جست‌وجوی استاد و پژوهشگر

• Computer Security
• Operating Systems Security
• Cloud Computing Security
• +۳ مورد دیگر

Jidong Xiao serves as a Senior Lecturer in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI), where he contributes to teaching and research in system security and virtualization technologies. His academic foundation includes a PhD from the College of William and Mary completed in 2016. Education: PhD in Computer Science, College of William and Mary (2016) Dr. Xiao's research spans computer security with specialized expertise in memory safety vulnerabilities, kernel-level security mechanisms, and hardware-assisted protection. His work addresses critical challenges in virtualization security, cloud infrastructure threats, and covert channel exploitation, frequently leveraging Intel platform features for innovative security solutions. Current investigations focus on fuzzing methodologies for use-after-free vulnerabilities and CPU-level covert communications. Analysis of his 15 most recent publications (2017-2024) reveals a sustained emphasis on low-level system security, with 73% of works addressing virtualization/cloud security and 60% exploring hardware-assisted techniques. His research demonstrates consistent progression from foundational virtual machine introspection (2017-2019) toward advanced topics including SGX-based patching (2020-2023) and cutting-edge CPU clock modulation exploits (2024). Scientific Awards: No scientific awards documented in source materials Available information does not specify graduate student supervision or research grant acquisitions. His technical contributions appear primarily through publications rather than advisory roles or funded projects. Laboratory affiliations and research team structures are not referenced in the provided documentation, though his work on Intel platform security suggests potential collaboration with hardware security groups.

Mark S. Shephardمشاهده پروفایل

استاد

• Scientific Computing
• High-Performance Computing
• Numerical Simulation
• +۵ مورد دیگر

Mark S. Shephard is the Samuel A. Johnson '37 and Elizabeth C. Johnson Professor of Engineering and Director of the Scientific Computation Research Center (SCOREC) at Rensselaer Polytechnic Institute, with joint appointments in Mechanical, Aerospace and Nuclear Engineering and Computer Science departments. His research pioneers Scientific Computing and High-Performance Simulation , driving innovations in automatic mesh generation , adaptive analysis methods , and parallel adaptive simulation technologies . SCOREC's work spans five core areas: High-Performance Simulation Methods - advanced mathematical models and discretization Simulation Reliability – uncertainty quantification and adaptive techniques Massively Parallel Computations – scalable solutions for real-world engineering problems Multiscale Computations - cross-scale modeling frameworks Construction of Simulation Systems – collaborative workflow development Applications include fusion plasma, soft tissue modeling, additive manufacturing, and microelectronics. Recent publications (2022-2025) reveal intense focus on GPU-accelerated unstructured mesh methods for fusion energy research and multiscale material science, with growing emphasis on exascale computing and cyberinfrastructure for plasma physics. His work increasingly bridges computational theory with industrial applications in CAE and medical device evaluation. Professor Shephard has graduated 24 Ph.D. students and secured over 65 research grants from 13 government agencies including DOE (SciDAC Institutes, Exascale Computing Program), NSF, NIH, DoD, and NASA, plus funding from 44 industry partners. His leadership extends to SCOREC's collaborations with ten+ universities and commercial impact through medical simulation software used in arterial stent evaluation. As SCOREC's founder and director for 32 years, he integrates faculty from seven departments across Rensselaer to advance simulation technologies. His Simmetrix Inc. co-founding role demonstrates commitment to translating research into engineering solutions, with current work targeting fusion plasma systems and heterogeneous supercomputing environments.

Hung Leمشاهده پروفایل

دانشیار

• Embedded Systems
• IoT
• Reconfigurable Systems
• +۴ مورد دیگر

Dr. Hung Le is an Instructional Associate Professor at the University of Houston's Cullen College of Engineering, Department of Electrical and Computer Engineering. He holds IEEE Life Senior Member and Senior Member of the National Academy of Inventors statuses. With over 30 years of industry experience in computer, telecom, and oil/gas sectors, his expertise spans embedded systems, IoT, reconfigurable systems, and memory controller design. Education: M.Sc., Electrical Engineering, University of Alberta Ph.D., Electrical Engineering, University of Houston Research Interests: Embedded Systems & IoT Reconfigurable Systems (ASIC/FPGA) Memory Controllers Machine Learning His work emphasizes hardware-software co-design, adaptive systems, and secure memory architectures. Publications highlight advancements in memory subsystems, dynamic buffer mechanisms, and secure embedded systems. Over 20 patents underscore his contributions to memory management, password security, and low-power device communication. Advising focuses on graduate instruction, with no listed advisees. Professional experience includes adjunct roles (2005-2008) and current instructional professorship since 2017. No specific labs or teams explicitly mentioned, though his patents indicate involvement in interdisciplinary hardware research.

Jianhui Yueمشاهده پروفایل

استادیار

• Computer Architecture
• Operating Systems
• System Optimization of Big Data Processing
• +۳ مورد دیگر

Jianhui Yue is an Assistant Professor in the Department of Computer Science at Michigan Technological University. His research focuses on computer architecture, operating systems, and system optimization for big data processing. He specializes in memory systems, persistent memory technologies, and hardware acceleration for graph processing and machine learning workloads. His work addresses challenges in optimizing performance, energy efficiency, and reliability in modern computing systems. Key research areas include hybrid memory architectures, in-storage accelerators (e.g., FlashGNN), and crash consistency mechanisms for non-volatile memory. His publications emphasize innovations in cache optimization, NAND flash management, and graph algorithms for dynamic data mining. His recent work (e.g., Cheetah, P3DC) highlights advancements in reducing latency and improving scalability in high-performance computing environments. Dr. Yue’s contributions span hardware-software co-design, with a focus on practical applications of computer architecture principles to real-world systems. His research bridges theoretical concepts with deployable solutions, addressing critical bottlenecks in data-centric computing.

Peng Zhangمشاهده پروفایل

استاد

• Power and Energy
• Quantum-Engineered Power Grids
• AI-Enabled Power Grids
• +۷ مورد دیگر

Peng Zhang is a tenured Full Professor of Electrical and Computer Engineering and a SUNY Empire Innovation Professor at Stony Brook University. He also holds affiliate professorships in Computer Science and Applied Mathematics & Statistics. His research focuses on cyber-physical grid resilience, including quantum-engineered grids, AI-enabled systems, and cybersecurity. He leads the Power Lab, developing technologies like software-defined grids and programmable microgrids. PhD: Electrical Engineering, University of British Columbia (Canada) Masters: Tsinghua University Bachelor's: Shandong University Research interests span quantum grids, AI-driven grid optimization, microgrid stability, and formal methods for resilience. Key projects include NSF-funded initiatives on resilient networked microgrids and quantum-security frameworks. Recent publications emphasize quantum computing applications in power systems, cybersecurity solutions, and fault management. Awards include the 2018 IEEE Technological Innovation Award and Excellence in Energy Award. Advises numerous PhD students and leads labs such as the Quantum Grids Lab and AI-Grid Lab. Active in grants and industry collaborations, including with Eversource Energy and DOE projects.

Zhoulai Fuمشاهده پروفایل

دانشیار

• Programming Language Theory and Implementation
• Program Analysis
• Testing and Verification
• +۵ مورد دیگر

Zhoulai Fu is a tenured Associate Professor at the State University of New York (SUNY), Korea, specializing in programming languages and software security. He also holds joint appointments as a Research Associate Professor at Stony Brook University and is affiliated with the Electrical and Computer Engineering Department at Virginia Tech. His educational background includes: Ph.D., 2009-2013, INRIA – Université de Rennes 1, France M.Eng., 2008-2009, Télécom ParisTech, France M.S, B.S, and French engineer degrees (Ingénieur), 2005-2008, École Polytechnique, France Professor Fu's research focuses on the intersection of Programming Languages, Software Security, and Large Language Models, with special emphasis on improving software reliability through formal methods, numerical error analysis, and scalable verification techniques . His work spans abstract interpretation, automated testing, and verification tools development. He has made significant contributions to floating-point analysis and program verification, with publications at top-tier conferences including PLDI, POPL, OOPSLA, ICSE, and CAV. His publication record shows a consistent trajectory in programming language theory with increasing practical applications. Early work focused on foundational aspects of abstract interpretation and floating-point analysis, while recent papers address security concerns through programming language techniques and incorporate modern approaches like incorrectness logic. Key themes across his publications include formal verification of low-level code, numerical error analysis, and developing scalable analysis tools for real-world software systems. His notable achievements include: Principal Investigator for DARPA E-BOSS Program funding Sole Principal Investigator for National Research Foundation of Korea funding Program Committee membership for POPL 2026, FSE 2024, and PLDI 2023 Professor Fu actively mentors students and has taught courses including Foundations of Computer Science, Programming Abstractions, and Research in Computer Science. His research is supported by significant grants from DARPA and NRF, enabling him to lead the Data & Intelligent Computing Lab at SUNY Korea. He is currently seeking postdocs, PhD, and graduate students to join his research team. He leads the Data & Intelligent Computing Lab, which focuses on advancing programming language techniques for software reliability and security. The lab collaborates with institutions including Virginia Tech, Stony Brook University, and international partners across Europe, working on projects that bridge theoretical computer science with practical software engineering challenges.

Ursula Eickerمشاهده پروفایل

استاد

• Urban energy systems
• 3D City modeling
• Urban data and simulation platform development
• +۷ مورد دیگر

Prof. Ursula Eicker is the Canada Excellence Research Chair in Smart, Sustainable and Resilient Cities and Communities at Concordia University , leading cutting-edge research in urban energy systems. Her work integrates 3D city modeling, renewable energy systems, and sustainable transport to develop zero-carbon city strategies. PhD in Solid State Physics (Heriot-Watt University) Habilitation in Renewable Energy Systems (Technische Universitat Berlin) Research Interests focus on urban simulation platforms, district energy networks, and climate-resilient infrastructure. The INSEL4Cities platform enables holistic urban modeling for building demands, transportation, and greenery. Her Residential Densification studies demonstrate 65% energy reduction through retrofits and solar integration. Recent publications explore urban solar shading , transactive energy systems , green infrastructure equity , and decentralized hydrogen production . Awards include the German-African Innovation Incentive and recognition for photovoltaic research in Egypt. Over 50 graduate students in her lab examine zero-carbon pathways. Teaches ENCS 691 on urban energy systems. Secured 10M CAD for the CERC chair and multiple grants. Co-Director of Concordia's Next Generation Cities Institute .

• Computer Architecture
• Reliability Engineering
• Cloud Computing
• +۷ مورد دیگر

Professor Gizopoulos Dimitris is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on advanced topics in computer architecture, reliability engineering, and hardware security. With a strong emphasis on fault tolerance and computational integrity, his work addresses critical challenges in modern computing systems such as silent data corruptions, GPU reliability, and RISC-V cloud ecosystems. Key research interests include microarchitecture-level analysis, cross-layer system reliability assessment, and energy-efficient computing. His contributions span fault propagation modeling, hardware-software co-design for resilience, and innovative approaches to detecting silent errors in CPUs and GPUs. He actively participates in large-scale projects like NEUROPULS and Vitamin-V, advancing secure neuromorphic architectures and open-source cloud infrastructure. Recent publications highlight trends in silent data corruption quantification, GPU vulnerability analysis, and energy-efficient RISC-V designs. His work bridges theoretical models with practical implementations, emphasizing real-world validation through frameworks like gem5 and fault injection experiments. Despite no listed advisees or grants in current records, his research collaborations and project leadership position him at the forefront of next-generation computing reliability. Labs and teams associated with his work include the Vitamin-V virtual environment development team and the NEUROPULS consortium for secure neuromorphic accelerators. These initiatives reflect his commitment to advancing both theoretical and applied aspects of dependable computing systems.

Karakostas Vasileiosمشاهده پروفایل

استادیار

• Computer Architecture
• Cloud Computing
• RISC-V Processors
• +۵ مورد دیگر

Karakostas Vasileios is an Assistant Professor at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens. His research focuses on computer architecture, cloud computing, and energy-efficient hardware systems. He specializes in areas such as RISC-V processors, virtual memory systems, and hardware security. Vasileios leads projects like NEUROPULS (neuromorphic secure accelerators) and Vitamin-V (RISC-V-based cloud infrastructure validation). His work emphasizes resilience analysis, performance optimization, and trustworthy development frameworks. Education and employment details are not explicitly provided in the source text, but his extensive publication record since 2011 demonstrates continuous academic engagement. Key research trends include: Memory systems optimization (e.g., TLB hierarchies, elastic translations) GPU and SoC fault tolerance analysis Cloud resource management (ACTiCLOUD, DAPHNE runtime) Open-source hardware validation (Vitamin-V project) Notable contributions include the Gem5-marvel simulator for heterogeneous architectures and BypassD for SSD access acceleration. His work bridges theoretical computer architecture with practical cloud and embedded system applications.

• Operating Systems
• Fault Tolerance
• Cyber-Physical Systems
• +۵ مورد دیگر

Marcus Völp is an Associate Professor and head of the CritiX research group at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT). His research focuses on ultra-reliable operating systems, fault and intrusion tolerant systems for cyber-physical environments, and hierarchical hybridization techniques to construct resilient computing platforms. His work bridges theoretical foundations with practical implementations, particularly in developing dependable systems-on-chip that can withstand faults and intrusions. Research spans formal verification methods, radiation-hardened hardware, blockchain security, and autonomous vehicle safety systems. Recent publications demonstrate advancement in parameterized system verification, radiation effects on routers, and N-version machine learning for autonomous systems. His group maintains strong focus on practical resilience mechanisms for real-time and critical systems across computing layers.

Perry Alexanderمشاهده پروفایل

استاد

• Formal Methods
• System-Level Design
• Cybersecurity
• +۵ مورد دیگر

Warren P. Alexander is the AT&T Distinguished Professor at The University of Kansas, specializing in formal methods applied to system-level design. His research focuses on ensuring reliable, secure, and trustworthy computer systems through mathematical methodologies, tool development, and curriculum integration. He emphasizes pragmatic engineering approaches to formal techniques, including protocol design and verification. Key research interests include remote attestation protocols, cybersecurity assurance, and trusted computing architectures. His work bridges theory and practice, with contributions to frameworks like Rosetta and Copland for system design and verification. Dr. Alexander’s publications span formal verification, system-level design, and cybersecurity, reflecting a commitment to advancing both academic and industrial applications of rigorous system design principles.

George Korresمشاهده پروفایل

استاد

• Power System Analysis
• Power System Operations
• Power Systems Protection
• +۲ مورد دیگر

Professor George Korres specializes in Electric Power Engineering at the National Technical University of Athens. His research encompasses power system analysis, protection schemes, and industrial control systems. Teaching responsibilities include courses on: Supervision/Management of Energy Systems Energy Control Centers Power System Protection Recent research focuses on advanced state estimation techniques for modern power grids, particularly hybrid measurement systems combining SCADA and PMU data. Publications demonstrate applications in transmission networks, HVDC systems, distribution grids with renewable integration, and adaptive protection for island systems.

Shubhendu Mukherjeeمشاهده پروفایل

استاد مدعو

• Computer Architecture
• Fault Tolerant Systems
• Soft Errors
• +۵ مورد دیگر

Shubhendu Mukherjee is a Distinguished Engineer at Cavium Networks and Adjunct Professor at the Indian Institute of Technology Kanpur. He is a Fellow of IEEE and ACM, and recipient of the 2009 Maurice-Wilkes Award for outstanding contributions to computer architecture. His career spans leadership roles at Intel and Compaq, where he pioneered fault-tolerant microarchitectures and performance modeling innovations. Education: PhD (1998) and MS (1993) in Computer Science from University of Wisconsin-Madison; B.Tech (1991) in Computer Science and Engineering from IIT Kanpur. Research Interests Mukherjee specializes in computer architecture , soft error modeling , and fault-tolerant design . His work includes Redundant Multithreading (RMT), architectural vulnerability modeling, and on-chip interconnect optimization. Recent publications focus on cache soft error anomalies, quantized AVF analysis, and architectural core salvaging for hard error tolerance. Scientific Awards Maurice-Wilkes Award (2009) IEEE Fellow (2009) ACM Fellow (2011) IEEE Top Picks Awards (2003, 2004) Intel Divisional Recognition Awards (2002–2009) Professional Activities Mukherjee served as General Chair of ASPLOS 2004 , Program Chair of HPCA 2011 , and editorial board member for IEEE Micro, IEEE Computer Architecture Letters, and IEEE Transactions on Dependable and Secure Computing. He also led Intel's SPEARS group (2001–2010), driving architectural innovations in enterprise processors.

• Modeling
• Software Design
• Digital Twins
• +۵ مورد دیگر

Antoine Beugnard is a Professor in the Department of Computer Science at IMT Atlantique (formerly Telecom Bretagne), located on the Brest campus, where he has served since December 2007. His academic journey began at ENST-Bretagne (1986), followed by a Doctorate in Computer Science from the University of Rennes 1 in 1993, and accreditation to supervise research in 2005. His educational background includes: Former student of ENST-Bretagne (1986) Doctorate in Computer Science from University of Rennes 1 (1993) Accreditation to supervise research (2005) Professor Beugnard's research centers on software modeling, particularly focusing on the meaning, notations, and properties like composition of models. Since 2017, he has applied his research to the Industry of the Future, specifically digital twins, participating in the "Digital Twin" working group of the Alliance Industrie du Futur. His work also explores static verification of names in heterogeneous languages, communication abstractions, component-based software engineering, and late-binding semantics in object-oriented languages. As a member of Lab-STICC (UMR 6285) and the P4S team, he contributes to the development of Openflexo for model federation. His recent publications demonstrate a strong evolution from foundational work on object-oriented languages and component models toward practical applications in Industry 4.0 contexts, with a pronounced focus on digital twin technology, model federation, and software engineering approaches to complex systems. The research trajectory shows increasing integration of theoretical modeling concepts with real-world industrial applications. Professor Beugnard has supervised numerous doctoral students throughout his career, guiding research in areas including model federation, digital twins, component-based software engineering, and socio-technical systems. His teaching philosophy emphasizes active learning with project simulations addressing both organizational and technical aspects of software development. He is responsible for the "Ingénierie Logiciel des Systèmes Distribués" (ILSD) thematic deepening program and teaches software engineering, UML design, object-oriented programming with Java, and fundamentals like concurrency, distribution, and design patterns. His approach centers on three principles: "explicitez" (make explicit the process and product at all levels), "adaptez" (adapt rules and methods to context), and "justifiez" (justify decisions and adaptations).

• Computer Engineering
• Hardware Security
• Artificial Intelligence
• +۳ مورد دیگر

Jaan Raik is a Tenured Full Professor and Head of the Centre for Dependable Computing Systems at Tallinn University of Technology (TalTech), Department of Computer Systems. His research focuses on hardware reliability, fault tolerance in embedded systems, and secure computing architectures. Key areas include fault-resilient deep neural network accelerators, approximation methods for DNNs, and vulnerability assessment in hardware-software systems. He leads the Centre for Dependable Computing Systems, which explores advanced reliability engineering techniques for modern computing systems. His work integrates formal verification, machine learning, and hardware design to address challenges in embedded systems, RISC-V processors, and edge AI chips. Notable contributions include frameworks like Saffira for DNN accelerator reliability assessment and innovative methods for assertion-based verification. Research interests span fault diagnosis, approximation computing, and security-aware architectures. He frequently publishes at top venues such as IEEE European Test Symposium and DDECS, with recent focus on resilient neural networks, cache leakage detection (CLD), and hardware Trojan mitigation. Collaborations include industry partnerships for practical deployment of fault-tolerant systems and academic initiatives to standardize reliability assessment methodologies. His work bridges theoretical computer engineering with applied solutions for real-world systems.