جست‌وجوی استاد و پژوهشگر

Bruce Jacobمشاهده پروفایل

استاد

• Memory Systems
• Computer Architecture
• Memory Devices
• +۷ مورد دیگر

Bruce Jacob is a Professor in the Cyber Science Department within the School of Engineering, Computing, and Weapons at the United States Naval Academy, where he joined in Fall 2022. Prior to USNA, he served as a professor of Electrical & Computer Engineering at the University of Maryland for 25 years, establishing himself as a leading expert in memory systems and computer architecture. Dr. Jacob received his A.B. in Mathematics from Harvard in 1988 and his Ph.D. in Computer Science & Engineering from The University of Michigan in 1997. Before graduate school, he worked in Boston start-ups as a software engineer at Boston Technology and later as chief engineer and system architect at Priority Call Management, which was successfully acquired in the late 1990s. His research focuses on memory systems, computer architecture, and memory devices, with significant contributions to memory system design across industry and government sectors. Jacob has designed computer-system architectures and memory-system architectures for major organizations including Micron (Hybrid Memory Cube DRAM architecture), Cray (Black Widow memory system), Northrop Grumman (experimental ultra-low-power datacenter), and the European Commission (1024-core Teraflux chip). His work spans resistive memory systems, non-volatile memory, memory simulation, and hardware security. His publication record demonstrates consistent leadership in memory systems research, with recent work focusing on ReRAM development, trusted execution environments for in-storage computing, and advanced memory simulation techniques. His research shows a clear trajectory toward monolithic memory integration, 3D stacking, and addressing the semantic gap between software and memory systems. Fellow of the IEEE Patent in memory-systems design Three patents in electric guitar circuit design Featured in Washington Post, Los Angeles Times, Chronicle of Higher Education, and NPR for guitar-related innovations Jacob has written two textbooks on computer memory systems and numerous articles spanning memory systems, computer design, embedded systems, operating system design, and even ventured into astrophysics and algorithmic composition. His DRAMsim memory simulator has become an industry standard tool. His practical industry experience complements his academic work, having consulted for major technology companies on memory system design challenges.

• Data Storage Systems
• Active Storage
• Data Replication
• +۵ مورد دیگر

Zhipeng Tan is an Assistant Professor at Huazhong University of Science and Technology, affiliated with the Data Storage and Application Lab. His work centers on innovative solutions in data storage technologies, particularly in active storage and replication mechanisms. His research interests lie in the domains of data storage systems, provenance management, and scalable storage architectures. He focuses on enhancing efficiency and scalability in large-scale storage environments, particularly through active storage frameworks and provenance data compression. The recent publications highlight a strong focus on provenance storage efficiency, active storage system design (e.g., Oasis), and scalable data management. Key themes include hybrid storage models, provenance graph compression, and compliance with T10 OSD standards, reflecting contributions to both theoretical and applied aspects of storage systems. Scientific Awards: No scientific awards mentioned in the text. Advising and Grants: There is no mention of student advising, research grants, or funding sources in the available information. Labs and Teams: Zhipeng Tan is associated with the Data Storage and Application Lab at Huazhong University of Science and Technology, a research group focused on advancing storage system technologies, including dynamic file systems and ultra-large scale data solutions.

• Parallel File and Storage Systems
• Modular Supercomputing
• Resource Disaggregation and Virtualization
• +۶ مورد دیگر

Sarah Neuwirth is a tenured Professor for Computer Science at Johannes Gutenberg University Mainz (JGU) and a Visiting Researcher at the Jülich Supercomputing Centre. She manages JGU's High Performance Computing (HPC) division, coordinates regional/national HPC activities, and represents JGU in NHR, Gauss-Allianz, and HPC committees. Education : PhD (Dr. rer. nat.) in Computer Science (2018), Heidelberg University Diplom in Computer Science (2012), University of Mannheim Bachelor of Science in Computer Science (2010), University of Mannheim Research Interests : Parallel File and Storage Systems Modular Supercomputing (resource disaggregation/virtualization) Performance Engineering High Performance Computing Networking Reproducible Benchmarking Parallel I/O Publications Trends : Her work focuses on HPC performance modeling, parallel I/O optimization, modular supercomputing, network characterization, and reproducible benchmarks. Key themes include resource disaggregation, automated workflows, and data-intensive distributed applications. Scientific Awards : 2023 PRACE Ada Lovelace Award for HPC ZONTA Science Award 2019 Grants & Leadership : She leads the High Performance Computing division at JGU, participated in European DEEP projects, and serves on SC conference committees.

David Huitinkمشاهده پروفایل

دانشیار

• Materials Science
• Thermal Sciences
• Electronics Reliability
• +۴ مورد دیگر

David Huitink is an Associate Professor and Twenty-First Century Professor in the Department of Mechanical Engineering at the University of Arkansas College of Engineering. His research spans the intersection of materials and thermal sciences, with a focus on leveraging fundamental thermophysical material behaviors for engineered applications. He directs the EMPIRE Laboratory (Engineered Multi-Physical Interactions & Reliability Evaluation), which focuses on reliability engineering for next-generation electronic packaging solutions. Dr. Huitink received his educational foundation at Texas A&M University, earning a Bachelor of Science (2006), Master of Science (2007), and Doctor of Philosophy (2011), all in Mechanical Engineering. As an NSF Graduate Research Fellow during his doctoral studies, he specialized in complex nano-scale interactions at material interfaces under chemical and mechanical influence. His research interests encompass materials science, thermal sciences, and reliability engineering, with particular focus on thermophysical material behaviors, energy sciences, and thermally active functional materials. The Huitink lab works closely with Electrical Engineering collaborators to develop next-generation high-density power electronics for electrified transportation and power conversion systems. Recent efforts include additive manufacturing for hot-spot thermal management, transient temperature abatement, and interconnect fabrication technology development for enhanced electronic packaging lifetimes through thermal cycling events. Analyzing his recent publication record reveals a clear trend toward advanced thermal management solutions for power electronics, with increasing focus on phase change materials, nanowire-enhanced interconnects, and reliability modeling under combined stress conditions. His work bridges fundamental materials science with practical engineering applications in high-power systems, particularly for electric vehicle technologies and aerospace applications. NSF Graduate Research Fellow (2007-2011) Texas A&M Graduate Diversity Fellow (2008-2011) Texas A&M Graduate Merit Fellow (2006-2007) National Merit Scholar (2002-2006) BSA Eagle Scout (2001) Dr. Huitink brings significant industry experience to his academic role, having spent over five years at Intel Corporation as Quality & Reliability Engineering Program Manager for Intel's Custom Foundry Division. There he pioneered advanced reliability prediction methods for silicon-based flip chip microelectronic packages and developed testing protocols and FEA methods for Design for Reliability guidance. He currently serves as Associate Editor of Microelectronics Reliability Journal and has patent applications filed in Low Z-height Electronic System design and thermal optimization of space-limited electronic systems. The EMPIRE Laboratory maintains strong connections with Arkansas's multi-disciplinary power electronics program, which includes 14 faculty members across 4 departments, approximately 100 graduate students, and nearly $10 million in annual research expenditures. The lab collaborates with several centers of excellence including GRAPES, POETS, and SEEDS, utilizing state-of-the-art facilities such as NANO, HiDEC, and NCREPT.

Lipeng Wanمشاهده پروفایل

استادیار

• Big Data Management
• High-Performance Computing
• Data-Intensive Computing
• +۳ مورد دیگر

Dr. Lipeng Wan is a tenure-track Assistant Professor of Computer Science at Georgia State University (GSU), located at 25 Park Place, room 733. He holds a B.Eng. in Communication Engineering from Nanjing University of Science and Technology (2008), an M.Eng. in Information and Communication Engineering from Southeast University (2011), and a Ph.D. in Computer Science from the University of Tennessee, Knoxville (2016). Prior to joining GSU, he served as a Computer Scientist at Oak Ridge National Laboratory (ORNL), first as a postdoctoral researcher (2016–2018) and later as a full-time research staff member (2018–202?). His research focuses on big data management and analytics , high-performance and data-intensive computing , and resilience and performance optimization for distributed systems . Key interests include scientific data workflows, I/O innovations for exascale systems, and error-controlled data compression frameworks like MGARD and HPDR. Dr. Wan’s recent work emphasizes adaptive data transmission (e.g., JANUS), load balancing in cloud environments (SciLance), and optimizing file access patterns on HPC systems. His publications address challenges in exascale computing, including I/O performance, geographically distributed data management, and feature-preserving compression for climate simulations. He leads research at GSU in collaboration with national labs like ORNL, focusing on advancing scalable data management techniques for high-performance computing applications.

Neil Bergmannمشاهده پروفایل

استاد

• Wireless Sensor Networks
• Internet of Things (IoT)
• Embedded Systems
• +۶ مورد دیگر

Neil Bergmann is an Honorary Professor at the School of Electrical Engineering & Computer Science, University of Queensland. His research focuses on wireless sensor networks, IoT, embedded systems, and machine learning with applications in cybersecurity, energy efficiency, and industrial monitoring. He has contributed extensively to fields like cryptographic acceleration, localization systems, and sensor network optimization. His work bridges hardware-software co-design and practical implementations in domains such as healthcare and industrial automation. His academic career includes significant contributions to journals and conferences, with a focus on advancing technologies like energy harvesting, real-time data processing, and secure communication protocols. Collaborations span academia and industry, addressing challenges in sensor networks, embedded systems, and smart environments. Notable research includes energy-efficient machine fault diagnosis using industrial wireless sensor networks and secure authentication systems leveraging kinetic energy harvesting. His publications highlight interdisciplinary approaches to solving complex technical problems, emphasizing practical applicability and innovation.

• Pervasive Computing
• Wireless Sensor Networks
• Healthcare Informatics
• +۳ مورد دیگر

John Herbert is a Senior Lecturer in Computer Science at University College Cork (UCC), Ireland. His research focuses on pervasive computing, wireless sensor networks, and healthcare informatics, with notable projects like the CARA framework for falls assessment in the elderly. He holds a PhD in Computer Science from Cambridge University and has held visiting roles at institutions including SRI International and the University of Cambridge. Education: BSc (Experimental Physics), MSc (Experimental Physics), Postgraduate Diploma (Computer Science) from UCC; PhD (Computer Science) from Cambridge University. Research Grants: Led projects funded by Science Foundation Ireland (€163,726) and the Irish Research Council (€71,250), focusing on cloud computing and healthcare applications. His work emphasizes context-aware systems, data quality in medical environments, and real-time analysis. Selected awards include an International Fellowship from Digital Systems Research Center (1989) and visiting fellowships at Cambridge (2008-2009). Teaching: Courses include Advanced Software Engineering, Formal Methods, and Model-Based Software Development. Outreach: Advisor to award-winning student teams (e.g., IEEE mobile app contest) and collaborator with industry partners in China and Europe.

Francisco Almeida Maiaمشاهده پروفایل

پژوهشگر

• Distributed Systems
• Cloud Computing
• Large Scale Data Management
• +۳ مورد دیگر

Francisco Almeida Maia is a Senior Researcher at HASLab (High Assurance Lab) affiliated with the University of Minho and INESC TEC. His research focuses on distributed systems, cloud computing, large-scale data management, and gossip-based protocols. He holds a Ph.D. in Computer Science from the MAP-i Doctoral Program (Universities of Minho, Aveiro, and Porto, 2015), advised by Professor Rui Oliveira. His doctoral work introduced DataFlasks, a scalable and resilient data store for large-scale systems using gossip protocols. Current research explores enhancing DataFlasks’ guarantees while maintaining scalability. Education: Ph.D. in Computer Science, MAP-i Doctoral Program (2015) Research Interests: Distributed systems security, privacy-aware cloud storage, scalable data architectures, and fault-tolerant protocols. Recent work emphasizes secure multi-cloud databases and distributed system testing frameworks. Publications: Focus on scalable systems, privacy in distributed environments, and testing methodologies. Notable contributions include d'Artagnan (secure NoSQL on untrusted clouds) and Minha (large-scale distributed testing). Advising & Grants: Supervised two theses at INESC TEC. Active in collaborative projects on distributed systems and security. Labs/Teams: Core member of HASLab, contributing to interdisciplinary research on high-assurance software and distributed computing.

Rodriguez Zalepinos Ramon Antonioمشاهده پروفایل

دانشیار

• distributed systems
• databases
• Big data
• +۶ مورد دیگر

Dr. Ramon Antonio Rodriguez Zalepinos is an Associate Professor at the Department of Software Engineering, Faculty of Computer Science, National Research University Higher School of Economics (HSE). With 16+ years of scientific and teaching experience, he specializes in geospatial data systems, distributed databases, and high-performance computing. Doctor of Science in Computer Science (2024) Candidate of Technical Sciences (2013) Master's in Computer Science (2008, Donetsk National Technical University) His research focuses on geospatial array databases , distributed systems , and Big Earth Data engineering , particularly through his ChronosDB and Quantum Tensor DBMS projects. He has pioneered cloud-native solutions for multi-terabyte environmental datasets and developed novel approaches for in-database road traffic simulations. Key publication trends show 7+ years of contributions to VLDB and SIGMOD conferences, with special emphasis on: Quantum-enhanced geospatial processing Web-based array database systems Cellular automata integration High-speed raster data aggregation Scientific recognition includes: Best Teacher award (2017-2021, 2023) HSE Personnel Reserve member Additional post-doctoral funding (2024-2027) Multiple publication bonuses (2019-2023) He supervises student research in geospatial data science and leads projects on satellite data processing systems, with implementations at major institutions including Amazon and Planet Labs.

• High-Performance Computing (HPC)
• Computational Fluid Dynamics
• Quantum Computing
• +۳ مورد دیگر

Stefano Markidis is a leading researcher in High-Performance Computing (HPC) and quantum computing. His work focuses on developing advanced simulation frameworks, such as the Neko framework for computational fluid dynamics, and optimizing algorithms for heterogeneous architectures. He collaborates extensively with institutions and researchers globally, contributing to fields like plasma physics, quantum systems, and machine learning applications. His research emphasizes scalability, performance optimization, and the integration of cutting-edge technologies like GPU acceleration and quantum computing. Key research interests include extreme-scale simulations, quantum algorithms, and in-situ data analysis techniques. He has published over 200 articles, with recent work addressing challenges in NISQ systems, tensor network simulations, and CUDA-based performance enhancements. His contributions span theoretical and applied domains, bridging computational methods with real-world applications in fusion energy, materials science, and space exploration. Notable collaborations include projects with Philipp Schlatter, Niclas Jansson, and the NISQ application development community. Markidis also explores hybrid frameworks combining classical and quantum computing, aiming to leverage emerging hardware for scientific breakthroughs.

Jim Jonesمشاهده پروفایل

دانشیار

• Computer and Network Security
• Digital Forensics
• Cybersecurity
• +۳ مورد دیگر

Jim Jones is an Associate Professor in the Department of Electrical and Computer Engineering at George Mason University's Volgenau School of Engineering. His work integrates cybersecurity, digital forensics, and practical applications, focusing on digital artifact analysis, malware detection, and data persistence. He holds a PhD in Computational Sciences and Informatics from George Mason University, an MS in Mathematical Sciences from Clemson University, and a BS in Industrial Engineering from Georgia Tech. Education: PhD, Computational Sciences and Informatics, George Mason University MS, Mathematical Sciences, Clemson University Bachelor's, Industrial Engineering, Georgia Tech Research Interests: Cybersecurity, Digital Forensics, Data Persistence, Malware Analysis, Machine Learning in Cybersecurity. His research is funded by agencies like DHS, NSF, and DoD, addressing challenges such as supply chain disruption detection, deleted file decay analysis, and cyber deception. Notable projects include the 'Digital Body Farm' for studying data decay and the 'Cyber P3 Scholarship Program.' He has advised numerous funded initiatives, including work on network topology discovery and insider threat evaluation. Collaborative efforts with industry and government emphasize bridging theory and practice in cybersecurity education and research.

André Brinkmannمشاهده پروفایل

استاد

• Data Center Management
• Cloud Computing
• Storage Systems
• +۵ مورد دیگر

André Brinkmann is a full professor at the Department of Computer Science, Johannes Gutenberg University Mainz, leading the Efficient Computing and Storage Group. He previously served as head of the university's data center (2011–2021) and was an assistant professor at Paderborn University (2008–2011). He holds a Ph.D. in Electrical Engineering from Paderborn University (2004) and managed the Paderborn Centre for Parallel Computing (PC²). His research focuses on algorithm engineering for data center management, cloud computing, storage systems, and high-performance computing (HPC). Notable projects include: Development of ad hoc file systems like GekkoFS and IO-SEA for exascale architectures Optimization of storage systems (e.g., hybrid RAID, SSD garbage collection) Quantum computing compiler research for trapped-ion architectures Leadership in initiatives like the I/O Trace Initiative and BINARY (Big Data in Atmospheric Physics) He serves as Senior Associate Editor of ACM Transactions on Storage and co-chairs major conferences like FAST 2026 and ARCS 2026.

• Cryptographic Protocols
• Cloud Security and Privacy
• Homomorphic Encryption
• +۳ مورد دیگر

Travis Mayberry is an Assistant Professor in the Cyber Security department at the United States Naval Academy. His research focuses on cryptographic protocols, cloud security, privacy-preserving technologies, homomorphic encryption, and secure voting systems. He holds a PhD in Computer Science from Northeastern University, with a dissertation on practical Oblivious RAM (ORAM) protocols for private data outsourcing. He also contributed to the Scantegrity project at the University of Maryland, Baltimore County, developing end-to-end verifiable voting systems. Key areas of research include privacy in mobile devices, secure communication protocols, and cryptographic mechanisms for data protection. His work has been published in top venues like Privacy Enhancing Technologies Symposium (PETS), Network and Distributed Systems Security Symposium (NDSS), and ACM Computer and Communications Security (CCS). He received a Distinguished Paper Award in 2014 for his research on combining ORAM and PIR for efficient private file retrieval. Mayberry’s publications analyze vulnerabilities in Bluetooth Low Energy protocols, TLS client authentication tracking, and MAC address randomization in mobile devices. He has collaborated extensively on secure voting systems (e.g., Scantegrity) and practical ORAM implementations like ObliviSync and rORAM. His contributions bridge theoretical cryptography with real-world applications in privacy and security.

• Personal Information Management (PIM)
• Information Ethics
• Digital File Management
• +۴ مورد دیگر

Prof. Jesse Dinneen is an Assistant Professor in the Department of Information Science at Humboldt University of Berlin, affiliated with the Philosophische Fakultät. His work focuses on personal information management (PIM), AI ethics in libraries, and societal implications of information systems. Contact: Email | Phone: +49 30 2093-70957. Research Interests: Exploring ethical challenges in AI integration within libraries Analysis of digital file management behaviors across demographics Intersection of death studies and information management practices Evaluation of global research collaboration dynamics Development of PIM frameworks for creative professionals Key Contributions: Recent work includes critical analyses of neurodivergence research methodologies, AI ethics foresight tools, and longitudinal studies of international research partnerships. His 2024 Annual Review paper on death and information management has sparked interdisciplinary dialogue. Professional Activity: Active in library science policy discussions, particularly regarding EU AI regulation. Coordinates research on digital housekeeping and voice assistant interactions. Frequently presents at iSchools Caucus events. Labs/Teams: Leads the Information Behavior Research Group within the IBI institute, focusing on sociotechnical information systems analysis.

Greg Eisenhauerمشاهده پروفایل

پژوهشگر

• High Performance Computing
• Systems
• Enterprise Computing
• +۳ مورد دیگر

Dr. Greg Eisenhauer is a Senior Research Scientist at the Georgia Institute of Technology's School of Computer Science and affiliated with the Center for Experimental Research in Computer Systems (CERCS). His research focuses on high-performance computing (HPC), systems, and enterprise computing, with an emphasis on program monitoring, dynamic adaptation, performance evaluation, and I/O systems like ADIOS. Supported by NSF, DOE, DARPA, and industry grants, his work addresses challenges in HPC workflows, data management, and streaming analytics. He leads efforts in scalable data environments, metadata optimization, and exascale computing resilience.