جست‌وجوی استاد و پژوهشگر

Yunming Xiaoمشاهده پروفایل

استادیار

• Computer Systems
• Networks
• Security
• +۳ مورد دیگر

Yunming Xiao is an Assistant Professor at the School of Data Science, The Chinese University of Hong Kong (CUHK), Shenzhen. Previously, he served as a Research Fellow at the University of Michigan and earned his Ph.D. in Computer Science from Northwestern University in 2024. His research focuses on computer systems, networks, and security, with emphasis on security and privacy of Internet services and performance optimization of cloud infrastructure. His work has been recognized with the Best Paper Award at APNet and Best Student Paper Award at ACM EuroSys. Education: Ph.D. in Computer Science, Northwestern University (2024) B.Eng. in Computer Science, Beijing University of Posts and Telecommunications (2019) His research bridges cloud infrastructure and security, where projects like SwiftRDMA, Conspirator, and MegaTE demonstrate innovative approaches to resource scheduling, SmartNIC integration, and traffic engineering at scale. These works highlight his focus on solving real-world performance and security bottlenecks in distributed systems. Scientific Awards: Best Paper Award, APNet'25 Best Student Paper Award, ACM EuroSys'24 Yunming actively collaborates with industry, having interned at Google, Hewlett Packard Labs, Nokia Bell Labs, and Bytedance. He serves on TPCs for major conferences including CCS'26, IMC'26, and IEEE S&P'26.

Andreas Herkersdorfمشاهده پروفایل

استاد

• Computer Architecture
• Embedded Systems
• Network-on-Chip (NoC)
• +۴ مورد دیگر

Prof. Dr. Andreas Herkersdorf is a Full Professor and Chair of Integrated Systems at the Technical University of Munich (TUM) School of Computation, Information and Technology. His research focuses on application-specific multicore processors (MPSoC), FPGA-based prototyping, fault-tolerant systems, and energy-efficient architectures, with applications in IP packet processing, automotive systems, and visual computing. He has received multiple IBM innovation awards and serves on editorial boards including the DFG Review Board for computer architecture. Education: Dipl.-Ing. Electrical Engineering (TUM, 1987), Dr. techn. Electrical Engineering (ETH Zurich, 1991) Research: MPSoC architectures, autonomic computing, NoC resilience, FPGA acceleration, and self-optimizing systems. Awards: IBM Master Inventor (1998), IBM Outstanding Technical Achievement Award (2001), multiple IBM Innovation Achievement Awards (1996-2003) His recent publications emphasize hardware/software co-design, machine learning integration for runtime optimization, and network-on-chip innovations. He collaborates on projects involving 6G systems, smartNICs, and automotive communication protocols.

Binoy Ravindranمشاهده پروفایل

استاد

• Computer Systems
• Software Verification
• Concurrency
• +۷ مورد دیگر

Binoy Ravindran is a Professor at Virginia Tech’s College of Engineering, Department of Electrical and Computer Engineering, leading the Systems Software Research Group (SSRG). His research focuses on computer systems, emphasizing security, performance, concurrency, distributed systems, and real-time computing, with recent work in software verification and heterogeneous-ISA platforms. Key projects: Low-level Reasoning Machine (LLRM), Popcorn Linux, LibrettOS, Hyflow, HermiTux, SlimGuard, HydraVM, KairosVM. He has co-authored 15+ papers from 2025 to 2022, spanning venues like ASPLOS, POPL, PLDI, VEE, PPoPP, and MIDDLEWARE, with awards including ACM Distinguished Scientist and eight Best Paper Awards. Service roles: Editorial Boards (IEEE Transactions on Cloud Computing, ACM TECS), Program Co-Chair (ACM Systor 2025), Committee memberships across ASPLOS, PLDI, and more.

Alex C. Snoerenمشاهده پروفایل

استاد

• Computer Networks
• Distributed Systems
• Networking Security
• +۵ مورد دیگر

Alex C. Snoeren is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego (UCSD). He is affiliated with the Systems and Networking Research Group, the Security and Cryptography Research Group, and the Center for Networked Systems. His work focuses on distributed systems, networking, and security, with notable contributions to data center networking, optical systems, and network measurement. He has advised numerous PhD students and has been actively involved in teaching courses such as CSE 120 (Principles of Computer Operating Systems), CSE 123 (Computer Networks), and graduate-level systems and networking courses. His research has led to innovations in network architecture, including projects like RotorNet (optical data center networking) and Eden (far memory integration). Key awards include the Best Paper at ACM SIGCOMM 2023 and multiple best student paper recognitions. His work spans both theoretical and applied domains, addressing challenges in network scalability, security, and efficiency.

• Computer Networking
• Software-Defined Networking (SDN)
• Distributed Systems
• +۳ مورد دیگر

Mario Baldi is a researcher affiliated with the Polytechnic University of Turin, Italy , with significant contributions to computer networking , distributed systems , and software-defined networking . Key research themes: network function virtualization , programmable dataplanes , time-driven scheduling , and traffic analysis . Recent work focuses on RDMA-enabled compute offloading (2023) and DNN inference in network data planes (2023). Longstanding expertise in multicast routing , voice/data packet efficiency , and XML-based protocol parsing (2000–2006). Collaboration network includes Yoram Ofek , Fulvio Risso , and Han Hee Song , with 99+ publications spanning 1994–2023.

Klajd Zylaمشاهده پروفایل

پژوهشگر

• Embedded Systems
• Computer Networks
• Network-on-Chip (NoC)
• +۳ مورد دیگر

Klajd Zyla is a PhD student and scientific assistant at the Chair of Integrated Systems, TUM School of Computation, Information and Technology, Technical University of Munich. His research focuses on architectures for flexible data packet processing in high-performance network cards, including NoC optimization, priority-aware scheduling, and RDMA acceleration. PhD Student at LIS (Chair of Integrated Systems), Technical University of Munich (since Jan 2022) Teaching: SystemC Laboratory (since SS 2022) His research investigates on-chip interconnects, packet scheduling with multiple priorities, and acceleration of transport protocols like RDMA for FPGA-based SmartNICs. Publications demonstrate expertise in crossbar architectures, deadlock avoidance, and resource management for MPSoCs. Supervised students include: Nour Abouelkheir (2D Mesh NoC design) Aleksa Stojkovic (HiPerNoC enhancement) Antra Pramanik (Packet-processing FPGA implementation) Arathi Anitha (Deadlock-avoidance algorithms) Johannes Ecker (Hardware schedulers comparison)

Sang-Woo Junمشاهده پروفایل

استاد

• Big Data Analytics
• Hardware Acceleration
• Non-Volatile Memory
• +۳ مورد دیگر

Professor Sang-Woo Jun is a leading researcher in systems and software for big data analytics, focusing on FPGA-based hardware acceleration and non-volatile memory (NVM) storage. His work spans applications such as graph analytics and bioinformatics, with a strong emphasis on cost-effective, high-performance computing architectures. He advises PhD students like Shengquan Ni and Yicong Huang, both of whom have achieved notable milestones (e.g., thesis defense, fellowship awards). Research Interests: Hardware Acceleration for Big Data FPGA-Based System Architectures Non-Volatile Memory Systems Graph Analytics and Bioinformatics Edge Computing and Low-Power Systems Recent Contributions: His articles highlight innovations in edge accelerators (e.g., IceSpy, Eciton), genomics acceleration (Bancroft), and scalable graph processing (Durin, Sting). These works emphasize reconfigurable systems, privacy-preserving techniques, and energy-efficient designs. Lab & Team: As part of the Intelligent Systems Group (ISG), he collaborates on events like the Southern California Database Day. His research bridges hardware-software co-design with real-world applications in IoT, environmental monitoring, and genomics.

• Computer Engineering
• Network Performance
• Network Security
• +۳ مورد دیگر

Xiaoqi Danny Chen is an Assistant Professor in the School of Electrical and Computer Engineering at Purdue University, located in West Lafayette. His office is in BHEE 327. He focuses on algorithm design for high-speed programmable network switches and SmartNICs to enhance network performance, security, and measurement. His primary research area is Computer Engineering. Research interests include optimizing network infrastructure through algorithmic advancements, with a focus on programmable hardware solutions. His work bridges theoretical algorithm design with practical network hardware implementation, targeting applications in high-throughput computing environments. No academic awards, grants, or advised students are explicitly mentioned in the provided information. No specific lab affiliations or collaborative teams are listed.

Elie Kfouryمشاهده پروفایل

استادیار

• Programmable Data Planes
• Network Security
• Blockchain Systems
• +۲ مورد دیگر

Elie Kfoury is Assistant Professor of Integrated Information Technology specializing in programmable network infrastructures. His research develops P4-based solutions for high-speed networks, cybersecurity, and blockchain integration. Research Leadership: Co-author of High-Speed Networks: A Tutorial used nationally for Science DMZ deployments. Innovator in programmable switch applications for TCP optimization and intrusion detection. Awards: Breakthrough Scholar (2023), Best Paper ICCNP 2018

• Cloud Computing
• Networked Systems
• Cybersecurity
• +۷ مورد دیگر

Dr. Qiang Fu is a Senior Lecturer at RMIT University's School of Computing Technologies, specializing in Cloud, Networked Systems, and Security. He holds a PhD from The University of Queensland and is actively involved in industry collaborations. His research focuses on Internet and Cloud-based systems, including Content Delivery Networks (CDNs), data centre design, Cyber-Physical Systems (CPS)/IoT, virtualization, and SDN/NFV. Recent work emphasizes network telemetry, fault detection, and IoT workflow optimization. He has published extensively in top-tier journals and conferences like IEEE Transactions and IFIP NOMS. Dr. Fu supervises PhD/Master students in areas such as network security, cloud computing, and IoT. His projects are often industry-funded and address real-world challenges like network scalability and blockchain integration. He is open to supervising students in these domains through RMIT's scholarship programs.

Muhammad Shahbazمشاهده پروفایل

استادیار

• Networking and Operating Systems
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Muhammad Shahbaz is the Kevin C. and Suzanne L. Kahn New Frontiers Assistant Professor in Computer Science at Purdue University. He specializes in designing domain-specific abstractions, compilers, and architectures for emerging workloads such as machine learning and self-driving networks. His research bridges networking, machine learning, and computer architecture to create high-performance, scalable systems. Shahbaz holds a Ph.D. and M.A. in Computer Science from Princeton University and a B.E. in Computer Engineering from the National University of Sciences and Technology (NUST). Before joining Purdue, he conducted postdoctoral research at Stanford University and worked as a Research Assistant at Georgia Tech and the University of Cambridge. His research interests include Networking and Operating Systems, Artificial Intelligence, Machine Learning, Computer Architecture, Distributed Systems, and Programming Languages/Compilers. He has developed influential open-source systems like Pisces, SDX, and NetFPGA-10G, which are widely adopted in industry and academia. Shahbaz has received prestigious awards including the Facebook, Google, and Intel Research Awards; IETF/IRTF ANRP Prize; ACM SOSR Systems Award; and APNet Best Paper Award. His work focuses on advancing edge computing, smartNICs, in-network machine learning, and scalable distributed systems. His research portfolio includes contributions to network caching, hardware acceleration, and AI-driven network optimization. He leads projects like CAREER (per-packet AI on heterogeneous data planes) and EdgeScaler (smart auto-scaling for 5G edge networks). His systems address challenges in tail latency, resource harvesting, and scalable multicast in modern networks.

Sean Choiمشاهده پروفایل

استادیار

• Computer Networking
• Programmable Hardware
• Machine Learning Infrastructure
• +۳ مورد دیگر

Sean Choi is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University. He holds a Ph.D. in Electrical Engineering from Stanford University (2020), M.S. in Computer Science from Stanford (2013), and a dual B.S. in Computer Science and Business Economics & Management from Caltech (2011). His research focuses on programmable network hardware, including smartNICs, and their applications in machine learning, blockchain, and cloud computing. Education: Ph.D. in Electrical Engineering, Stanford University (2020) M.S. in Computer Science, Stanford University (2013) B.S. in Computer Science & Business Economics, California Institute of Technology (2011) Research Interests: Programmable Network Switches, SmartNIC Acceleration, Cloud Infrastructure, Serverless Computing, Blockchain Optimization, and Privacy-Preserving Machine Learning . Recent Work: Explores leveraging programmable hardware for low-latency machine learning inference, blockchain scalability via NIC-assisted consensus, and privacy-preserving federated learning through homomorphic encryption offload. His NSF-funded project develops ultra-low-latency ML systems using programmable networks. Awards: NSF CRII 2023 Award Hewlett Packard Enterprise Grant Labs/Teams: Leads research on network programmability and hardware acceleration within Santa Clara University's School of Engineering. Collaborates with industry on data center network optimization and cloud infrastructure projects.

Karl-Johan Grinnemoمشاهده پروفایل

دانشیار

• Network Quality Analysis
• 5G and Beyond Cellular Networks
• Multi-Connectivity Solutions
• +۵ مورد دیگر

Karl-Johan Grinnemo is an Associate Professor at Karlstad University's Department of Computer Science, specializing in network quality, 5G, and IoT research. His work focuses on multi-connectivity, network slicing, edge computing, and energy-efficient IoT protocols. Grinnemo has held roles including Senior Lecturer (2014) and tenured position since 2010. He collaborates with institutions like KTH Royal Institute of Technology, RISE, and European universities on EU-funded projects. His research includes the PLANS policy framework for network slicing and machine learning-driven NB-IoT optimization. Grinnemo teaches advanced courses in networking, databases, and machine learning, and advises numerous student projects. He is a Senior IEEE Member and has published over 100 papers on transport protocols and cellular networks. Education: PhD in Computer Science (2006), postdoctoral work at Karlstad University. Research: Policy-based network slicing, edge computing optimization, and 6G/IoT innovations. Awards: Senior Member of IEEE.

Yiming Qiuمشاهده پروفایل

استادیار

• Systems
• Networking
• Security
• +۵ مورد دیگر

Dr. Yiming Qiu is an Assistant Professor at the Department of Computer Science , University of Hong Kong (HKU). Prior to joining HKU, he worked as a Postdoctoral Researcher co-hosted by Prof. Ang Chen at the University of Michigan CSE and Prof. Sylvia Ratnasamy at UC Berkeley EECS. He earned his PhD in Computer Science and Engineering from the University of Michigan, following a three-year PhD journey at Rice University and BS studies at Beijing University of Posts and Telecommunications (BUPT). Current Role: Assistant Professor, University of Hong Kong Postdoctoral Affiliation: University of Michigan CSE, UC Berkeley EECS Education: PhD (University of Michigan), BS (BUPT) Dr. Qiu's research focuses on systems, networking, and security , with a specific emphasis on applying program analysis , formal reasoning , and machine learning techniques to advance cloud automation and datacenter networks . His work bridges theoretical rigor with practical applications in network function offloading, programmable switches, and AI-driven cloud management. Dr. Qiu's recent publications (2025-2020) highlight trends in cloud infrastructure management, AI agents for scientific experimentation, SmartNIC offloading, and formal methods for network security. Key contributions include best paper awards and frameworks for runtime programmable networks. Scientific Awards: Best Paper Award at APNet 2025 Service: Journal reviewer (IEEE/ACM Transactions on Networking, Computer Networks, IEEE JSAC), Conference reviewer (ASPLOS, APSys, WWW, P4 Workshop), NSF Innovation Corps Entrepreneur lead Teaching: Teaching Assistant for Secure and Cloud Computing (Rice COMP 436/536, 2020-2021)

• Data center networking
• Optical circuit switching
• Distributed systems
• +۳ مورد دیگر

Paolo Costa is a Senior Principal Research Manager at Microsoft Research Cambridge and Honorary Lecturer at Imperial College London. His research bridges distributed systems and networking with focus on optical technologies for next-generation data centers. Key innovations include Sirius nanosecond optical switching architecture, soliton microcomb-based circuit switching, and PANAMA in-network aggregation for machine learning clusters. Research explores programmable switches, hardware acceleration, and AI infrastructure optimization. Projects include 'CamCube' and 'Predictable Datacenters' enhancing application-network integration. Recent publications examine memory systems for AI, stateful in-network computing, and lite-GPU clusters for scalable AI infrastructure.