جست‌وجوی استاد و پژوهشگر

Diana Marculescuمشاهده پروفایل

استاد

• energy-aware computing
• reliability-aware computing
• hardware aware machine learning
• +۱۰ مورد دیگر

Diana Marculescu is Department Chair, Cockrell Family Chair for Engineering Leadership #5, and Professor, Motorola Regents Chair in Electrical and Computer Engineering #2 at the University of Texas at Austin. She previously served as the David Edward Schramm Professor at Carnegie Mellon University, where she was Founding Director of the College of Engineering Center for Faculty Success (2015-2019) and Associate Department Head for Academic Affairs (2014-2018). Her educational background includes: Dipl.Ing. degree in computer science from Polytechnic University of Bucharest, Romania (1991) Ph.D. degree in computer engineering from University of Southern California, Los Angeles (1998) Dr. Marculescu's research bridges hardware design and machine learning, focusing on energy- and reliability-aware computing, hardware-aware machine learning, and computing for sustainability. She leads the EnyAC (ENergY Aware Computing) research group and founded the iMAGiNE Consortium for industry-university collaboration in engineering intelligent machines from cloud to edge. Her work addresses the critical need for efficient AI systems across diverse hardware platforms. Analysis of her recent publications reveals a strong trend toward hardware-efficient machine learning, with emphasis on neural architecture search, model compression, and energy-aware deep learning systems. Her research tackles the fundamental challenge of co-designing machine learning models and hardware to achieve optimal performance and efficiency. Dr. Marculescu has received numerous prestigious awards: National Science Foundation Faculty Career Award (2000-2004) ACM SIGDA Technical Leadership Award (2003) Carnegie Institute of Technology George Tallman Ladd Research Award (2004) IEEE Circuits and Systems Society Distinguished Lecturer (2004-2005) Australian Research Council Future Fellowship (2013-2017) Marie R. Pistilli Women in EDA Achievement Award (2014) Barbara Lazarus Award from Carnegie Mellon University (2018) Fellow of ACM, IEEE, and AAAS Dr. Marculescu has advised more than a dozen doctoral students, 35+ master students, and more than two dozen undergraduates. Her research has been supported by significant grants including the NSF Career Award and Australian Research Council Future Fellowship. She has served as Technical Program Chair and General Chair for multiple major conferences including ACM/IEEE International Symposium on Low Power Electronics and Design, IEEE/ACM International Symposium on Networks-on-Chip, and IEEE/ACM International Conference on Computer-Aided Design. She leads the EnyAC research group which focuses on sustainable computing and computing for sustainability, and founded the iMAGiNE Consortium to foster industry-university collaboration in engineering intelligent machines from cloud to edge.

Dakai Zhuمشاهده پروفایل

استاد

• Dependable computing
• Low-power computing
• IoT (Internet of Things)
• +۳ مورد دیگر

Dakai Zhu is a Professor, Assistant Department Chair, and Graduate Advisor of Record for PhD programs in the Department of Computer Science at the University of Texas at San Antonio (UTSA). He holds the Kay and Steve Robbins Faculty Teaching Fellowship Award in Computer Science, reflecting his commitment to education and research excellence. His research focuses on dependable and low-power computing, IoT innovations, real-time embedded systems, and cloud computing performance management. Education: Ph.D. in Computer Science, University of Pittsburgh M.E. in Computer Science and Technology, Tsinghua University B.E. in Computer Science and Technology, Xi'an Jiaotong University Dr. Zhu's work emphasizes sustainable computing frameworks for AI-driven healthcare applications, energy-efficient fault-tolerant systems, and privacy-preserving IoT solutions. His recent research includes real-time health monitoring using wearable sensors (e.g., PPG-based heart rate analysis), cybersecurity for cyber-physical systems, and optimization of embedded systems for assistive technologies like power wheelchair control. He also investigates scheduling algorithms for multiprocessor systems and cloud resource management to enhance reliability and energy efficiency. His publications span topics from AI-enabled health frameworks to fault-tolerant scheduling strategies, showcasing a blend of theoretical rigor and practical applications. Awards highlight his contributions to teaching and interdisciplinary research bridging computer science with healthcare and embedded systems.

JoAnn M. Paulمشاهده پروفایل

دانشیار

• Bio-inspired Computer Architecture
• Computer Architecture
• Heterogeneous Multiprocessing
• +۳ مورد دیگر

JoAnn M. Paul is an Associate Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. She is affiliated with the Virginia Tech Research Center - Arlington, where she conducts research on bio-inspired computer architecture, heterogeneous multiprocessing, and computational neuroscience. Her work explores how principles from neurobiology can inform the design of parallel computing systems, particularly in contexts like computational dreaming and chip-level performance optimization. Education: Ph.D., University of Pittsburgh, 1994 M.S.E.C.E., Carnegie Mellon University, 1987 B.S.E.E., University of Pittsburgh, 1983 Research Interests: Her research focuses on advancing heterogeneous computing architectures through interdisciplinary approaches. Key areas include bio-inspired system design, computational models of dreaming, and performance evaluation metrics for parallel systems. She investigates how structural intelligence and paradox resolution can enhance system efficiency, with applications in embedded systems and real-time processing. Publications Trends: Her work spans over three decades, with notable contributions to heterogeneous multiprocessor design, capacity metrics, and stochastic simulation. Recent publications emphasize integrating cognitive-inspired algorithms into hardware architectures to address challenges in parallel computing scalability and energy efficiency. Labs/Teams: As part of the Virginia Tech Research Center, she collaborates on projects blending academic and industrial needs, particularly in embedded and high-performance computing domains.

Binoy Ravindranمشاهده پروفایل

استاد

• Computer Systems
• Operating Systems
• Concurrency
• +۷ مورد دیگر

Binoy Ravindran is a Professor and Bradley Senior Faculty Fellow in the Department of Electrical and Computer Engineering at Virginia Tech, where he leads the Systems Software Research Group. He holds a Ph.D. from The University of Texas at Arlington (1998). His research focuses on computer systems, emphasizing security, performance, energy efficiency, and timeliness in areas like concurrent, heterogeneous, distributed, and real-time computing. Recent projects include the Low-level Reasoning Machine (LLRM), Popcorn Linux, and LibrettOS. He teaches courses such as ECE/CS 5510 (Multiprocessor Programming), ECE/CS 5544 (Compiler Optimizations), and ECE 5984/SS (Modern Binary Exploitation). His service roles include editorial board positions at IEEE Transactions on Cloud Computing and ACM Transactions on Embedded Computing Systems, and he co-chaired ACM Systor 2025. Ravindran has published over 330 papers, earning nine best paper awards, and has mentored 26 PhD students, 23 postdocs, and 11 research faculty. Notable honors include ACM Distinguished Scientist and an Office of Naval Research Faculty Fellowship. His research group explores projects like LLRM (binary security verification), Popcorn Linux (heterogeneous ISA systems), and KairosVM (real-time hypervisor). Recent advancements include Stramash OS (ASPLOS'25) and Hexo (DOD infrastructure offloading).

• Computer Science Education
• Computer Systems
• Object-Oriented Programming
• +۵ مورد دیگر

Mark A. Holliday is a Professor of Computer Science at Western Carolina University (WCU), where he has served since 2004. He holds a Ph.D. in Computer Science from the University of Wisconsin–Madison (1986) and has extensive experience in academia, including roles as Interim Department Head (2007–2009) and Visiting Research Scientist at institutions like the University of Portsmouth (UK) and the University of Toronto. His primary affiliation is with the Department of Mathematics and Computer Science at WCU. Education Background: Ph.D. in Computer Science, University of Wisconsin–Madison (1986) Master's in Computer Science, University of Wisconsin–Madison (1982) B.A. in Mathematics and Economics, University of Virginia (1978) Research Interests: Holliday focuses on enhancing computer science education, particularly in teaching methodologies for programming concepts (e.g., memory diagrams for object-oriented programming), computer systems, and networking. His work includes developing educational tools like interactive animations for network concepts and memory diagram assessments. He also explores performance analysis of parallel architectures and distributed computing. Prior Research Areas: Included grid computing, web services, memory reference traces in parallel systems, and shared memory multiprocessors. His recent projects include the National Storm Surge Database and applications for public access to environmental data. Advising & Grants: While no specific students are listed, Holliday has led curriculum development initiatives and collaborated on projects funded by institutions like the National Oceanic and Atmospheric Administration (NOAA). He has served on the ABET Computing Accreditation Commission since 2023, contributing to accreditation standards. Labs/Teams: His work involves interdisciplinary collaboration, including contributions to the Distributed Systems Group (University of Portsmouth) and the development of the Storm Surge Viewer application.

• Parallel Computing
• System Software
• Computational Biology
• +۳ مورد دیگر

Jaswinder Singh is a Professor of Computer Science, Technology and Societal Change at Princeton University. He is affiliated with the High Meadows Environmental Institute (HMEI) as part of its Grand Challenges Program. His research focuses on parallel computing systems, system software for multiprocessors, and applications in computational biology, particularly protein-structure determination and immune system simulation. He also contributes to HMEI's Public Health and Infectious Disease research area. Affiliations: Professor, Department of Computer Science HMEI Associated Faculty Grand Challenges Program Participant Research Interests: Dr. Singh explores the intersection of high-performance computing and societal challenges. His work on parallel architectures addresses software and hardware design trade-offs, while his computational biology research applies these systems to biomedical problems. Recent efforts include modeling immune responses and protein structures, with implications for infectious disease understanding. Grants & Advising: No specific grants or advising details are provided in the text. Labs/Teams: No lab affiliations explicitly mentioned, though his work aligns with interdisciplinary teams at HMEI and the Computer Science department.

Jed Yangمشاهده پروفایل

دانشیار

• computational complexity
• combinatorics
• decidability
• +۳ مورد دیگر

Jed Yang is an Associate Professor of Mathematics and Computer Science at Bethel University, located in St. Paul, Minnesota. He joined the university in 2018 and is affiliated with the Department of Mathematics & Computer Science within the College of Arts and Sciences. His research focuses on computational complexity, combinatorics, decidability, discrete geometry, and tiling problems. Education: B.S. in Mathematics, California Institute of Technology (2008) Ph.D. in Mathematics, University of California, Los Angeles (UCLA), under advisor Igor Pak (2013) Research Interests: Yang investigates theoretical computer science and discrete mathematics, particularly exploring the boundaries of computationally feasible problems (computational complexity), combinatorial structures, and geometric tiling patterns. His work often intersects graph theory, algorithm design, and formal verification. Teaching: Yang has taught a variety of courses including Introduction to Proofs, Discrete Mathematics, Algorithms and Data Structures, Computability and Complexity, and Programming Languages. Recent courses include MAT 242, COS 341, and COS 100 (Interim 2022). Professional Contributions: His publications span NP-complete problems in planar graphs, undecidability in tiling, and geometric algorithms. He maintains an active research agenda with a focus on interdisciplinary connections between mathematics and computer science.

• Data Analytics
• Information Security
• Computer Science
• +۳ مورد دیگر

Kevin Huggins, Ph.D., CISSP, is a Professor of Computer and Data Science at Harrisburg University of Science and Technology. Previously, he served as a retired military officer in military intelligence with experience in Latin America and as a faculty member and research director at the U.S. Military Academy's Department of Electrical Engineering and Computer Science. He held roles as Director of Research in Network Science and Director of the Information Technology Program. Additionally, he was a visiting scientist at École des Mines de Paris, focusing on parallel algorithms for MPSoC architectures. Education: Ph.D. in Computer Science (Mines ParisTech), M.S. in Computer Science (Naval Postgraduate School), B.S. in Computer Science (U.S. Military Academy). His research focuses on the intersection of data analytics and information security, aiming to enhance computing system security through data-driven approaches. He has contributed to international collaborative research initiatives and served as a program evaluator for ABET. Dr. Huggins has also consulted on computing curriculum development and startup competitions, such as 'launchU.' He received the Fulbright Specialist Program Award and has been actively involved in ABET accreditation processes, including roles as a commissioner and team chair.

Laurent Pautetمشاهده پروفایل

استاد

• Real-Time Systems
• Critical Systems Design
• Embedded Systems
• +۷ مورد دیگر

Laurent Pautet is a Professor at Télécom Paris since 2005 and Head of the Autonomous Critical Embedded Systems (ACES) research team at the Information Processing and Communication Laboratory (LTCI). He holds a PhD in Computer Science from Télécom Paris (1993) and an HDR (2001) from Université Pierre et Marie Curie (UPMC). His research focuses on real-time systems, critical systems design, security, and model-based engineering. He leads the ACES team, which addresses challenges in concurrent systems, scheduling algorithms, and safety-critical applications. His academic background includes a PhD supervised by Dassault Electronics and an HDR emphasizing formal methods and distributed systems. His work spans real-time scheduling (e.g., mixed-criticality systems), embedded software reliability, and intrusion detection systems. He has contributed to tools like the Ocarina AADL tool suite and frameworks such as Flex-eWare for embedded distributed systems. Research interests also include cybersecurity threats to intrusion detection systems (IDS), motion control for autonomous vehicles, and application of mixed-criticality scheduling in AI-driven systems like Monte Carlo Tree Search. He actively supervises internships and theses on topics like renewable energy-aware real-time scheduling and 5G NR in SCADA systems. Pautet’s publications span journals like Journal of Systems Architecture and conferences such as RTSS and IEEE CSR. His work bridges theoretical foundations (e.g., linear programming for scheduling) with practical implementations in domains like aerospace and automotive systems.

Koushik Chakrabortyمشاهده پروفایل

استاد

• Computer Architecture
• Near-Threshold Computing
• Hardware Security
• +۳ مورد دیگر

Koushik Chakraborty is a Professor in Electrical and Computer Engineering at Utah State University. His research focuses on computer architecture, energy-efficient near-threshold computing systems, and hardware security. He holds a PhD from the University of Wisconsin-Madison and has received multiple best paper awards. Research encompasses fault-tolerant architectures, hardware security countermeasures, and machine learning accelerators. Recent work develops timing error-resilient systems for deep learning hardware and security frameworks for neuromorphic computing. His group investigates voltage noise mitigation in network-on-chip designs and process variation-aware GPU architectures. Dr. Chakraborty teaches courses in Computer Architecture, Systems Programming, and VLSI Design. He has mentored over 18 graduate students and received teaching recognition including the 2010 Outstanding Undergraduate Mentor Award.

• Parallel Algorithms & Architectures
• Distributed Systems & Databases
• Multiprocessor Operating Systems
• +۵ مورد دیگر

Vassilios Mamalis is a full Professor at the University of West Attica (UniWA) in the Department of Informatics and Computer Engineering, and an external academic partner at the Hellenic Open University (HOU). He holds a Diploma and Ph.D. in Computer Engineering and Informatics from the University of Patras (1993 and 1998). His career includes over 25 years of academic and research experience, with roles at the Technological Educational Institute of Athens and RACTI. His research focuses on parallel algorithms, distributed systems, wireless sensor networks, cloud computing, and information retrieval. Education: 1988-1993: Diploma in Computer Engineering & Informatics, University of Patras 1994-1998: Ph.D. in Computer Engineering & Informatics, University of Patras Research Interests include: Parallel Algorithms & Architectures Distributed Systems & Databases Wireless Sensor Networks Cloud Computing & IoT Information Retrieval He has authored 15+ journal articles , contributed to 2 books, and participated in numerous EU and Greek government-funded research programs. His teaching spans undergraduate and postgraduate courses in Operating Systems, Parallel Computing, and Distributed Systems. Current doctoral advisees include Vasiliki Giannou and Leontios Sotiriadis. Research contributions include work on energy-efficient WSN clustering, hybrid GPU-CPU parallelization, and cloud task scheduling. He has led projects like the PROSENS and PROTEAS initiatives, and serves on editorial boards and conference committees.

• Real-time Systems
• Operating Systems
• Information Theory
• +۳ مورد دیگر

Dr. Carlos A. Rincon C. is an Instructional Assistant Professor in the Computer Science Department at the University of Houston. His research focuses on real-time systems, operating systems, information theory applications to scheduling, and storage systems. He holds a PhD in Computer Science from the University of Houston and has industry experience in software development prior to his academic career. Current research projects include optimizing probabilistic compression algorithms based on symbol position, developing machine learning models for disk failure prediction in heterogeneous environments, and applying information theory principles to real-time multiprocessor scheduling. His work bridges theoretical computer science with practical system optimization challenges. Dr. Rincon teaches core computer science courses including Operating Systems (COSC 3360) and Introduction to Programming (COSC 1437), with learning objectives centered on foundational concepts in system design, process management, memory management, and object-oriented programming principles. As Director of the ConocoPhillips Computer Science Learning Center, he oversees academic support programs and resources for computer science students. His pedagogical approach emphasizes algorithmic thinking and practical problem-solving skills development.

Jens Frederik Dalsgaard Nielsenمشاهده پروفایل

دانشیار

• Electronics
• Mixed-Criticality Systems
• Airborne Systems
• +۴ مورد دیگر

Jens Frederik Dalsgaard Nielsen is an Associate Professor at the Department of Electronic Systems, Aalborg University, within The Technical Faculty of IT and Design. He leads research in mixed-criticality systems, airborne computing architectures, and aerospace engineering education. His work integrates interdisciplinary collaboration with hands-on project-based learning. Primary affiliations: Automation & Control Group, Green Lab, and Aalborg University Space Center Research focuses on: Mixed-criticality system architectures for aerospace applications Real-time multiprocessor systems and on-chip networks Student satellite projects (e.g., AAUSAT series) Interdisciplinary PBL in engineering education Recent work emphasizes reliable airborne systems and platform architecture designs for aerospace applications. His contributions to CubeSat technologies have been highlighted in international media. Awards: 2025 Novo Nordisk Foundation Prize for Excellence in Technical Science Teaching Active in industry collaborations and international space education initiatives, including leadership roles in the DISCO student satellite program.

Rajeev Baruaمشاهده پروفایل

استاد

• Computer Science
• Cybersecurity
• Parallel Computing
• +۵ مورد دیگر

Rajeev Barua is a Professor of Electrical and Computer Engineering at the University of Maryland, College Park, affiliated with the Institute for Systems Research (ISR) and the Computer Science Department. He holds a Ph.D. from MIT in Electrical Engineering & Computer Science (2000) and a B.Tech. from the Indian Institute of Technology Delhi (1992). His research focuses on compilers, cybersecurity, and parallel computing, with notable contributions to binary rewriting, automatic parallelization, and memory management for embedded systems. He has secured $6.95M in research grants and holds five patents. Barua founded SecondWrite Inc., commercializing cybersecurity software based on his research. He has received awards such as the NSF CAREER Award (2002) and the UMD George Corcoran Teaching Excellence Award (2003). Affiliations: Electrical & Computer Engineering Department, ISR, Computer Science Department Education: Ph.D., MIT (2000); S.M., MIT (1994); B.Tech., IIT Delhi (1992) Research Themes: Binary Rewriting, Cybersecurity, Parallel Programming, Embedded Systems, Compiler Optimization Key Projects: SecondWrite Inc., Raw Architecture chip development (IBM), ICE programming model for parallel computing Grants & Patents: $6.95M in grants, $2.4M in startup funding, five issued patents Teaching: Courses include ENEE 446 (Compilers), ENEE 350H (Embedded Systems), and advanced graduate topics. His work on binary rewriting addresses security and performance optimization, while his parallel computing research advances declarative programming models like ICE. Recent publications emphasize malware detection and efficient multiprogramming on multicore systems. Awards: NSF CAREER Award (2002) UMD George Corcoran Teaching Excellence Award (2003) UMD Jimmy Lin Innovation Award (2014) President of India Gold Medal (1992) Finalist, Inventor of the Year (2005) Labs & Teams: Leads research groups in compiler optimization and cybersecurity at UMD, collaborating with industry partners like IBM and Tilera. SecondWrite’s cybersecurity software has commercial applications in malware mitigation.

Czesław Smutnickiمشاهده پروفایل

استاد

• Manufacturing Systems
• Operations Research
• Optimization
• +۳ مورد دیگر

Prof. Czesław Smutnicki is the Dean and Head of the Department of Computer Engineering at the Faculty of Information and Communication Technology, Wrocław University of Science and Technology. His research focuses on manufacturing systems, operations research, and optimization, with a particular emphasis on scheduling algorithms and metaheuristics. Current Position: Dean, Department of Computer Engineering Institution: Wrocław University of Science and Technology Research Areas: Cyclic scheduling, Lagrangian relaxation, quantum annealing, and multi-criteria optimization Recent publications show a trajectory from classical scheduling (1996-2018) to modern applications involving quantum computing and distributed systems. The articles cluster around three main themes: (1) quantum-enhanced scheduling optimization, (2) Lagrangian relaxation techniques for tardiness minimization, and (3) robust scheduling under uncertainty in multi-vehicle/worker environments. Contact: czeslaw.smutnicki@pwr.edu.pl