جست‌وجوی استاد و پژوهشگر

• Computational Physics
• Molecular Dynamics
• Tribology
• +۷ مورد دیگر

Mauro Ferrario is a Full Professor at the Department of Physical, Computer and Mathematical Sciences (former Physics campus) within the University of Modena and Reggio Emilia . His academic leadership is evident through dual roles in Computational Physics Laboratory (Physics degree program) and Physics teaching for Biological Sciences . Research Pillars: Non-Equilibrium Molecular Dynamics (NEMD/D-NEMD) Quantum-informed machine learning potentials Green lubricant additive development 2D material tribology (graphene, phosphorene) Multi-scale modeling from atomistic to continuum Surface passivation and chemical reactivity under stress Methodological Expertise: Ab initio/DFT simulations QM/MM hybrid approaches Constraint dynamics and thermostat algorithms High-throughput interface characterization Transient transport phenomena analysis The 2025-2024 publications reveal cutting-edge work on machine learning-enhanced simulations for green lubricants, NEMD melt-front modeling, and superlubricity mechanisms. His 2023-2022 studies on phosphorene oxidation, tribochemical constraints, and friction reduction through nanoscale patterning demonstrate sustained innovation across 15 recent articles . Teaching Impact: He develops computational physics curricula emphasizing Python programming, numerical algorithms, and interdisciplinary applications. His Computational Physics Laboratory course integrates DataCamp tools, while Physics for Biological Sciences bridges classical mechanics with life science applications through digital whiteboard instruction. Contact: Office MO-17-04-011 , Via Campi 213/A. Reception: Mondays 9:00-10:00 or by email appointment.

Martin Krulišمشاهده پروفایل

دانشیار

• Parallel Computing
• GPU Programming
• Self-adaptive Systems
• +۵ مورد دیگر

Martin Kruliš serves as an Associate Professor in the Department of Distributed and Dependable Systems (D3S) at Charles University's Faculty of Mathematics and Physics in Prague, Czech Republic. His academic work focuses on the intersection of parallel computing, GPU programming, and self-adaptive systems, with significant contributions to both theoretical frameworks and practical implementations in high-performance computing environments. Dr. Kruliš's research interests center on optimizing computational systems through innovative approaches to parallelism and adaptability. His work demonstrates particular expertise in GPU-accelerated algorithms, self-optimizing architectures, and the integration of machine learning techniques into system design. He has developed substantial expertise in creating abstractions that simplify complex parallel programming tasks while maintaining high performance. His publication record reveals a clear trajectory from foundational work in parallel algorithms and GPU programming toward increasingly sophisticated integration of machine learning with self-adaptive systems. Recent work shows a strong emphasis on applying machine learning to optimize parallel computing environments, particularly through novel abstractions that make these techniques accessible to developers. As an educator, Dr. Kruliš teaches Programming in Parallel Environment (NPRG042) and Advanced Programming in Parallel Environment (NPRG058), demonstrating his commitment to training the next generation of parallel computing specialists. He has also contributed to the ReCodEx project, an automated system for evaluating coding assignments that has been used for over five years at his institution. Dr. Kruliš actively participates in the academic community through conference service, having served on committees for ECOOP 2022 and other major computer science conferences. His work with the D3S research group reflects a collaborative approach to tackling complex problems in distributed and dependable systems.

Karystinos Georgiosمشاهده پروفایل

استاد

• Telecommunications theory and systems
• Coding theory
• Adaptive signal processing
• +۷ مورد دیگر

George N. Karystinos is a Professor at the School of Electrical and Computer Engineering , Technical University of Crete , where he has served since 2005. Since 2021, he also holds the position of Dean of the School. Previously, he was an Assistant Professor at Wright State University (2003–2005). Education: Ph.D. in Electrical Engineering, State University of New York at Buffalo , 2003 Diploma in Computer Engineering and Science, University of Patras , 1997 Additional studies in Piano, National Conservatory of Athens and State University of New York at Buffalo Research Interests: His research spans telecommunications theory and systems , coding theory , adaptive signal processing , wireless communications , MIMO systems , neural networks , and optimization with limited data . He is particularly known for contributions to L1-norm PCA , noncoherent detection , RFID systems , and code design for CDMA . Scientific Awards: IEEE Transactions on Neural Networks Outstanding Paper Award (2003) IEEE ICT Best Paper Award (2001) IEEE ISWCS Best Paper Award (2013) IEEE ICASSP Best Student Paper Award (2015) IEEE RFID-TA Second Best Student Paper Award (2011) IEEE MOCAST Best Student Paper Award (2018) Laboratory and Teaching: He leads research at the Telecommunications Laboratory and teaches courses such as Signals and Systems , Information and Code Theory , and Probability and Random Process Theory . Grants and Projects: While specific grant details are not listed, his extensive publication record and award history indicate active participation in funded research projects, particularly in wireless communications and signal processing.

Karl-Ludwig Besserمشاهده پروفایل

استادیار

• Ultra-reliable communications
• Resilience of communication systems
• Copulas
• +۲ مورد دیگر

Karl-Ludwig Besser serves as Assistant Professor in the Division of Communication Systems within Linköping University's Department of Electrical Engineering since January 2025. Previously, he completed a postdoctoral fellowship at Princeton University's Department of Electrical and Computer Engineering (March 2023–December 2024), following his 2022 PhD from Technische Universität Braunschweig. His academic foundation includes: Dipl.-Ing. in Electrical Engineering, Technische Universität Dresden (2018) PhD in Electrical Engineering, Technische Universität Braunschweig (January 2022) Dr. Besser's research centers on ultra-reliable communication systems , physical layer security under resource constraints , and copula-based modeling of channel dependencies . His work bridges theoretical information theory with practical machine learning applications, particularly in reconfigurable intelligent surfaces (RIS) and integrated sensing-communication (ISAC) systems. Recent publications demonstrate expertise in secret-key budget management for resilient networks and UAV swarm coordination using 3D beamforming techniques. Analysis of his 15 most recent publications (2024–2025) reveals three dominant themes: (1) RIS optimization using physics-informed neural networks addressing mutual coupling challenges, (2) fundamental limits of physical layer security in dependent fading channels with secret-key budgets, and (3) machine learning solutions for UAV mobility management and mmWave resource allocation. His work consistently targets ultra-reliable low-latency communication (URLLC) requirements for next-generation networks. As part of Linköping University's Communication Systems division, Dr. Besser contributes to research initiatives including Wireless Communications for Distributed Intelligence and Integrated Sensing and Communications (ISAC) . While specific grant details aren't documented in source materials, his research aligns with European 6G initiatives and national security-focused wireless projects. The division actively supervises 25+ PhD students across topics including drone swarm communication, energy-efficient signal processing, and smart city sensor networks, where Dr. Besser likely participates in student mentorship.

Martin Krulišمشاهده پروفایل

دانشیار

• High-performance computing
• GPU programming and CUDA optimization
• Parallel algorithms and data structures
• +۴ مورد دیگر

Martin Kruliš is an associate professor in the Department of Distributed and Dependable Systems at the Faculty of Mathematics and Physics, Charles University , Prague, Czech Republic. His primary roles include research, teaching, advising, and leading projects that bridge high-performance computing, GPU programming, and self-adaptive systems. Education: While exact details of his own degrees are not provided, Dr. Kruliš’s extensive publication record and faculty position at Charles University indicate advanced training in computer science with specialization in parallel and distributed computing. Research Interests: High-Performance GPU Computing: Deep investigation into CUDA kernel optimization, memory bandwidth utilization, and workload dispatching for massively parallel accelerators. Self-Adaptive & Self-Optimizing Systems: Designing ensemble-based abstractions that integrate machine-learning estimators to enable runtime adaptation in component architectures. Parallel Algorithms & Data Structures: Development of cache-friendly, SIMD-aware, and GPU-accelerated algorithms for clustering, dimensionality reduction, and similarity search. Software Engineering for Parallelism: Creation of C++ libraries, DSLs (e.g., Bobolang), and educational tools (ReCodEx) that simplify parallel programming and automated evaluation. Publication Trends: Across 2011–2025, Kruliš’s articles reveal a clear trajectory from foundational GPU-accelerated indexing and multimedia retrieval toward sophisticated self-adaptive systems that leverage machine learning. Recent works (2023–2025) increasingly focus on integrating LLMs and neural networks into compiler and runtime optimization loops, reflecting a convergence of AI and systems research. Scientific Awards & Recognition: No specific awards or fellowships are mentioned in the provided text; however, sustained publication in top-tier venues (JPDC, IPDPS, Euro-Par, SEAMS) and active involvement in program committees and tool development indicate strong peer recognition. Teaching & Student Supervision: Teaches Programming in Parallel Environment (NPRG042) , Advanced Programming in Parallel Environment (NPRG058) , Computer Systems (NSWI170) , and Software Projects . Supervises numerous bachelor’s and master’s theses; exact student names are not listed in the text. Labs, Projects & Tools: ReCodEx: A widely used platform for semi-automated evaluation of programming assignments at Charles University. Simdex: A modular simulator of the ReCodEx backend that enables realistic experimentation with self-adaptive job dispatching and machine-learning controllers. Active contributor to open-source repositories on GitHub, focusing on GPU kernels, benchmarking frameworks, and educational tooling.

Romy Lorenzمشاهده پروفایل

استاد پژوهشی

• Cognitive Neuroscience
• Neurotechnology
• Brain-Computer Interfaces
• +۷ مورد دیگر

Dr. Romy Lorenz is a Max Planck Research Group Leader at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, where she leads the Cognitive Neuroscience & Neurotechnology research group. She previously held postdoctoral positions at the University of Cambridge, Stanford University, and the Max Planck Institute for Human Cognitive & Brain Sciences from 2018 to 2023 as a Sir Henry Wellcome Postdoctoral Fellow. Dr. Lorenz's educational background includes: BSc in Psychology from Leuphana University (2009) MSc in Human-Machine Interaction from TU Berlin (2012) PhD in Neurotechnology from Imperial College London (2017) Her research focuses on understanding the frontoparietal brain network mechanisms that underpin high-level cognition and adaptive behavior. She employs an interdisciplinary approach combining subject-specific brain-computer interface technology, fMRI at standard and ultrahigh magnetic field strengths (3T, 7T, and 9.4T), EEG, non-invasive brain stimulation, computational modeling, and machine learning techniques. A key innovation in her work is the development of neuroadaptive Bayesian optimization methods that allow for real-time, closed-loop experimental design in cognitive neuroscience. Dr. Lorenz's recent publications demonstrate a clear trend toward investigating brain function at increasingly fine-grained spatial scales, particularly exploring layer-specific processing in the prefrontal cortex using ultrahigh-field fMRI. Her work bridges computational neuroscience, cognitive psychology, and neurotechnology, with applications ranging from basic cognitive science to clinical rehabilitation. A significant portion of her research focuses on closed-loop systems that integrate real-time brain imaging with adaptive experimental design and stimulation protocols. Her notable scientific achievements include: Outstanding Contributions in AI Innovation Award Sir Henry Wellcome Postdoctoral Fellowship Funding from the German Scholar Organisation Fellowships from the Wellcome Trust and Engineering and Physical Sciences Research Council Dr. Lorenz has secured significant research funding for her work, including support from the Wellcome Trust and German funding agencies. She has mentored several students, including Master's students like Pedro who has presented their collaborative work at conferences. Her research group actively recruits postdoctoral researchers and students interested in cognitive neuroscience and neurotechnology. Dr. Lorenz leads the Cognitive Neuroscience & Neurotechnology research group at the Max Planck Institute for Biological Cybernetics, which focuses on developing and applying advanced neuroimaging and computational methods to understand high-level cognitive functions. She has also co-initiated interest groups such as CoCoNUT (Computational Cognitive Neuroscience at the Max Planck Institute) to foster interdisciplinary collaboration. Her lab utilizes cutting-edge technologies including real-time fMRI at ultrahigh field strengths, EEG, and non-invasive brain stimulation to investigate frontoparietal network function.

Semiha Tedik Başaranمشاهده پروفایل

استادیار

• Wireless communications
• Network coding
• 5G and beyond networks
• +۷ مورد دیگر

Semiha Tedik Başaran is an Assistant Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University's Faculty of Electrical and Electronics Engineering. She received her PhD in Telecommunications Engineering from Istanbul Technical University in 2019 and has been working at the university since 2011, first as a Research Assistant and then as an Assistant Professor starting in 2020. Her educational background includes: PhD in Telecommunications Engineering from Istanbul Technical University (2013-2019) MSc in Telecommunications Engineering with Thesis from Istanbul Technical University (2011-2013) Bachelor's Degree in Electronics and Communication Engineering (Double Major) from Istanbul Technical University (2006-2011) Dr. Başaran's research focuses on wireless communications, network coding, and next-generation wireless networks. Her work spans theoretical analysis and practical implementation of communication systems, with particular emphasis on network coded cooperation, physical layer security, and wireless network reliability. She has made significant contributions to understanding the performance of network coded systems in various wireless environments, including satellite communications and 5G/6G networks. Her recent publications demonstrate a growing interest in integrating artificial intelligence with wireless communications, particularly for IoT applications and edge computing, while also advancing research in THz communication systems and their challenges in adverse weather conditions. Her scientific achievements have been recognized with several prestigious awards: Doctoral Thesis Award from Istanbul Technical University (2020) IEEE Türkiye Doctoral Thesis Award (2020) Best Poster Award at IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE-2016) (2016) Dr. Başaran serves as Principal Investigator for multiple research projects including 'Designing 5G and Beyond Cellular Private Networks Secure Against DDoS Attacks,' 'Performance Analysis of THz Communication Systems,' 'Coverage Analysis of LEO Satellite Systems,' and 'Development of Multiple Access Techniques Providing Low Latency Performance for Next Generation Communication Systems.' Her h-index of 8 (based on Scopus) reflects her impactful contributions to the field of wireless communications, with 36 research outputs spanning from 2013 to 2024. She maintains an active research lab focused on wireless communications and network coding, where her team works on both theoretical analysis and practical implementation of next-generation communication systems using software-defined radio platforms, with strong international collaborations extending across multiple countries as indicated by her research footprint.

John-Paul Oreمشاهده پروفایل

استادیار

• Robot Software Reliability & Testing
• Program Analysis for Cyber-Physical Systems
• Flying Robots for Environmental Monitoring
• +۶ مورد دیگر

John-Paul Ore is an Assistant Professor in the Department of Computer Science at North Carolina State University's College of Engineering. His research bridges software engineering and field robotics, with a focus on program analysis, system testing, and high-resolution physical simulators for robotics systems, particularly those built with the Robot Operating System (ROS). He develops software engineering methods that improve the dependability of robotics systems through techniques for dimensional analysis without developer annotations, open-source tools like PHYS, and public datasets documenting dimensional inconsistencies in real-world systems. His educational background includes a Ph.D. from the University of Nebraska-Lincoln (2019) and a B.A. in Philosophy from the University of Chicago. His interdisciplinary background informs his approach to combining software engineering with robotics to address challenges in reasoning about full-system behavior across multiple layers of abstraction. Ore's research interests center on applying program analysis techniques to software that controls robots and interacts with the physical world. His work includes abstract type inference of physical unit types (like 'meters-per-second'), probabilistic techniques for combining semantic information in identifiers with code flow inference, and empirical measurements of how developers make decisions about robotic software. He focuses on program analysis and software testing that enhances system safety and reliability while remaining practical and economically efficient. His research has significant applications in environmental monitoring, addressing climate challenges, food production, and liberating people from dangerous, dirty, and dull work. His publication record shows a clear trajectory from foundational work on dimensional analysis in robotics software to increasingly complex applications in environmental monitoring and autonomous systems. The most recent publications demonstrate expansion into Large Language Models for code analysis while maintaining focus on practical robotics applications. His research consistently addresses the critical gap between theoretical program analysis and practical robotics system development. Best Tool Demonstration Award, ISSTA'17 for Phriky-Units ACM SIGSOFT Travel Award ($300) Othmer Fellowship 2014-2018 ($8K/year) UNL CSE Outstanding Master's Thesis Award 2015 RSS 2013 Travel Grant ($500) Ore actively mentors students, having served as research mentor for undergraduates Becca Horzewski (2016-17) and Lambros Karkazis (2018). His research is supported by significant grants including FARM BILL: NRI: INT ($1,018,596 from NSF), SHF: SMALL ($499,994 from NSF), and North Carolina Space Grant ($5,000 from NASA). He is currently recruiting PhD students for his lab focused on robotics and software engineering. His laboratory work combines robotics, software engineering, and environmental monitoring, with projects including autonomous aerial water sampling systems, UAV-based environmental sensing, and tools for improving robotics software reliability. His team develops both theoretical approaches and practical implementations, often creating open-source tools that bridge the gap between academic research and industry applications.

Jonathan Fullerمشاهده پروفایل

استادیار

• Binary Analysis
• Cyber Forensics
• Security Measurements
• +۲ مورد دیگر

Jonathan Fuller is an Assistant Professor in the Electrical Engineering and Computer Science (EECS) department at the U.S. Military Academy. He directs the Digital Forensics Course and serves as the Chief Information Security Officer (CISO) at the institution. His career spans military service and academic roles, with a focus on cybersecurity and network engineering. Education : Ph.D. in Electrical and Computer Engineering (Georgia Institute of Technology, 2022); M.S. in Computer Science (Air Force Institute of Technology, 2016). Research Interests include binary analysis, cyber forensics, security measurements, and IoT/mobile security. His work explores covert monitoring, plugin-based malware, and protocol vulnerabilities. Publications span conferences like USENIX Security and ACM CCS, emphasizing practical network and malware security challenges. Scientific Awards include Artifact Evaluated Badges (2023) and CSAW’22 Applied Research Competition Finalist status (2022).

Charalampos Tsimenidisمشاهده پروفایل

استاد

• Wireless Communications
• Underwater Acoustic Communications
• Internet of Things (IoT)
• +۷ مورد دیگر

Professor Charalampos Tsimenidis serves as Head of the Digital Innovation Group at IMEC, Deputy Lead for NTU's Engineering REF2029 submission, and Director of the Smart Wireless Innovation Facility (SWIFt) at Nottingham Trent University's School of Science and Technology, Department of Engineering. Previously a Professor of Digital Communications at Newcastle University for 25 years, he held leadership roles including Head of the Intelligent Sensing and Communications Group (2017-2022) and MSc Programme Coordinator. His research spans Wireless Communications , Underwater Acoustic Communications , and Internet of Things (IoT) technologies, with specific expertise in Adaptive Array Signal Processing, Coded OFDM Systems, Physical Layer Network Coding, Massive MIMO, and Turbo Equalization. Current research focuses on Massive MIMO, Intelligent Reflective Surfaces, and IoT-based systems, supported by substantial grants including EU Horizon Europe's SENSES project (£320k) and EPSRC's Full-Duplex For Underwater Acoustic Communications (£420k). Professor Tsimenidis has supervised 53 PhD students to completion and currently mentors 5 doctoral candidates. His professional service includes extensive editorial work (IEEE Journal of Oceanic Engineering), external examining for top UK universities, and organizing technical sessions at major conferences like IEEE Oceans and Globecom. He has chaired over 80 conference technical programs since 2004 and delivered 7 professional tutorials on underwater communications. Senior Member of IEEE Member of Institution of Engineering and Technology (IET) External Examiner for University of Manchester (2020-2024) and University of Loughborough (2021-2024) Author of book chapters including 'Underwater Acoustic Communications' in Applied Underwater Acoustics (Elsevier, 2017)

Giovanni Camuratiمشاهده پروفایل

پژوهشگر ارشد

• System Security
• Wireless Technologies
• Side-Channel Attacks
• +۷ مورد دیگر

Giovanni Camurati is a postdoctoral researcher at ETH Zurich in the System Security Group under Prof. Srdjan Capkun. Previously, he earned his PhD at Sorbonne Université, conducted at EURECOM, and visited UC Louvain. His research focuses on system security at the physical layer , particularly targeting UWB , GNSS , and mixed-signal chips in wireless devices. Key research areas: Side-channel attacks, Covert channels, Firmware analysis, Automotive network security Awards: Distinguished Paper at USENIX Security 2024, Runner-up PhD Award from GDR Sécurité Informatique (2020), 3rd place at CSAW Europe 2018 Article trends show expertise in distance reduction attacks (Ghost Peak, Time for Change), EM leakage exploitation (Noise-SDR, Screaming Channels), and security testing frameworks (Inception, MCRank). His work bridges theoretical analysis with practical attacks on commercial systems like Apple U1 chips and Google Eddystone beacons. Contact: camurati@eurecom.fr

• Security
• Cryptography
• Embedded Systems
• +۴ مورد دیگر

Jerome Lacan is a Professor at the Higher Institute of Aeronautics and Space (ISAE) and Head of the Department of Complex Systems Engineering (DISC). He leads the BLEND research group focused on blockchains for aerospace systems and contributes to the Sysco team. PhD in Computer Science from Paul Sabatier University (Toulouse, France) Accreditation to supervise research (2008) His research spans security and cryptography, with emphasis on: Blockchains for embedded systems (drones, satellites) Threshold cryptography and post-quantum cryptography Secure satellite communications (nano-satellites, authentication) Erasure codes and network coding (TETRYS protocol) His 15 most recent supervised theses (2012–2020) demonstrate expertise in cryptographic protocols, satellite communication reliability, and coding theory. Key themes include blockchain integration in aerospace, erasure coding for multimedia, and cross-layer network optimization. He has supervised 23 theses since 2008, covering topics like physical-layer security, transport protocol interactions, and high-throughput satellite systems.

• Orthogonal Frequency Division Multiplexing
• Secure Communication
• Physical Layer Security
• +۴ مورد دیگر

Ertuğrul Güvenkaya is an Assistant Professor at Istanbul Technical University's Department of Electronics and Communication Engineering. His work spans communications and signal processing , focusing on physical layer security and wireless communication systems. Current academic affiliation: Istanbul Technical University (since 2023) Industry experience: Apple (Wireless Systems Engineer, 2020-2023), MaxLinear (Sr Staff Communications Systems Engineer, 2016-2020) Education: Ph.D. and M.S. from University of South Florida; B.S. from Middle East Technical University His research centers on physical layer security , OFDM-based systems , and millimeter-wave communication , with a focus on waveform design, interference rejection, and spatial adaptation. His publications include works on cyclic prefix alignment, orthogonal space-time block codes, and secure signal transmission frameworks. Scientific output trends reveal expertise in physical layer concepts , waveform optimization , and non-orthogonal multiple access techniques . Key projects include Improving wireless communication systems using non-orthogonal multiple access (2024-2025) and Advanced Companion-Signal Design (2024-2027), both as principal investigator.

Nikos Christakisمشاهده پروفایل

استاد مدعو

• Meteorology
• Atmospheric Physics
• Computational Fluid Dynamics
• +۳ مورد دیگر

Nikos Christakis is an Adjunct Professor at the University of Crete, affiliated with the Department of Meteorology. His research focuses on the intersection of Meteorology , Atmospheric Physics , and Computational Fluid Dynamics , with a recent emphasis on integrating Artificial Intelligence and Machine Learning into these domains. Education: PhD in Meteorology from UMIST, Manchester (1998). Christakis specializes in applying computational methodologies to complex systems, including: Modeling wind potential and atmospheric flows Unsupervised learning for particle and virus dispersion Hybrid computational frameworks for environmental and granular material studies Historical work on ionospheric sporadic E layers and tidal variability His recent publications (2025-2021) demonstrate a strong trend toward AI-driven solutions for meteorological and environmental challenges, such as indoor climate analysis, pandemic forecasting, and particle dynamics. While no scientific awards are explicitly mentioned, his work bridges theoretical fluid dynamics with practical AI applications. Contact: nchristakis@tem.uoc.gr

• Information Theory
• Data Analytics
• Wireless Networks
• +۷ مورد دیگر

Anke Schmeink is a Professor at the Chair of Information Theory and Data Analytics within the College of Engineering Sciences at RWTH Aachen University. Her work bridges information theory and practical applications in wireless communication systems. Rector’s Delegate for Engineering Sciences Member of the ICT Profile Area Steering Committee Based in ICT Cube 2, Electrical Engineering, Aachen Her research focuses on machine learning integration in wireless networks, ultra-reliable low-latency communication (URLLC), UAV-assisted systems, physical layer security, and distributed learning frameworks. Recent publications explore optimization techniques for edge computing, NOMA applications, and finite blocklength regime challenges. She contributes to advancing 5G/6G architectures through interdisciplinary approaches combining reinforcement learning, sensor networks, and robust network design principles. Contact: anke.schmeink@inda.rwth-aachen.de