جست‌وجوی استاد و پژوهشگر

Scott Shenkerمشاهده پروفایل

استاد

• Networking
• Software-Defined Networks
• Datacenter Infrastructure
• +۴ مورد دیگر

Scott Shenker is a Professor at the University of California, Berkeley, and a Research Director at the International Computer Science Institute (ICSI). He previously served as Chief Scientist at ICSI (2012-2021) and held roles at Xerox PARC, University of Southern California, and Cornell University. PhD in Physics, University of Chicago (1983) ScB in Physics, Brown University (1978) His research spans Internet architecture, software-defined networks, datacenter infrastructure, and game theory. He has contributed to distributed systems, privacy mechanisms, and network protocols, with a focus on scalable and resilient designs. Recent work includes advancements in memory management for distributed systems, cloud resource optimization, and SDN frameworks. His 15 most recent publications highlight innovations in datacenter networking, packet scheduling, and storage efficiency. IEEE Computer Society Women of ENIAC Computer Pioneer Award (2023) Fiat Lux Faculty Award (2022) IETI Distinguished Fellow (2020) National Academy of Sciences Member (2019) Paris Kanellakis Theory and Practice Award (2017) ACM SIGCOMM Test of Time Paper Awards (2017, 2011, 2006) IEEE Internet Award (2006) ACM and IEEE Fellowships National Academy of Engineering Member (2012) Shenker has advised numerous PhD and Master’s students, including A. Ermolinskiy, M. Perry, Y. Harchol, and T. Das. His research teams at UC Berkeley and ICSI explore next-generation networking solutions, including open-source frameworks like Spark and Mesos.

Angelos Bilasمشاهده پروفایل

استاد

• Computer Systems
• Computer Architecture
• Storage Systems
• +۴ مورد دیگر

Angelos Bilas is a Professor of Computer Science at the University of Crete, Greece, and a collaborating researcher at FORTH-ICS (Foundation for Research and Technology-Hellas). He received his PhD in Computer Science from Princeton University in 1998 and has held academic positions at the University of Crete since 2002, including Department Chair (2016-2020). His research focuses on systems software for storage systems, computing architectures, and parallel systems with emphasis on flash storage optimization. PhD, Princeton University (1998) MA, Princeton University (1995) BEng, University of Patras (1993) His research interests span computer systems, storage architectures, and parallel computing , with notable contributions in memory-mapped I/O optimization, LSM key-value store design, and heterogeneous accelerator integration. He has developed frameworks like TeraHeap for DRAM pressure mitigation in big data systems and Arax for decoupling applications from accelerators. Prominent trends in his recent publications include flash storage optimization (TeraHeap), LSM tree efficiency (Tebis), and cloud-HPC convergence (EVOLVE, KNoC). His work appears in top venues like ASPLOS, USENIX ATC, and ACM Transactions on Storage. Scientific recognitions include: Marie Curie Excellent Teams Award (2005-2009) Best Presentation Award, USENIX HotStorage'20 He has served on editorial boards (ACM Transactions on Storage) and program committees (ACM HotStorage, HPCA). His research involves 35 master’s and 8 PhD students, with 45+ EU/national projects and 4 patents licensed to industry.

Rishabh Iyerمشاهده پروفایل

استادیار

• Computer Systems
• Performance Analysis and Optimization
• Operating Systems
• +۵ مورد دیگر

Rishabh Iyer is an Assistant Professor in the Electrical Engineering and Computer Sciences department at the University of California, Berkeley. His research bridges computer systems, networking, and formal methods with a focus on performance predictability and reliability. Prior to Berkeley, he completed his PhD at EPFL and undergraduate studies at IIT Bombay. His educational background includes: PhD in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL) Bachelor's degree from Indian Institute of Technology Bombay (IIT Bombay) Iyer's research centers on performance interfaces for computer systems – creating succinct abstractions that allow engineers to reason about system performance without understanding implementation details. His work spans three major directions: (1) Extracting performance interfaces from implementations, (2) Designing systems with predictable performance, and (3) Formally verifying performance claims. This research combines operating systems, networking, computer architecture, and formal verification techniques to address performance unpredictability in modern systems. His group develops tools like PIX for network functions, KFlex for kernel extensions, and Software LPN for hardware accelerators. His publications reveal strong focus on performance modeling for network functions, kernel extensions, and hardware accelerators, with recent work expanding into real-time systems and SD-WAN validation. The research consistently targets practical impact, with deployments at companies like Meta and Alibaba. Scientific recognition includes: ACM SIGOPS Dennis M. Ritchie Award Eurosys Roger Needham PhD Award Dimitris N. Chorafas Award Best Paper at VDAT 2019 Iyer actively advises students at UC Berkeley and teaches courses including CS 294-262 (Performance Analysis) and CS 168 (Internet Architecture). Previously at EPFL, he taught Principles of Computer Systems, Software Engineering, and Vector Calculus. His group seeks talented students interested in building reliable, high-performance systems. Current research directions include performance interfaces for distributed applications, next-generation kernel extensions, and formally verified network systems. He leads research within UC Berkeley's systems community and maintains strong connections with EPFL's Dependable Systems Lab where he completed his PhD.

Mosharaf Chowdhuryمشاهده پروفایل

دانشیار

• AI/ML Systems
• Energy Efficiency in AI
• Memory Disaggregation
• +۴ مورد دیگر

Mosharaf Chowdhury is an Associate Professor at the University of Michigan's College of Engineering, Department of Electrical Engineering and Computer Science. He leads the SymbioticLab (https://symbioticlab.org/), focusing on AI/ML systems optimization and energy-efficient computing. Current roles: Associate Professor, Director of SymbioticLab Key projects: Infiniswap (memory disaggregation), Salus (GPU sharing), FedScale (federated learning), Zeus (GPU energy optimization) Original co-creator of Apache Spark Research Interests center on large-scale systems for AI/ML and big data, with emphasis on: Energy consumption optimization Memory disaggregation via CXL GPU resource management Data privacy in distributed systems Federated learning scalability Scientific Awards include multiple paper awards from top systems venues (NSDI, OSDI, ATC, MICRO) and fellowships. Teaching includes courses like EECS 489 (Computer Networks) and EECS 598 (Systems for AI/ML).

Amy Ousterhoutمشاهده پروفایل

استادیار

• Operating Systems
• Computer Networks
• High-Performance Computing
• +۳ مورد دیگر

Amy Ousterhout is an Assistant Professor in Computer Science and Engineering at the University of California, San Diego . Prior to UCSD, she was a postdoctoral researcher at UC Berkeley's NetSys Lab and earned her Ph.D. from MIT CSAIL in 2019, where she was advised by Hari Balakrishnan and Adam Belay. She received her B.S.E. in Computer Science from Princeton University . Her research focuses on designing efficient, high-performance systems for datacenter applications , including CPU scheduling (Shenango, Caladan, Scheduling Policies), memory management (Cornflakes, Eden, Fastswap), and leveraging new hardware features (xUI, Aspen). She has taught graduate and undergraduate courses such as CSE 221 (Graduate Operating Systems) , CSE 291 (Operating Systems in Datacenters) , and CSE 120 (Operating Systems Principles) . Her publications span conferences like NSDI, ASPLOS, SOSP, HotOS, CIDR, EuroSys, HotCloud, and SIGCOMM , with notable awards including the Best Paper Award at NSDI 2025 . Her work explores microsecond-scale task scheduling , zero-copy serialization , far memory efficiency , and hardware-aware software design . Scientific Awards : Best Paper Award, NSDI 2025 Advising : She advises students such as Liam Arzola, Ani Canumalla, and Linsong Guo , with a focus on systems research and datacenter optimization.

Binoy Ravindranمشاهده پروفایل

استاد

• Computer Systems
• Operating Systems
• Concurrency
• +۷ مورد دیگر

Binoy Ravindran is a Professor and Bradley Senior Faculty Fellow in the Department of Electrical and Computer Engineering at Virginia Tech, where he leads the Systems Software Research Group. He holds a Ph.D. from The University of Texas at Arlington (1998). His research focuses on computer systems, emphasizing security, performance, energy efficiency, and timeliness in areas like concurrent, heterogeneous, distributed, and real-time computing. Recent projects include the Low-level Reasoning Machine (LLRM), Popcorn Linux, and LibrettOS. He teaches courses such as ECE/CS 5510 (Multiprocessor Programming), ECE/CS 5544 (Compiler Optimizations), and ECE 5984/SS (Modern Binary Exploitation). His service roles include editorial board positions at IEEE Transactions on Cloud Computing and ACM Transactions on Embedded Computing Systems, and he co-chaired ACM Systor 2025. Ravindran has published over 330 papers, earning nine best paper awards, and has mentored 26 PhD students, 23 postdocs, and 11 research faculty. Notable honors include ACM Distinguished Scientist and an Office of Naval Research Faculty Fellowship. His research group explores projects like LLRM (binary security verification), Popcorn Linux (heterogeneous ISA systems), and KairosVM (real-time hypervisor). Recent advancements include Stramash OS (ASPLOS'25) and Hexo (DOD infrastructure offloading).

Kristjon Cikoمشاهده پروفایل

پژوهشگر ارشد

• Network Architecture
• Distributed Systems
• Recursive InterNetwork Architecture (RINA)
• +۳ مورد دیگر

Kristjon Ciko is a Research Fellow at the University of Oslo's Faculty of Mathematics and Natural Sciences, affiliated with the Department of Informatics under the Networks and Distributed Systems group. His work focuses on advancing network architectures and distributed systems. Research Interests: Ciko's research spans network architecture, particularly Recursive InterNetwork Architecture (RINA), congestion control mechanisms, and energy-efficient computing. His studies address challenges in next-generation network design, throughput optimization, and sustainable computing systems. Publications: Recent work includes innovations in energy efficiency for throughput computing, software-based server energy management, and congestion control solutions for datacenter networks. His research bridges theoretical advancements with practical implementations.

Alexandru Iosupمشاهده پروفایل

استاد

• Benchmarking
• Cloud Computing
• Serverless Computing
• +۳ مورد دیگر

Prof. Alexandru Iosup is a Full Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science (Department of Computer Systems), Network Institute, and Massivizing Computer Systems. He specializes in distributed systems, cloud computing, and performance engineering. His work focuses on benchmarking, serverless computing, and sustainable data center operations. Academic Roles: Full Professor in Computer Systems, Network Institute, and Massivizing Computer Systems. Research Interests: Cloud computing, serverless systems, data center risk analysis, and large-scale graph processing. His research spans 197 publications, emphasizing empirical studies of cloud services, data center management frameworks (e.g., RADiCe, FAILS), and sustainability in computing. Notable achievements include the Royal Dutch Young Academy induction (2016) and Netherlands ICT Research Award (2016). Current projects include leading the Extreme and Sustainable Graph Processing initiative, aiming to address societal challenges through scalable graph analytics. He teaches courses like Honours Research Projects and Distributed Systems.

Balaji Prabhakarمشاهده پروفایل

استاد

• Computer Networks
• Data Center Networks
• Societal Networks
• +۵ مورد دیگر

Balaji Prabhakar is a Professor of Electrical Engineering and Computer Science at Stanford University. He holds the VMware Founders Professorship in Computer Science and is affiliated with the School of Engineering. His research focuses on computer networks, including data center networks, societal networks (transportation, energy, recycling), and network algorithms. He has pioneered congestion control mechanisms like QCN and DCTCP, and developed incentive systems to reduce traffic congestion through behavioral 'nudges.' Prabhakar's work integrates principles from computer networks with societal infrastructure challenges. Key areas include energy-efficient transmission, randomized algorithms for scheduling, and network measurement architectures like Counter Braids. He has received numerous accolades, including the IEEE Innovation in Societal Infrastructure Award and the Rollo Davidson Prize. His teaching includes courses on probabilistic systems analysis, network algorithms, and incentive mechanisms. Current and former students have contributed to foundational work in data center networking and societal infrastructure optimization. His lab collaborates with industry partners like VMware and Infosys, applying theoretical insights to real-world systems.

Manya Ghobadiمشاهده پروفایل

دانشیار

• Computer Networks
• Machine Learning Systems
• Cloud Infrastructure
• +۴ مورد دیگر

Manya Ghobadi is an Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, affiliated with the Computer Science & Artificial Intelligence Laboratory (CSAIL). Her research focuses on efficient systems for machine learning, cloud infrastructure, and reconfigurable networks. She holds appointments in both the School of Engineering and the Department of EECS at MIT. Education: PhD from the University of Toronto, prior experience at Microsoft Research and Google before joining MIT. Research Interests: Systems for ML, cloud infrastructure, data center networks, optical networks, hardware-software co-design, and network optimization. Publications: Over 50+ papers in top venues including SIGCOMM, NSDI, HotNets, and MLSys, with awards such as the NSF CAREER and Sloan Fellowship. Students: Advises 10+ PhD candidates including Mingran Yang (Microsoft Research Fellow) and Sudarsanan Rajasekaran. Awards: Sloan Fellowship, ACM SIGCOMM Rising Star, Optica Simmons Memorial Speakership. Labs/Teams: Leads research on photonic computing (NetBlocks, Lightning) and network optimization (Cassini, TopoOpt). Collaborates with industry partners like Juniper and Google.

Dean M. Tullsenمشاهده پروفایل

استاد

• Computer Architecture
• Multithreading
• Multicore Processors
• +۷ مورد دیگر

Dean M. Tullsen is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego. He leads the High Performance Processor Architecture and Compilation Lab and focuses on computer architecture, particularly multithreading, multicore processors, secure execution, and energy-efficient design. His research bridges hardware and software for parallel computing, security, and resource optimization. Education: Ph.D. from the University of Washington (1996), B.S. and M.S. from UCLA. Research Interests: Computer architecture, multithreading, speculative execution, hardware security, energy efficiency, and heterogeneous computing. Scientific Awards: Best Paper Awards at USENIX Security Symposium (2024), IEEE S&P (2023), and Distinguished Paper Awards at POPL (2021), ASPLOS (2023), plus the 2020 ACM SIGARCH/IEEE-CS TCCA Influential ISCA Paper Award. Students: Advised 30+ graduate students, including Craig Disselkoen, Mohammadkazem Taram, and Ashish Venkat, who now hold positions at Google, Microsoft, and academia. Lab: Leads the High Performance Processor Architecture and Compilation Lab, advancing techniques in secure execution and parallel computing.

Jason Marsمشاهده پروفایل

استاد

• Computer Architecture
• Warehouse-Scale Computing
• Machine Learning Systems
• +۳ مورد دیگر

Jason Mars is a Professor at the University of Michigan's Department of Electrical Engineering and Computer Science, leading the Clarity-Lab. His research focuses on cross-layer architectures and runtimes for future computing systems, particularly in warehouse-scale computers. He has pioneered projects like Sirius (an open voice/vision personal assistant), Protean Code (dynamic code transformations), and Adrenaline (tail latency management). His work addresses challenges in energy efficiency, resource allocation, and performance optimization in large-scale systems. Key contributions include architectural designs for AI services, thermal management strategies, and compiler techniques for approximate computing. Mars collaborates with industry leaders like IBM and has advised numerous students who have published at top conferences such as ASPLOS and HPCA. Recent research spans AI ethics, scalable programming models (e.g., Data Spatial Programming), and edge-cloud collaboration frameworks like Neurosurgeon. He has delivered invited talks at Baidu, IBM Watson, and conferences worldwide, emphasizing the societal impact of computing systems.

Stephan Olariuمشاهده پروفایل

استاد

• Vehicular Ad Hoc Networks (VANETs)
• Cybersecurity
• Telemedicine
• +۴ مورد دیگر

Stephan Olariu is a Professor of Computer Science at Old Dominion University (ODU), affiliated with the College of Sciences. He holds a Ph.D., M.Sc., and B.S. in Computer Science from McGill University (1982–1986). His research focuses on vehicular ad hoc networks (VANETs), cybersecurity, telemedicine, and vehicular cloud computing. He has led projects like TRENDS, a cyber-physical system for traffic event detection, funded by ODU (2011). Dr. Olariu's work emphasizes vehicular networks' security and efficiency, including solutions for VANETs, UAV-based medical supply delivery, and blockchain-driven decentralized marketplaces. He explores smart city technologies, such as traffic optimization and environmental impact reduction. His recent publications address topics like drone coordination for surveillance, trust frameworks in blockchain systems, and UAV applications in counterterrorism. Grants: TRENDS (2011) and others focused on vehicular systems and telemedicine. Key Themes: Vehicular cloud computing, cybersecurity, UAV systems, and smart infrastructure. His contributions span academic leadership in computer science, with a focus on translating theoretical research into real-world applications like emergency response systems and resilient decentralized platforms.

Haonan Luمشاهده پروفایل

استادیار

• Distributed Systems
• Databases
• Concurrency Control
• +۳ مورد دیگر

Haonan Lu is an Assistant Professor in the Department of Computer Science and Engineering at the University at Buffalo (School of Engineering and Applied Sciences). His research focuses on distributed systems and databases, with particular emphasis on concurrency control, transaction processing, and database performance optimization. He holds a PhD in Computer Science from the University of Southern California (2019). Education: PhD, Computer Science, University of Southern California, 2019 Dr. Lu's work addresses challenges in distributed database systems, including optimizing skewed workloads, concurrency control mechanisms, and cross-datacenter storage efficiency. His recent projects explore latency-optimal read transactions and natural concurrency control (NCC) frameworks. He actively publishes in top-tier conferences and maintains an open research website and Google Scholar profile. Awards: No awards explicitly listed in provided materials. Advising and Grants: No specific advising records or grant information provided in the text. His research is likely supported through standard academic funding channels. Labs/Teams: No dedicated lab or team structure explicitly described in the provided content.

Jacob Hochstetlerمشاهده پروفایل

استادیار بالینی

• Connected and Autonomous Vehicles
• Data Storage Systems
• Edge Computing
• +۳ مورد دیگر

Jacob Hochstetler is a Clinical Assistant Professor in the Department of Computer Science and Engineering at the University of North Texas. His research focuses on advanced computing architectures for connected autonomous vehicles, data storage systems reliability, and edge computing applications in mixed reality environments. Key research areas include vehicular networks, SSD performance optimization, ZFS-based data protection, and low-latency data sharing protocols. His work bridges theoretical computer science with practical implementations in urban smart systems and embedded deep learning for vehicular edge computing. Publications span topics from quad-level cell SSDs to police patrol optimization in smart cities, demonstrating cross-disciplinary engagement with both technical and societal challenges. No awards or grants are explicitly listed in the provided materials. No formal advisees are recorded, though his research areas suggest potential for collaborative projects in automotive systems and data center reliability.