جست‌وجوی استاد و پژوهشگر

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.

Justine Sherryمشاهده پروفایل

دانشیار

• Networked Systems
• Middleboxes
• Congestion Control Algorithms
• +۵ مورد دیگر

Justine Sherry is the A. Nico Habermann Associate Professor of Computer Science at Carnegie Mellon University (CMU). Her research focuses on networked systems across software and hardware layers, particularly middleboxes, congestion control, FPGA-based acceleration, and Internet fairness. Affiliations: Computer Science Department (CSD) , CyLab , SNAP Lab . Academic Rank: Associate Professor Her recent work explores radical shifts in datacenter architectures via SmartNICs, hardware-software co-design for network functions, and database proxy innovation using eBPF. She leads research on Internet fairness , denial-of-service mitigation , and high-speed intrusion detection through systems like Pigasus. Key scientific contributions span 15 recent publications at venues like SIGCOMM, OSDI, and VLDB, addressing topics such as: Mathematical fairness in congestion control KERNEL bypass strategies in FPGA SmartNICs BBR algorithmic unfairness Wireless latency optimization (Zhuge) Heterogeneous hardware performance analysis Open-source security infrastructure Major awards include: Sloan Research Fellowship VMWare Systems Award NSF grants Intel Outstanding Researcher Award Early Career Diamond from UW Engineering She mentors students in systems research, including Ranysha Ware , Nirav Atre , and Hugo Sadok , while collaborating with institutions like Google, Facebook, and DARPA.

Dave Andersenمشاهده پروفایل

دانشیار

• Computer Systems
• Distributed Systems
• Networked Environments
• +۱۲ مورد دیگر

Dave Andersen is an Associate Professor at the School of Computer Science, Carnegie Mellon University , with research focusing on memory and power-efficient computing, robust distributed systems, and networked environments. He also serves as CTO of Enriched Ag . Education: Ph.D. and M.S. in Computer Science from MIT (2001, 2004), B.S. in Computer Science and Biology from the University of Utah (1995). Research Trends: Explores systems design in the post-Moore's Law era, emphasizing concurrency, low-latency geo-replicated storage, and RDMA in datacenters. Key projects include MemC3, Eiger, Cuckoo Filter, and FAWN. Teaching: Courses in Advanced OS, Distributed Systems, Low-Power Computing, and Network Security. Professional Service: Program committee roles at SOSP, NSDI, SIGCOMM, and DARPA ISAT advisory group. Personal: Active in running, climbing, and outdoor activities with detailed route guides for Pittsburgh and Boston.

Kunle Olukotunمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Programming
• Chip Multiprocessors
• +۴ مورد دیگر

Kunle Olukotun is a Professor of Electrical Engineering and Computer Science at Stanford University's School of Engineering, where he has been faculty since 1991. He directs the Stanford Pervasive Parallelism Lab (PPL) and co-leads the Transactional Coherence and Consistency (TCC) project. His research focuses on computer architecture, parallel programming environments, and scalable parallel systems. Key areas include chip multiprocessors (CMPs), transactional memory systems, domain-specific languages (DSLs) for heterogeneous computing, and hardware-software co-design for machine learning workloads. His work bridges theoretical foundations with practical systems implementation. Notable contributions include the Stanford Hydra research project (one of the first chip multiprocessors with thread-level speculation), founding Afara Websystems (acquired by Sun Microsystems), and developing the Niagara processor architecture. His DSL frameworks like Green-Marl and Spatial enable efficient graph analysis and hardware acceleration. His publications reveal strong trends in parallel systems evolution: from foundational CMP research (2000s) to transactional memory (2004-2010), then DSLs for heterogeneous computing (2010-2015), and currently foundation model systems (2023-2025). Subfield analysis shows consistent focus on hardware-software co-design, sparse computation, and compiler techniques across decades. ACM Fellow (2006) for contributions to multiprocessors on a chip and multi-threaded processor design Best Paper Award at IEEE International Symposium on Workload Characteristics (IISWC '10) for EigenBench Olukotun actively mentors researchers through the Stanford Pervasive Parallelism Lab (PPL), which seeks to proliferate parallelism across application domains. His projects have secured significant industry partnerships, including the acquisition of his startup Afara Websystems by Sun Microsystems. Current research focuses on compiler frameworks for foundation model systems and hardware acceleration for sparse machine learning workloads, supported by collaborations with major tech companies. He leads the Stanford Pervasive Parallelism Lab (PPL), which develops compiler and runtime systems for heterogeneous architectures. The lab's work spans DSLs, hardware acceleration, and parallel programming models, with strong industry ties to companies like NVIDIA and Google. Current initiatives include the Mosaic compiler framework and Stardust architecture for sparse tensor computation.

Rodrigo Fonsecaمشاهده پروفایل

دانشیار

• distributed systems
• networking
• operating systems
• +۵ مورد دیگر

Rodrigo Fonseca is an Associate Professor with Tenure in the Computer Science Department at Brown University's School of Engineering. He received his PhD from UC Berkeley in 2008 under Ion Stoica, focusing on execution tracing for distributed systems. His educational background includes a PhD in Computer Science from UC Berkeley (2008). Fonseca's research focuses on distributed systems, networking, and operating systems, with particular interest in understanding complex system behavior. His work spans distributed tracing and debugging (X-Trace, Pivot Tracing), network management in datacenters (2DFQ, Planck), power management in mobile systems (Quanto, Application Modes), and software-defined networking (Participatory Networking, Simon). His research integrates theoretical insights with practical implementations that have influenced both academic and industrial systems. His publication record shows a strong focus on distributed system instrumentation, with recurring themes of causal tracing, resource management, and network monitoring. The most recent publications demonstrate continued innovation in data-aware indexing structures, in-network packet analysis, and context propagation techniques for distributed systems. Fonseca has received significant recognition including an NSDI Test of Time Award for X-Trace, an NSF CAREER Award, and a Best Paper Award at SOSP for Pivot Tracing. His work has been consistently published in top-tier venues including SIGCOMM, NSDI, SOSP, and OSDI. He has mentored numerous graduate students, with five PhD graduates as of 2019 who have gone on to positions at Google, Microsoft, Apple, and MPI-SWS. His research has been supported by funding from the National Science Foundation, Google, Intel, and Microsoft Research, where he also spent visiting periods. He is actively involved in the research community, having served on program committees for major conferences and co-organizing workshops including HotCloud and the New England Networking and Systems Day. In 2019-2020, he served as PC co-chair for HotNets and General Chair for SoCC'2020.

Cristinel Ababeiمشاهده پروفایل

دانشیار

• Network-on-chip architectures
• Embedded systems
• Multicore processors
• +۷ مورد دیگر

Cristinel Ababei serves as an Associate Professor in the Department of Electrical and Computer Engineering at Marquette University's Opus College of Engineering. He directs the Marquette Embedded Systems (MESS) Laboratory and holds a Ph.D. in Electrical and Computer Engineering from the University of Minnesota (2004), with prior degrees from Technical University of Iasi in Romania. Ph.D., 2004, Electrical and Computer Engineering, University of Minnesota M.S., 1998, Signal Processing, Technical University of Iasi B.S., 1996, Microelectronics, Technical University of Iasi Dr. Ababei's research spans network-on-chip architectures, embedded systems design, FPGA implementations, and energy optimization systems. His work particularly focuses on uncertainty modeling in embedded systems, multicore processor optimization, and applications in underwater drones, LiDAR systems, and battery management. The MESS Lab under his direction conducts research in embedded systems (including tinyML and IoT applications), FPGAs as accelerators for computer vision, and network-on-chip architectures with emphasis on carbon emissions and uncertainty modeling. His recent publications demonstrate a clear trajectory toward integrating machine learning techniques with traditional hardware design, particularly in energy management systems, battery optimization, and environmental monitoring applications. This includes work on HVAC optimization using reinforcement learning, carbon-aware datacenter scheduling, and TinyML applications for battery health monitoring. William and Nancy Stemper Award for underwater drone prototype IEEE Senior Member (2015) Multiple NSF research grants as PI and Co-PI Teaching innovation grants for entrepreneurship-focused courses Dr. Ababei actively mentors students through the NSF REU Site program 'Hardware, Embedded Software, and Analytics for Environment Quality Monitoring' and has graduated multiple Ph.D. and M.S. students. He has secured significant research funding including NSF grants for uncertainty modeling in heterogeneous embedded systems, cross-layer optimization of energy and cost in multiple buildings, and REU site funding for environmental monitoring. He also founded the 'Men as Advocates and Allies Group' at Marquette as part of the Advance Program. His laboratory work includes the development of underwater drones for water quality monitoring, SmartBuilds energy simulation framework, and various embedded systems for environmental sensing applications. He has been instrumental in organizing WE-GIRLS Summer Camps to encourage girls in engineering from grades 6-8.

Panagiotis Papadimitriouمشاهده پروفایل

دانشیار

• Software-Defined Networking
• Network Function Virtualization
• Cloud Networking
• +۶ مورد دیگر

Panagiotis Papadimitriou serves as an Associate Professor at the Department of Applied Informatics, University of Macedonia in Thessaloniki, where he leads the NetCloud research group. Previously, he held positions as Assistant Professor at Leibniz University Hanover's Institute of Communications Technology and as a Post-Doctoral Researcher at Lancaster University (UK) and Telecom SudParis (France), with additional research experience at the University of Cambridge. His research spans Internet architectures and technologies with emphasis on Network Function Virtualization (NFV), Software-Defined Networking (SDN), Time-Sensitive Networking (TSN), Internet-of-Things (IoT), and Edge Computing. His work includes ML-assisted NFV orchestration (SFC-graph embedding, transformation, and multi-domain partitioning), network slicing orchestration, programmable dataplanes with P4, deterministic networks, datacenter network fabrics, and edge computing. Notable research outcomes include distributed network processing architectures (MIDAS, DistNSE), multi-provider service mapping mechanisms (Nestor), open-source NFV orchestration platforms (TeNOR), and orchestration platforms for cross-slice communication (MESON). His recent publications show a strong focus on In-Band Network Telemetry, Service Function Chain optimization, Time-Sensitive Networking implementations, and cross-slice communication systems, demonstrating his leadership in network virtualization and edge computing research areas. His work consistently addresses practical implementation challenges while advancing theoretical foundations in network management. Scientific Recognition: Senior Member of IEEE Associate Editor of IEEE Transactions on Network and Service Management Counselor of the IEEE Student Branch at University of Macedonia As Principal Investigator of the Horizon Europe NEPHELE project and previous EU-funded projects (NECOS, T-NOVA, CONFINE), he has secured over 1M euro in research funding. He actively contributes to the academic community through conference organization roles including IEEE ICC NGNI 2025, IEEE ICIN 2024, and IFIP/IEEE CNSM 2022 as General Co-Chair. The NetCloud research group he leads maintains a dedicated edge computing facility used for both research and teaching, and is known for its commitment to open-source software and community service through academic network resources. His educational background includes a Ph.D. in Electrical and Computer Engineering from Democritus University of Thrace (2008), an M.Sc. in Information Technology from University of Nottingham (2001), and a B.Sc. in Computer Science from University of Crete (2000).

• High Performance Computing
• Distributed Systems
• Deep Learning
• +۴ مورد دیگر

Muhammad Mustafa Rafique is an Associate Professor in the Department of Computer Science at Rochester Institute of Technology's Golisano College of Computing and Information Sciences. His research specializes in optimizing large-scale computing systems, with focus areas including: High-performance computing (HPC) resource management Distributed deep learning acceleration Fault-tolerant cloud architectures GPU-accelerated checkpointing systems Serverless computing frameworks Dr. Rafique's work demonstrates consistent innovation in improving computational efficiency for containerized HPC workflows, multi-GPU scheduling, memory optimization, and distributed training pipelines. His publications frequently appear in premier IEEE/ACM conferences, reflecting contributions to systems performance engineering. While no awards or student advisees are mentioned in available materials, his research collaborations include co-authors from institutions worldwide, indicating active engagement in the high-performance computing research community. Current work explores emerging memory technologies like CXL and advanced containerization techniques for next-generation datacenters.