جستجوی استاد راهنمای دانشگاهی

Marios Kogiasمشاهده پروفایل

استادیار

• Operating Systems
• Networking
• Distributed Systems
• +۴ مورد دیگر

Marios Kogias is an Assistant Professor in the Department of Computing at Imperial College London, conducting research at the intersection of operating systems, networking, and distributed systems with a focus on tail-tolerance, fault-tolerance, and confidentiality using emerging datacenter hardware. He holds a PhD in Computer Science from EPFL (2020) supervised by Ed Bugnion, where his thesis won the Dennis M. Ritchie Award and received an Honourable Mention for the Eurosys Roger Needham PhD Award. His undergraduate degree in Electrical and Computer Engineering is from NTUA. His research spans operating systems, networking, distributed systems, cloud computing, and confidential computing, with significant contributions to microsecond-scale computing, serverless architectures, and eBPF applications. Current work emphasizes tail-latency optimization in datacenter environments and confidential computing security. Recent publications reveal strong trends in microsecond-scale systems, confidential computing, and serverless workflows, demonstrating expertise in leveraging hardware innovations for performance and security guarantees across distributed environments. His scientific awards include: Dennis M. Ritchie Award (2021) Honourable Mention for the Eurosys Roger Needham PhD Award (2021) IBM Fellowship Microsoft Swiss JRC Fellowship Distinguished Artifact Award (ASPLOS 2021) Best Student Paper Award (Eurosys 2020) Dr. Kogias actively mentors PhD students including Konstantinos Prasopoulos (co-advised with Ed Bugnion), Scofield Liu, Farzad Mohammadi, and Adel Sefiane. He teaches Networked Systems, Computer Networks and Distributed Systems, and Object-Oriented Design at Imperial, supported by fellowships from IBM and Microsoft during his doctoral research. His collaborative work spans EPFL, Microsoft Research Cambridge, and Imperial College London, focusing on systems architecture for next-generation datacenter applications.

Nico Christiansonمشاهده پروفایل

پژوهشگر ارشد

• Algorithms
• Machine Learning
• Optimization
• +۴ مورد دیگر

Nico Christianson is a Stanford Energy Postdoctoral Fellow at Stanford University, hosted by Ellen Vitercik and Ram Rajagopal. In Fall 2026, he will join Johns Hopkins University as an Assistant Professor of Computer Science and a member of the Data Science and AI Institute and the Ralph O’Connor Sustainable Energy Institute. His research bridges algorithms, machine learning, and optimization to create reliable systems for decision-making under uncertainty, with applications in energy and datacenters. PhD in Computing and Mathematical Sciences, Caltech BSc in Applied Mathematics, Harvard Research focuses on online algorithms, learning-augmented systems, uncertainty quantification, risk-aware optimization, and sustainable energy applications. His work integrates theoretical rigor with practical deployment, addressing challenges in energy efficiency and grid stability. Recent publications highlight algorithmic innovation for energy systems, including robust scheduling, adaptive bitrate control, and uncertainty-quantified calibration. He actively recruits PhD students and postdocs for his future group at Johns Hopkins. NSF Graduate Research Fellowship PIMCO Data Science Fellowship Ben P.C. Chou Doctoral Prize in Information Science and Technology Demetriades-Tsafka-Kokkalis Prize in Renewable Energy

Feng Wangمشاهده پروفایل

استادیار

• Next Generation Internet
• Network Performance Measurement
• Big Data Verification
• +۶ مورد دیگر

Dr. Feng Wang is an Assistant Professor in the School of Engineering at Liberty University, specializing in network reliability, interdomain routing, and software-defined networking. His research addresses challenges in next-generation internet architectures, network performance measurement, and secure IoT device management. Education: B.E. in Electrical and Computer Engineering from Zhejiang University (China) M.S. in Electrical and Computer Engineering from Yanshan University (China) Ph.D. in Electrical and Computer Engineering from the University of Massachusetts, Amherst Research focuses on: - Detecting transient routing failures and improving network performance through real-time diagnostic systems (e.g., collaboration with AT&T). - Designing scalable addressing schemes for IoT and wireless sensor networks. - Developing intrusion detection systems (e.g., MOCA framework) and network anomaly mitigation techniques. His publications (2015-2023) emphasize network security, routing protocol optimization, and scalable internet architectures. Notable work includes BGP rerouting solutions, real-time routing failure diagnosis, and variable-length addressing for 6LoWPAN. No scientific awards were explicitly listed in the provided texts. Collaborations include Agilent, AT&T, and Intel, focusing on practical network reliability and security solutions. Dr. Wang has advised no listed students or managed grants in the provided texts. His research extends to lab implementations of lightweight routers (SoC-based) and stability-aware protocols for RPL networks.

• Computer networks and communications
• Cybersecurity
• Industry 4.0
• +۷ مورد دیگر

Guido Marchetto is a Full Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino , where he conducts cutting-edge research in computer networks, cybersecurity, machine learning, and Industry 4.0. He is a member of the NETGROUP - Computer Networks Group , the SmartData@PoliTO interdepartmental center, and leads research at ACS LAB and LABINF . He serves as Deputy Coordinator of the Doctoral College in Computer and Systems Engineering and is the Scientific Advisor for the European Technology Platform for High Performance Computing (ETP4HPC). PhD Students: Federico Rinaudi, Doriana Monaco, Antonino Angi Research Groups: NETGROUP, SmartData@PoliTO Labs: ACS LAB, LABINF His research focuses on intelligent network management, explainable AI for networking, reinforcement learning, federated learning, and softwarized networks. He has led multiple EU and commercial research projects such as MIRANDA and DESIRE , with applications in cybersecurity, edge computing, and digital twins. Marchetto’s recent publications reveal a strong trend toward integrating AI/ML techniques—especially reinforcement learning and language models—into network automation, traffic engineering, and IoT systems. His work bridges theoretical innovation with practical implementation in cloud, edge, and telco environments. Scientific Awards: Best Paper Award Finalist, IEEE HPSR (2014) Best Paper Award, IEEE ICC (2007) He is a Senior Member of IEEE and serves on the editorial board of IEEE Transactions on Vehicular Technology . He has also been a Contract Professor at the Turin Polytechnic University in Tashkent from 2012 to 2022. His extensive grant leadership includes EU Horizon projects and numerous commercial research contracts with a focus on network intelligence and automation. He is actively involved in doctoral education and curriculum development, contributing to multiple degree programs and supervising ongoing PhD research in AI-driven networking and cybersecurity.

E. A. Valentijnمشاهده پروفایل

استاد

• Astronomy
• Astrophysics
• Cosmology
• +۴ مورد دیگر

E. A. Valentijn is a Professor at the University of Groningen's Faculty of Science and Engineering, Department of Astronomy. He coordinates the Target project as chair of its steering committee and leads OmegaCEN, a National datacenter for wide-field astronomical imaging funded by the Netherlands Research School for Astronomy (NOVA). At OmegaCEN, he oversees approximately 17 staff and PhD researchers focused on developing advanced data processing systems for large astronomical datasets. Valentijn also serves as the National Project Manager for the Euclid mission since 2013 and holds membership in the Scientific Technical Council of SURF. Research Focus Valentijn's research integrates astronomy, astrophysics, and data science with specialized focus on: Galaxy clusters and dark matter cosmology Wide-field astronomical imaging systems Large-scale data processing methodologies Machine learning applications in astronomy Euclid mission scientific objectives His work contributes to UN Sustainable Development Goals through scientific innovation. Publications Overview His recent publications (2025) predominantly focus on Euclid mission data analysis, featuring gravitational lens detection using convolutional neural networks, galaxy cluster dynamics, and multi-wavelength catalog development. These works demonstrate strong emphasis on machine learning applications in astronomical data processing and survey science. Leadership and Initiatives Valentijn founded and directs multiple scientific organizations including OmegaCEN (2002), Astro-WISE (2001), Target (2008), and the Infoversum Foundation (2012). His team at OmegaCEN includes 17 researchers and PhD students working on astronomical data infrastructure.

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).

• Operating systems
• Distributed systems
• Computer Science
• +۳ مورد دیگر

Professor Willy Zwaenepoel is a distinguished academic and Dean of the Faculty of Engineering at the University of Sydney. He holds Fellowships from ACM, IEEE, and ATSE. His research focuses on distributed systems, operating systems, and experimental computer science. Previously, he spent two decades at Rice University and nine years as Dean of EPFL's School of Computer and Communication Sciences before joining Sydney in 2018. Education: BS/MS, Ghent University (1979) MS/PhD, Stanford University (1980/1984) Research Interests: His work emphasizes distributed systems and operating systems, with contributions to key-value stores, transactional systems, and large-scale graph processing. Recent projects include optimizing geo-replicated systems and improving datacenter scheduling efficiency. Articles Trends: Recent publications address OS scheduling (Nest), distributed graph mining (Tesseract), and transactional systems' performance limits. He explores hardware-software co-design for multicore systems and energy-efficient data centers. Awards: Fellow of ACM (2021) Fellow of IEEE (2020) Fellow of ATSE (2019) Grants & Advising: Active grants include adaptive key-value store research (2021) and large-graph processing systems (2018). He advises PhD students and postdocs on distributed systems and storage challenges. Labs/Teams: Leads the Sydney systems research group focusing on scalable distributed systems and cloud infrastructure.

Tianyin Xuمشاهده پروفایل

استادیار

• Programming Languages
• Formal Methods
• Software Engineering
• +۳ مورد دیگر

Tianyin Xu is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), with a courtesy appointment in the Department of Electrical and Computer Engineering (ECE). His research focuses on ensuring reliability and security in large-scale cloud and datacenter systems, with particular emphasis on configuration management, system verification, and distributed system resilience. He has held positions including a year at Facebook's Core Systems and completed his PhD at the University of California San Diego. Dr. Xu teaches courses such as CS 598(XU) on Cloud-Scale System Reliability, CS 523 (Advanced Operating Systems), and CS 423 (Operating Systems Design). He actively contributes to academic communities through roles like co-editing the SIGOPS Blog, serving on program committees for conferences like NSDI, OSDI, and EuroSys, and organizing the UIUC Systems Research Seminar. His research has been recognized with awards including the 2025 Best Paper Award at ASPLOS, 2024 Jay Lepreau Best Paper Award, and NSF CAREER Award. His work has led to impactful contributions like the Sieve framework for testing configuration changes and the Rex tool for kernel extension safety. Dr. Xu advises a vibrant group of students and collaborates with industry partners including VMware, IBM, and Intel. His lab focuses on advancing system reliability through innovative tools and methodologies.

Truşcă Mihail Radu Cătălinمشاهده پروفایل

پژوهشگر

• Datacenter Management
• Computer Network Administration
• Server Systems
• +۵ مورد دیگر

Truşcă Mihail Radu Cătălin serves as a Researcher and Technology Development Engineer I at the National Institute for Research and Development of Isotopic and Molecular Technologies (INCDTIM) in Cluj-Napoca, Romania, within the Datacenter department and Hi-Tech Engineering and Advanced Technologies research team. His work directly supports the institute's Advanced Computing Platform for Emerging Technologies. His educational qualifications include: MSc in Science of Systems and Computers (1996, Târgu-Mureş University, Romania) PhD in Systems Engineering (2015, Technical University of Cluj-Napoca, Romania) Truşcă specializes in applied datacenter infrastructure engineering, focusing on networked computer/server management, environmental monitoring (temperature, air conditioning, power), hardware maintenance for scientific equipment, and data-voice cabling system design. His expertise bridges operational technology with research-driven solutions for optimizing datacenter functionality through proprietary and commercial monitoring systems. He actively coordinates research grants as project leader and manages significant R&D projects for enterprises, including technology transfer initiatives. His peer-review activities extend to international research programs, demonstrating engagement with the broader scientific community. Based in Building B, Room B0.01 at INCDTIM, Truşcă develops webpages and databases essential for institutional operations while maintaining Romania's isotopic and molecular research infrastructure.

Anthony Goodacreمشاهده پروفایل

استاد

• Computer Architecture
• High-Performance Computing (HPC)
• Embedded Systems
• +۷ مورد دیگر

Anthony Goodacre is a Professor of Computer Architectures at the School of Computer Science, holding a part-time role while serving as Director of Technology and Systems at ARM Ltd. in Cambridge. He leads research spanning nanotechnology, hardware design, operating systems, and heterogeneous runtimes, with a focus on scalable, power-efficient systems for embedded, enterprise, and HPC applications. Research interests include: Exascale computing through EU-funded projects like EUROSERVER and ExaNoDe 3D silicon integration and system virtualization for heterogeneous architectures Quantum-classical programming languages (e.g., Quff) Power management techniques like cyclic power-gating Memory models and runtime systems for ARM-based data centers His 15 most recent publications highlight trends in FPGA acceleration, radiation-hardened MPSoC systems, and hybrid quantum-classical programming. Contributions to EU FP7/H2020 projects (e.g., EUROSERVER, ExaNEST) emphasize commercialization of ARM technology for exascale computation. Current collaborations include: KALEAO Limited (CSO/CTO since 2015) ARM Ltd. (Director since 2002) Technology Strategy Board (member since 2015) Academic partnerships in EU H2020 projects He co-supervises two PhD students and contributes to policy discussions, including parliamentary select committee evidence. His work aligns with UN SDGs for energy efficiency and sustainable computing.

• High-Performance Computing
• Distributed Systems
• Parallel Computing
• +۱۲ مورد دیگر

Juan Jose Costa Prats is a researcher in the Department of Computer Architecture at the Universitat Politècnica de Catalunya (UPC), affiliated with the Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona. He is a key member of the CRAAX - Centre de Recerca d'Arquitectures Avançades de Xarxes, contributing to advanced research in computing systems and network architectures. His work is deeply integrated into competitive R&D projects, including Horizon Europe and national initiatives focused on digital innovation and infrastructure. Research Interests: Costa Prats specializes in high-performance and distributed computing, with a strong focus on parallel programming models (especially OpenMP), software distributed shared memory (SDSM), cloud computing, virtualization, and cybersecurity. His recent work emphasizes secure and resilient computing systems, particularly through RISC-V-based architectures, hypervisor extensions, and runtime malware detection using opcode analysis and machine learning. He also contributes to educational innovation through remote datacenter laboratories. Publication Trends: His recent publications (2021–2024) reflect a shift toward secure, trustworthy computing environments, especially in cloud and IoT contexts. Themes include RISC-V virtualization, intrusion detection using transfer learning, GPS spoofing detection, and secure development frameworks like Vitamin-V. These works highlight a convergence of system architecture, security, and machine learning. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While no formal students are listed, Costa Prats collaborates extensively with leading researchers such as Beatriz Otero, Ramon Canal, and Javier Verdú. He participates in numerous competitive R&D+i projects funded by the Spanish government and the European Union, including Horizon Europe, RIS3CAT, and national research programs, focusing on cloud resilience, intelligent cloud management, and RISC-V ecosystem development. Labs and Teams: He is an active member of the CRAAX research group at UPC, which works on advanced computing architectures. His research often involves collaboration with the Barcelona Supercomputing Center. His projects, such as Vitamin-V and Remote DasaLAB, indicate involvement in both secure computing environments and innovative educational platforms.

• Machine Learning
• Data Mining
• Social Network Analysis
• +۴ مورد دیگر

Yllka Velaj is an Assistant Professor in the Faculty of Computer Science, affiliated with the Research Group on Data Mining and Machine Learning. Her research focuses on machine learning, data mining, and network analysis, with applications in social networks, recommendation systems, and AI-enhanced education. She actively contributes to advancing methodologies for uncertain graphs, game-based learning in IT project management, and educational technologies targeting non-computer science students. Her scholarly activities include organizing events such as the Austrian Computer Science Day 2024. Her work bridges theoretical computer science with practical applications, emphasizing learner-centered approaches in data science education and innovative solutions for complex network problems. Key research areas include node embedding, cluster analysis, and algorithm design for social influence maximization. She collaborates on projects addressing multi-relational graph clustering, semi-supervised learning, and optimizing communication in datacenters.

Robert Ricciمشاهده پروفایل

استاد پژوهش

• Infrastructure
• Operating Systems
• Networking
• +۶ مورد دیگر

Robert Ricci is a Research Professor in the Kahlert School of Computing at the University of Utah and director of the Flux Research Group. He has been affiliated with the University of Utah since 1997, earning a BS (2001) and PhD (2010) in Computer Science, advised by Jay Lepreau and Sneha Kasera. He also serves as an Adjunct Professor at Westminster College. His research focuses on infrastructure systems, including operating systems, networking, cloud computing, and security, with an emphasis on empirical methods and reproducibility. Ricci leads development of testbeds like Emulab and CloudLab, enabling large-scale experiments in distributed systems. Education: B.S. in Computer Science, University of Utah (2001, Honors) Ph.D. in Computer Science, University of Utah (2010) Research Interests: Infrastructure systems (OS, networking, distributed systems) Cybersecurity and privacy Testbeds for experimental research Performance measurement and reproducibility Cloud computing and resource management Key Contributions: Co-developer of Emulab and its successors (CloudLab, GENI) Pioneered work on network testbed mapping and disk image deployment Advances in cloud performance variability analysis and anomaly detection Research on security protocols and malware detection in cloud environments Students: Supervises 7 current PhD students and has advised over 30 alumni, many now in industry leadership roles at companies like Microsoft, Google, and Amazon. Labs/Teams: Leads the Flux Research Group, collaborating on projects like CloudLab, PhantomNet, and POWDER wireless testbed.

Dustin Richmondمشاهده پروفایل

استادیار

• Computer Architecture
• FPGA
• RISC-V
• +۴ مورد دیگر

Dustin Richmond is an Assistant Professor in the Department of Computer Science and Engineering at the Baskin School of Engineering, University of California, Santa Cruz. His work focuses on secure, usable hardware systems with applications in FPGA acceleration, RISC-V architectures, and side-channel analysis. Email: drichmond@ucsc Office: Engineering 2, Room 221 Research Interests: Secure hardware systems FPGA-based computing Manycore processors High-level synthesis Side-channel vulnerabilities Notable Article Trends: Recent publications emphasize cloud FPGA security, manycore design optimization, and hardware security. Earlier works focus on RISC-V acceleration, OpenCL compiler enhancements, and heterogeneous computing systems. GitHub Contributions: Maintains open-source projects like RISC-V-On-PYNQ and PYNQ-HLS, addressing FPGA programming challenges and RISC-V integration. Active in resolving community issues related to toolchain compatibility and hardware-software interfaces.

C. (Chrysa) Papagianniمشاهده پروفایل

استادیار

• Network Softwarization
• Software-Defined Networking
• Network Slicing
• +۷ مورد دیگر

Dr. C. (Chrysa) Papagianni is an Assistant Professor at the Informatics Institute within the Faculty of Science, Mathematics and Computer Science at the University of Amsterdam . She holds a Ph.D. in Electrical and Computer Engineering from the National Technical University of Athens and has held academic and research positions at institutions including the University of Maryland, Hellenic Open University, and Nokia Bell Labs (Belgium). Ph.D., Electrical and Computer Engineering, NTUA (2009) M.Sc., Information Systems (2017-2019), Hellenic Open University Her research focuses on network softwarization , SDN , network slicing , and AI/ML-driven network intelligence for next-generation networks. Recent work explores machine learning for resource allocation , programmable data planes , and intent-based networking . Her publications span journals like IEEE Transactions on Network and Service Management and conferences including IEEE ICC and IEEE CoNEXT . Key projects include NSF FABRIC , H2020 FED4FIRE+ , and 5Growth platform development. She contributes to technical standards in edge computing and cloud-native networks via 5GPPP white papers.