جست‌وجوی استاد و پژوهشگر

John Francisمشاهده پروفایل

استاد

• Welding and Cladding Processes
• Welding Metallurgy
• Residual Stresses in Welded Joints
• +۴ مورد دیگر

John Francis is a Professor of Materials Welding and Joining at The University of Manchester, leading the Laser Processing Research Centre. He holds Fellowships from the Institute of Materials, Minerals & Mining (FIMMM) and the Higher Education Academy (FHEA), and is accredited as a European/International Welding Engineer (EWE/IWE). He joined the university in 2011 as a Senior Lecturer, progressing to Reader and Chair. His career spans over 20 years in welding and cladding technologies, with early work at CSIRO in Australia addressing aerospace and power generation challenges. Education: PhD in Principles for Open-Arc Weld Deposition of High-Chromium White Iron Surface Layers, The University of Adelaide (1995–1999) Bachelor of Engineering (Mechanical Engineering), The University of Adelaide (1991–1995) Research Interests: John’s work focuses on microstructure evolution and residual stresses in welded joints, post-weld heat treatment, and in-service performance. He develops welding procedures to mitigate cracking and enhance structural performance. Key areas include: Large steel component fabrication Steel weld toughness optimization Dissimilar material joining Research Output Trends (2020–2025): Recent articles address electron beam welding in nuclear pressure vessels, novel cobalt-free alloys, and additive manufacturing processes. Themes include residual stress mitigation, advanced reactor design, and material characterization for nuclear applications. Awards & Fellowships: Fellow of the Institute of Materials, Minerals and Mining (FIMMM) Fellow of the Higher Education Academy (FHEA) EWE/IWE Certification Advising & Grants: Supervised 11 postgraduate research students and led projects like the Laser Processing Research Centre (LPRC) and Materials for Demanding Environments CDT. His work spans nuclear engineering, laser processing, and innovative manufacturing. Labs & Facilities: Academic lead for equipment including MEBW-60 Micro Electron Beam Welders and Robotic Welding Cells at the Henry Royce Institute for Advanced Materials.

• Computer Architecture
• Embedded Systems
• Parallel and Distributed Computing
• +۳ مورد دیگر

Jürgen Teich is a Professor at the University of Erlangen-Nuremberg, Department of Computer Science. His research focuses on computer architecture, embedded systems, and hardware-software co-design, with particular emphasis on energy-efficient and sustainable computing. He leads projects involving FPGA-based accelerators, neural networks on microcontrollers, and real-time systems optimization. His work spans topics such as approximation computing, MPSoCs (Multiprocessor Systems-on-Chip), and IoT device architectures. Key contributions include methodologies for optimizing resource allocation in heterogeneous systems and developing energy-harvesting solutions for embedded systems. Teich has authored numerous publications in top-tier conferences and journals, including DATE, FPL, and ACM Transactions. His research often collaborates with industry partners, emphasizing practical applications and open-source hardware.

Siddhartan Govindasamyمشاهده پروفایل

استاد

• Wireless Communications
• Signal Processing
• Energy Efficiency
• +۴ مورد دیگر

Siddhartan Govindasamy is a Professor and Sabet Family Dean's Faculty Fellow at Boston College, specializing in wireless communications and signal processing. His research focuses on energy-efficient wireless systems, environmental/physiological sensing, and frugal innovation for under-resourced communities. He teaches courses including Physical Modeling, Digital Signal Processing, and Engineering Foundations. Education: Ph.D. in Electrical Engineering and Computer Science from MIT. His work spans interdisciplinary collaborations, such as high-altitude balloon projects for solar eclipse studies and affordable infant hearing screening devices. He emphasizes hands-on engineering education through lab courses and curriculum development. Research highlights include cooperative massive MIMO systems, deep learning in relay networks, and multiband network optimization. He has authored books and peer-reviewed journals, with recent publications in IEEE Open Journal of Communications, Academic High Altitude Conference, and International Journal of Engineering Education. Awards: Sabet Family Dean's Endowed Faculty Fellow. Active in grant-funded projects and serves as a faculty leader in engineering education innovation.

Huiping Caoمشاهده پروفایل

استاد

• Databases
• Deep Learning
• Data Mining
• +۷ مورد دیگر

Huiping Cao is a Professor in the Department of Computer Science at New Mexico State University (NMSU). She holds a Ph.D. from The University of Hong Kong (2007), and bachelor’s and master’s degrees from Renmin University of China (1999 and 2002). Her expertise spans databases, deep learning, data mining, time series analysis, and graph mining. Her research focuses on developing computational methodologies to extract knowledge from complex data such as sequences and graphs, with applications in smart grids, animal and range sciences, agriculture, and high-performance computing. Dr. Cao’s work emphasizes interdisciplinary applications, including real-time cattle monitoring using sensors (GPS and accelerometers) for disease detection, parturition prediction, and grazing behavior analysis. She has developed tools like GRAZETOOLS for livestock behavior analysis and contributed to precision ranching systems using LoRa-WAN sensors. Her methodological innovations include backbone index models for multi-cost road networks and federated learning frameworks to address data imbalance in distributed systems. Her research has addressed challenges such as uncertainty quantification in time series analysis, probabilistic modeling for segmentation tasks, and sensor error evaluation. She collaborates across disciplines, integrating machine learning with environmental and agricultural domains. Dr. Cao’s contributions also include advancements in graph-based influence discovery, semantically annotated observational data systems, and compression techniques for power grid monitoring data.

Lisa Fryeمشاهده پروفایل

استاد

• Computer Science Education
• Network Security
• Ontology-Based Systems
• +۴ مورد دیگر

Dr. Lisa Frye is a Professor and Department Chair in the Computer Science & Information Technology Department at Kutztown University. She holds a PhD in Computer Science from Lehigh University with research focused on ontology applications in network management and cybersecurity pedagogy. Her academic leadership includes NSF grants totaling over $2M to develop culturally relevant CS education frameworks and enhance STEM retention programs. Research interests span network security, ontology-based systems, computational thinking integration, and women in tech. Recent work emphasizes K-12 CS education equity and culturally responsive teaching strategies. Publications include studies on intrusion detection systems using ontologies and semantic web technologies. Grants include NSF CSforAll (2021-2024), S-STEM scholarships (2020-2025), and infrastructure grants for network management research. Awards include Kutztown's Dean's Outstanding Faculty Award (2024) and multiple teaching excellence recognitions. Teaching spans courses like CSC480 (Semantic Web Technologies) and CSC135/136 (Computer Science Fundamentals). Advises projects in network security, ontology systems, and educational technology. Active in professional organizations including ACM and Association of Women in Computing.

• Computer Architecture
• Reconfigurable Computing
• Hardware Acceleration
• +۶ مورد دیگر

Dionysios Pneumatikatos is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) since September 2019. Previously, he served as a Professor and Chair of the Department of Electronic and Computing Engineering at the Technical University of Crete (2000–2019) and is an Associate Researcher at the Foundation for Research and Technology (FORTH) since 1997. His primary affiliations include the Computing Systems Laboratory (CSLab) at NTUA and the Computer Architecture and VLSI Systems (CARV) Laboratory at FORTH. Education: B.Sc. in Computer Science, University of Crete (1989) M.Sc. and Ph.D. in Computer Science, University of Wisconsin–Madison (1991, 1995) Research Interests: Computer Architecture Reconfigurable Computing Hardware Acceleration (e.g., FPGA, RISC-V) Energy-Efficient Systems Reliable System Design Application-Specific Architectures His work focuses on heterogeneous parallel systems , bioinformatics accelerators , and virtualization frameworks for reconfigurable platforms . Recent Projects & Contributions: Coordinator of the FASTER (FP7) project Principal Investigator in EDRA (H2020), EXTRA , and dReDBox Key roles in AXIOM , DeSyRe , and VPLANET These projects explore FPGA-based HPC systems , RISC-V ecosystems , and disaggregated data center architectures . Teaching & Mentorship: Teaches courses on Computer Architecture , Parallel Processing , and Logic Design at NTUA and TU Crete Supervised multiple national/EU projects, fostering interdisciplinary research in embedded and high-performance systems Labs & Networks: Active member of the HiPEAC European Network Program Committee roles at ISCA , FPL , and DATE Led the 21st International Conference on Field-Programmable Logic and Applications (FPL)

• Network Science
• Data Science
• Complex Networks
• +۳ مورد دیگر

Artur Ziviani is a Senior Researcher at the Data Extreme Lab (DEXL) of the National Laboratory for Scientific Computing (LNCC), a research unit under Brazil's Ministry of Science, Technology, and Innovation (MCTI). He coordinates LNCC's Multidisciplinary Graduate Program in Computational Modeling (M.Sc./Ph.D.). With a Ph.D. from Université Pierre et Marie Curie (Paris 6) and a B.Sc./M.Sc. from Federal University of Rio de Janeiro (UFRJ), he has held visiting positions at INRIA (France) and taught at Paris 6. His research focuses on network science, data science, and interdisciplinary applications, including complex networks, machine learning, and mobility analysis. He is a Senior Member of IEEE and ACM, and an Affiliated Member of the Brazilian Academy of Sciences (2013-2017). His work spans algorithmic information theory, network centrality, and human-aware communication strategies. Recent projects include mobility modeling, protein interaction networks, and biodiversity informatics. Education: Ph.D. (Paris 6, 2003), M.Sc. (UFRJ, 1999), B.Sc. (UFRJ, 1998). Research interests include network characterization, data-driven modeling, and applications in healthcare and biodiversity. His publications analyze network structures, centrality metrics, and spatiotemporal data, with contributions to IEEE, ACM, and Elsevier journals. He also leads initiatives on SDN architectures for high-performance computing and collaborative learning platforms. Awards include recognition as an IEEE Impact Creator and senior fellowships. His team works on projects like SafeCityMap (mobility during pandemics) and MobHet (heterogeneous mobility prediction). He serves on editorial boards for Computer Networks and IEEE Communications Surveys.

• Numerical Methods
• Scientific Computing
• Cardiac Electrophysiology Modeling
• +۳ مورد دیگر

Ngoc Mai Monica Huynh is a Researcher in the Department of Mathematics at the University of Pavia, specializing in Scientific Computing with a focus on Numerical Methods and Applications. Her work centers on developing advanced numerical techniques for simulating cardiac electrophysiology, particularly through high-performance computing approaches. Her research interests include parallel algorithms, domain decomposition methods (BDDC/FETI-DP), and virtual element discretizations applied to cardiac models like the Bidomain equations. She has contributed to scalable solvers for reaction-diffusion systems and implicit time discretization techniques in heterogeneous media. Recent work emphasizes robust preconditioners for discontinuous Galerkin discretizations, algebraic multigrid solvers, and cellular-resolution simulations of cardiac tissue. Her publications reflect a strong focus on computational efficiency and mathematical rigor in biomedical modeling. Dr. Huynh's research is supported by collaborations within the Department's Scientific Computing group and leverages high-performance computing resources. Her expertise bridges numerical analysis, parallel computing, and biophysical modeling for cardiac electrophysiology applications.

JAVIER LOPEZ FANDIÑOمشاهده پروفایل

استادیار

• High Performance Computing
• Remote Sensing
• GPU Processing
• +۴ مورد دیگر

JAVIER LOPEZ FANDIÑO is an Assistant Professor at the Department of Electronics and Computer Engineering, Higher Technical School of Engineering, University of Santiago de Compostela (USC). He obtained his PhD in Computer Science Research from USC in 2018 under the supervision of Dra. Dora B. Heras and Dr. Francisco Argüello. He is affiliated with the research groups ARQCOMP (Computer Architecture) at USC and collaborates with Centro Singular de Investigación en Tecnoloxías Intelixentes (CiTIUS) and Galician Centre for Mathematical Research and Technology (CITMAga). Education: BSc (2012) and MSc (2014) in Computer Science from USC, PhD (2018) in Computer Science Research. Research Areas: High performance computing for remote sensing, GPU processing of multidimensional images, anomaly detection, change detection in multi-temporal datasets, deep learning for hyperspectral classification. His recent publications focus on heterogeneous computing, edge computing, and neural networks for real-time anomaly detection in multispectral images. Key methodologies include extinction profiles, isolation forest, attention-based CNN, and CUDA optimizations. Notable affiliations include the ARQCOMP research group and collaborations with CiTIUS and CITMAga. He has not been explicitly associated with scientific awards in the provided texts.

Alberto Proençaمشاهده پروفایل

استاد

• Computer Science
• High-Performance Computing
• Parallel Computing
• +۷ مورد دیگر

Alberto Proença is a Full Professor at the Department of Computer Science, School of Engineering of the University of Minho (DI-EEUM). A pioneer in computational science, he founded Portugal's first national parallel computing service in 1994 and led the SeARCH heterogeneous computing cluster since 2005. His research spans digital electronics, high-performance computing architectures, and applications in cultural heritage, computer vision, physics, and chemistry. Born in Mozambique (1954), migrated to Portugal (1975) Bachelor's from University of Coimbra; PhD from University of Manchester (UK) Longstanding affiliation with UMinho since 1977 Researcher at Algoritmi Centre Contributions include: Chaired UMinho's Computer Centre Initiated Erasmus exchange programs with University of Bristol Directed Advanced Computing in Portugal-US collaboration Received accolades during jubilation ceremony on 14 June 2024 at Gualtar Campus, attended by institutional leaders and collaborators.

Tiziana Di Matteoمشاهده پروفایل

استاد

• Econophysics
• Complex Systems
• Complex Networks
• +۳ مورد دیگر

Professor Tiziana Di Matteo is the world's first Professor of Econophysics at King's College London (KCL), appointed in 2014. She is affiliated with the Department of Mathematics within the Faculty of Natural & Mathematical Sciences. Additionally, she serves as External Faculty at the Complexity Science Hub in Vienna and is a member of the UCL Centre for Blockchain Technologies. Her roles include Enterprise and Engagement Lead at KCL and Knowledge Exchange Champion for the UK Knowledge Exchange Hub for Mathematical Sciences. Di Matteo holds a BSc (Hons) in Physics (1994) and a PhD in Physics (1999) from the Università di Salerno, Italy. Her research focuses on interdisciplinary applications of physics to economics and finance, spanning: Econophysics : Analyzing financial markets using statistical physics. Complex Systems & Networks : Studying interdependencies in financial and social systems. Data Science : Developing tensor-based methods for multidimensional forecasting. Her 120+ publications predominantly explore volatility modeling, network theory, and machine learning applications in economics. Recent work emphasizes multiscaling analysis, blockchain impacts, and pandemic-related economic resilience. Scientific Awards: Elsevier’s Most Cited Article Award (2010) QEII Fellowship (2003-2008) INFM/CNR Fellowships (1994-1995) Erasmus Fellowship (1992) She leads PhD students (names unspecified) and collaborates globally. Editorial responsibilities include serving as Main Editor for Physica A and Editor for Chaos, Solitons & Fractals .

Ronald Haynesمشاهده پروفایل

استاد

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۴ مورد دیگر

Ronald Haynes is a Full Professor and Chair of the Scientific Computing Graduate Programs at the Department of Mathematics and Statistics, Memorial University of Newfoundland. He holds a PhD from Simon Fraser University (2003) and has held academic roles at Acadia University and Memorial University. His research focuses on numerical methods for partial differential equations, domain decomposition, parallel computing, and optimization, with applications in industrial mathematics. Education: B.Sc. (Hons) in Applied Mathematics (Memorial University, 1996), M.Sc. (Simon Fraser University, 1998), PhD (Simon Fraser University, 2003). Research interests include numerical analysis, scientific computing, and computational methods for PDEs. He has led initiatives such as the 25th International Domain Decomposition Conference and contributed to software libraries like RIDC-DD and DD-CPM. Dr. Haynes is an active editor for CAIMS journals and a leader in the Canadian Applied and Industrial Mathematics Society. Awards include the President's Award for Outstanding Research (2018) and the Dean of Science Distinguished Teaching Award (2017). He advises graduate students in numerical methods and optimization, and collaborates with industry on projects like drilling strength prediction and reservoir simulation. His work also emphasizes inclusive teaching practices and STEM education.

Dirk Grunwaldمشاهده پروفایل

استاد

• Computer Networks
• Wireless Communication
• Computer Architecture
• +۶ مورد دیگر

Dirk Grunwald is a Professor in the Department of Computer Science at the University of Colorado Boulder, with a joint appointment in Electrical and Computer Engineering. He has been on the faculty since 1989 and previously directed the Colorado Center for Information Storage (CCIS). He founded the online Post-Baccalaureate degree in Computer Science. His research focuses on computer systems, including networking (wireless, 5G/4G), computer architecture, privacy, high-performance storage, and technology policy. Research interests span wireless propagation models, spectrum management, distributed systems optimization, and cybersecurity. Recent work examines QoE-driven video conferencing, 5G edge effects, and secure emergency alert systems. Grunwald has advised over 50 students, including notable PhD graduates now at Sandia Labs, Google, Meta, and AMD. He has pioneered tools like the Cognitive Radio Kit Framework and contributed to spectrum policy debates. Key contributions include advanced caching strategies (e.g., eMRC), network primitives (MRTOM), and experimental platforms (ExperimenTor). His work bridges theory and practice, addressing real-world challenges in wireless systems and distributed computing.

• High-Performance Computing
• Parallel Programming
• Task Parallelism
• +۶ مورد دیگر

Stephen L. Olivier is a prominent researcher in high-performance computing at Sandia National Laboratories, with a distinguished publication record spanning nearly two decades. His work focuses on parallel programming models, performance optimization, and energy-efficient computing across diverse architectures including CPUs, GPUs, and FPGAs. Olivier has made significant contributions to OpenMP standards and Kokkos programming model development, collaborating extensively with Department of Energy national laboratories and international research teams. Olivier's research interests center on task parallelism, memory management in distributed systems, and performance portability across heterogeneous architectures. His work addresses critical challenges in exascale computing, including efficient task scheduling for unbalanced workloads, power management in large-scale systems, and optimization of communication patterns. More recently, he has expanded his research into medical imaging applications, applying high-performance computing techniques to tuberculosis detection in rural healthcare settings. Analysis of Olivier's recent publications (2021-2024) reveals a strong focus on practical performance engineering for next-generation computing platforms. His work spans traditional HPC domains while increasingly incorporating data science applications and medical imaging analysis. The research demonstrates consistent innovation in parallel programming models, particularly around OpenMP tasking and Kokkos abstractions, with growing emphasis on energy efficiency and hardware-specific optimizations for emerging architectures. Olivier has maintained a prolific research output with numerous publications in top-tier conferences including SC, IPDPS, and IWOMP. His collaborative work extends across multiple Department of Energy laboratories and international institutions, reflecting the interdisciplinary nature of modern high-performance computing research. While specific grant information isn't detailed in the publication record, his work on DOE systems suggests significant involvement in national supercomputing initiatives.

Christoforos Kachrisمشاهده پروفایل

استادیار

• Hardware Accelerators
• FPGAs
• Edge AI
• +۵ مورد دیگر

Christoforos Kachris is an Assistant Professor at the Department of Electrical and Electronics Engineering, University of West Attica since 2023. Previously, he co-founded and led InAccel, a startup pioneering FPGA deployment in the cloud, securing €500k in funding and winning awards like the Venture Impact Award (2021) and DeepBlue Cup (2019). He led EU projects such as VINEYARD (€6.3M, 2016–2018), the first to deploy FPGAs in cloud data centers. His research spans reconfigurable computing, hardware accelerators, cloud computing, and optical interconnects, with over 90 publications and 2,700+ citations. Education: Ph.D. (2007, Delft University of Technology), M.Sc. (2003, Technical University of Crete), and Diploma (2001, Technical University of Crete). His Ph.D. focused on FPGA-based network processing, with internship at Xilinx Research Labs, resulting in a US patent on configurable transactional memories. Research interests include machine learning on embedded systems, FPGAs, edge AI, reconfigurable computing, and optical interconnects. He has advised numerous students, many now in tech roles at Cisco, IBM, Ericsson, and startups. Notable contributions include a highly cited survey on optical interconnects in data centers and leadership in projects like VINEYARD and CloudAccel (Principal Investigator). Awards include Venture Impact Award and recognition in international hardware competitions.