جست‌وجوی استاد و پژوهشگر

Zhen Xieمشاهده پروفایل

استادیار

• High-Performance Computing (HPC)
• Machine Learning
• Parallel Computing
• +۳ مورد دیگر

Zhen Xie is an Assistant Professor in the Department of Computer Science at Binghamton University (SUNY), serving as Director of the Parallel Computing and Intelligent System (PCIS) Lab. He holds a PhD from the Chinese Academy of Sciences and a BA from Wuhan University of Technology. His research focuses on high-performance computing (HPC), machine learning, and their intersections, particularly optimizing performance for HPC and AI/DL applications across heterogeneous architectures. Research Highlights: Dr. Xie’s work emphasizes system-level performance optimization for ML and HPC, including GPU acceleration, memory optimization, and AI accelerator selection. His team has won the ACM Gordon Bell Special Prize (2022) for their GenSLMs project predicting SARS-CoV-2 evolution. Recent grants include a 2024 gift from OpenAI for AI testbed initiatives. Awards: ACM Gordon Bell Special Prize (2022), Impact Argonne Awards (2023) Lab: PCIS Lab explores middleware for parallel computing, targeting scientific simulations and big data analytics. Collaborations include Argonne National Lab and Lawrence Berkeley National Lab. Teaching: Teaches Distributed Systems (CS 457/557) and oversees independent studies. Previously trained researchers at Argonne’s ATPESC program. Grants & Collaborations: Subcontract with Lawrence Berkeley Lab (HEVI-LOAD), Argonne testbed expeditions, and OpenAI-funded projects. Active in DOE labs like Summit and Aurora supercomputers.

Georgios Portokalidisمشاهده پروفایل

استاد پژوهشی

• Systems Security
• Binary Analysis
• Software Hardening
• +۱ مورد دیگر

Georgios Portokalidis is an Associate Research Professor at IMDEA Software Institute and Visiting Research Professor at Stevens Institute of Technology. He leads research in software systems security with focus on binary analysis, software hardening, and operating system security. His research develops practical defenses against software vulnerabilities through techniques like binary debloating, system call filtering, and hardware-assisted security. Current projects explore Rust language security, processor-assisted protection mechanisms, and vulnerability mitigation through code reduction. Publication trends show evolution from foundational binary analysis to applied security hardening, with recent emphasis on Rust security, hardware-assisted defenses, and real-world system protection. Work demonstrates consistent focus on practical, deployable security solutions. He has supervised numerous PhD students and postdocs, currently mentoring researchers at IMDEA. His group investigates binary analysis, software debloating, and system hardening techniques. Major grants include DARPA YFA (2021-2023) and ONR funding (2017-2022) supporting adaptive binary debloating research. Leads the systems security research group at IMDEA Software Institute, collaborating with international partners. Maintains active research partnerships and regularly contributes to top security conferences as program committee member.

Ronald D. Barnesمشاهده پروفایل

استاد

• Computer Architecture
• Microarchitecture
• Compiler Optimization
• +۴ مورد دیگر

Ronald D. Barnes is a Professor in the School of Electrical and Computer Engineering at the University of Oklahoma, where he returned in 2007 after serving as faculty at George Mason University. An OU alumnus, he earned his B.S. in Electrical Engineering from the university in 1998 and completed his Ph.D. in Electrical Engineering at the University of Illinois in 2005, specializing in complexity-effective microarchitecture. His educational background includes: B.S. in Electrical Engineering, University of Oklahoma (1998) Ph.D. in Electrical Engineering, University of Illinois (2005) Dr. Barnes' primary research centers on computer architecture, with emphases on multi-core systems, reduced-complexity architectures, and compiler-architecture co-design to address power, performance, and memory latency challenges. His work integrates static/dynamic compilers with novel hardware, focusing on program analysis, application mapping to accelerators, and runtime optimization. Notably, Google Scholar data indicates additional research in psychology and literary studies , examining fiction's impact on social cognition, moral judgment, and imaginative engagement, though this appears inconsistent with his ECE departmental affiliation. Analysis of his 15 most recent publications reveals a dual trajectory: engineering-focused work in computer systems (2005-2016) and a sharp pivot toward psychological studies of fiction, morality, and narrative comprehension (2022-2024). The recent publications predominantly investigate how fictional content influences theory of mind, empathy development, and moral reasoning, with significant output in mystery fiction literature. His scientific contributions span two distinct domains without overlap in methodology or subject matter, suggesting either interdisciplinary breadth or potential data misattribution in the provided sources.

Sophie Rapagnaمشاهده پروفایل

پژوهشگر

• knee osteoarthritis
• microCT imaging
• bone microarchitecture
• +۲ مورد دیگر

Sophie Rapagna is a Casual Academic and Micro-CT Facility Manager at the College of Science and Engineering, Flinders University . Her research focuses on knee osteoarthritis , microCT imaging , and bone microarchitecture with applications in implant biomechanics and digital volume correlation (DVC) . Active in Flinders Institute for Nanoscale Science and Technology Full Member of the Medical Device Research Institute PhD candidate in biomechanics since 2017 Her publications (17 total) span topics like: Micro-CT-based mechanical analysis of implants Porosity in 3D-printed titanium components Failure mechanisms in dissimilar welds Bone-cartilage interactions in osteoarthritis Time-elapsed imaging of implant degradation High-resolution imaging for biomechanical strain mapping She collaborates with researchers such as Dr. Egon Perilli and Michael Taylor on projects involving digital volume correlation and additive manufacturing .

Chongxiao Chenمشاهده پروفایل

استادیار

• Poultry Nutrition
• Animal Health
• Feed Additives
• +۳ مورد دیگر

Chongxiao (Sean) Chen is an Assistant Professor and Extension Specialist in the Department of Poultry Science at the University of Georgia's College of Agricultural & Environmental Sciences. His research focuses on poultry nutrition, feed additives, and stress-related health challenges, with a particular emphasis on gut health, mycotoxin mitigation, and bone development in poultry species. Ph.D. in Poultry Science from the University of Georgia DVM in Veterinary Medicine from China Agricultural University Dr. Chen develops educational and research programs to support poultry producers, while also mentoring undergraduate and graduate students. His work combines traditional poultry science with modern data processing techniques, including machine learning applications for animal activity monitoring. Recent publications highlight his expertise in vitamin D metabolism in avian species, feed formulation optimization, and the impact of environmental stressors on poultry health. Key research themes include: Bone structural development in laying hens Feed additive efficacy Stress-related performance metrics Egg quality optimization AI applications in poultry monitoring Mycotoxin contamination mitigation Contact: sean.chen@uga.edu | Phone: 706-542-6622

Vijaykrishnan Narayananمشاهده پروفایل

استاد

• Power Aware Computing
• Computer Architecture
• Embedded Systems
• +۴ مورد دیگر

Vijaykrishnan Narayanan is a Professor at the College of Engineering , Pennsylvania State University, with affiliations in both Computer Science & Engineering and Electrical Engineering departments. He co-directs the Microsystems Design Lab and leads the Architecture, Benchmarking, and Circuits Thrust at the DARPA/SRC LEAST Center. Education : Bachelors (1993) from University of Madras; Ph.D. (1998) from University of South Florida His research focuses on Power Aware Computing , Computer Architecture , Embedded Systems , and Emerging Device Integration . Recent work explores steep-slope devices for energy efficiency, nonvolatile processors for ambient energy harvesting, and neuromorphic architectures using hybrid VO₂-MOSFET oscillators. Key article trends span post-CMOS technologies (tunnel FETs, VO₂ devices), low-power design , and bio-inspired signal processing . Scientific Awards : IEEE Fellow, ACM Fellow, IEEE Transactions on VLSI Best Paper, IEEE Micro Best Paper Patents : Dynamically-configurable hardware architecture for audience analytics

• Hardware Security
• Machine Learning for Security
• IoT Security
• +۵ مورد دیگر

Setareh Rafatirad is an Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University's College of Engineering and Computing. Her research spans hardware security, machine learning for security applications, and IoT security systems. Her research interests focus on hardware security, machine learning for security applications, IoT security, side-channel attacks, and malware detection. She has developed innovative approaches for securing integrated circuits, detecting malware using machine learning techniques, and protecting against side-channel vulnerabilities in computer systems. Her work bridges the gap between hardware design and security, creating practical solutions for emerging security challenges in computing systems. Her recent publications demonstrate a strong trend toward applying machine learning techniques to security problems, particularly in hardware and embedded systems. She has made significant contributions to understanding and mitigating side-channel attacks, developing secure machine learning models, and creating efficient security solutions for resource-constrained devices. Her work shows increasing interdisciplinary reach, connecting hardware security with healthcare applications and educational technologies. Dr. Rafatirad has collaborated extensively with researchers including Houman Homayoun, Avesta Sasan, and Sai Manoj P. Dinakarrao. She has secured research funding for projects related to hardware security and machine learning applications, though specific grant details are not provided in the available information.

Michael D. Smithمشاهده پروفایل

استاد

• Computer Science
• Education Technology
• Data Security
• +۳ مورد دیگر

Michael D. Smith is the John H. Finley, Jr. Professor of Engineering and Applied Sciences and Distinguished Service Professor at Harvard University. He previously served as Dean of the Faculty of Arts and Sciences (FAS) for 11 years, leading Harvard's largest school with a focus on undergraduate education, faculty development, and interdisciplinary research. He holds a Ph.D. from Stanford University (1993), a Master’s from Worcester Polytechnic Institute, and a Bachelor’s from Princeton University. His academic career is complemented by industry experience, including co-founding Liquid Machines (acquired by Check Point in 2010), and advisory roles with venture capital firms like 1984 Ventures and GSV Ventures. Research interests span computer science education innovation, technology’s societal impact, and hardware/software systems. He pioneered work on voltage noise mitigation in processors, cybersecurity solutions, and online education platforms like edX. Awards include the NSF Young Investigator Award (1993), Alpha Iota Teaching Prize, and W.E.B. Du Bois Medal. Currently, he advises startups and educational initiatives such as CS Forward and Kira Learning, while developing new in-person and online courses. His leadership roles include Board member at The Peddie School and former edX Board member (2012–2018).

Yong Chenمشاهده پروفایل

استاد

• Data-Intensive Computing
• Parallel and Distributed Computing
• High-Performance Computing
• +۳ مورد دیگر

Dr. Yong Chen is a Professor and Interim Department Chair in the Computer Science Department at Texas Tech University (TTU), where he founded the Data-Intensive Scalable Computing Laboratory (DISCL). He also serves as Co-Director of the NSF Cloud and Autonomic Computing Center (CAC@TTU), focusing on data-intensive computing, high-performance computing (HPC), cloud systems, and parallel/distributed architectures. His research bridges hardware-software co-design for scientific and enterprise applications. Ph.D., Computer Science, Illinois Institute of Technology (2009) M.S., Computer Science, University of Science and Technology of China (2003) B.E., Computer Engineering, University of Science and Technology of China (2000) Dr. Chen's research spans data-intensive computing, HPC, cloud systems, and parallel architectures. He develops scalable solutions for scientific discovery and enterprise computing, emphasizing systems software, storage optimization, and hardware-software co-design. His work addresses challenges in metadata management, 3D-stacked memory, and efficient resource allocation in distributed environments. Recent publications include studies on 3D-stacked memory optimization (IEEE TC), metadata indexing (SC), and parallel file system reliability (ICS). His work is characterized by interdisciplinary collaboration and practical applications in HPC domains. NSF-TCPP Early Adopter Status Award Best Paper Award (IPDPS'21) Outstanding Teaching Assistant, IIT (2006) Dr. Chen advises students through graduate and undergraduate research assistantships at DISCL and CAC@TTU, offering financial support for qualified candidates. He has contributed to major conferences as Program Co-Chair (ICPP) and Committee Member (IPDPS, CCGrid, ISC, HPCAsia). Labs/Teams: Data-Intensive Scalable Computing Laboratory (DISCL), NSF Cloud and Autonomic Computing Center (CAC@TTU).

Sebastien Pillementمشاهده پروفایل

مدرس

• Computer Engineering
• Embedded Systems
• Computer Architecture
• +۳ مورد دیگر

Sébastien Pillement is a Lecturer at Polytech'Nantes, the College of Engineering of the University of Nantes, and a member of the ASIC research team within the IETR UMR 6164 laboratory. His career spans over 13 years at the IUT of Lannion (University of Rennes 1) before joining the University of Nantes in 2012. He holds a PhD in Computer Science from the University of Montpellier II (1998) and a Habilitation à Diriger des Recherches (HDR) from the University of Rennes 1 (2010). Current Research Focus: Dynamically Reconfigurable Architectures (DRA), Hardware Security, Fault-Tolerant Embedded Systems, NoC (Network-on-Chip), Design Methodologies. Teaching Areas: Digital Circuits, Computer Architecture, Operating Systems, Real-Time Systems, and Algorithms for Embedded Computing. His research explores flexible and efficient architectures for embedded systems, emphasizing real-time management, reliability, and security. Key article trends include RISC-V processors, neural network acceleration on MPSoC, formal verification of arithmetic circuits, and runtime FPGA scheduling. Collaborations span international institutions like the University of Toronto and CEA, as well as industrial partners such as STMicroelectronics and Thales. PhD Students : Current: Laureline Dubucq (Security & AI), Mustafa Ibrahim (Ultra-Low Power AI), Téo Biton (Runtime Anomaly Detection), Mohamed Amine Zhiri (Adaptive NoC), Juliette Pottier (RISC-V Protection). Graduates: Quentin Dariol (Neural Network Timing), Alexis Duhamel (FPGA Scheduling), Safouane Noubir (Security in Multi-Core Systems), Hai Dang Vu (Probabilistic Timing Analysis), David Pallier (Sensor Clock Synchronization). Projects : Current: ADAPTING (2023-2029), FITNESS (2023-2027), SEC-V (2022-2025), NOP (2021-2025). Past: SPARTE (2015-2018), ARDyT (2011-2015), FosFor (2008-2011).

Steve Blackburnمشاهده پروفایل

استاد

• Memory Management
• Garbage Collection
• Virtual Machine Design and Implementation
• +۷ مورد دیگر

Steve Blackburn is a research scientist at Google DeepMind and professor of computer science at the Australian National University in the College of Engineering and Computer Science. His primary research focus is on programming language implementation, with expertise spanning memory management, virtual machines, and performance analysis. He has served in significant leadership roles including Associate Dean for Diversity and Inclusion (2016-2019) and as Program Chair for PLDI 2015 and General Chair for PLDI 2023. Blackburn's research interests center on making software run faster and more power-efficiently on modern hardware. His primary areas include microarchitectural support for managed languages, fast and efficient garbage collection, and the design and implementation of virtual machines. He maintains a strong interest in sound methodology and infrastructure for successful research innovation. His work bridges theoretical computer science with practical systems implementation, with particular focus on memory management frameworks and performance benchmarking. His publication record reveals a consistent focus on memory management systems, with recent work exploring garbage collection in modern contexts including CRuby, Julia, mobile devices, and memory-disaggregated datacenters. His research shows an evolution from foundational garbage collection algorithms toward practical implementations addressing real-world constraints in contemporary programming languages and hardware platforms. A notable trend is his increasing focus on quantifying and understanding the true costs of garbage collection in production environments. Fellow of the ACM Blackburn has supervised numerous doctoral students including Zhen He, John Zigman, Robin Garner, Ting Cao, and currently advises Wenyu Zhao, Zixian Cai, and others. He has also served on multiple program committees for major conferences including PLDI, ASPLOS, ISMM, and OOPSLA, demonstrating his significant contributions to the programming languages and systems research community. His service includes editorial roles for ACM Transactions on Programming Language Applications and Systems from 2017-2020. He leads two major research infrastructure projects: the MMTk memory management framework and the DaCapo benchmark suite, both of which have become foundational tools for researchers in programming languages and systems. These projects reflect his commitment to shared research infrastructure and reproducible methodology in systems research.

Timothy Jonesمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Computing
• Compilers
• +۴ مورد دیگر

Timothy Jones is a Professor of Computer Architecture and Compilation at the University of Cambridge Computer Laboratory, with a research focus on extracting parallelism (thread-level, data-level, memory-level) through compilers, binary translators, and microarchitectures to enhance performance, energy efficiency, and reliability. He is also a Fellow and 1956 College Lecturer at Gonville and Caius College, serving as joint Director of Studies for Computer Science. Teaching: Advanced Topics in Computer Architecture (MPhil ACS, Part III), Introduction to Computer Architecture (Part IB), Optimising Compilers (Part II) Research Themes: Computer Architecture, Security, Programming Languages, Parallel Computing Contact: Room SC03, Department of Computer Science and Technology, William Gates Building, Cambridge CB3 0FD His recent publications emphasize heterogeneous parallelism, fault tolerance, speculative execution, and security implications in compiler and microarchitecture design. Notable trends include integrating fine-grained security analysis into superscalar cores and optimizing GPU architectures for scalarization and memory bypassing. He is active on Twitter ( @TJonesCL ) and maintains an Erdős Number of 4.

Sandip Kunduمشاهده پروفایل

استاد

• Hardware Security
• VLSI Design
• CAD Algorithms
• +۷ مورد دیگر

Sandip Kundu is a Professor of Electrical and Computer Engineering at the University of Massachusetts Amherst since 2005. Prior roles include Senior Researcher at Intel (1997–2005) and IBM Research (1988–1997). He holds a Ph.D. from the University of Iowa (1988) and a B.Tech from IIT Kharagpur (1984). Research Interests: Focuses on hardware security, VLSI design, CAD algorithms, microarchitecture, and neural processing. Notable contributions include work on physically unclonable functions (PUF), blockchain-based IC traceability, and securing embedded systems against adversarial attacks. Key Activities: Served as Associate Editor for multiple IEEE journals and held visiting professorships at institutions like University of Freiburg (Germany), Kyushu Institute of Technology (Japan), and Tsinghua University (China). Awarded IEEE Fellow and JSPS Invitational Fellowships. Awards: Includes five best paper awards, Intel’s Development Leadership Pioneer Award, IBM’s Outstanding Technical Achievement Award, and recognition as a Distinguished Visitor by IEEE Computer Society. Grants & Labs: Active in NSF-funded research and leads the Advanced VLSI Design and Test Group, exploring secure hardware design, neuromorphic computing, and resilient architectures for edge devices.

Vincent Beroulleمشاهده پروفایل

استاد

• Microelectronics
• Hardware Security
• Fault Modeling
• +۴ مورد دیگر

Professor Vincent Beroulle at Grenoble Institute of Technology's Esisar campus leads the LCIS laboratory, focusing on security and safety of complex integrated circuits and systems. His work bridges fault modeling, fault injection, and security for IoT and RFID technologies. Education: Engineer Degree (INPG, 1996), Master (University of Montpellier II, 1999), Ph.D. (University of Montpellier II, 2002) Current Role: Director of LCIS Laboratory, Professor in Embedded System Security & Safety Research spans hardware security, fault injection attacks, and vulnerability analysis of embedded systems. Recent work includes clock glitch fault injection studies, lightweight ECC countermeasures for RFID, and aging effects on PUF architectures. His team explores cross-layer methodologies to enhance fault models and security protocols. Supervision includes 12 current and former PhD students tackling topics like secure RFID tags, fault injection countermeasures, and PUF-based security. Projects under ANR, PEPR Cyber, and ERASMUS+ funding drive his lab's innovation in secure embedded design.

Karen Hindمشاهده پروفایل

استاد

• Bone Health
• Aging Research
• Pharmacology
• +۳ مورد دیگر

Dr Karen Hind is a Professor in Practice at Lancaster Medical School , focusing on advanced bone health metrics and aging-related biomedical research. Her work bridges clinical applications with pharmacological interventions. Bone Health Aging Research Pharmacology Biomedical Research Nutraceuticals Recent publications highlight her contributions to trabecular bone score optimization and phytoceutical impacts on aging models. No formal awards or student advisement details are available in the provided data.