جستجوی استاد راهنمای دانشگاهی

• Performance Analysis and Engineering
• Energy Efficient Computing
• Parallel and Distributed Computer Architectures
• +۷ مورد دیگر

Vladimir Getov is a Professor at the University of Westminster with extensive international affiliations including Honorary Professor at Technical University of Sofia and Visiting Lab Fellow at Pacific Northwest National Laboratory. His leadership roles span the IEEE Computer Society (Governor since 2015), CoreGRID/ERCIM Working Group (Topic Leader 2009-2015), and multiple editorial positions including Area Editor for High Performance Computing at IEEE Computer. His research centers on Performance Analysis and Engineering, Energy Efficient Computing, and Parallel and Distributed Architectures with significant contributions to cloud computing, wireless sensor networks, and component-oriented design. Recent work focuses on energy-drain attack prevention in MAC protocols and application-specific thermal modeling for multi-core processors. Key awards include the Bulgarian National Scientific Award 'Pythagoras' (2009), IEEE Computer Society Certificates of Appreciation (2008, 2010), and CoreGRID Outstanding Contribution Award (2008). His publication record spans 35+ years with over 100 papers including the 2024 IEEE ICAI conference paper on electronic digital computing history. As leader of the Distributed and Intelligent Systems Research Group since 1996, he has supervised 7 PhD students to completion with frameworks like AGOCS cloud simulator and TunableMAC protocol. His EU project leadership includes CoreGRID (2004-2009) and GridCOMP (2006-2010), securing sustained research funding including Daiwa Foundation support (2017) for low-energy co-design methodology.

Sathish Kumarمشاهده پروفایل

دانشیار

• Cybersecurity
• Machine Learning
• Distributed Systems
• +۶ مورد دیگر

Sathish Kumar is an Associate Professor in the Department of Electrical Engineering and Computer Science at Cleveland State University's Washkewicz College of Engineering. He serves as Director of the Intelligent Secure Cyber-Systems Analytics and Applications Research (ISCAR) Lab and holds editorial positions with PLOS One, IEEE Access, and Nature Scientific Reports. With over a decade of industry experience prior to joining academia in 2013, Dr. Kumar has established himself as a prominent researcher in cybersecurity and emerging technologies. Dr. Kumar's research spans Cybersecurity, Machine Learning, Distributed Systems, and Quantum Computing, with applications in Intelligent Cyber Physical Social Systems, Smart Cities, Blockchain, Disaster Resilience, and Health Informatics. His work demonstrates a consistent focus on practical security solutions for emerging technologies, particularly in IoT and IIOT environments. Recent publications show increasing emphasis on quantum machine learning applications and reinforcement learning approaches to security challenges. His research program has attracted significant funding, including multiple NSF grants as PI and Co-PI, CDC and NIH funding for public health applications, and industry partnerships. Dr. Kumar has published over 80 technical papers and co-edited a book on IoT security challenges. His editorial roles with major journals reflect his standing in the research community. National Science Foundation Grant ($799,985) as PI for quantum sensor research (2022-2025) National Science Foundation Grant ($434,431) as Co-PI for HPC infrastructure (2022-2025) Multiple additional NSF, CDC, and industry-funded projects Dr. Kumar actively mentors students at all levels, currently supervising multiple PhD students, postdoctoral researchers, and undergraduate honors students. His lab provides opportunities for students to engage in cutting-edge research with practical applications in cybersecurity and emerging technologies, supported by substantial external funding that ensures resources for student participation.

• 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.