جست‌وجوی استاد و پژوهشگر

Yifan Sunمشاهده پروفایل

استادیار

• GPU Architecture
• Computer Architecture Simulation
• Multi-GPU Systems
• +۵ مورد دیگر

Yifan Sun is an Assistant Professor in the Department of Computer Science at William & Mary, leading the Scalable Architecture Lab. He holds a Ph.D. in Electrical and Computer Engineering from Northeastern University (2020). His research focuses on GPU architecture, simulation tools, and multi-GPU system design. Recent work includes TrioSim (a lightweight DNN workload simulator) and NetCrafter (optimizing multi-GPU network traffic). He has published extensively at top venues like ISCA, MICRO, and IEEE Vis. Educations: Ph.D. in Electrical and Computer Engineering, Northeastern University (2020); M.S. and B.S. not explicitly stated but implied through academic progression. Research Interests: Developing explainable architecture tools, improving simulation frameworks (Akita/MGPUSim), and addressing challenges in wafer-scale GPU design. His work bridges hardware-software co-design with visualization techniques to enhance human understanding of complex architectures. Grants: Awarded NSF CCRI and CRII grants for simulation-as-a-service and explainable architecture projects. Collaborations include UVA, NUS, and Northeastern University. Labs/Teams: Scalable Architecture Lab (SARCHLAB), focusing on GPU systems, simulation, and visualization. Active in organizing workshops and GitHub repositories (e.g., https://github.com/sarchlab).

Roy Harrisonمشاهده پروفایل

استاد

• Air Pollution
• Environmental Health
• Atmospheric Chemistry
• +۳ مورد دیگر

Professor Roy Harrison OBE FRS is the Queen Elizabeth II Birmingham Centenary Professor of Environmental Health at the University of Birmingham and holds an Adjunct Professor position at King Abdulaziz University, Saudi Arabia. With a 45-year academic career, he specializes in air pollution , focusing on emissions, atmospheric transformations, and health impacts of particulate matter. B.Sc. (Chemistry, 1969) Ph.D. (Organic Chemistry, 1972) D.Sc. (Environmental Chemistry, 1989) His research spans airborne particle characterization , chemical aging of aerosols, traffic emission mitigation technologies, and environmental policy development . Recent publications emphasize source apportionment , oxidative potential measurement , and machine learning applications in pollution modeling. Scientific recognition : Officer of the Order of the British Empire (2004) Fellow of the Royal Society (2017) Web of Science Highly Cited Researcher Professor Harrison has supervised 30+ doctoral researchers and serves on numerous advisory boards including DEFRA's Air Quality Expert Group and WHO air quality guidelines committees. He is Editor-in-Chief of Climate and Atmospheric Science (Nature) and maintains active roles in multiple editorial boards.

Muhammad M. Sherifمشاهده پروفایل

استادیار

• Smart Materials
• Structural Systems
• Machine Learning Applications
• +۴ مورد دیگر

Dr. Muhammad M. Sherif is an Assistant Professor in the Department of Civil, Construction, and Environmental Engineering at the University of Alabama at Birmingham (UAB), part of the School of Engineering. He joined UAB in Fall 2019 after completing his Ph.D. at the University of Virginia and M.S. at Carnegie Mellon University, both in structural engineering. His research focuses on smart materials, structural systems, and machine learning applications in civil infrastructure. He is particularly interested in additive manufacturing for construction and the development of innovative materials like engineered cementitious composites. Education: B.S., United Arab Emirates University M.S., Carnegie Mellon University Ph.D., University of Virginia Research Interests: Dr. Sherif’s work spans material characterization, machine learning models for structural analysis, and the integration of advanced materials into infrastructure systems. He explores topics like crack detection using UAVs, superelastic shape memory alloys, and multi-objective optimization in welding processes. His Advanced Materials and Smart Infrastructure Systems (AMSIS) lab emphasizes interdisciplinary approaches to solving civil engineering challenges. Publications: His recent work includes studies on UAV-based pavement crack detection, machine learning for concrete strength prediction, and optimization of tube-to-tubesheet joints. These reflect trends toward AI-driven solutions and sustainable material innovations. Advising: He actively mentors students in multidisciplinary research projects, emphasizing self-motivation and innovation. His lab collaborates on topics like composite materials, structural health monitoring, and infrastructure resilience. Labs/Teams: His AMSIS lab at UAB focuses on advancing smart materials and infrastructure systems through cutting-edge research and collaboration.

Mohammad Karimمشاهده پروفایل

استاد

• Optical Computing
• Information Processing
• Pattern/Target Recognition
• +۵ مورد دیگر

Mohammad Karim, PhD, is a Professor in the Department of Electrical & Computer Engineering at the University of Massachusetts Dartmouth (UMass Dartmouth), affiliated with the College of Engineering. He previously held leadership roles including Provost, Executive Vice Chancellor for Academic Affairs, and Chief Operating Officer at UMass Dartmouth. His career includes serving as Vice President of Research at Old Dominion University (2004–2013), Dean of Engineering at City College of New York (2000–2004), and Head of Electrical and Computer Engineering at the University of Tennessee (1998–2000). He is an elected fellow of multiple prestigious organizations, including IEEE, OSA, and SPIE. Dr. Karim holds a BS Honors in Physics from the University of Dhaka (1976) and MS in Physics (1978) and MS/PhD in Electrical Engineering (1979/1981) from the University of Alabama. His research focuses on optical computing, pattern recognition, electro-optical systems, and sensors, with funding from agencies like the Office of Naval Research and NASA. He has authored 19 books, over 365 papers, and 13 book chapters, and served as guest editor for 36 journal special issues. His awards include Fellowships from IEEE, OSA, and the Bangladesh Academy of Sciences. He mentors students in MS/PhD programs and advises on research proposals. His work spans academic leadership, technical innovation, and interdisciplinary collaboration in engineering and optics.

• IoT Security
• Network Measurement
• Privacy Engineering
• +۳ مورد دیگر

Dr. Anna Maria Mandalari is an Assistant Professor at University College London (UCL), affiliated with the Electronic and Electrical Engineering Department. She serves as Director of the SafeNetIoT laboratory and the Internet Engineering/Telecommunications MSc/MRes Programme at UCL. She holds an Honorary Research Fellow position at the Institute for Security Science and Technology at Imperial College London. Her research focuses on IoT security, privacy engineering, and network measurement techniques, particularly analyzing information exposure from consumer devices and developing adaptive network security strategies. Her work has led to significant contributions such as the IMC'19 Community Contribution Award-winning study on multidimensional IoT device exposure and the Telekom Challenge-winning IoTrim prototype for blocking non-essential IoT traffic. She has secured funding through InnovateUK’s CyberASAP program and participated in high-impact projects like NATwatcher and the European roaming analysis initiative. Key Awards: Community Contribution Award (IMC'19), Best Paper Award (C2B(I)D 2015) Grants: InnovateUK CyberASAP Phase 2 funding, Telekom Challenge Development Stream Top 5 prize Labs/Teams: Director of SafeNetIoT Lab, Leading M2M and IoT security teams at UCL Her recent work addresses IoT device misactivation risks (e.g., smart speakers), scalable detection of IoT devices in the wild, and protocol design informed by crowdsourced data. She actively collaborates with industry partners like Telekom and academic institutions on network infrastructure security and performance optimization.

• Production Systems Optimization
• Flow Simulation
• Energy-Efficient Optimization
• +۵ مورد دیگر

Abdelkader Mekhalef Benhafssa serves as a Teacher-Researcher at CESI Engineering School within the Engineering and Digital Tools research team. His work spans industrial engineering, robotics, and sustainable manufacturing systems. Education: Doctorate in Electrical Engineering (2017) Master's degree in Electrical Engineering specializing in Electrical Networks and High Voltage Techniques (2013) His research focuses on optimizing production systems through multi-agent simulations, human-robot collaboration in Industry 5.0 contexts, and energy-efficient manufacturing. Key areas include flow simulation, autonomous vehicle scheduling in logistics, and electrostatic separation techniques for plastic waste recycling. His experimental work examines tribocharging mechanisms and particle behavior in recycling processes. Publications reveal a strong trend toward human-centric manufacturing systems, with recent work (2023-2025) emphasizing collision avoidance algorithms, dynamic scheduling for autonomous vehicles, and energy-conscious production planning. Earlier research (2014-2018) established expertise in electrostatic separation for plastic waste recycling. Supervision & Projects: Supervised Kader Sanogo's 2024 thesis on optimizing transport tasks for collaborative robots in Industry 5.0 Currently supervising Nesrine Hebbadj's research (2024-2027) on human-centered production planning Leading DYNALOG project (2025-2027) on robotic intra-logistics systems His work integrates industrial engineering with environmental sustainability, particularly through advanced recycling technologies for plastic waste and energy-efficient production systems.

Tayfun Akgülمشاهده پروفایل

استاد

• Image Processing
• Signal Processing
• Audio and Speech Processing
• +۵ مورد دیگر

Tayfun Akgül is a Professor at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, Department of Electronics and Communication Engineering. With academic affiliations spanning decades, he combines engineering rigor with innovative research in signal processing and underwater acoustics. His research focuses on advanced signal processing techniques, including Compressive sensing and cyclostationary analysis Underwater acoustic monitoring and sensor arrays Thermal imaging and infrared reflection modeling Biometric identification through facial attributes Seismic signal processing Recent publications demonstrate expertise in Propeller noise analysis in maritime environments Micro-Doppler helicopter signature detection Seismic activity precursor identification Novel fisheye camera human detection systems Awarded Most Successful Doctoral Thesis Award from TESID (2024) IEEE Top 10 Award (2013) he maintains active IEEE membership since 1992 and has led multiple high-impact projects including casualty detection systems and electric vehicle warning systems.

• Atmospheric Dispersion
• Turbulent Flows
• Urban Environmental Engineering
• +۳ مورد دیگر

Lionel Soulhac is a Professor at INSA Lyon and serves as the Deputy Director of the Laboratoire de Mécanique des Fluides et d’Acoustique (LMFA) . He leads the AIR team (Atmospheric and Industrial Research) and is affiliated with the École Centrale de Lyon . His academic focus lies in the Department of Fluid Mechanics, Acoustics, and Energy (MFAE). Dr. Soulhac’s research emphasizes urban atmospheric dispersion , turbulent flows in complex environments , and numerical modeling of pollutant transport . He has contributed to developing operational models like SIRANE and BUILD , which address air quality and emergency response scenarios in urban and industrial settings. Teaching responsibilities include courses on fluid mechanics, environmental engineering, and pollution dynamics at École Centrale de Lyon and the University of Lyon. Research highlights include studies on concentration fluctuations , vegetation effects in urban canopies , and inverse modeling for source characterization . His work integrates experimental wind tunnel studies and computational fluid dynamics (CFD) to assess dispersion patterns and urban microclimates. Recent projects, such as the DIPLOS initiative, focus on pollutant dispersion in street networks and risk assessment methodologies. His contributions bridge academic research with practical applications in environmental safety and urban planning.

• Cybersecurity
• Access-Control Systems
• Machine Learning Security
• +۲ مورد دیگر

Simon Parkinson is a Professor at the University of Huddersfield specializing in cybersecurity and machine learning applications in security systems. His research focuses on empirical analysis of access-control systems, threat prediction, and defensive AI strategies. Parkinson's work combines data mining, behavioral analysis, and computational methods to address real-world security challenges. Recent publications demonstrate strong emphasis on biometric security, IoT protection, and forensic investigation techniques. His 2023-2025 research explores LLM-based event log analysis, wearable biometric cryptosystems, and zero-day DDoS detection in IoT networks. Collaborative projects include international case studies in Bahrain and innovative applications of computer vision in security diagnostics. Parkinson contributes to cybersecurity education initiatives and stakeholder engagement for security standardization.

Juha Latvalaمشاهده پروفایل

پژوهشگر

• Railway Track Drainage
• Geotechnical Engineering
• Transportation Infrastructure
• +۴ مورد دیگر

Juha Latvala is a Staff Scientist at the Department of Civil Engineering, Faculty of Built Environment, Tampere University. His research focuses on railway infrastructure, particularly railway track drainage systems, sub-ballast layer behavior, and the effects of water content on track stability. He holds a Doctoral degree from Tampere University (2024) and has collaborated extensively with institutions like Väylävirasto on railway engineering challenges. Education: Doctoral Thesis in Civil Engineering (2024) Research Interests: Latvala’s work emphasizes understanding and mitigating issues related to railway track drainage, seasonal frost impacts on track structures, cyclic loading resistance of materials, and moisture content analysis. His studies often involve field measurements, laboratory testing, and case studies to improve infrastructure durability and safety. Publications Overview: His recent articles highlight advancements in drainage solutions, sub-ballast material behavior under varying conditions, and the design of monitoring systems for heavy railway traffic. Key themes include optimizing track performance through moisture management and enhancing infrastructure resilience in cold regions. Grants & Collaborations: Collaborations with Väylävirasto and Tampere University have supported projects on railway traffic monitoring stations and drainage improvements. His research integrates geotechnical engineering principles with practical infrastructure solutions.

Daniel Barbaráمشاهده پروفایل

استاد

• Data Mining
• Machine Learning
• Databases
• +۳ مورد دیگر

Daniel Barbará is a Professor in the Department of Information and Software Engineering at George Mason University since 1997. He holds a PhD and MS in Computer Science from Princeton University, and a BS in Electrical Engineering from Universidad Metropolitana. Research Interests: Data mining, machine learning, cybersecurity, mobile computing, and fractal-based data analysis. His work focuses on clustering algorithms, intrusion detection, data compression, and handling high-dimensional datasets. Grants: Multiple NSF and Air Force grants including "Clustering by Impact" (2002-2005) and "Data Mining Support for NIAC" (1999-2000). Scientific Awards: Outstanding Researcher, CS Department, George Mason University Best Paper Finalist at WWW 2002 Projects: Developed ADAM (Intrusion Detection), COOLCAT (Categorical Clustering), Fractal Mining, and Quasi-Cubes (Approximate Query Processing).

• Quantum Computing
• Spin Qubits
• Semiconductor Nanostructures
• +۴ مورد دیگر

Dr. Frederico Martins is a Senior Research Fellow and solid-state physicist specializing in quantum computing with spin qubits. He currently leads the Spin Qubit team at QuantrolOx, a University of Oxford spinout developing machine-learning-based software for quantum processor automation. Previously, he led the Quantum Information team at Hitachi Cambridge Laboratory (University of Cambridge). His work bridges quantum hardware and intelligent software to address scalability and reliability in quantum architectures. Research interests include spin qubit control in semiconductor nanostructures, machine learning integration for device calibration, and overcoming challenges in multi-dot systems such as charge sensing and Pauli spin blockade detection. He focuses on high-fidelity spin manipulation, readout, and scaling to enable robust quantum computing platforms. His articles demonstrate expertise in silicon spin qubits, quantum dot characterization, and noise mitigation. Collaborations with industry and academia aim to advance scalable quantum technologies. Current projects emphasize automating quantum device control through AI-driven algorithms.

• Geochemistry
• Environmental Science
• Air Pollution
• +۴ مورد دیگر

Jesús Damián de la Rosa Díaz serves as a Professor in the Department of Earth Sciences within the Faculty of Experimental Sciences at the University of Huelva, Spain. He maintains active affiliations with the Sustainable Chemistry Research Center and was previously associated with the RNM347 research group focused on Geology and Analytical Chemistry. His research expertise spans: Environmental geochemistry with emphasis on trace element behavior in sediments and air particulate matter Advanced source apportionment techniques for PM10 in urban and industrial settings Ecotoxicological assessment of mining and industrial pollution impacts Volcanic emission characterization and atmospheric dispersion modeling Development of low-cost sensor networks for real-time air quality monitoring Analysis of his 15 most recent publications (2023-2025) reveals a dominant focus on Southern European and Latin American environmental challenges. Key trends include quantification of industrial and mining emissions, volcanic plume impacts, North African dust interactions, and innovative monitoring approaches using machine learning and low-cost sensors. His work consistently addresses regulatory needs through source-specific pollution characterization. Scientific Awards: No awards were documented in the provided materials Advising and Grants: Student advising information was not disclosed Research grant details were absent from the source data Labs and Teams: Dr. de la Rosa Díaz operates within the Sustainable Chemistry Research Center infrastructure at the University of Huelva and previously contributed to the RNM347 Geology and Analytical Chemistry research group, focusing on collaborative environmental geochemistry projects across European and Latin American networks.

• Network Engineering
• Internet Infrastructure
• Data Analysis
• +۳ مورد دیگر

Zachary Bischof is a Researcher at Georgia Tech's School of Computer Science within the College of Computing. His work focuses on internet infrastructure, network reliability, and broadband analysis. He investigates topics such as outage detection, submarine cable networks, and the geographic and technical aspects of internet systems. His research spans from foundational studies on IPv4 utilization to applied projects like the iGDB platform integrating physical/logical network layers. Key areas of interest include internet measurement methodologies, infrastructure resilience, and the societal impact of telecommunications policies. He has contributed to improving outage detection algorithms, analyzing AS relationships, and evaluating consumer broadband experiences across diverse regions. His work often bridges technical and policy dimensions, emphasizing real-world applications. Notably, his publications explore undersea cable criticality, Google's AMP project's impact, and the utility of service-level agreements (SLAs) for broadband providers. While no formal awards are listed, his consistent output reflects sustained engagement with high-impact networking challenges. Zachary collaborates on projects like the Dasu platform for edge-based ISP measurements and has advised on submarine cable vulnerability assessments. His research integrates machine learning (e.g., hostname geolocation extraction) with traditional networking analysis, demonstrating interdisciplinary strengths. Future directions include expanding measurement frameworks and addressing emerging infrastructure challenges.

• Fuzzy Logic
• Artificial Intelligence
• Neural Networks
• +۶ مورد دیگر

Professor Mahdi Mahfouf holds a Chair in the School of Electrical and Electronic Engineering at the University of Sheffield. He has held academic roles since 1997, progressing from Lecturer to Professor in 2005. His research focuses on Fuzzy Logic, Control Systems, and their applications in biomedical and industrial contexts. Mahfouf leads the Intelligent Systems Research Laboratory and has contributed over 370 publications, including influential work on fuzzy modeling and predictive control. Education: Ing.Dipl. (Hons) in Control Systems MPhil in Control Systems (University of Sheffield, 1988) PhD in Control Systems (University of Sheffield, 1991) Research Interests: Fuzzy Logic applications, Artificial Intelligence, Neural Networks, Model-Based Predictive Control, Biomedical Engineering (e.g., ICU Decision Support Systems), and Manufacturing Systems (e.g., granulation processes, surface metrology). Key Achievements: Recipient of the IEE Hartree Premium Award (1992) and MEDIPEX Innovation Award. His work integrates fuzzy logic into real-time systems for aviation, healthcare, and robotics. Grants & Labs: Leads the Intelligent Systems Research Lab. Active in collaborative projects with industry (e.g., pharmaceuticals, aerospace). His research bridges theory and practice, emphasizing data-driven solutions for complex systems.