جست‌وجوی استاد و پژوهشگر

Christof Kochمشاهده پروفایل

استاد پژوهشی

• Neuroscience
• Consciousness
• Computational Neuroscience
• +۲ مورد دیگر

Christof Koch is a renowned neuroscientist serving as Meritorious Investigator at the Allen Institute for Brain Science and Chief Scientist at the Tiny Blue Dot Foundation. His primary research explores the neural mechanisms underlying consciousness, integrating theoretical neuroscience with experimental approaches. With over 300 publications, his work spans neurophysiology, computational modeling, and clinical applications of consciousness research. His research focuses on understanding how neuronal activity gives rise to subjective experience, utilizing techniques ranging from single-cell recordings to large-scale brain mapping. Koch investigates neural correlates of consciousness through integrated information theory and develops neurotechnological approaches for brain disorders. Koch's recent publications demonstrate a strong focus on cortical circuit mechanisms, consciousness assessment methodologies, and comparative neuroanatomy. His work combines advanced neuroimaging, electrophysiological techniques, and theoretical modeling to unravel brain complexity. The research consistently bridges fundamental neuroscience with clinical applications, particularly in neuromonitoring and brain-computer interfaces. He leads multidisciplinary teams at the Allen Institute and collaborates internationally, driving innovations in brain mapping and consciousness research. Koch mentors numerous early-career neuroscientists through the MindScope program and various institutional initiatives.

Anna Wienhardمشاهده پروفایل

استاد

• Geometry
• Group Theory
• Dynamics
• +۶ مورد دیگر

Anna Wienhard is an Honorary Professor at the University of Leipzig's Mathematical Institute and Director of the 'Geometry, Groups, and Dynamics' division at the Max Planck Institute for Mathematics in the Sciences. Her research focuses on geometric structures, representation varieties, and their applications in mathematics and data science. She leads collaborative initiatives like the International Max Planck Research School and ScaDS.AI, integrating geometric methods with machine learning. Research Interests: Her work spans higher Teichmüller theory , Anosov representations , and geometric structures on manifolds. Recent projects explore applications of Higgs bundles, moduli spaces, and persistent homology in quantum dynamics and data analysis. Publications: Her 2025 papers advance Anosov representation theory and total positivity, while 2021 works apply geometric methods to machine learning. Earlier contributions include foundational studies on maximal surface group representations and Hitchin components. Awards: Membership in the Hector Fellow Academy (2021). Grants: Leads AEI-DFG projects on stability and representation varieties, and coordinates DFG-funded clusters like STRUCTURES and SFB/TRR 191. Teaching: Oversees doctoral training programs and collaborates with Leipzig University’s Mathematical Institute. Labs/Teams: Directs the Max Planck division, collaborates with ScaDS.AI, and chairs international workshops on Teichmüller theory and geometric dynamics.

James Kirkpatrickمشاهده پروفایل

پژوهشگر

• Charge Transport
• Organic Semiconductors
• Multiscale Modeling
• +۳ مورد دیگر

James Kirkpatrick is a Researcher at the Max Planck Institute for Polymer Research, focusing on multiscale modeling of charge transport in conjugated materials. His work integrates atomistic simulation, quantum chemical methods, and numerical charge transport simulations to understand electronic properties in organic semiconductors. He completed his PhD at Imperial College (2007), where his research involved developing computational tools for calculating electrostatic disorder and transfer integrals in conjugated materials, with applications in organic solar cells and molecular disorder studies. Key research areas include molecular dynamics of discotic liquid crystals like hexabenzocoronene, charge carrier mobility in columnar mesophases, and the relationship between molecular structure and electronic transport properties. His studies combine ab initio quantum chemistry with large-scale simulations to predict material behavior for organic electronics. Publications emphasize computational methodologies for charge transport analysis, including a software toolkit for simulating organic semiconductors. His work bridges theoretical and applied aspects of materials science, with implications for next-generation optoelectronic devices.

Sadegh Soudjaniمشاهده پروفایل

پژوهشگر

• Cyber-Physical Systems
• Formal Verification
• Stochastic Hybrid Systems
• +۵ مورد دیگر

Sadegh Soudjani is currently a Senior Research Group Leader at the Max Planck Institute for Software Systems (MPI-SWS) since December 2023. Prior to this, he served as the director of the AMBER group and a Reader (full professor) in Cyber-Physical Systems at Newcastle University, United Kingdom. His research focuses on developing integrated environments for programming, verifying, and designing high-performance, scalable cyber-physical systems in uncertain physical environments. Education: BSc in Pure Mathematics BSc in Electrical Engineering MSc in Control Engineering PhD in Systems & Control Research Interests: Formal synthesis, abstraction, and verification of complex dynamical systems under probabilistic temporal specifications. Applications include energy networks, autonomous systems, smart grids, transportation systems, and systems biology. Projects: SymAware (€4 million EIC-funded), CodeCPS (EPSRC-funded), MoVeS, Safe-CPS, AMBI. His work bridges control theory and formal methods, with a focus on stochastic hybrid systems. Scientific Awards: EPSRC New Investigator Award (2021, £484k) DISC Best PhD Thesis Award (2015) QEST Best Paper Award (2018) Newcastle Teaching Award (2020) Best Repeatability Prize at IFAC ADHS'21 Advising & Grants: Supervised 4 PhD students jointly with Max Planck Institute and Ludwig Maximillian University. Secured €4 million for SymAware and €728k for 7 PhD studentships. Led collaborative projects with institutions like KTH, Uppsala, TU Eindhoven, Siemens, and Netherlands Aerospace Centre. Labs & Teams: Currently leads the AMBER group at MPI-SWS, previously directed AMBER group at Newcastle University. Organized international workshops including V2CPS, SNR, VARS, and ARCH (stochastic category).

• Population Genetics
• Mathematical Biology
• Statistical Mechanics
• +۳ مورد دیگر

Dr. Enrico Di Gaspero is affiliated with Bielefeld University's Faculty of Engineering, specifically within the Biomathematics and Theoretical Bioinformatics working group. He is also part of the SFB 1283 Collaborative Research Centre investigating ancestral lines in population models with interaction. His research integrates mathematical and computational approaches to study population genetics, stochastic processes, and statistical mechanics. His work focuses on ancestral line structures, mutation dynamics under selection, and mathematical modeling of biological systems. He contributes to interdisciplinary projects such as the SFB 1283, emphasizing the application of mathematical frameworks to biological phenomena. No awards or grants are explicitly listed in the provided texts. He has no documented advisees. Dr. Di Gaspero’s affiliations include dual roles in the Faculty of Mathematics and Faculty of Engineering, reflecting his expertise in biomathematical and theoretical bioinformatics research.

• High Performance Computing
• Fault Tolerant Systems
• Quantum Computing Integration
• +۷ مورد دیگر

Thomas J. Naughton is a researcher affiliated with the University of Reading and Oak Ridge National Laboratory. He specializes in High Performance Computing (HPC), focusing on fault tolerance, quantum computing integration, and distributed systems. Research Interests: His work bridges HPC and quantum computing, develops fault-tolerant systems, and explores computational models through optical computing. Recent Publications: His 2026-2024 papers address quantum-HPC convergence software stacks, virtualization performance, and fault injection frameworks. Educational Contributions: He co-developed Bebras-inspired computational thinking resources for K-12 education, emphasizing task-based learning.

• Artificial Intelligence
• Machine Learning
• Biomedical Informatics
• +۷ مورد دیگر

Xin Chen is an active academic researcher affiliated with the University of Alabama at Birmingham and other institutions, including universities in China, USA, UK, and Singapore. With expertise in Artificial Intelligence , Machine Learning , and Biomedical Informatics , Chen contributes to diverse areas such as autonomous vehicle systems, medical imaging, and cybersecurity. Key Research Areas : Deep Learning for Autonomous Systems Biomedical Data Analysis Network Security and Fault Diagnosis Cross-Domain AI Applications Recent Publications (2025): Chen has published extensively in journals like IEEE Access , Briefings in Bioinformatics , and Neurocomputing , focusing on applications of AI in healthcare, industrial systems, and data science.

• Optical Quantum Computers
• Dielectric Metasurfaces
• Hybrid Metasurfaces
• +۳ مورد دیگر

Paul Oleynik is a Scientist and Fast-Track PhD candidate at the Brandenburgische Technische Universität Cottbus-Senftenberg, affiliated with the Experimental Physics and Functional Materials department. Born in Cottbus (2001), he holds a B.Sc. in Physics (2019-2023) and completed his M.Sc. Physics (2023-2024). His research focuses on dielectric/hybrid metasurfaces for integrated sensors, numerical methods for electromagnetic wave simulation, and optical quantum computing technologies. As part of Prof. Inga Fischer's research team, he collaborates with experts like Dr. Markus Ratzke and peers such as Jon Schlipf and Ahsan Hayat. His work bridges theoretical electromagnetics with experimental nanophotonics, contributing to advancements in CMOS-compatible photonic device fabrication and plasmonic characterization techniques. No specific grants or awards are listed, but his active participation in high-tech materials research positions him at the forefront of next-generation sensor and quantum computing innovations.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Ning Zhang is a researcher affiliated with Tsinghua University , Department of Electronic Engineering, focusing on interdisciplinary applications of computer science and artificial intelligence in domains such as medical imaging, fault diagnosis, and multimodal systems. Their work bridges theoretical advancements with practical implementations in engineering, agriculture, and finance. Research Interests : Machine learning, signal processing, graph neural networks, and neuromorphic computing. Key Contributions : Recent publications highlight innovations in event-based tracking, digital twin systems, and reinforcement learning integration with vision-language models. Technological Focus : Applications include fault diagnosis in rotating machinery, medical image segmentation (CT-Net), and AI-driven urban risk assessment. The 2024-2025 publication trends reveal a strong emphasis on deep learning for remote sensing, reinforcement learning security, and stochastic control systems. Collaborations span institutions like the University of Manchester, Peking University, and Washington University in St. Louis.

• Biomedical Signal Processing
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Jie Luo is a researcher affiliated with Harvard Medical School's Radiology Department, Brigham and Women's Hospital, and collaborates with institutions like Colorado State University and Beihang University. Their work spans biomedical signal processing, machine learning, computer vision, and wireless communication. Key research interests include neuroscience applications such as epileptic zone localization, AI-driven medical imaging with transformers, and telecommunications advancements in hollow-core fiber transmission. Publications reflect interdisciplinary expertise in robot evolution , steganography , and 3D reconstruction . Recent articles focus on integrating high-frequency EEG analysis robust point cloud merging quantum-classical signal co-transmission lightweight AI for industrial quality control across 2025 journals like Biomedical Signal Processing and Control and IEEE Transactions . No awards or student advising data are currently available.

Corinna Coupetteمشاهده پروفایل

استادیار

• Legal Network Science
• Computational Legal Theory
• Graph Theory
• +۵ مورد دیگر

Corinna Coupette is an Assistant Professor of Computer Science at Aalto University's School of Science, leading the Telos Lab. She holds dual PhDs in Law and Computer Science from the Max Planck Institutes. Her research focuses on computational legal theory, integrating code, data, and law to model complex systems like information societies. She serves as Program Director for the interdisciplinary Master’s Program in Information Networks and is a Research Affiliate at the Max Planck Institute for Tax Law and Public Finance. Education: Dr. iur. (Law, 2018, summa cum laude) and Dr. rer. nat. (Computer Science, 2023, summa cum laude). Awards include the Otto Hahn Medal and Caroline von Humboldt Prize. Her work spans legal network science, graph theory applications, and ethical AI regulation. Active in teaching, she leads courses like 'Algorithms and Society' and 'Information Visualization', and collaborates internationally through ELLIS and the Max Planck Society.

Yuri Kivsharمشاهده پروفایل

استاد

• nonlinear physics
• nonlinear photonics
• physics of metamaterials
• +۷ مورد دیگر

Yuri Kivshar is a Distinguished Professor in the Department of Materials Physics at The Australian National University (ANU) in Canberra, Australia, where he leads the Nonlinear Physics Centre (NLPC). Recognized as one of the world's leading experts in nonlinear physics and nanophotonics, he has established himself as a pioneer in metamaterials research and all-dielectric metaphotonics. Professor Kivshar's research spans multiple cutting-edge areas in modern photonics, with particular emphasis on nonlinear optical phenomena, bound states in the continuum, topological photonics, and chiral light-matter interactions. His work bridges fundamental physics with practical applications, developing novel optical devices for imaging, sensing, and quantum technologies. The NLPC under his leadership maintains both theoretical and experimental programs that are internationally recognized for their innovation and impact. His research portfolio demonstrates a clear evolution from fundamental nonlinear optics toward advanced nanophotonic structures and metamaterials, with recent work focusing on bound states in the continuum, topological photonics, and nonlinear effects at the nanoscale. This progression reflects both the maturation of the field and Kivshar's ability to identify and develop emerging research directions. Humboldt Research Award (2017) Two consecutive Federation Fellowships from the Australian Research Council Listed as one of the 'Most Cited Scientists in Physics' (ISI: h-index 91 with over 35,000 citations) Author of 5 influential books and over 80 papers in Physical Review Letters and 15 in Nature-family journals Through his leadership and research funding, including ARC Discovery and Linkage grants, Professor Kivshar established world-leading theoretical and experimental capabilities at the NLPC. His team has developed major experimental infrastructure including ultrafast laser systems, scanning near-field optical microscopes with sub-100nm resolution, and specialized facilities for nanofabrication. The NLPC actively collaborates with numerous international research groups and hosts visiting researchers from around the world, fostering a dynamic research environment that bridges theory and experiment. The Nonlinear Physics Centre operates as a comprehensive research hub with strong theoretical foundations complemented by cutting-edge experimental capabilities. The center maintains specialized laboratories for nonlinear optics, nanophotonics, and metamaterials research, featuring state-of-the-art equipment for fabrication, characterization, and theoretical modeling. This integrated approach has enabled groundbreaking discoveries including the first generation of Airy plasmons, observation of vortices in liquid crystals, and development of novel out-of-plane metamaterials.

Thomas Wiegandمشاهده پروفایل

استاد

• Solid-State NMR Spectroscopy
• Catalysis
• Magnetic Resonance
• +۵ مورد دیگر

Prof. Thomas Wiegand is a W2 Heisenberg Professor at RWTH Aachen University and the leader of the Max Planck Research Group for Magnetic Resonance of Complex Materials and Catalysts at the Max Planck Institute for Chemistry and Catalysis (MPI CEC). He holds a Diploma in Chemistry from the University of Münster (2010), a PhD under Prof. Hellmut Eckert (2013), and completed a Habilitation at ETH Zurich (2019), followed by a Venia Legendi (2020). His research focuses on magnetic resonance spectroscopy, particularly solid-state NMR, to study catalytic processes in biology and chemistry, with an emphasis on non-covalent interactions, phase separation in biomolecular systems, and energy conversion mechanisms in proteins. Wiegand's work integrates advanced NMR techniques like fast magic-angle spinning (MAS) and para-hydrogen-induced polarization (PHIP) to investigate systems ranging from frustrated Lewis pairs to protein-DNA interactions. His team also explores phase transitions in proteins linked to neurodegenerative diseases and ATP-driven motor proteins in DNA replication. Current group members include Dr. Riza Dervisoglu (lab coordinator) and PhD students Leeroy Hendrickx and Sven Moos. His research outputs span high-impact journals such as Advanced Materials , Journal of the American Chemical Society , and Nature Communications , addressing topics like mechanochemical synthesis, hydrogenation catalysis, and RNA-protein interactions. While no specific awards are listed, his contributions to NMR methodology and interdisciplinary applications are evident through frequent collaborations and leadership roles. Wiegand actively mentors students across all levels, emphasizing experimental and computational approaches to unravel molecular mechanisms in catalysis and biophysics. His lab bridges gaps between chemistry and biology, aiming to unify concepts in catalytic processes across disciplines.

Christine Silberhornمشاهده پروفایل

استاد

• Quantum Optics
• Quantum Information Science
• Nonlinear Photonics
• +۳ مورد دیگر

Christine Silberhorn is a Professor of Physics at Paderborn University, heading the Integrated Quantum Optics group within the Faculty of Science. She holds leadership roles in the Center for Optoelectronics and Photonics (CeOPP) and the Institute for Photonic Quantum Systems (PhoQS), serving as Speaker of the Transregional Collaborative Research Centre 142. Her research focuses on quantum optics, nonlinear photonics, and photonic quantum systems. She earned her PhD in Experimental Physics from the University of Erlangen-Nuremberg (2003), followed by postdoctoral work at Oxford (2003-2004) and habilitation in 2008. She leads major projects like MIRAQLS (mid-IR quantum sensing) and PhoQuant (photonic quantum computing). Awardees of the Gottfried Wilhelm Leibniz Prize (2011) and Heinz Maier-Leibnitz Prize (2008), she has received numerous accolades including OSA Fellow status (2018). Her recent publications explore scalable quantum systems and quantum timing resolution. She actively organizes conferences like QIM 2021 and chairs key scientific bodies such as the German Science and Humanities Council (2023-2026).

• Fluid Mechanics
• Machine Learning
• Chaotic Systems
• +۳ مورد دیگر

Luca Magri is a Reader in Data-Driven Fluid Mechanics at Imperial College London's Department of Aeronautics. He holds affiliations as a Fellow of The Alan Turing Institute and a Hans Fischer Fellow at the Technical University of Munich (TUM). His research focuses on physics-constrained machine learning, chaotic systems, and fluid mechanics. Magri’s work bridges computational methods with fluid dynamics, addressing challenges in turbulence, combustion, and acoustics through innovative approaches like reservoir computing and adjoint-based optimization. Education & Career PhD in Engineering, University of Cambridge (2015) Postdoctoral Fellow, Stanford University Center for Turbulence Research (2015–2017) Lecturer at Cambridge University Engineering Department (2017–2018) Current: Reader at Imperial College London since 2018 Research Interests Magri’s research integrates machine learning with fluid dynamics to model chaotic systems, optimize combustion processes, and analyze turbulence. Key areas include: Physics-informed neural networks for extreme event prediction Adjoint-based methods for thermoacoustic stability Bayesian data assimilation in nonlinear systems Publications & Awards His impactful work has been recognized with awards such as the ERC Starting Grant (2019), Royal Aeronautical Society Fellowship (2022), and multiple fellowships from Stanford and Cambridge. Over 50 publications span journals like Journal of Fluid Mechanics and Proceedings of the Royal Society A . Grants & Collaborations Magri leads projects funded by the EU Horizon 2020, UKRI, and the ERC. He collaborates globally, including with TUM’s Institute for Advanced Study and Cambridge’s Engineering Department.