جست‌وجوی استاد و پژوهشگر

• High Performance Computing
• Numerical Methods
• Scientific Computing
• +۳ مورد دیگر

Anne Reinarz is an Associate Professor in the Department of Computer Science at Durham University. Her research focuses on high performance computing, numerical methods, and scientific computing. She specializes in developing parallel algorithms for large-scale simulations of wave phenomena and uncertainty quantification techniques. She currently supervises multiple postgraduate students in computational mechanics and numerical analysis. Her work develops scalable computational frameworks for complex physical systems including wave propagation, material fracture, and spacetime evolution. She contributes to the ExaHyPE engine for adaptive simulations and investigates fault tolerance in high-performance computing environments. Her methods enable efficient solution of partial differential equations on exascale architectures. Dr. Reinarz's publications demonstrate consistent focus on parallel algorithms for scientific computing challenges. Her recent work includes fracture modeling in composite materials, sparse grid approximations for boundary integrals, and multilevel Monte Carlo methods for uncertainty quantification.

Abdel-Hamid Solimanمشاهده پروفایل

استاد

• Automation (Smart Cities, Energy Management)
• Fibre Optic Communication Systems
• Data Acquisition Systems
• +۵ مورد دیگر

Abdel-Hamid Soliman is a Professor in the Department of Digital, Tech, Innovation & Business at Staffordshire University, UK. His academic roles include teaching, research leadership, and industrial collaboration. He holds a PhD in Image Processing and multiple postgraduate certifications in research supervision and methods. Education Background: PhD in Image Processing MSc in Information Systems and Data Acquisition Systems BEng (Hons) Distinction in Electronics and Communications PGC in Research Supervision PGC in Research Methods Research focuses on bridging academia and industry through automation technologies (Smart Cities, Energy Management, Safety Systems), fibre optics, IoT, and advanced signal/image processing. He leads EU-funded projects like CERES-TEMPUS, PEACE Erasmus Mundus, and WatERP-FP7. His work emphasizes community impact through innovation. Industrial Collaboration: Consultant for oil companies (VIBA, AGIP, etc.) Co-founder of ICentrica Ltd (spin-out company) Delivered projects for Sturge Industries, Universal Systems, and Direct Radio Response Grants & Partnerships: Secured EU funding via FP7 and Erasmus Mundus programs National/international partnerships in North Africa/Middle East Labs/Teams: Involved with Staffordshire's research groups and ICentrica Ltd's innovation activities. Active in training programs for industry professionals and university collaborations.

Yavuz Yardimمشاهده پروفایل

پژوهشگر ارشد

• Structural Engineering
• Sustainability
• Advanced Technologies
• +۵ مورد دیگر

Dr. Yavuz Yardim is a Research Fellow and university teacher at the School of Engineering, University of Edinburgh, specializing in structural engineering, sustainability, and AI-driven structural health monitoring. His research focuses on enhancing infrastructure resilience through innovative materials and techniques, including fiber-reinforced polymers and sustainable low-carbon bricks. Current academic role: University Teacher/Research Fellow Research institutes: Infrastructure and Environment Specialties: Structural performance assessment, earthquake-resistant design, historical masonry, sustainable materials Dr. Yardim holds a PgCAP in Academic Practice (University of Edinburgh, 2025), Associate Professorships from Turkey and Albania (2013), a Ph.D. in Structural Engineering (University Putra Malaysia, 2008), and degrees from University Putra Malaysia and University of Gaziantep. He is a Chartered Civil Engineer (ICE) and member of Turkey's Chamber of Civil Engineers. His teaching includes Conceptual Design and Sustainability for Civil Engineers , Engineering Principles 1 , and Behaviour and Design of Structures 2 , alongside prior roles in reinforced concrete design, bridge engineering, and advanced structural analysis. Research projects emphasize experimental and computational studies on reinforced concrete, historical masonry, and AI-driven bridge inspection using Retrieval-Augmented Generation and knowledge graphs. Recent publications highlight advancements in ultra-high-performance concrete hybridization, FRP retrofitting for non-circular columns, and sustainable construction materials like water-based polymeric binders. His work bridges structural resilience with modern technologies, addressing global challenges in civil infrastructure. 2025 : Steel/glass fiber hybridization for UHPC 2024 : Bridge engineering innovations 2023 : FRP strengthening for RC columns, ferrocement in masonry 2022 : URM shear resistance, bridge deficiencies 2019-2016 : Masonry retrofitting, historical structure analysis

• Transportation and Freight Services
• Artificial Intelligence and Image Processing
• Automotive Engineering
• +۳ مورد دیگر

Felix Feng is a Research Fellow and Manager of the Intelligent Infrastructure and Transport Systems (IITS) Laboratory at Imperial College London's Department of Civil and Environmental Engineering. His work focuses on developing configurable automotive system models for autonomous vehicle safety validation and simulating interactions with road users. He holds a PhD in Mechanical Engineering (University of Bath, 2019), an MSc in Mechatronics (University of Bath, 2014), and a BEng in Mechatronics (Tongji University, 2013). Education: PhD in Mechanical Engineering, University of Bath (2015–2019) MSc in Mechatronics Engineering, University of Bath (2013–2014) BEng in Mechatronics Engineering, Tongji University (2009–2013) His research interests span autonomous vehicles , artificial intelligence , transportation systems , and control systems . Notable projects include driver model development using machine learning and safety validation frameworks for autonomous systems. His recent work explores multimodal traffic prediction, digital twin simulations, and reinforcement learning applications in urban logistics. Publications highlight advancements in traffic risk modeling, GNSS fault detection, and smart infrastructure solutions. Felix’s contributions address challenges in autonomous vehicle interaction safety, urban mobility optimization, and resilient air traffic networks. His IITS Lab at Imperial focuses on translating cutting-edge research into practical tools for safer, smarter transportation ecosystems.

• Financial History
• Economic History
• Communication Networks
• +۸ مورد دیگر

Andrew M. Odlyzko is a Professor at the School of Mathematics, University of Minnesota, specializing in interdisciplinary research spanning financial history, economic theory, and communication networks. His work examines historical financial manias, railway development, and market dynamics with a focus on bubbles, fraud, and irrational investment behaviors. He has published extensively on topics such as the 1840s Railway Mania, the South Sea Bubble, and Victorian-era financial systems. Affiliations: University of Minnesota, School of Mathematics Research Focus: Technology manias, financial history, cryptography, computational number theory Odlyzko's research highlights recurring patterns in financial crises through historical analysis, blending economics, sociology, and information sciences. His papers often critique classical economic assumptions using data-driven historical evidence. He has contributed to debates on market inefficiencies, railway network planning, and the role of financial innovation. Key themes include the psychology of speculative bubbles and the long-term impacts of infrastructure investments.

• Wireless Communications
• Digital Communication Theory
• Error Control Coding
• +۷ مورد دیگر

Branka Vucetic is a Laureate Professor and ARC Laureate Fellow at The University of Sydney's School of Electrical and Computer Engineering. She leads the Centre for IoT and Telecommunications, focusing on advancing wireless communication systems, including mmWave, URLLC, and IoT. Her research spans coding theory, multi-user detection, and networked control systems. With over 300 publications and four books, she has received prestigious awards such as the Chinese Government Friendship Award and the CSIRO Eureka Prize. She advises numerous PhD and Master’s students on topics like RIS-assisted wireless communications and AI-driven clinical decision support. Education: MSc and PhD from the University of Belgrade. Research interests include 6G technologies, reconfigurable intelligent surfaces, and mission-critical IoT applications. Her work addresses latency, reliability, and energy efficiency challenges in modern communication networks. Current roles include Director of the Centre for IoT and Telecommunications and Fellowships in multiple academies. Awards highlight her contributions to innovation and leadership in engineering and science. She collaborates on projects funded by ARC and industry partners, focusing on practical applications like smart grids and autonomous systems.

Anne Hranchookمشاهده پروفایل

دانشیار

• Nurse Anesthesia
• Patient Safety
• Quality Improvement in Healthcare
• +۴ مورد دیگر

Anne Hranchook, DNP, CRNA serves as Associate Professor & Assistant Director of the OU-Beaumont Graduate Program of Nurse Anesthesia at Oakland University's School of Nursing. Based in the Human Health Building, Room 3056, she leads the nurse anesthesia program in collaboration with Corewell Health - William Beaumont University Hospital. Her dual role bridges academic instruction with clinical practice in anesthesiology. Dr. Hranchook's educational background includes: DNP from Oakland University MSN in Nurse Anesthesia from Oakland University BSN from University of Detroit Her research program focuses on quality and safety in anesthesia delivery and the implementation of technology in clinical practice. With extensive clinical experience from 20 years at William Beaumont University Hospital, she specializes in translating research into evidence-based practice that enhances patient outcomes. Her work particularly addresses how administrative decision-making can promote cultures of critical thinking and accountability within healthcare settings. Analysis of her recent publications reveals consistent themes in patient safety, with particular attention to closed claims analysis, technology integration in anesthesia practice, and the educational implications of these findings. Her research demonstrates a longitudinal commitment to understanding and improving anesthesia safety through systematic analysis of adverse events and implementation of evidence-based solutions. Her scientific recognition includes: AANA Foundation Oral Poster Award ($1,000) Dr. Hranchook has secured significant research funding, most notably multiple Nurse Anesthesia Traineeship grants from the Health Resources and Services Administration spanning over a decade (2012-2022), plus an Oakland University Research Committee Faculty Research Grant. These awards demonstrate sustained external validation of her work in anesthesia education and patient safety. As Assistant Director of the OU-Beaumont Graduate Program of Nurse Anesthesia, she plays a pivotal role in shaping the next generation of nurse anesthetists through curriculum development, clinical oversight, and research mentorship in collaboration with Corewell Health.

Ahmed Arafaمشاهده پروفایل

دانشیار

• Communication Theory
• Information Theory
• Machine Learning
• +۵ مورد دیگر

Dr. Ahmed Arafa is an Associate Professor in the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte. His research focuses on Communication Theory, Information Theory, Machine Learning, and Signal Processing, with emphasis on data freshness, federated learning, and energy harvesting systems. Education: Ph.D., University of Maryland, College Park, MD (2017) M.Sc., Nile University, Egypt (2012) B.Sc., Alexandria University, Egypt (2010) Research Interests: His work spans advanced communication protocols, optimization of information freshness in networks, and secure machine learning frameworks. He has contributed to theories on energy harvesting communication systems and privacy-aware data transmission. Recent trends in his publications highlight innovations in federated learning over unreliable networks and hierarchical learning architectures under delay constraints. Publications: His recent work explores timely status updating mechanisms, robust federated learning strategies, and multi-class information optimization. These studies address challenges in network latency, data accuracy, and distributed computing scalability. Scientific Awards: No awards explicitly listed. Advising & Grants: No student advisees or grant details provided in the available text. His contributions are primarily through research and publications. Labs & Teams: No specific lab affiliations or collaborative teams explicitly mentioned.

Ahmed BOUBRIMAمشاهده پروفایل

پژوهشگر

• Sensor Networks
• Drone Networks
• Wireless Sensing
• +۳ مورد دیگر

Dr. Ahmed Boubrima is a tenured faculty researcher at Inria (AGORA team, Lyon, France) since 2023, specializing in sensor networks, drone networks, and environmental sensing. He holds a Ph.D. from INSA Lyon (2019) and master's degrees from École Nationale Supérieure d'Informatique, Algiers (2015). His research focuses on optimizing wireless sensor network deployment for environmental monitoring, with applications in urban air quality and autonomous drone systems. Boubrima has led projects like the ASTRO postdoc at Rice University (2019-2022) and contributed to initiatives at the University of Ottawa as a visiting researcher. Research Interests: Design of energy-efficient sensing platforms for environmental monitoring Autonomous data-driven sensing via networked drones Optimization models for sensor network deployment Resilient environmental mapping using UAVs Awards: Best Paper Award at ACM DroNet@MobiSys 2020 Best Paper Award at UNET 2016 IEEE ComSoc France Chapter Prize (2015) Advising & Teaching: Supervises PhD students and mentors over 20 graduate researchers. Teaches networking courses at INSA Lyon's Telecommunications Department, including Fundamentals of Computer Networking and Performance Analysis. Labs/Teams: Leads the AGORA team at Inria, focusing on algorithmic game theory and networked systems. Collaborates with global institutions on environmental sensing and drone networks.

Elizabeth Behrmanمشاهده پروفایل

استاد

• Quantum Information Theory
• Quantum Computing
• Quantum Machine Learning
• +۳ مورد دیگر

Elizabeth Behrman is a Professor at Wichita State University (WSU), affiliated with the Department of Mathematics, Statistics, and Physics within the Fairmount College of Liberal Arts and Sciences. She holds a Ph.D. from the University of Illinois at Urbana-Champaign (1985). Her research spans quantum computing, quantum machine learning, and quantum neural networks, with interdisciplinary collaborations in Mathematics, Electrical Engineering, Aerospace Engineering, and Chemistry. Her work includes pioneering studies on quantum control, entanglement estimation, and applications of quantum algorithms in fields like medical imaging and language processing. Key research interests include quantum information theory, quantum algorithms, and the integration of machine learning with quantum systems. Behrman’s contributions to quantum repeaters, quantum generative adversarial networks, and qutrit-based learning networks highlight her focus on advancing quantum technologies for practical applications. She has published extensively on topics ranging from quantum circuit design to noise-resilient algorithms. Collaborative projects involve optimizing quantum hardware through machine learning and exploring hybrid quantum-classical methods. Her work has been featured in venues like IEEE Transactions and YouTube, emphasizing both theoretical and experimental advancements. Behrman’s research also extends to historical contributions in materials science, including studies on ceramic superconductors and inorganic buckyballs. While no specific scientific awards are listed, her prolific publication record and interdisciplinary impact reflect significant contributions to quantum science. Her advising and grant activities are not detailed here, but her collaborations suggest active participation in research networks and funding initiatives.

Xavier Picمشاهده پروفایل

پژوهشگر ارشد

• DNA Data Storage
• Image Coding
• Data Compression
• +۳ مورد دیگر

Xavier Pic is a Research Fellow at EURECOM's Data Science department. His work focuses on advancing DNA-based data storage technologies, particularly in the intersection of computer science, bioengineering, and machine learning. He specializes in developing innovative coding algorithms, entropy coders, and neural network architectures for robust image and media storage on synthetic DNA. Key research areas include implicit neural representations, multiple description coding, and compressive autoencoders. His contributions address challenges in long-term data preservation, error resilience, and efficient encoding-decoding processes. Xavier actively explores applications ranging from molecular biology-driven storage solutions to hybrid systems combining classical algorithms (e.g., JPEG) with modern deep learning techniques. His research portfolio reflects interdisciplinary collaboration, bridging computer science with synthetic biology. Prior to his current role, he contributed to text alignment projects using deep learning and dynamic programming for historical document analysis.

• Wireless Communications
• Network Optimization
• Quality of Service (QoS)
• +۳ مورد دیگر

Francisco M. Delicado Martínez is an academic researcher specializing in telecommunications, wireless networks, and IoT applications. His work focuses on Quality of Service (QoS) mechanisms, Software Defined Networks (SDN), and blockchain integration in fog computing environments. He has contributed to optimizing resource allocation in OFDMA and IEEE 802.16 networks, and developed IoT-based systems for environmental monitoring (e.g., glyphosate detection, agrochemical spray drifts, and Aedes aegypti surveillance). His recent research emphasizes low-cost IoT ecosystems and blockchain-driven e-government services for public administration and construction management. Research interests span across wireless communications, network optimization, and distributed computing architectures. His publications address challenges in contention resolution, bandwidth request mechanisms, and machine learning integration for disease vector monitoring. Collaborations include projects on fog computing orchestration, SDN-based network enhancements, and multimedia transmission over TDMA/TDD wireless networks. Key contributions include the S-HIDRA architecture (blockchain & SDN for fog computing), DriftGLY and SpectroGLY IoT systems, and the MosquIoT framework for mosquito population monitoring. His work bridges theoretical network protocols with practical applications in agriculture, public health, and smart infrastructure.

Ewa Deelmanمشاهده پروفایل

استاد پژوهشی

• Scientific Workflow Management
• Distributed Systems
• Resource Provisioning
• +۵ مورد دیگر

Ewa Deelman is a Research Professor in the Department of Computer Science at the University of Southern California (USC) and a Principal Scientist at the USC Information Sciences Institute. She also directs Science Automation Technologies, a research group focused on automating scientific processes through advanced workflow management solutions. Her work is foundational in enabling complex scientific computations across distributed computing environments. Deelman's research centers on scientific workflow automation, including resource provisioning, data management, and job scheduling in distributed systems. She pioneered workflow planning for distributed computations and leads the development of the Pegasus Workflow Management System. Current interests extend to anomaly detection using machine learning, quantum-classical hybrid workflows, and edge-to-cloud continuum integration. Her group's work bridges theoretical advances with practical tools for domain sciences like seismology and molecular dynamics. Analysis of her recent publications reveals a strong emphasis on enhancing workflow robustness through machine learning and emerging technologies. Key trends include LLM-based scheduling optimization, pandemic-driven resilience studies, and quantum workflow integration. Her work increasingly addresses cross-cutting challenges in data-intensive science, particularly in managing computational workflows across heterogeneous infrastructures from edge devices to cloud platforms. As Director of Science Automation Technologies, Deelman oversees a team that has made Pegasus a cornerstone tool in scientific computing. The system handles complex workflow orchestration for projects like CyberShake (seismic hazard analysis) and molecular dynamics simulations, automating data movement, execution, and error recovery across campus clusters, supercomputers, and cloud resources.

• Cryptography
• Cybersecurity
• Hardware Security
• +۳ مورد دیگر

Elisabeth Oswald is a University Professor at the Alpen-Adria-Universität Klagenfurt, affiliated with the Institut für Artificial Intelligence und Cybersecurity. Her research focuses on cryptographic security, side-channel attacks, and leakage detection in hardware and software implementations. She is a key contributor to advancements in cryptographic resilience, countermeasures against side-channel vulnerabilities, and the development of efficient security evaluation frameworks. Her work spans theoretical and applied cryptography, with a strong emphasis on practical security challenges in embedded systems and cryptographic protocols. Notable areas include the analysis of masking techniques, multi-task learning applications in AES implementations, and the certification of leakage-resistant systems. She also explores statistical methods for evaluating cryptographic systems' robustness, such as mutual information estimation and distinguisher-based approaches. Her articles from 2021–2025 highlight contributions to post-quantum cryptography (e.g., FrodoKEM optimization), leakage model completeness, and the practical implications of side-channel countermeasures. While no specific awards are listed, her extensive publication record underscores her influence in the field. She is actively involved in academic governance, including membership in the Curricularkommission Informatik.

Burcu Özkanمشاهده پروفایل

پژوهشگر

• Algorithms
• Theory & Logic
• Programming Languages
• +۹ مورد دیگر

Burcu Özkan is a researcher at the Max Planck Institute for Software Systems (MPI-SWS), part of the Max Planck Society. Her work focuses on foundational areas of computer science including algorithms, programming languages, verification, and cyber-physical systems. She also explores distributed systems, networked/mobile systems, security, privacy, and social/information systems. Her research interests span theoretical and applied topics such as formal methods for system verification, resilient distributed computing, and privacy-preserving technologies. While no specific articles or awards are listed, her affiliations suggest involvement in cutting-edge CS research aligned with MPI-SWS's focus areas. Email: burcu@mpi-sws.org | Website: https://people.mpi-sws.org/~burcu (Note: The website currently returns a 404 error)