جست‌وجوی استاد و پژوهشگر

Dubravka Akšamovićمشاهده پروفایل

استاد

• Competition Law
• Corporate Law
• Bankruptcy Law
• +۵ مورد دیگر

Prof. Dubravka Akšamović is a Full Professor and Head of the Department of Commercial, Financial, Maritime and General Traffic Law at the Faculty of Law, Osijek. She holds a PhD in Competition Law and has been actively involved in academic leadership since 2003, including directing the Law Clinic and co-leading the interdisciplinary Law and Economics Clinic with the Faculty of Economics. Fluent in English, German, and Italian, she teaches courses on Company Law, Commercial Law, Bankruptcy Law, and Competition Law at undergraduate, graduate, and doctoral levels. Her research focuses on EU competition law, judicial review mechanisms, and corporate governance, with notable contributions to publications like Competition Law in Croatia (2019) and EU Competition and State Aid Rules (2018). She chairs specialist programs in Business Law and Transactions and serves on international bodies such as the European Network for Clinical Legal Education (ENCLE). Awards include the 2020/21 Dean’s Award for Excellence in Teaching. Her work bridges legal theory with practical clinical education, emphasizing access to justice and interdisciplinary collaboration. Education: Bachelor’s (Faculty of Law Osijek), PhD in Competition Law (2008). Professional Roles: Bar member since 2003, Head of Clinical Programs, Jean Monnet Module Lead in EU Competition Law (2018–2021). Key Contributions: Over 50 publications, involvement in EU-funded projects, and regulatory advisory roles including the Council of Conciliators at ICSID.

Pau Batlle Franchمشاهده پروفایل

پژوهشگر ارشد

• Statistics
• Applied Mathematics
• Uncertainty Quantification
• +۴ مورد دیگر

Pau Batlle Franch is a Research Fellow in the Computing and Mathematical Sciences Department at California Institute of Technology (Caltech), working with Professor Houman Owhadi. He holds a PhD from Caltech (June 2025) and was a research affiliate at NASA Jet Propulsion Laboratory (JPL). His research focuses on the intersection of statistics and applied mathematics, including frequentist confidence intervals in inverse problems, game-theoretical uncertainty quantification, and Gaussian processes. He has applied his work to domains like remote sensing, biology, earthquake prediction, and telecommunications engineering. Education : PhD in Computing and Mathematical Sciences (Caltech, 2025); Double undergraduate degree in Mathematics and Engineering Physics from Universitat Politècnica de Catalunya (CFIS program); Research visitor at NYU's Center for Data Science. His research interests include optimization-based statistical methods, Gaussian process frameworks for scientific computing, and uncertainty quantification in physical systems. Notable contributions include resolving the Burrus conjecture and developing computational hypergraph discovery techniques applied to NASA JPL projects. His work bridges theory and application, addressing challenges in ill-posed inverse problems and robust statistical inference. Recent activities include presenting at SIAM conferences and workshops on inverse problems in Earth science. His Gaussian process methods have been published in journals like PNAS and SIMODS, with applications ranging from PDE solving to RNA classification. Collaborations include JPL and the Groningen seismic study. Grants & Collaborations : Ongoing work with NASA JPL on lunar rover control and computational graph discovery; Seismic modeling in the Groningen gas field with epistemic/aleatoric uncertainty frameworks. He maintains an active GitHub profile showcasing projects in machine learning and scientific computing, including repositories like DarwinProjectAnalytics and emb4class .

Amel MAMMARمشاهده پروفایل

استاد

• Formal Methods
• Software Verification
• Computer Security
• +۳ مورد دیگر

Amel MAMMAR is a Professor at Telecom SudParis, specializing in formal methods and software verification. Her work focuses on applying the Event-B method to model and verify critical systems such as automotive systems, railway signaling, and cloud applications. She has contributed extensively to the development of formal approaches for ensuring correctness in embedded systems, smart contracts, and security protocols. Her research integrates formal modeling with tools like SAGEMATH for hybrid systems analysis and ProB for policy validation. MAMMAR collaborates on projects involving requirements engineering, safety-critical systems, and access control mechanisms. Her key contributions include Event-B models for automotive exterior lighting systems, railway standards (ERTMS/ETCS), and cloud resource allocation. She has published widely in venues like the International Journal on Software Tools for Technology Transfer and IEEE Transactions, emphasizing formal verification techniques for safety and security. Her work bridges theoretical formal methods with practical applications in industry sectors like transportation and aerospace.

Paul Richardsonمشاهده پروفایل

استاد

• Automotive Engineering
• Computing and Networks
• Robotics

Paul Richardson is a Professor in the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn’s College of Engineering and Computer Science. His research spans automotive systems, real-time networks, and robotics. PhD in Systems Engineering, Oakland University His work focuses on Automotive Engineering , Computing and Networks , and Robotics . Key contributions include innovations in intra-vehicle networks, UWB channel modeling, and real-time control systems. Recent publications highlight advancements in OFDM signal processing, PAPR reduction techniques, and adaptive scheduling for QoS in vehicular and mobile networks. Collaborations include researchers like W. Xiang and A. Elkateeb. He is affiliated with the Institute for Advanced Vehicle Systems at UM-Dearborn. Contact: richarpc@umich.edu .

Jean-Yves Le Boudecمشاهده پروفایل

استاد

• Network Calculus
• Time-Sensitive Networking
• Deterministic Networking
• +۷ مورد دیگر

Jean-Yves Le Boudec is a Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences and the Institute of Electrical Engineering. He has been a key figure in advancing the theory and application of network calculus and deterministic networking, contributing significantly to standards such as IEEE Time-Sensitive Networking (TSN) and IETF DetNet. His research focuses on network calculus , time-sensitive and deterministic networking , traffic regulation , worst-case delay analysis , and cyber-physical systems , with cross-cutting applications in smart grids , real-time communication , and network security . He has co-authored foundational texts on network calculus and developed theoretical frameworks for traffic regulators, service curves, and delay bounds in complex networked systems. The recent publications highlight a strong trend in analyzing and improving performance guarantees in deterministic networks, including scheduling mechanisms like Deficit Round-Robin and Cyclic Queuing and Forwarding, traffic shaping via interleaved regulators, and security against time-synchronization attacks in power systems. The work spans theoretical modeling using stochastic and min-plus/max-plus algebra, practical algorithm design, and application to critical infrastructure. IEEE Fellow Le Boudec has advised numerous researchers and PhD students, including Ehsan Mohammadpour, Ludovic Thomas, and Seyed Mohammadhossein Tabatabaee. His collaborative projects often involve grants related to European and Swiss research initiatives in networking and smart grid technologies. He leads a research group focused on networked systems at EPFL, contributing to both theoretical advances and real-world implementations in industrial and energy-critical networks. His lab work centers on modeling and verification of time-sensitive network behaviors, integrating formal methods with practical experimentation. The team investigates regulators, shapers, and synchronization mechanisms, aiming to ensure robustness, predictability, and security in next-generation communication infrastructures. Future work continues to explore the interplay between communication, control, and energy systems in highly reliable environments.

Lukas Iffländerمشاهده پروفایل

استاد

• Cybersecurity
• Cryptography
• Network Security
• +۴ مورد دیگر

Prof. Dr. Lukas Iffländer serves as a Professor within the Faculty of Informatics / Mathematics at Westsächsische Hochschule Zwickau, Germany, maintaining an active office (Room U 452) with contactable phone number +49 351 462 3516. His academic profile demonstrates continuous engagement through recent publications extending into 2025, with research appointments scheduled by prior arrangement reflecting his operational availability. His research program centers on cybersecurity with exceptional depth in cryptographic systems and infrastructure protection. Key specialties include homomorphic encryption optimization (notably CKKS scheme implementations), IoT security protocols for resource-constrained environments, and railway system vulnerability analysis. His methodology consistently integrates performance benchmarking with security validation, particularly examining computational overhead in privacy-preserving technologies and physical attack vectors against critical transportation infrastructure. This dual focus on theoretical cryptography and real-world system security establishes him as a bridge between academic research and industrial implementation challenges. Analysis of his 15 most recent publications (2023-2025) reveals three dominant research trajectories: (1) Cryptographic performance evaluation, where he pioneers benchmarking frameworks for homomorphic and attribute-based encryption in practical scenarios like linear regression; (2) Railway security innovation, addressing digital interlocking systems and physical attack mitigation through technology forecasting; (3) IoT security optimization, developing multi-objective recommendation systems for group communication protocols. His work consistently emphasizes measurable performance impacts, with 60% of recent publications containing empirical benchmarking data, reflecting an engineering-driven approach to security research. No scientific awards were documented in the source materials. Information regarding student supervision, research grants, or laboratory affiliations remains unavailable in the provided documentation, though his publication volume suggests active research group leadership. His technical focus on virtual machine introspection and hypercall handling indicates potential involvement in low-level systems security teams, while railway security publications imply collaboration with transportation infrastructure entities.

• Quantum Computing
• Embedded Systems
• Electronic Engineering
• +۳ مورد دیگر

Andrea Marchesin serves as an Adjunct Professor at Politecnico di Torino, holding dual affiliations with the Department of Control and Computer Science (DAUIN) and the Department of Electronics and Telecommunications (DET) within the School of Engineering. His teaching responsibilities include Embedded Systems Integration for Electronic Engineering students and Quantum Hardware Design and Optimization modules within the Quantum Engineering program for the 2024/25 academic year. Dr. Marchesin's research centers on practical applications of quantum computing, with particular emphasis on quantum annealing approaches for real-world optimization problems. His scholarly work demonstrates a strategic focus on near-term quantum applications that can deliver tangible benefits despite current hardware limitations. He has developed quantum models specifically targeting urban traffic optimization and has contributed to computer architecture through tools like Octantis for exploring beyond von Neumann paradigms. His publication trend reveals a consistent trajectory toward engineering applications of quantum technologies, with recent work appearing in high-impact venues including IEEE Access and IEEE Transactions on Quantum Engineering. The research portfolio spans both theoretical algorithm development and practical implementation challenges, reflecting a bridge between quantum computing theory and engineering practice. As an academic advisor, Dr. Marchesin served as relatore (thesis advisor) for doctoral research on quantum algorithms for engineering applications. His teaching portfolio spans multiple academic years (2021/22-2024/25) and includes specialized workshops on SoC Verification Strategies alongside core courses in digital electronics and embedded systems.

Tamás Tettamantiمشاهده پروفایل

استاد

• Road Traffic Control
• Intelligent Transportation Systems
• Traffic Simulation
• +۳ مورد دیگر

Tamás Tettamanti is a Professor at Budapest University of Technology and Economics, serving as Deputy Head of the Department of Control for Transportation and Vehicle Systems. He holds a PhD (2013), Habilitation (2023), and DSc (2023) in Transportation Engineering, with expertise in road traffic modeling and control. 2007–2010: PhD Student 2010–2013: Assistant Lecturer 2014–2018: Senior Lecturer 2019–2024: Associate Professor 2025–present: Full Professor Education: High School Graduation (2001), DEUG (2004), MSc in Transportation Engineering (2007), Jazz Trumpet Graduate (2008) PhD (2013), Habilitation (2023), DSc (2023) Research focuses on road traffic modeling, intelligent transportation systems (ITS), autonomous vehicle integration, and emission-aware traffic control. His work bridges theoretical developments with real-world applications, including wireless traffic light systems and deep learning for urban mobility peaks. Scientific Awards: BME PhD Research Prize (2012) Literary Awards from Hungarian Scientific Association for Transport (2013, 2017, 2021, 2023) Bolyai János Research Scholarship (2017–2020) Michelberger Master Prize (2022) BME Jubilee Medal (2023) He has led major projects such as Dynamic Adaptive Traffic Control Services (2020–2024) and Deep Learning Anticipated Urban Mobility Peaks (DARUMA) (2021–2024), with industry collaborations including Google-BME Traffic Lab.

Balázs Vargaمشاهده پروفایل

پژوهشگر ارشد

• Road Traffic Modeling and Control
• AI-based Traffic Flow Prediction
• Urban Traffic Simulation
• +۳ مورد دیگر

Dr. Balázs Varga is a Research Fellow at the Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics (BME). He holds a PhD in Transportation and Vehicle Sciences (2021) and an MSc in Vehicle Engineering (2015) from BME. His industry experience includes roles at AVL Hungary as a Software and Function Developer (2016–2018) and academic positions at Chalmers University of Technology (2015) and SZTAKI (2012–2014). Current Role: Research Fellow (2021–present) Teaching: Programming, Control Theory, Traffic Modeling (English language course) Research Interests: Varga specializes in road traffic modeling and control, focusing on AI-based traffic estimation and dynamic traffic management. His work integrates machine learning with mesoscopic and microscopic traffic simulation tools like SUMO to optimize urban mobility and reduce emissions. Projects: He leads the 2020–2024 national development project 'Dynamic, adaptive traffic control services and evaluation tools based on digitally connected data sources' (2019-1.1.1-PIACI KFI). This initiative leverages connected data sources for real-time traffic control and policy evaluation. Key Publications Trends: His recent articles explore topics such as graph neural networks for sensor placement, multiobjective control of emissions, and mixed-reality V2X testing. These works emphasize data-driven approaches, emission reduction, and simulation frameworks for autonomous vehicles.

• Road Traffic Control
• Traffic Automation
• Transportation Systems
• +۲ مورد دیگر

Dr. Varga István is a Full Professor at the Budapest University of Technology and Economics (BME) in the Faculty of Transportation Engineering and Vehicle Engineering, and a Scientific Advisor at the HUN-REN Institute for Computer Science and Control. He holds a D.Sc. from the Hungarian Academy of Sciences (2020), a Ph.D. (2007), and an M.Sc. in Transportation Engineering (1998). His primary research focuses on road traffic control and traffic automation systems , with expertise in intelligent transportation solutions and vehicle mechatronics. His research integrates control theory with practical applications in urban mobility, including dynamic traffic light systems, autonomous vehicle impacts, and emission modeling. Recent work explores V2X communication, platooning technologies, and microscopic traffic simulation for urban optimization. He has led major projects such as the national innovation project 'Dynamic, adaptive traffic control services based on digital data sources' (2020-2024) and industrial collaborations with Knorr-Bremse, Siemens, and nuclear energy sectors. Awards include the Hungarian Academy of Sciences Young Prize (2007) and multiple recognitions for technological innovation. Educational activities include courses on Road Traffic Control, Mathematical Methods, and Vehicle System Modeling. Laboratory leadership includes the Road Traffic Control Lab with industry partnerships like Bosch and SWARCO.

Xiaoyan Hongمشاهده پروفایل

دانشیار

• Distributed Systems
• Internet of Things (IoT)
• Wireless Communications
• +۴ مورد دیگر

Dr. Xiaoyan Hong is an Associate Professor in the Department of Computer Science at The University of Alabama's College of Engineering. Her research focuses on mobile/wireless networks, vehicular networks, and delay-tolerant systems. Ph.D., Computer Science, University of California-Los Angeles (2003) M.S., Computer Science, Zhejiang University (2000) Research spans Internet of Things (IoT) , Connected Vehicles , and Underwater Wireless Networks . Key projects include NSF-funded underwater robot communication infrastructure and smart traffic light systems. Recent work explores Named Data Networking (NDN) in vehicular environments, Task Synchronization for autonomous vehicles, and V2I Communication for traffic optimization. NSF Research Experience for Undergraduates (REU) grant recipient $1.5M NSF grant for underwater robotics networking Her research integrates with multiple engineering centers, including the Center for Advanced Vehicle Technologies and Center for Transportation Operations .

Michael Dinitzمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Approximation Algorithms
• Online Algorithms
• +۵ مورد دیگر

Michael Dinitz is an Associate Professor in the Department of Computer Science at Johns Hopkins University with a secondary appointment in the Department of Applied Mathematics and Statistics . He is a member of the Algorithms and Complexity group and the Mathematical Institute for Data Science . His research focuses on Theoretical Computer Science , with emphasis on approximation algorithms , online algorithms , and distributed algorithms , particularly in applications to computer networking , distributed systems , and machine learning . His recent work involves differential privacy , dynamic networks , and resilient network design . His publications cover diverse topics in graph theory , privacy-preserving algorithms , and online optimization , with a focus on practical applications of theoretical results. He has received multiple NSF grants including a CRII award and Algorithms in the Field funding, and was honored with the Professor Joel Dean Excellence in Teaching Award . He advises a research group with PhD, MSE, and undergraduate students , and serves on program committees for leading theory conferences like FOCS , STOC , and ICALP . Education PhD in Computer Science, Carnegie Mellon University (2010), advised by Anupam Gupta AB in Computer Science, Princeton University (2005), advised by Sanjeev Arora Grants & Awards NSF CRII Grant (2015) NSF Algorithms in the Field Grant (2016) Multiple NSF Algorithmic Foundations grants (2019, 2022, 2025) NSF Graduate Research Fellowship (2005-2010) ARCS Foundation Scholarship (2005-2010) Best Paper Awards at ICDCS (2014) and DISC (2017)

• Human Factors
• Ergonomics
• Automated Driving
• +۳ مورد دیگر

André Dietrich serves as a Researcher at the Department of Ergonomics, Technical University of Munich, since March 2015. His work centers on pedestrian-vehicle interactions within automated driving contexts, utilizing advanced simulation methodologies and field studies to enhance urban traffic safety. Education: Diploma in Aerospace Engineering from Technical University of Munich specializing in aircraft propulsion and aerospace engineering Completed diploma thesis "Feasibility Analysis of a Pedestrian Simulator" in December 2014 Research Interests: Dietrich investigates pedestrian crossing behavior in automated urban environments through human factors and ergonomics frameworks. His work pioneers external human-machine interfaces (eHMIs) for vehicle-pedestrian communication, examining kinematic effects, cultural influences, and age-related perception differences. Key methodologies include augmented reality simulations, LiDAR-based field observations, and motion-platform pedestrian simulators to capture behavioral nuances in traffic scenarios. His research directly addresses safety challenges posed by increasing vehicle automation levels in complex urban settings. Publication Trends: Analysis of Dietrich's 12 publications (2016-2022) reveals consistent focus on pedestrian-AV interaction mechanisms. His work demonstrates evolving methodologies from controlled simulator studies toward real-world field validations, with growing emphasis on inclusive eHMI design for diverse user groups. Cross-cultural comparisons and technical innovations in projection-based interfaces represent significant thematic threads across his publication history. Advising and Grants: No student supervision or grant funding details are documented in the provided materials. Labs and Infrastructure: Dietrich operates within TUM's Ergonomics Chair facilities including the Dynamical Mock-Up, Modular Ergonomic Mockup, Static Driving Simulator, and robotics labs. These resources support his research on cabin design, automated driving systems, and human-robot interaction within traffic contexts.

Abbas Razaghpanahمشاهده پروفایل

پژوهشگر

• Internet Privacy
• Network Security
• Mobile Security
• +۴ مورد دیگر

Abbas Razaghpanah is a Researcher at the International Computer Science Institute (ICSI) , focusing on Internet privacy, security, and network measurement . He earned his PhD at Stony Brook University and previously interned at ICSI, leading the Haystack Project and developing the Lumen app . Research Focus: Mobile app security, TLS deployment, censorship measurement, and traffic differentiation Key Projects: Haystack, Lumen, ICLab Scientific Awards : ACM Research Competition Runner-Up Award Open Technology Fund Information Controls Fellowship ACM IMC 2018 Distinguished Paper Award His work involves collaboration with Citizen Lab at the University of Toronto and includes grants for studying global information controls. Abbas develops tools for user-space network monitoring to enhance transparency and regulatory compliance.

• Control Engineering
• Automotive Engineering
• Model Predictive Control
• +۵ مورد دیگر

Dr.-Ing. Frank-Josef Heßeler is a Senior Research Engineer (Geschäftsführender Oberingenieur) and Deputy Institute Director at the Institute of Control Engineering (IRT), RWTH Aachen University . His work focuses on control systems for automotive and urban mobility applications, including model predictive control, vehicle localization, and intelligent infrastructure. He actively contributes to research in autonomous driving, hybrid drivetrains, and thermal systems optimization. Control Engineering Automotive Systems Model Predictive Control Thermal Diagnostics Urban Traffic Simulation His publications highlight advancements in connected vehicle localization, scenario-specific motion modeling, and hybrid drivetrain control. He collaborates extensively with Dirk Abel and other researchers. No scientific awards or student advisement details are explicitly mentioned in the provided texts. He is affiliated with the Institute of Control Engineering, engaging in projects like CERMcity (autonomous urban driving testbed) and Galileo-based navigation systems. His work integrates simulation platforms, Neuro-Fuzzy models, and hardware-in-the-loop testing for automotive control solutions.