate and HDR imaging Real-time HDR/SDR conversion systems Recent publications demonstrate extensive work in virtual production technologies, including LED volume workflows, HDR broadcast graphics, and light field displays. His research consistently addresses both theoretical foundations and practical implementation challenges in cinematography and broadcast engineering.

• Physical Chemistry
• Nanotechnology
• Spectroscopy
• +۴ مورد دیگر

Professor Eckart Rühl holds a faculty position in the Department of Physical and Theoretical Chemistry at the Institute of Chemistry and Biochemistry, Free University of Berlin. His research program bridges fundamental physical chemistry with applied nanotechnology, focusing on molecular dynamics and therapeutic delivery systems. Research interests include: High-resolution inner-shell spectroscopy of molecules and molecular clusters Photoionization dynamics and electronic structure determination Nanoparticle-cell membrane interaction mechanisms Redox-responsive nanocarrier drug delivery systems Mid-infrared chemical imaging via Bayesian compressed sensing Professor Rühl has secured extensive DFG funding through diverse mechanisms, serving as Speaker for Collaborative Research Center SFB 1112 on nanocarriers and leading major equipment projects including a cryo scanning electron microscope. His work consistently combines experimental precision with theoretical modeling across completed projects in photoexcitation, nanoparticle physics, and biomedical applications. Current research directions emphasize label-free cellular imaging and ultrafast laser-induced phenomena in deposited nanoparticles.