جستجوی استاد راهنمای دانشگاهی

• Information-Theoretic Security
• Quantum Communication
• Wireless Communication Networks
• +۹ مورد دیگر

Moritz Wiese is a Researcher at the Chair of Theoretical Information Technology within the Department of Electrical and Computer Engineering at Technische Universität München (TUM) . His work focuses on information-theoretic security, quantum communication, and wireless networks, with significant contributions to interference modeling and secure coding schemes. Research Interests : Information-Theoretic Security, Quantum Wiretap Channels, MIMO Systems, 5G/6G Technologies, Physical Layer Security, and Network Coding. Key Grants : Involved in DFG-funded projects (Gottfried Wilhelm Leibniz Prize, UKoloS) and BMBF initiatives (6G-life, QuaDiQua). Collaborations : Worked with Prof. Holger Boche, Christian Deppe, and Rami Ezzine on secure communication and randomness generation. Labs : Active in the ACES Lab and 6G-life research hub, focusing on joint communication/sensing and neuromorphic computing. Publications : Over 20 papers on secure estimation, wiretap channels, and quantum secrecy, including top-tier journals like IEEE Transactions on Information Theory and Journal of Mathematical Physics .

• Wireless Communications
• Internet of Things
• Reconfigurable Intelligent Surfaces
• +۴ مورد دیگر

Xingwang Li is an active researcher affiliated with the School of Physics and Electronic Information Engineering at Henan Polytechnic University in Jiaozuo, China. He obtained his PhD from Beijing University of Posts and Telecommunications in 2015, specializing in networking and switching technology. His research spans wireless communications, IoT systems, reconfigurable intelligent surfaces (RIS), and physical-layer security, with a strong focus on 6G-enabling technologies. Dr. Li's work primarily explores: Optimization of RIS-aided satellite-terrestrial networks Covert communication systems for enhanced security AI-driven signal processing for massive MIMO Integrated sensing and communication frameworks Energy-efficient protocols for IoT networks His recent publications (2023-2025) demonstrate a consistent focus on RIS applications, with 82% of works addressing reconfigurable surface optimization. Key trends include the integration of deep learning with communication systems (notably reinforcement learning for resource allocation), advancement of THz and near-field technologies for 6G, and novel approaches to physical-layer security. The research shows increasing emphasis on practical implementations, including UAV networks and autonomous vehicle communications.

• Power Systems
• Smart Grids
• Energy Infrastructure
• +۱ مورد دیگر

Antonello Monti is a Professor and Director of the Institute for Automation of Complex Power Systems at RWTH Aachen University. His research focuses on modern power systems, including smart grid technologies, hybrid AC-DC grids, and quantum computing applications in energy systems. Recent publications demonstrate innovations in grid resilience, EV charging optimization, quantum-assisted power system planning, and advanced simulation techniques. His team develops open-source tools like JuliaGrid for power system analysis and validates concepts through real-time testing platforms. Research addresses energy transition challenges including renewable integration, grid modernization, cyber-physical security, and next-generation optimization methods combining quantum computing with traditional power engineering approaches.

• Neuroscience
• Neurobiology
• Computational Neuroscience
• +۶ مورد دیگر

Prof. Dr. Fred Wolf is a leading scientist affiliated with the Campus Institute for Dynamics of Biological Networks (CIDBN) at Georg-August-Universität Göttingen. His research focuses on the intersection of neuroscience, computational biology, and epithelial morphogenesis, utilizing advanced imaging techniques and theoretical models to study neural circuits and tissue dynamics.

• Signal Processing
• Wireless Communications
• Networking
• +۳ مورد دیگر

Philippe Ciblat is a Professor at TELECOM Paris Tech, affiliated with the Department of Signal Processing and Communications. His research spans signal processing, wireless communications, and machine learning applications in networking. He has collaborated extensively with institutions like the University of Paris-Saclay and international researchers in areas such as cooperative communication protocols, resource allocation, and coding theory. Research Interests: Machine learning for signal processing, wireless channel modeling (Rician fading), lattice decoding, caching strategies, and distributed optimization. Notable Work: Pioneered transformer-based packet scheduling, neural network approaches to lattice decoding, and effective capacity analysis in fading channels. His contributions include over 170 publications in top venues (IEEE Trans. Signal Process., IEEE Trans. Wireless Commun.) and collaborations with industry partners on practical implementations like cache-aided polar coding. He has advised multiple researchers in distributed systems and wireless resource management.

• Mathematical Data Science
• Machine Learning
• Compressed Sensing
• +۵ مورد دیگر

Johannes Maly is an Assistant Professor at the Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence at LMU Munich. He previously held postdoctoral positions at Catholic University of Eichstaett-Ingolstadt and RWTH Aachen University, and completed his PhD at TUM Munich under Prof. Massimo Fornasier. PhD in Mathematics (2019, TUM Munich) M.Sc. in Mathematics (2015, TUM Munich) B.Sc. in Mathematics (2013, TUM Munich) His research focuses on mathematical data science and machine learning, specifically addressing: Robust covariance estimation under quantization Neural network approximation properties Implicit bias in gradient descent training Multi-structured signal recovery Quantization effects in deep learning and compressed sensing His recent publications analyze dithered quantization in covariance estimation, implicit regularization in overparameterized models, and multi-structured data recovery. He applies mathematical rigor to practical challenges in wireless communications (e.g., MIMO systems) and neural network training. Scientific recognition includes: relAI Fellow MCML Associate He supervises code/toolbox development for reproducibility and teaches graduate courses in convex optimization, high-dimensional probability, and mathematical data science. His work bridges theoretical mathematics and applied signal processing.

Chase Broederszمشاهده پروفایل

استاد

• Statistical Physics
• Biological Physics
• Soft Matter Physics
• +۴ مورد دیگر

Prof. Dr. Chase Broedersz is a tenured W2 Professor of Theoretical Physics – Statistical and Biological Physics at Ludwig-Maximilians-Universität München (LMU Munich) since 2015. He also holds a secondary affiliation as Associate Professor at VU Amsterdam since 2020. He is a member of the Young College of the Bavarian Academy of Science since 2017. Education Ph.D. in Theoretical Physics , VU Amsterdam (2011) MSc. in Physics , VU Amsterdam (2007) BSc. in Physics and Astronomy , VU Amsterdam (2005) Research Interests Prof. Broedersz leads a research program at the intersection of statistical physics and biological physics , with a focus on: Soft Matter Physics : mechanics of biopolymer networks, semiflexible filaments, and composite materials Active Matter : non-equilibrium dynamics in living systems, motor-driven networks, and active gels Cell Mechanics : confined cell migration, mechanosensing, and force transmission in tissues Chromosome Organization : bacterial chromosome structure, protein-DNA interactions, and SMC condensins His work combines theoretical modeling , computational simulations , and experimental collaborations to uncover the physical principles governing complex biological systems. Publication Trends Prof. Broedersz has authored over 50 peer-reviewed publications since 2010. His recent work (2019–2025) emphasizes: Cell migration in confined and soft environments, with studies in Nature Physics and PNAS Non-equilibrium dynamics in active biological systems, including broken detailed balance and emergent contractility Machine learning approaches to infer stochastic dynamics in biological data, published in Nature Communications and Physical Review Letters Chromosomal organization in bacteria, combining polymer physics with genomic data Labs and Teams He leads the Statistical and Biological Physics Group at LMU Munich, affiliated with the Arnold Sommerfeld Center for Theoretical Physics (ASC) . The group collaborates closely with experimental teams at LMU, Princeton, and other institutions, focusing on interdisciplinary biophysics research. Teaching Prof. Broedersz has taught advanced courses including: Advanced Statistical Physics Soft Matter Physics Stochastic Processes in Physics and Biology

Jonas Gebeleمشاهده پروفایل

پژوهشگر

• Blockchain-based Prediction Markets
• Maximal Extractable Value (MEV)
• Privacy Preserving Smart Contracts (PPSCs)
• +۳ مورد دیگر

Jonas Gebele is a Researcher at the Chair of Informatics 19 (Software Engineering for Business Information Systems) at the Technical University of Munich, Germany. He joined the institution in August 2024 and contributes to blockchain research with a focus on Maximal Extractable Value (MEV) and privacy-preserving technologies. Education: Master of Science in Data Engineering and Analytics (2024), Bachelor of Science in Informatics (TU Munich) His research explores MEV extraction techniques on first-come-first-served blockchains like Algorand, blockchain-based privacy-preserving smart contracts , and prediction market architectures. Publications analyze arbitrage strategies, transaction ordering, and network clogging attacks in FCFS environments. Jonas actively supervises blockchain-related thesis projects and teaches courses such as Blockchain-based Systems Engineering and SEBA Lab Course . His work connects theoretical analysis with practical implementation in decentralized finance systems. Labs/Teams: SEBIS (Software Engineering for Business Information Systems) research group

• Power Systems
• Smart Grids
• Renewable Energy Integration
• +۳ مورد دیگر

Prof. Ferdinanda Ponci is a Professor at RWTH Aachen University, leading the Department of Monitoring and Distributed Control for Energy Systems. Her work focuses on smart grid technologies, renewable energy integration, and control systems for modern power networks. She actively contributes to advancing grid resilience, EV charging infrastructure, and cybersecurity in energy systems. Key research interests include hybrid AC-DC grids, distributed energy resources coordination, and application of AI in grid management. She has pioneered frameworks like datafev for EV charging management and SMU platforms for synchronized measurements. Her interdisciplinary approach also addresses diversity in engineering and societal impacts of energy systems. Prof. Ponci’s laboratory activities involve hardware-in-the-loop testing, blockchain-based grid solutions, and development of educational toolboxes for emerging technologies. She collaborates on projects such as submarine transmission systems and grid interoperability testing, contributing to both academic and industrial advancements in power systems engineering.

• Wireless Communications
• Information Theory
• Physical Layer Security
• +۷ مورد دیگر

Eduard A. Jorswieck is a University Professor of Communication Systems at the Institute of Communications Engineering , Technical University of Braunschweig, since 2019. He has previously held a professorship at TU Dresden (2008–2019) and has been a lecturer at TU Berlin (2005–2008). Currently, he serves as the Geschäftsführender Leiter (Managing Director) of the Institute of Communications Engineering. Education: Dipl.-Ing. in Computer Engineering (2000), Doctorate (2004) from TU Berlin. Research Interests: His work bridges information theory and wireless communications, focusing on physical layer security , energy efficiency , reconfigurable intelligent surfaces (RIS) , NOMA , MIMO systems , and machine learning for network optimization . He explores stochastic orders, game theory, and fractional programming for resource allocation in 5G/6G networks. Publications & Trends: Recent articles emphasize RIS-aided URLLC , STAR-RIS , 6G security , and AI-driven resource management . His studies span multi-antenna systems , terahertz ISAC , and multi-agent reinforcement learning for UAV networks. Awards: IEEE Signal Processing Society Best Paper Award (2006) IEEE Fellow (2020) Fellow of Industry Academy (AIIA, 2024) Best Paper Award at IEEE ICC 2024 Students & Collaborations: He has mentored researchers like K.-L. Besser, P.-H. Lin, and M. Mross. His lab collaborates on projects involving quantum communication , industrial IoT , and multi-agent systems .

• Wireless Communication
• 5G Networks
• Millimeter-Wave Technology
• +۳ مورد دیگر

Randy Verdecia-Peña is a researcher specializing in wireless communication and 5G technologies, focusing on millimeter-wave (mmWave) systems, software-defined radio (SDR), and network protocols. His work emphasizes practical experimentation with advanced signal processing techniques, including machine learning for channel estimation and hardware prototyping for integrated access and backhaul (IAB) architectures. Key contributions include phased array-aided 5G prototypes, flexible layer 2 protocols, and cooperative relay node design in both indoor and outdoor environments. Collaborations frequently involve hardware validation and performance analysis across frequencies like 26 GHz and 60 GHz.

• Wireless Communication
• Satellite Networks
• 5G/6G Technologies
• +۷ مورد دیگر

Mohamed-Slim Alouini is a Professor affiliated with King Abdullah University of Science and Technology (KAUST), specifically linked to the Center for Uncertainty Quantification (SRI UQ) in Thuwal, Saudi Arabia, and also associated with Texas A&M University at Qatar. His research focuses on cutting-edge wireless communication technologies, including 5G/6G systems, satellite networks, UAV-based communication, free-space optics (FSO), and THz frequencies. He has made significant contributions to network optimization, interference management, and energy-efficient designs. His work spans theoretical analysis and practical implementations, with a strong emphasis on stochastic geometry, signal processing, and multi-hop communication systems. Notable areas include reconfigurable intelligent surfaces (RIS), non-terrestrial networks (NTN), and integration of aerial-ground-space networks. His research addresses challenges in rural connectivity, emergency communication systems, and interference mitigation in dense networks. Alouini's articles highlight advancements in FSO mesh networks, LiDAR-assisted positioning for airborne terminals, and energy-efficient optimization in aerial infrastructure-based (IAB) networks. He also explores the application of large language models to satellite-aerial-terrestrial systems and surveys random access protocols for IoT over LEO satellites. While no awards are explicitly listed in the provided text, his prolific publication record (over 2,160 entries) underscores his impactful contributions to the field. His work is often collaborative, with frequent co-authorships on topics ranging from UAV-VLC systems to THz channel modeling.

• Nonlinear Dynamics
• Bifurcation Theory
• Piecewise Smooth Systems
• +۷ مورد دیگر

Professor Viktor Avrutin is an extraordinary professor (Apl. Prof.) at the University of Stuttgart, Germany, affiliated with the Institute for Systems Theory and Automatic Control. He holds a Dr. rer. nat. habil. degree in Computer Science from the University of Stuttgart, where he was appointed as an extraordinary professor in 2020 after obtaining his Privatdozent status in 2011. Avrutin completed his academic journey with a B.Sc. from St. Petersburg State Polytechnical University (1992), an M.Sc. in Computer Science with Mathematics from the University of Stuttgart (1997), and a Ph.D. from the University of Stuttgart (2003) with a thesis on piecewise-smooth dynamical systems. His research focuses on nonlinear dynamics with particular emphasis on bifurcation theory for piecewise smooth systems, border collision and homoclinic bifurcations, low-dimensional chaos, and bifurcations of chaotic attractors (crises). He also investigates numerics, simulation software, algorithms, and neural networks. His work spans multiple disciplines including electrical engineering (power converters and inverters), mechanical systems (vibration machines), biological modeling (Goodwin's oscillator), and ecological systems (predator-prey models). Analysis of his recent publications reveals a consistent focus on piecewise smooth dynamical systems, with particular attention to border collision bifurcations, chaotic attractors, and their transformations. His research demonstrates strong interdisciplinary applications, connecting theoretical mathematics with practical engineering problems in power electronics, mechanical systems, and biological modeling. The recurring themes across his work include the study of complex nonlinear phenomena in systems with discontinuities, transformation of attractors, and the interplay between deterministic and stochastic elements in nonlinear systems. Professor Avrutin teaches courses including Nonlinear Dynamics and Chaos Theory I (summer term), Dynamics of Nonsmooth Systems, and Nonlinear Dynamics and Chaos Theory II (winter term) at the University of Stuttgart.

• Neuroscience
• Systems Neuroscience
• Sensory Processing
• +۳ مورد دیگر

Dr. Anton Sumser is a researcher at the Faculty of Biology, Ludwig Maximilian University of Munich, where he contributes to Prof. Laura Busse's research group and the Vision Circuits collaboration (Busse & Katzner). His work focuses on neural circuit mechanisms underlying sensory processing in mouse models, with emphasis on thalamic function in vision and touch. Sumser's research investigates how active versus passive sensory inputs are differentially processed in the thalamus, revealing specialized neural pathways for touch perception during movement. His studies integrate in vivo electrophysiology, viral tracing, and behavioral paradigms to dissect visuomotor coordination, demonstrating how thalamic hub-and-spoke networks enable visual perception during action. Additional work explores panoramic visual statistics shaping retinal organization and develops advanced rabies viral vectors for neural circuit mapping. His publication record (2016-2025) shows consistent contributions to sensory neuroscience, with recent work highlighting thalamic roles in multisensory integration. Key trends include methodological innovation in circuit tracing and the characterization of neural coding principles across visual and somatosensory systems. Sumser is embedded in the Vision Circuits group at LMU Munich, which examines the neural basis of visual perception in behavioral contexts. No information is available regarding students advised or research grants secured.

A. Lee Swindlehurstمشاهده پروفایل

استاد

• Signal Processing
• Wireless Communications
• Biomedical Applications
• +۳ مورد دیگر

A. Lee Swindlehurst is a Professor and Associate Dean for Research and Graduate Studies at the Henry Samueli School of Engineering of the University of California, Irvine . He is also a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study , where he collaborates on next-generation wireless communications research. Ph.D., Stanford University (Electrical Engineering, 1991) M.S., Brigham Young University (Electrical Engineering, 1986) B.S., Brigham Young University (Electrical Engineering, 1985) Swindlehurst's research focuses on sensor array signal processing for radar, wireless communications, and biomedical applications. His work addresses detection and estimation theory , system identification, and channel modeling, with recent emphasis on massive MIMO systems , low-resolution hardware, and physical layer security . His 2018-2017 publications demonstrate technical advances in precoding algorithms , channel estimation , and ADC/DAC optimization for emerging wireless architectures. IEEE Fellow (2004) IEEE Signal Processing Society Best Paper Awards (2010, 2006) Stephen O. Rice Prize in Communications Theory (2006) IEEE W.R.G. Baker Prize Paper Award (2000) Karl G. Maeser Research Award (2004) His research has produced foundational work on space-time block codes , vector-perturbation techniques , and blind equalization methods that continue influencing modern wireless system design.