جست‌وجوی استاد و پژوهشگر

• Computer Architecture
• Distributed Systems
• Cloud Computing
• +۵ مورد دیگر

Randy H. Katz is a distinguished Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley's College of Engineering. With an extensive publication record spanning over two decades, he has established himself as a leading researcher in computer systems, distributed computing, and energy-efficient architectures. His work bridges theoretical foundations with practical implementations in cloud computing, networking, and smart infrastructure systems. Professor Katz's research interests span a broad spectrum of computer systems topics, with particular emphasis on energy-efficient computing, distributed systems design, and infrastructure for emerging applications. His work on FireSim represents a major contribution to FPGA-based system simulation, while his research on energy-aware datacenters and smart grids addresses critical sustainability challenges in computing infrastructure. He has pioneered approaches in serverless computing, blockchain systems, and mobile augmented reality that balance performance with energy constraints. Analysis of Professor Katz's recent publications reveals a strong focus on hardware-software co-design for emerging computing paradigms. His work consistently addresses the tension between performance and energy efficiency across multiple domains including cloud infrastructure, smart buildings, and mobile systems. A notable trend is his focus on making complex systems more accessible and manageable through innovative abstractions like FireSim for hardware simulation and Cirrus for serverless machine learning workflows. Scientific Awards: IEEE James H. Mulligan, Jr. Education Medal (2010) - Recognizing his exceptional contributions to engineering education Professor Katz has advised numerous PhD and Master's students who have gone on to influential positions in both academia and industry. His research has been supported by major grants from NSF, DARPA, and industry partnerships with leading technology companies. His work on Mesos, a cluster resource management system, has had significant industry impact, and his energy-efficient computing research has informed datacenter design practices across the industry. His research group at UC Berkeley has been instrumental in developing frameworks like FireSim for hardware acceleration and FirePerf for performance profiling. These tools have become important resources for the computer architecture community, enabling researchers to explore new hardware designs with unprecedented efficiency. His work on smart buildings through projects like SnapLink demonstrates his commitment to applying computing research to solve real-world sustainability challenges.

Hassan Chizariمشاهده پروفایل

مدرس ارشد

• Cyber Security
• Randomness Extraction
• Cryptography
• +۵ مورد دیگر

Hassan Chizari is a Senior Lecturer and Academic Course Leader for the MSc Cyber Security program at the University of Gloucestershire. He leads the Cisco Network Academy and manages the Cisco Lab, teaching networking and advanced cybersecurity topics. His research focuses on randomness extraction in physiological signals for cryptographic applications, funded by InnovateUK. He has published over 40 peer-reviewed articles and supervised 20+ postgraduate students. Chizari holds a BSc in Computer Hardware (Shiraz University, 1999), MSc in Artificial Intelligence and Robotics (Shiraz University, 2003), and PhD in Networking (Universiti Teknologi Malaysia, 2011). His work has earned awards including Gold Medals at Malaysia Technology Expo (2016) and Malaysian Research Conference (2015), and Bronze Medals for innovations like Indoor Air Quality Monitoring and Smart Environment Monitoring. His research bridges cybersecurity, bio-inspired algorithms, and IoT infrastructure. Recent work includes cryptographic key extraction from ECG signals and energy-efficient cloud resource allocation using nature-inspired techniques. He collaborates with Crossword Company to commercialize physiological signal-based security solutions. His teaching spans undergraduate to postgraduate levels, emphasizing practical lab work and industry-relevant skills. Awards and recognitions include multiple medals for innovations in environmental monitoring and sensor networks. His grants include InnovateUK funding for medical device security. Chizari’s advising focuses on cybersecurity, networking, and bio-inspired systems, contributing to over 20 completed theses. He actively explores green computing, wireless sensor networks, and resilient critical infrastructure frameworks. Chizari’s research group develops secure IoT applications and trustworthy smart systems, addressing challenges in data privacy, anomaly detection, and energy efficiency. Current projects aim to integrate bio-signals into cryptographic protocols and optimize cloud/fog computing infrastructure for sustainability.

Panagiota Nikolaouمشاهده پروفایل

مدرس

• Computer Architecture
• Fault Tolerance
• Edge and Cloud Deployments
• +۷ مورد دیگر

Panagiota Nikolaou is a Lecturer in Computer Engineering and Course Leader of the BEng (Hons) Computer Engineering program at the School of Sciences, UCLan Cyprus. She holds a PhD in Computer Science from the University of Cyprus (2020), along with MSc and BSc degrees in Computer Science from the same institution. Her research focuses on computer architecture, fault tolerance, edge/cloud deployments, memory reliability, power optimizations, and intelligent vehicles. She has held roles including Research Associate at the KIOS Research and Innovation Center of Excellence and Lecturer at Alexander College. Her teaching responsibilities include Digital Electronics, Probability Theory for Engineers, and Engineering Professionalism. She has extensive research experience in EU-funded projects such as SESAME (Horizon 2020) and UNISERVER, addressing topics like reliability in embedded systems and energy-efficient computing. Her publications span domains like UAV reliability, real-time forest fire detection, and cost analysis of edge vs. cloud deployments. Notable awards include the Best Poster Award at the 2020 SERESSA conference. She actively participates in academic activities, including serving as Program Chair for the VLSI-SoC conference (2026) and roles in IEEE committees. Her research grants include leadership in projects like CERCIRAS (2020–2024) and participation in Horizon 2020 initiatives. She emphasizes interdisciplinary collaboration, bridging hardware reliability, software optimization, and real-world applications in critical systems.

• Computational Sustainability
• Cloud Computing
• Edge Computing
• +۳ مورد دیگر

Ivona Brandic is a Full Professor of High Performance Computing Systems at TU Wien's Institute of Information Systems Engineering, leading the HPC Research Group. She specializes in Computational Sustainability, Cloud/Edge Computing, and Quantum-Classical Systems. Her roles include Head of the Computational Sustainability Research Unit and membership in TU Wien's Faculty Council. She teaches courses such as AI/ML in Climate Change and Hybrid Quantum-Classical Systems. Her research focuses on sustainable IT, energy-efficient systems, and hybrid quantum-classical workflows. Projects include computational sustainability initiatives funded by the Austrian Science Fund (FWF) and industry partnerships like the Virtual Shepherd project. She has contributed to over 50 publications, emphasizing edge computing, quantum algorithms, and HPC optimization. Notable contributions include developing frameworks like RIGOLETTO for hybrid scientific workflows and FRESCO for edge offloading. Her work bridges theoretical advancements with practical applications in environmental monitoring and energy efficiency.

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.

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.

Peter Westمشاهده پروفایل

استادیار

• Natural Language Processing
• Artificial Intelligence
• Large Language Models
• +۳ مورد دیگر

Peter West is an incoming Assistant Professor at the University of British Columbia (UBC) Computer Science Department, specializing in Natural Language Processing (NLP) and AI. His research focuses on understanding the capabilities and limitations of large language models (LLMs) and generative AI systems, emphasizing their divergence from human intuition and alignment challenges. He holds a PhD from the University of Washington (2024), supervised by Yejin Choi, and a BSc (Honours Computer Science) from UBC (2017). His work has been recognized with awards including Best Method Paper at NAACL 2022 and Outstanding Paper awards at ACL 2023 and EMNLP 2023. He conducted internships at the Allen Institute for AI and Microsoft Research’s NLP group. Research interests include analyzing LLM behavior through a natural sciences lens, exploring model capabilities versus human expectations, and developing decoding algorithms to infuse models with algorithmic logic. His recent publications address generative AI paradoxes, constrained text generation, and symbolic knowledge distillation. He serves on panels for NeurIPS workshops and is beginning a postdoc at Stanford with Chris Potts. His research group at UBC seeks students interested in generative AI’s analytical frontiers.

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.

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.

Malte Schwarzkopfمشاهده پروفایل

دانشیار

• Distributed Systems
• Operating Systems
• Privacy-Preserving Systems
• +۵ مورد دیگر

Malte Schwarzkopf is an Associate Professor of Computer Science at Brown University. He was previously a postdoc at MIT CSAIL (2016-2019) and earned his PhD at the University of Cambridge (2016). His research spans distributed systems, operating systems, and privacy-preserving systems, focusing on building high-performance, user-friendly systems through novel abstractions. Education: PhD, University of Cambridge, 2016 MA, University of Cambridge, 2013 BA, University of Cambridge, 2009 His work addresses critical challenges in datacenter scheduling, privacy compliance in web applications, and secure multi-party computation. Recent projects include Quicksand for resource allocation and Sesame for GDPR compliance by design. Scientific awards include the Google ML and Systems Junior Faculty Award (2025), NSF CAREER Award (2021), Amazon Research Award (2024), and multiple best paper/test-of-time awards at NSDI (2015), EuroSys (2013, 2023), and VLDB (2025). He has advised numerous students, including Justus Adam, Lillian Tsai, and Jon Gjengset, who are now at institutions like MIT, Google, and Stanford. His research is supported by NSF, Amazon, Google, Microsoft, and VMware.

Samy El-Tawabمشاهده پروفایل

استاد

• Intelligent Transportation Systems
• Computer Networks
• Vehicular Ad-Hoc Networks (VANET)
• +۶ مورد دیگر

Samy El-Tawab is a Professor and the Information Technology Program Director at James Madison University (JMU) within the College of Integrated Science and Engineering 's Department of Computer Science . He has been at JMU since 2012, progressing from Assistant to Associate to Full Professor in 2024. Education: Ph.D. in Computer Science (2012), Old Dominion University M.Sc. in Computer Science (2006), Alexandria University B.Sc. in Computer Science (2002), Alexandria University Research Interests span Intelligent Transportation, Vehicular Ad-Hoc Networks (VANET), Wireless Sensor Networks (WSN), Network Security, Internet of Things (IoT), Cloud Computing, and Autonomous Vehicles. His work focuses on creating passenger-aware autonomous systems and improving transportation efficiency through low-cost IoT solutions. Selected Projects include: Independent Mobility for the Elderly (2019): $120,000 Jeffress Trust Award 4-VA Transit Bus Optimization (2015): $37,700 Madison Trust Smart Parking (2016): Cloud-based parking app STEM Outreach (2015): Mobile tech integration for K-12 education Scientific Awards : 2020 Madison Scholar 2018 Virginia Governor's Technology Award 2017 Outstanding Junior Faculty 2017 CFI Engaged Teacher Scholar 2014 IEEE MASS Travel Award Teaching includes courses like Autonomous Vehicles, Wireless Networking, Security & Forensics, and TCP/IP Networks. He emphasizes project-based learning, with students working on real-world problems like parking solutions and transit monitoring systems.