جستجوی استاد راهنمای دانشگاهی

• Telecommunications
• Signal Processing
• Wireless Communications
• +۴ مورد دیگر

George Alexandropoulos is an Associate Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on telecommunications, signal processing, and reconfigurable intelligent surfaces (RIS) for next-generation wireless networks. He has contributed to advancements in integrated sensing and communications (ISAC), 6G technologies, and holographic beamforming. His work includes experimental validation of RIS prototypes, optimization of RIS-assisted systems, and analysis of secure communication strategies. Research interests include RIS hardware design, channel modeling, and applications in IoT, UAV communications, and disaster recovery networks. He explores topics like energy-efficient RIS operation, multi-RIS coordination, and RIS-enabled localization. His studies often address challenges at sub-THz frequencies, mutual coupling effects, and hardware impairments. Publications emphasize practical implementations of RIS in both indoor and outdoor settings, with a focus on real-world performance evaluation. Awards and grants are not explicitly mentioned, but his extensive publication record indicates significant academic contributions. His research often integrates machine learning for RIS configuration and reinforcement learning for resource optimization in dynamic networks.

Yuan Hongمشاهده پروفایل

دانشیار

• Security
• Privacy
• Trustworthy Machine Learning
• +۸ مورد دیگر

Dr. Yuan Hong is an Associate Professor and Collins Aerospace Professor at the University of Connecticut's School of Computing, affiliated with the Connecticut Advanced Computing Center (CACC). He previously held an Assistant Professor position at Illinois Institute of Technology. His expertise spans Security, Privacy, and Trustworthy Machine Learning, with a focus on differential privacy, secure computation, adversarial attacks, and robustness in AI systems. He has received notable awards including the NSF CAREER Award and Cisco Research Awards, and his work has been published in top-tier venues like S&P, CCS, NeurIPS, and CVPR. Education: Ph.D. (Rutgers University), M.Sc. (Concordia University), B.Sc. (Beijing Institute of Technology). Research interests include adversarial machine learning, federated learning security, and privacy-preserving techniques. His recent work addresses challenges in machine unlearning, certified defenses, and robust watermarking for graph learning systems. He actively advises students (Ph.D., M.Sc., undergraduate) and leads the DataSec Lab. Current teaching includes Cybersecurity Lab, Computer Security, and Database Organization. Awards include the CCS Distinguished Paper Award (2024) and the Taylor L. Booth Graduate Fellowship for a student. He organizes conferences such as WPES'22 and DBSEC'22, and serves on editorial boards for IEEE Transactions on Dependable and Secure Computing, IEEE Transactions on Information Forensics and Security, and others. Key contributions include frameworks for certified adversarial robustness (e.g., UniCR), differential privacy mechanisms for federated learning, and defenses against poisoning attacks in video and code generation models.

Yidi Wangمشاهده پروفایل

استادیار

• Real-Time Systems
• Embedded Systems
• Cyber-Physical Systems
• +۵ مورد دیگر

Yidi Wang is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University (SCU). She holds a Ph.D. in Electrical and Computer Engineering from the University of California, Riverside (2023), and previously worked as a Postdoctoral Scholar at UCR (2023–2024). Her research focuses on real-time, embedded, and cyber-physical systems, particularly addressing challenges in GPU scheduling, energy efficiency, and batteryless device operation. She teaches courses such as Introduction to Embedded Systems and Operating Systems at SCU. Education: Ph.D. in Electrical and Computer Engineering, UC Riverside (2023) M.S. in Electrical and Computer Engineering, UC Riverside (2019) B.S. in Electrical Engineering, Huazhong University of Science and Technology (2018) Research Interests: Real-time scheduling for GPU-accelerated applications, energy-efficient computing, heterogeneous platforms, and reliable systems for intermittently powered devices. Her work spans system-level implementations and theoretical analysis, including novel scheduling algorithms and mathematical models for performance optimization. Awards: None explicitly listed in the provided texts. Advising & Grants: Currently mentoring 3 students (2 MS, 1 undergraduate) and recruiting PhD/MS candidates. She serves on technical committees for RTSS and RTAS conferences and has reviewed for journals like Transactions on Computers and Real-Time Systems. Labs/Teams: Leads research on GPU scheduling and batteryless systems, collaborating with industry and academic partners.

Peter Lewisمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Socio-Technical Systems
• Self-Awareness
• +۷ مورد دیگر

Peter Lewis is an Associate Dean (Research and Graduate Studies) and Associate Professor at Ontario Tech University's Faculty of Business and Information Technology, holding a Canada Research Chair in Trustworthy Artificial Intelligence. He specializes in socio-technical systems, self-aware computing, and AI ethics. His work bridges foundational AI research with practical applications in industry, emphasizing trust, collective action, and socially intelligent systems. Education PhD in Computer Science, University of Birmingham, UK MSc in Natural Computation, University of Birmingham, UK BSc in Computer Science, University of Leicester, UK PGCert in Learning and Teaching Higher Education, Aston University, UK Research Interests His research focuses on trustworthy AI, self-aware systems, and the societal implications of AI. Key areas include explainable AI for accessibility, ethical AI governance, and modeling social institutions. He co-edited Self-Aware Computing Systems and serves on editorial boards for IEEE journals. Publications & Awards Over 75 peer-reviewed papers in journals/conferences Winner of the 2020 Aston Achievement Award for Business Engagement Best Paper Award at IEEE SASO 2018 Labs & Collaborations He leads research in the Business Analytics & AI group, collaborating on projects with industry partners. His work addresses real-world challenges in AI ethics, sustainability, and human-AI collaboration.

Adel Abusittaمشاهده پروفایل

استادیار

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Adel Abusitta is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he conducts research at the intersection of artificial intelligence and cybersecurity. With expertise in secure and resilient AI systems, IoT security, and malware analysis, Dr. Abusitta has established himself as a significant contributor to the field of AI-powered cybersecurity solutions. Education: PhD in Computer Engineering from Polytechnique Montréal Postdoctoral Fellow at University of Montréal Postdoctoral Fellow at McGill University Dr. Abusitta's research focuses on developing secure and trustworthy artificial intelligence systems with applications in cybersecurity. His work spans several critical areas including explainable AI for security applications, AI-powered malware analysis, intrusion detection systems, and IoT security. He has made significant contributions to the understanding of how AI can be both secured against attacks and used to enhance security systems. His research addresses the dual challenge of making AI systems resilient to adversarial manipulation while leveraging AI's capabilities to detect and prevent cyber threats in complex environments like cloud computing and IoT networks. Analysis of Dr. Abusitta's recent publications reveals a strong focus on the intersection of AI and cybersecurity, particularly in developing robust anomaly detection systems, explainable security solutions, and resilient architectures for IoT environments. His work demonstrates a consistent trajectory toward making AI systems both more secure and more useful for security applications, with increasing emphasis on practical implementations that can withstand real-world challenges. Dr. Abusitta has collaborated extensively with Defence Research and Development Canada (DRDC) on projects related to AI-powered data analytics for discerning malware intent. He has also worked with industrial partners through the Institute for Data Valorization (IVADO) to develop privacy-preserving machine learning techniques that maintain accuracy while protecting sensitive information. His research has practical applications in critical infrastructure protection and secure AI deployment.

• Synthetic Biology
• Chemical Engineering
• Biomedical Engineering
• +۹ مورد دیگر

Dr. Francesca Ceroni is a Senior Lecturer in the Department of Chemical Engineering at Imperial College London, part of the Faculty of Engineering. She holds affiliations with the Centre for Synthetic Biology, the CRUK Convergence Science Centre, and the UKRI Artificial Intelligence for Engineering Biology Consortium, among others. Her research focuses on synthetic biology, host-aware cell engineering, and the integration of computational biology with AI for synthetic design. She has developed tools to mitigate cellular burden in engineered systems and pioneered work on synthetic cells for therapeutic applications. Dr. Ceroni earned her BSc, MRes, and PhD in Bioengineering from the University of Bologna. Her postdoctoral training included a Visiting Research Fellowship at Harvard Medical School and roles at Imperial College London, where she became a Junior Research Fellow in 2016. Her work bridges engineering principles with biological systems, emphasizing ethical and biosecurity considerations in synthetic biology. Her research spans six core areas: host-aware engineering of mammalian and bacterial cells, computational biology/AI-driven design, engineered synthetic cells, gene expression control, and biosecurity governance. Key contributions include identifying resource competition in engineered cells and developing non-invasive assays for cell growth characterization. Her team collaborates with industry partners like AZ and Bayer to translate findings into biomedical applications. Education: BSc in Pharmaceutical Biotechnologies, University of Bologna (2001–2004) MRes in Bioengineering, University of Bologna (2004–2007) PhD in Bioengineering, University of Bologna (2008–2011) Dr. Ceroni has been recognized with the 2016 Junior Research Fellowship from Imperial College London. Her work is published in high-impact journals like Nature Communications , Nature Reviews Bioengineering , and Science , with a focus on advancing synthetic biology’s technical and ethical dimensions.

• Wireless Communication
• Network Optimization
• Machine Learning
• +۳ مورد دیگر

Athanasios Gkelias is a Research Fellow in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. His research focuses on advanced wireless communication systems, network optimization, machine learning applications, and quantum computing methodologies. He contributes to interdisciplinary projects involving IoT coalitions, adversarial signal detection, and cognitive behavior analysis. Key research areas include: (1) Network resource management in Software-Defined Networks (SDN), (2) Localization systems for indoor environments, (3) 3D reconstruction using photometric stereo and origami-based modeling, and (4) distributed optimization frameworks for ad-hoc networks. His recent work explores quantum approaches to combinatorial optimization and self-supervised learning methods. Publications span 20+ years with notable contributions in network coding, vehicular ad-hoc networks (VANETs), and cross-layer design for wireless mesh networks. His work emphasizes practical implementations through frameworks like iVisher for caller ID spoofing detection and cooperative MAC protocols for multi-antenna systems. No scientific awards are listed in the provided information. His research has been applied in healthcare technology through emotion understanding systems for Alzheimer’s patients and in battlefield communication through IoBT coalitions. Active participation in Imperial College's Engineering faculty reflects his commitment to advancing telecommunications and network science.

Rahul Sharmaمشاهده پروفایل

دانشیار

• Control Systems
• Renewable Energy
• Power Systems
• +۵ مورد دیگر

Associate Professor Rahul Sharma is affiliated with the School of Electrical Engineering and Computer Science at The University of Queensland (UQ), within the Faculty of Engineering, Architecture and Information Technology. His primary research focuses on control systems applications, particularly in solar farm fault detection, grid-connected inverter control, and demand side management. His work emphasizes system modeling, control development, and model-based fault diagnosis, with significant industrial relevance in renewable energy and smart grid technologies. Research Interests: - Solar farm fault detection and diagnosis via control theory to identify underperforming panels. - Advanced control methods for grid-connected inverters to enhance power quality and stability. - Demand side management through novel control algorithms for distributed energy resources. His experimental work includes field trials at Gatton Solar Farm and collaborations with industry partners. Articles Trends: Recent publications emphasize network-aware control of distributed energy resources, dynamic operating envelopes for demand response, and smart grid optimization. Key themes include low-voltage distribution networks, prosumer P2P trading, and fault diagnosis in power systems. Advising & Labs: He supervises prospective PhD students in control systems and renewable energy. Experimental setups at UQ and field trials at Gatton Solar Farm support his research on fault detection and grid systems.

Orran Kriegerمشاهده پروفایل

استاد

• Cloud Computing
• Operating Systems
• Virtualization
• +۳ مورد دیگر

Orran Krieger is a Professor in the Department of Electrical and Computer Engineering at Boston University. He serves as the Founding Director of the Cloud Computing Initiative (CCI) and Resident Fellow of the Hariri Institute for Computing and Computational Science & Engineering. His work focuses on cloud computing infrastructure, operating systems, and virtualization technologies. Prior roles include leading the Advanced Operating System Research Department at IBM T.J. Watson and contributing to VMware's vCloud initiatives. Education: PhD and MASc in Electrical Engineering from the University of Toronto. Research interests include cloud resource management, unikernel-based systems, security in distributed environments, and performance optimization. His leadership in the Massachusetts Open Cloud project and Open Cloud Testbed (OCT) demonstrates expertise in scalable cloud platforms. Key contributions span innovations in OS design (e.g., EbbRT framework), cloud marketplace architectures, and hardware-as-a-service models. His research bridges theoretical advancements with practical implementations in modern data centers.

• High-Performance Computing
• Parallel Programming
• Computer Architecture
• +۳ مورد دیگر

Prof. Dr. rer. nat. Matthias S. Müller is a Universitätsprofessor and Director of the IT Center at RWTH Aachen University. His research focuses on High-Performance Computing (HPC), parallel programming models, correctness verification, energy-aware computing, and tools for distributed systems. He leads the High-Performance Computing group, contributing to advancements in HPC resource management, runtime systems, and sustainable computing practices. Key areas of expertise include MPI and OpenMP correctness checking, static and dynamic analysis techniques, performance optimization for heterogeneous architectures, and energy footprint modeling. Müller has extensively collaborated on projects like MUST (MPI correctness tool), OMPT tools, and frameworks for analyzing hybrid parallel applications. His work bridges theoretical computer science with practical implementation challenges in large-scale computing environments. Notable contributions include developing methods for data race detection in Remote Memory Access (RMA) programs, latency-aware power management models, and educational frameworks for HPC lab courses. His research often emphasizes tool development, runtime systems, and interdisciplinary applications of HPC across engineering domains. Müller's lab is part of RWTH Aachen's IT Center, which provides infrastructure and expertise for computational research. He actively publishes in top-tier conferences and journals, addressing challenges in parallel programming, energy efficiency, and distributed computing systems.

Young Leeمشاهده پروفایل

مدرس ارشد

• Edge Computing
• Blockchain Technology
• Fog Computing
• +۳ مورد دیگر

Young Lee is a Senior Lecturer in Computing at Macquarie University, affiliated with the School of Computing and three research centers: Data Horizons Research Centre, Future Communications Research Centre, and Smart Green Cities Research Centre. His research focuses on edge computing, blockchain technology, fog computing, and resource scheduling in distributed systems, with a strong emphasis on applications in IoT, healthcare, and sustainability. He has led or contributed to over 150 research outputs since 2005, including influential works on edge-based video analytics, blockchain frameworks, and cloud-edge resource optimization. Dr. Lee's projects include 'Extreme-Scale Computing for Big Data Analytics' (2016–present) and 'Synergising the Power of the Cloud with the Power of the Crowd' (2016–present), demonstrating expertise in scalable computing and cloud-crowd integration. His work bridges theoretical advancements in scheduling algorithms with practical implementations in energy-efficient data centers and mobile edge environments. Research interests span edge computing architectures, blockchain oracles, and fog caching strategies, with recent contributions to carbon-conscious travel systems and malware detection frameworks. His interdisciplinary approach addresses challenges in resource allocation, network security, and distributed system efficiency.

Timo Hönigمشاهده پروفایل

استاد

• Operating Systems
• System Software
• Energy-Aware Computing Systems
• +۳ مورد دیگر

Prof. Timo Hönig is a Professor leading the Bochum Operating Systems and System Software (BOSS) Research Group at Ruhr-Universität Bochum (RUB). Previously, he served as an Assistant Professor at Friedrich-Alexander-University Erlangen-Nürnberg (FAU), where he was part of Department of Computer Science 4. His research focuses on Energy-Aware Computing Systems, Operating Systems, and System Software design with applications in embedded and real-time systems. Key research projects include the DFG Collaborative Research Center/TR 89 (Invasive Computing) and the DFG SPP 1914 (Latency- and Resilience-Aware Networking). He has received notable awards such as the SOSP SRC Gold Medal (2019) and the ISORC Best Paper Award (2017). He actively contributes to conferences like ACM EuroSys and USENIX ATC, and has led initiatives like the Albatross runtime system for energy-efficient HPC clusters. Teaching includes courses on Energy-Aware Computing and Operating Systems Technology. His work bridges theoretical system software design with practical applications in energy efficiency and heterogeneous architectures. The BOSS group explores future system software challenges for many-core and NVM-based systems.

Daniel Mosseمشاهده پروفایل

استاد

• Computer Architecture
• Computer Systems
• Cyber-Physical Systems
• +۸ مورد دیگر

Dr. Daniel Mosse is a Professor in the Department of Computer Science at the University of Pittsburgh. He holds a PhD from the University of Maryland, College Park, and has been a faculty member since 1993. His research focuses on distributed systems, real-time systems, power management, security, and fault tolerance, bridging operating systems and networking research. He has held leadership roles, including Chair of the Department of Computer Science since 2009 and Visiting Professorships in Brazil. His work spans grants totaling millions, addressing energy-efficient computing, secure infrastructure, and embedded systems. Education: PhD (1993), MS (1990), and BS (1985) in Mathematics and Computer Science. Research interests include distributed real-time systems, multicore systems, embedded systems, and wireless networks. Notable awards include the 2007 Provost's Innovation in Education Award and the 2006 Bellet Teaching Award. Key grants include NSF-funded projects on energy-efficient data centers, secure emergency management systems, and power-aware scheduling. He advises numerous students and teaches courses on operating systems and distributed systems. His contributions to real-time systems, fault tolerance, and energy management have been recognized through over 150 publications and international collaborations.

Bingyao Liمشاهده پروفایل

استادیار

• Computer Architecture
• High-Performance Computing
• Multi-GPU Systems
• +۴ مورد دیگر

Bingyao Li is an incoming tenure-track Assistant Professor at the University of California, Riverside's Computer Science and Engineering Department, starting Fall 2025. She is currently a fourth-year Ph.D. student at the University of Pittsburgh, advised by Dr. Xulong Tang. Her research focuses on computer architecture, particularly multi-GPU systems, virtual memory management, and address translation for high-performance computing. Educational Background: She holds a B.E. (2017) and M.S. (2020) from Tianjin University's College of Intelligence and Computing. Her Ph.D. work at Pitt emphasizes GPU architecture and system-level optimizations for large-scale applications. Research Interests: Her work spans advanced computer architectures, multi-GPU optimization, and parallel computing systems. She explores solutions like object-aware page management (OASIS), TLB enhancements (STAR), and dynamic page placement (GRIT) to improve multi-GPU performance. She also investigates system-level optimizations for large language models and GPU ecosystems from hardware to applications. Awards: She has received the CS50 Outstanding Research Fellowship (2022, 2023) and the SCI Fellowship from the University of Pittsburgh. Her contributions include internships at NVIDIA's Architecture Research Group and talks on multi-GPU computing at NVIDIA and Tianjin University. Future Work: As a faculty member, she plans to mentor PhD students in Winter/Spring/Fall 2026, focusing on next-generation GPU systems and high-performance computing challenges. Her lab will address scalability, efficiency, and emerging applications in parallel computing.

Srinivas Shakkottaiمشاهده پروفایل

استاد

• Networking
• Wireless Networks
• Reinforcement Learning
• +۶ مورد دیگر

Srinivas Shakkottai is a Professor in the Department of Electrical and Computer Engineering (ECE) and affiliated faculty in the Department of Computer Science and Engineering (CSE) at Texas A&M University. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (2007), followed by a postdoctoral stint at Stanford University. Since 2008, he has been at Texas A&M, advancing through roles from Assistant to Associate Professor before attaining full Professor status. Education: Ph.D., Electrical Engineering, University of Illinois at Urbana-Champaign (2007) Postdoctoral Associate, Stanford University Research Interests: Focus on algorithms for communication, energy, and transportation networks. Key areas include wireless networks, reinforcement learning, caching/content distribution, multi-agent learning, game theory, networked markets, and systems design. He co-directs the LENS Laboratory and the Texas A&M Initiative on Connected Intelligence (TICI). Key Awards: NSF CAREER Award (2012) Google Faculty Research Award (2010) Defense Threat Reduction Agency Young Investigator Award (2009) Grants & Labs: Leads research projects funded by NSF, including collaborative efforts on EdgeRIC (NextG cellular networks) and Caching systems. Active in labs focused on AI-driven network optimization and intelligent control systems. Lab & Teams: Co-director of LENS Lab and TICI, emphasizing real-time intelligent control, edge computing, and networked intelligence.