جست‌وجوی استاد و پژوهشگر

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.

Zhenlin Wangمشاهده پروفایل

استاد

• Compilers
• Operating Systems
• Computer Architecture
• +۹ مورد دیگر

Zhenlin Wang is a Professor and Chair of the Department of Computer Science at Michigan Technological University's College of Computing. He earned a BS (1992) and MS (1995) from Peking University, and a PhD in Computer Science from the University of Massachusetts, Amherst (2003). He joined Michigan Tech in 2003 as an assistant professor, became associate professor in 2009, and full professor in 2015. University: Michigan Technological University School: College of Computing Department: Computer Science Academic Rank: Professor His research bridges compilers, operating systems, and computer architecture , with core focus on memory system optimization and virtualization. Key research areas include: Memory hierarchy optimization Cache replacement modeling GPU programming and architecture Virtualization and cloud computing Datacenter resource management Heterogeneous memory systems Recent publications analyze GPU speculation (GSpecPal), hardware-assisted virtualization (Accelerating Address Translation), and graph neural network-based memory inefficiency detection (GRAPHSPY). His work often integrates compiler analysis with hardware insights for performance improvements. Scientific Awards NSF CAREER Award 0643664 (2007-2012) NSF SaTC2225424 (2022-2025) Best Paper Award at ICS’23 (FLORIA paper) He has advised numerous PhD and MS students in memory systems, virtualization, and distributed computing. Current advisees include Shiwei Ding (PhD candidate) and Junyao Yang (PhD candidate).

Andrew Nereمشاهده پروفایل

استادیار

• Machine Learning
• Computer Architecture
• Embedded Systems
• +۳ مورد دیگر

Andrew Nere serves as Assistant Professor of Computer Science in the Math & Computer Science Department at Western Colorado University, teaching courses including Introduction to Web Design, Computer Science I, and Software Entrepreneurship since joining the faculty in Fall 2022. His industry background includes co-founding Thalchemy (2013), a startup specializing in embedded machine learning for wearable and environmental sensor applications, alongside prior internships at IBM and Qualcomm. His educational credentials feature: PhD in Electrical Engineering from University of Wisconsin-Madison (2013) MS in Electrical Engineering from University of Wisconsin-Madison (2010) B.S. in Computer Engineering from St. Cloud State University (2007) Nere's research centers on hardware-software co-design for efficient AI deployment, with dual focus on neuromorphic computing architectures and practical embedded systems implementation. He bridges theoretical neuroscience with engineering solutions, particularly for resource-constrained environments like fitness trackers and environmental sensors where computational efficiency is paramount. His work emphasizes translating academic research into real-world applications rather than pure theoretical exploration. Analysis of his 2010-2013 publications reveals consistent innovation in brain-inspired computing hardware, with recurring themes of GPU-accelerated neural simulations, specialized cache architectures for AI workloads, and energy-efficient neuromorphic designs. The research demonstrates strong interdisciplinary collaboration across computer architecture, neuroscience, and machine learning communities, frequently targeting hardware acceleration for cognitive computing tasks. Scientific recognition includes: Best Paper Nomination at IEEE International Symposium on Workload Characterization (2012) Best Paper in Track at International Parallel and Distributed Processing Symposium (2011) Nere brings substantial industry experience to academia, having served as university collaborator on the DARPA/IBM SyNAPSE project modeling brain functionality in computing systems. His startup Thalchemy exemplifies his commitment to applied research translation, while his current Software Entrepreneurship course provides students with practical business development frameworks for technology ventures. He actively leverages Gunnison Valley's natural environment for both recreation and potential research applications, noting particular interest in environmental sensing opportunities afforded by the region's wilderness proximity and diverse ecosystems.

Resit Sendagمشاهده پروفایل

استاد

• Computer Architecture
• Processor Architecture
• Multicore Processors
• +۱۰ مورد دیگر

Resit Sendag is a Professor and Director of Graduate Studies in the Department of Electrical, Computer and Biomedical Engineering at the University of Rhode Island. He serves as Director of both the URI Computer Architecture Laboratory and the URI Generative AI Development Group, leading cutting-edge research in computer architecture and high-performance computing. His academic credentials include: Ph.D. in Computer Engineering from the University of Minnesota (2003) B.Sc. in Electrical Engineering from Hacettepe University, Ankara (1994) Professor Sendag specializes in computer architecture with research interests spanning processor design, memory systems, parallel computing, and hardware acceleration. His work focuses on improving computational performance through innovative techniques in cache management, prefetching, branch prediction, and specialized hardware implementations using FPGAs and GPUs. Recent research has expanded into applying these architectural principles to solve complex optimization problems like vehicle routing. His publication record demonstrates a consistent evolution from fundamental computer architecture research toward practical applications of architectural techniques. The most recent work shows strong emphasis on implementing genetic algorithms for vehicle routing problems using specialized hardware platforms (FPGAs and GPUs), while maintaining his foundational research on memory access optimization through sophisticated prefetching techniques. Professor Sendag has secured research funding from the Office of Naval Research through collaborative projects with the University of Connecticut focused on advanced manufacturing, shipbuilding processes, and material tracking systems. He actively mentors graduate students, with current advisees working on challenging computer architecture projects. His former students have achieved notable success at leading technology institutions including ETH-Zurich, Intel, NVIDIA, AMD, and various research laboratories. Professor Sendag leads key research initiatives including the URI Computer Architecture Laboratory, the Generative AI Development Group, and the PatternFinder project (an NSF-funded open-source tool for program behavior analysis).

Vincent Weaverمشاهده پروفایل

دانشیار

• Hardware Performance Counters
• Computer Architecture
• High Performance Computing
• +۸ مورد دیگر

Vincent Weaver is an Associate Professor in the Electrical and Computer Engineering Department at the University of Maine's College of Engineering. He leads the VMW Research Group, focusing on low-level systems research including hardware performance counters, computer architecture, and operating systems. Weaver received his BS in Electrical Engineering from the University of Maryland College Park in December 2000, followed by MS (January 2009) and PhD (May 2010) degrees in Electrical and Computer Engineering from Cornell University. He joined the University of Maine faculty in July 2012 as an Assistant Professor and earned tenure and promotion to Associate Professor in September 2018. His research centers on hardware performance analysis, architectural simulation, and systems programming with emphasis on Linux kernel development and embedded systems. Weaver's work bridges theoretical computer architecture with practical systems implementation, often resulting in open-source tools that advance the field. His publications reveal a consistent focus on performance analysis techniques, code optimization, and security through low-level system understanding. Weaver maintains an active teaching schedule including courses in embedded systems, operating systems, and network engineering. He values students with strong programming skills and encourages open source contributions as part of the learning process. His research group provides hands-on experience with cutting-edge processor architectures and performance analysis tools.

• High Performance Computing
• Distributed Systems
• Deep Learning
• +۴ مورد دیگر

Muhammad Mustafa Rafique is an Associate Professor in the Department of Computer Science at Rochester Institute of Technology's Golisano College of Computing and Information Sciences. His research specializes in optimizing large-scale computing systems, with focus areas including: High-performance computing (HPC) resource management Distributed deep learning acceleration Fault-tolerant cloud architectures GPU-accelerated checkpointing systems Serverless computing frameworks Dr. Rafique's work demonstrates consistent innovation in improving computational efficiency for containerized HPC workflows, multi-GPU scheduling, memory optimization, and distributed training pipelines. His publications frequently appear in premier IEEE/ACM conferences, reflecting contributions to systems performance engineering. While no awards or student advisees are mentioned in available materials, his research collaborations include co-authors from institutions worldwide, indicating active engagement in the high-performance computing research community. Current work explores emerging memory technologies like CXL and advanced containerization techniques for next-generation datacenters.