Find Academic Supervisors

• Real-time computer resource management systems
• Heterogeneous memory systems
• Programming models for heterogeneous computing systems
• +2 more

Lazaros Papadopoulos serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Democritus University of Thrace since May 2024, focusing on computational resource management for embedded and high-performance systems. His work bridges hardware-software co-design with energy-efficient computing paradigms. His academic credentials include: Bachelor's in Electrical and Computer Engineering from Democritus University of Thrace (2005) Master's degree from the same institution (2008) PhD from the National Technical University of Athens (2016) Research centers on optimizing computing infrastructure through real-time resource management, heterogeneous memory architectures, and AI workload acceleration. His investigations target energy-performance tradeoffs in GPU systems, persistent memory integration, and edge-device neural network deployment, with direct applications in sustainable computing and high-performance data processing. Publication analysis (2018-2022) reveals consistent focus on heterogeneous system optimization, particularly energy-aware GPU acceleration frameworks, memory management for DRAM/NVM hybrids, and efficient CNN implementations for edge devices. Key thematic threads include sustainable computing practices, hardware-aware AI deployment, and memory hierarchy innovations. Scientific recognition includes: Two Best Paper Awards Research leadership spans major EU initiatives: Work Package Coordinator for LAGO (Horizon Europe, 2022-2024) and PRAETORIAN (H2020, 2022-2024); Technical Coordinator for EXA2PRO (H2020, 2018-2021); and Work Package Coordinator roles in SDK4ED (H2020, 2018-2020) and EXCESS (H2020, 2013-2016). These projects address embedded systems security, exascale programming models, and energy-efficient computing toolchains. He operates within the Computer Architecture and High Performance Systems laboratory, directing research on computational resource orchestration for next-generation heterogeneous platforms.

Haris VolosView profile

Assistant Professor

• Computer Architecture
• Operating Systems
• Data Storage and Processing
• +4 more

Haris Volos is an Assistant Professor in the Department of Informatics at the University of Cyprus . He holds a Ph.D. in Computer Science from the University of Wisconsin-Madison (2012), following B.E.E. degrees from the National Technical University of Athens (2005). Before academia, he worked at Hewlett Packard Labs (2013–2018) and Google (2018–2019). His research focuses on Computer Architecture , Operating Systems , and Data Storage and Processing , with recent work on energy-efficient CPU architectures, disaggregated memory systems, and persistent memory frameworks. Education: B.E.E. (2005), National Technical University of Athens M.Sc. (2007), University of Wisconsin-Madison Ph.D. (2012), University of Wisconsin-Madison Key Research Themes: Energy-efficient CPU core idle-state architectures Disaggregated memory protection and replication Persistent memory systems and transactional memory Big data processing over hybrid memory tiers Recent Contributions: His work includes frameworks like Panthera for holistic memory management and AgileWatts for energy-proportional servers. He also pioneered systems like HOPS (Hands-off Persistence System) for persistent memory. Labs/Teams: Active in the university's informatics research clusters, focusing on hardware-software co-design and scalable data systems.

Daniel O'KeeffeView profile

Senior Lecturer

• distributed systems
• security
• databases
• +7 more

Daniel O'Keeffe is a Senior Lecturer in Computer Science at the Department of Computer Science, Royal Holloway University of London (RHUL). He is affiliated with the Centre for Programming Languages and Systems (CPLS) and the Systems and Software Security Lab (S3Lab). PhD from University of Cambridge Computer Laboratory Post-doctoral research at Imperial College London Industry experience in financial software engineering His research spans distributed systems, security, databases, and networking, with a focus on cloud computing security and blockchain security. Recent work explores performance-security trade-offs in proof-of-stake blockchains under the Revoke project. Key research projects include SecureCloud (cloud security for critical infrastructure), ITA-DSM (edge computing stream processing), SeReCa (secure hardware for cloud protection), and CloudSafetyNet (data leakage monitoring). Current projects receive funding from the Engineering and Physical Sciences Research Council (EPSRC) and the Ethereum Foundation. Scientific Awards : ERA Track - Best Paper Award at SANER 2024 Grants : REDONDA: EPSRC-funded project on Byzantine State-Machine Replication for blockchain (2024-2027) Consensus-layer mitigations for validator ransomware attacks: Ethereum Foundation grant (2022-2023) Labs & Groups : Centre for Programming Languages and Systems (CPLS) Systems and Software Security Lab (S3Lab) OPERA group (University of Cambridge) LSDS group (Imperial College London)

Panagiota FatourouView profile

Professor

• Parallel and Distributed Computing
• Concurrent Data Structures
• Transactional Memory
• +8 more

Dr. Panagiota Fatourou is a Professor in the Department of Computer Science at the University of Crete and a senior researcher at the Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH). She holds a dual affiliation, contributing significantly to both institutions. She has previously served as faculty at the University of Ioannina and held postdoctoral positions at the Max-Planck-Institut für Informatik and the University of Toronto. She has also been a visiting professor at École Polytechnique Fédérale de Lausanne (EPFL). Her research spans the theoretical and practical foundations of parallel and distributed computing. She is a leading expert in concurrent data structures, transactional memory, and the use of persistent memory in system design. Her work integrates theoretical rigor with practical implementation, often publishing in top-tier venues like PPoPP, PODC, SPAA, and PVLDB. Recent publications highlight her focus on efficient garbage collection for multiversioning, persistent data structures, and distributed data series similarity search, reflecting a trend towards high-performance, fault-tolerant systems for modern hardware. Best Paper Award, PPoPP 2022 Marie-Curie Individual Fellowship FSMP Distinguished Professor Fellowship ACM Distinguished Speaker Featured ACM Member Dr. Fatourou has a strong record of leadership and mentorship. She has advised numerous MSc and PhD students and is actively recruiting for her PERSIST project, funded by HFRI. She has led major research initiatives, including the EU-funded TransForm network and the GreenVM project. Her leadership extends to the broader community, where she has served as Past Chair of the ACM Europe Council, Chair of the Greek ACM-W Chapter, and on the steering committees of PODC and OPODIS. She has also co-organized key events on gender equality in computing, such as the Summits on Gender Equality in Computing (GEC) and the WISTEM Summer School. She is deeply involved in the academic service, frequently serving on program committees for premier conferences such as SPAA, NETYS, and SRDS. Her laboratory and research team at FORTH ICS and the University of Crete focus on building the theoretical underpinnings and practical implementations of next-generation concurrent and distributed systems.

• Microelectronics
• Nanotechnology
• VLSI Design
• +7 more

Sumeet Gupta is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School of Electrical and Computer Engineering. His research focuses on device-circuit co-design in emerging nanotechnologies, spintronics, and low-power VLSI design. He leads interdisciplinary efforts in ferroelectric devices, neuromorphic computing, and energy-efficient hardware for AI applications. Education: B.Tech from IIT Delhi (2006), M.S. and Ph.D. from Purdue University (2008, 2012). Research Interests: Ferroelectric and spintronic materials for next-gen computing Non-Boolean computing architectures Compute-in-memory accelerators Low-power and variation-tolerant VLSI design Domain wall dynamics in thin films Neuromorphic engineering Key Contributions: Over 50+ peer-reviewed publications on ferroelectric transistors, crossbar array optimizations, and fault-tolerant neural network hardware. His work bridges material science, device physics, and circuit design to enable energy-efficient computing systems.

Nathan BeckmannView profile

Professor

• Computer Architecture
• Embedded Systems
• Energy-Efficient Computing
• +4 more

Nathan Beckmann is a Courtesy Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, part of the College of Engineering. His research focuses on computer architecture, embedded systems, energy-efficient computing, and memory hierarchy design. He explores topics such as dataflow architectures, near-data computing, and cache optimization to enhance performance and reduce energy consumption in modern systems. His work spans both theoretical and applied aspects, including hardware-software co-design for reconfigurable systems, low-power IoT architectures, and novel caching strategies for emerging memory technologies like flash and MRAM. Key contributions include frameworks for ultra-low-power CGRAS, energy-minimal dataflow SoCs, and sustainable caching solutions. Dr. Beckmann's recent articles emphasize innovations in spatial dataflow programming models, task parallelism control, and polymorphic cache hierarchies. His research often targets real-world applications in edge computing, embedded systems, and high-performance datacenters.

• Parallel Computing
• Distributed Systems
• Intelligent Storage Systems
• +5 more

Cheng Li is an Associate Professor at the School of Computer Science, University of Science and Technology of China , and Director of the Information Computing Platform at the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center. His research focuses on parallel and distributed intelligent computing systems, with an emphasis on optimizing computational efficiency through data-centric approaches. Education: PhD in Computer Science from Max Planck Institute for Software Systems (MPI-SWS) and Saarland University (2016) Bachelor's degree in Computer Science from Nankai University (2009) Research interests include distributed systems, machine learning optimization, database systems, and high-performance computing. Notable contributions include innovations in distributed training of deep neural networks, geo-replicated databases, and efficient graph processing. His work has been published in top-tier conferences like NSDI, AAAI, VLDB, and SOSP. Professional Activities : PC member at OSDI 2025, EuroSys 2024/2025, FAST 2024, and SOSP 2021. Teaching includes Systems Seminar and Compiler Principles at USTC since 2017. Grants : Secured $500k/year funding from Chinese government agencies and collaborations with Huawei/Alibaba. Active in cloud-native systems and AI infrastructure research.

Mohammadkazem TaramView profile

Assistant Professor

• Computer Architecture
• Computer Security
• Microarchitectural Attacks
• +4 more

Mohammadkazem Taram is an Assistant Professor in the Department of Computer Science at Purdue University, joining in Fall 2022. He holds a PhD from the University of California San Diego (UCSD), completed in 2022. His research focuses on computer architecture and computer security, particularly microarchitectural attacks, performance mitigations, and security-enhanced hardware design. He has been awarded the ACM SIGMICRO Dissertation Award for his doctoral work and has received several best paper awards for his publications in top-tier conferences like ASPLOS and ISCA. His research interests include hardware security vulnerabilities, secure execution environments, and optimizing performance-security trade-offs. Notable contributions include work on Extended User Interrupts (xUI) , Pathfinder control-flow attacks, and Hardware-Assisted Fault Isolation (HFI) . He actively collaborates with industry and academia, evidenced by his roles in developing novel mitigation techniques against speculative execution and side-channel attacks. Teaching: CS-426 (Computer Security), CS-593 (Microarchitecture Security), and CS-593 (Principles in Computer Architecture) at Purdue. Students: Advises Milad Esrafilian Najafabadi, Berk Aydogmus, and others, with co-advisory roles on Qi Ling and Gustavo Franco Camilo. Labs/Teams: Leads a research group focusing on hardware security and architecture, with a focus on practical and scalable defenses. Publications span top venues like ASPLOS, ISCA, and USENIX Security, with artifacts and open-source contributions. His work emphasizes bridging the gap between theoretical security concepts and real-world hardware implementations.

• Semiconductor Reliability
• Machine Learning for CAD
• Hardware Security
• +6 more

Hussam Amrouch is a Professor (W3) at the Technical University of Munich (TUM) , leading the Chair of AI Processor Design (AI-Pro) and affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI) . He also serves as the head of Semiconductor Test and Reliability (STAR) at the University of Stuttgart. His academic journey includes a Ph.D. (Dr.-Ing.) summa cum laude from Karlsruhe Institute of Technology (KIT) and leadership of the Dependable Hardware Research Group at KIT. His research spans design for reliability and testing , machine learning for CAD , hardware security , approximate computing , and emerging technologies with a focus on ferroelectric devices . Recent publications highlight applications in hyperdimensional computing , cryogenic circuits , and neuromorphic systems . Amrouch has received 8 HiPEAC Paper Awards and best paper nominations at top EDA conferences. His work is funded by organizations including the German Research Foundation (DFG) , Advantest Corporation , and the U.S. Office of Naval Research (ONR) . He has over 200 publications across multidisciplinary domains from semiconductor physics to computer architecture. As an editor at Nature Scientific Reports , he contributes to journal oversight. His technical leadership extends to program committees of major EDA conferences like DAC, ASP-DAC, and ICCAD.

Xin XinView profile

Assistant Professor

• Computer Architecture
• Memory Systems
• Reliable Hardware
• +4 more

Xin Xin is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at the University of Central Florida since 2023, specializing in computer architecture with emphasis on memory systems and reliable hardware. Her educational background includes: Ph.D. in Electrical and Computer Engineering from University of Pittsburgh (2023) Master's degree from Tsinghua University (2016) Bachelor's degree from Lanzhou University (2013) Research focuses on resilient memory subsystems, domain-specific architectures, and hardware/software reliability. Key areas include processing-in-memory designs for databases, chip-kill ECC schemes, hybrid NVM-DRAM systems, and neural network accelerator reliability. Her work bridges computer architecture with IC design and semiconductor devices. Recent publications (2019-2022) demonstrate consistent contributions to memory hierarchy optimization across top conferences (MICRO, DAC, HPCA), featuring techniques for DRAM latency reduction, cache security, and in-memory processing. The research shows progression toward energy-efficient, fault-tolerant memory systems applicable to databases and AI workloads. She actively recruits PhD students for computer architecture research and serves as a journal reviewer for IEEE Computer Architecture Letters and Transactions on Embedded Computing Systems. Current projects include low-cost processing-in-memory for in-memory databases and reliable neural network accelerators.

Jishen ZhaoView profile

Professor

• Computer Architecture
• System Software
• Machine Learning
• +5 more

Professor Jishen Zhao leads research in computer architecture, system software, and machine learning at UC San Diego's Jacobs School of Engineering. He heads the Non-Volatile System Laboratory (NVSL), ML Systems Group, and contributes to PRISM and MICS centers. His work spans memory systems, ML-infused architectures, and autonomous vehicle computing systems. Recent achievements include ACM SIGSOFT Distinguished Paper (ISSTA 2024), IEEE Micro Top Picks recognition (2021-2022), and MICRO Hall of Fame induction (2019). He advises Ph.D. students like Hengyu Zhao and Xiao Liu, and collaborates on tools like PRO-V for RTL verification and MAGE for hardware design. Key research areas include persistent memory systems (e.g., SubZero filesystem), hardware-software co-design (e.g., Learn-to-Share framework), and autonomous vehicle safety (COLA latency optimization). He serves on program committees for ISCA, MICRO, and HPCA, reflecting his industry leadership in computer architecture.

Simon PeterView profile

Associate Professor

• Operating Systems
• Networking
• Data Center Systems
• +5 more

Simon Peter is an Associate Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington since 2022. His research focuses on operating systems, networking, and energy-efficient data center systems. Previously, he held positions as an Assistant Professor at UT Austin (2016–2022) and earned his Ph.D. (Dr. sc. ETH) from ETH Zurich in 2012, with a Dipl.-Inf. from Carl-von-Ossietzky University of Oldenburg in 2006. Education: Ph.D. in Computer Science, ETH Zurich, 2012 Dipl.-Inf. (M.Sc.), Computer Science, Oldenburg University, 2006 Research Interests: Design of low-latency, scalable, and energy-efficient data center systems Virtual machine and OS design (QoS in memory management, zero-copy I/O) Programmable NICs/switches (RDMA offloading, in-network ML preprocessing) Power control planes and disaggregated storage systems Teaching: Recent courses include CSE481A Operating Systems Capstone and Data Center Systems Extensive teaching history at UW and UT Austin in operating systems and data center topics Awards & Recognition: Not explicitly listed in provided materials Advising & Grants: Actively recruiting Ph.D. students via UW’s program No grant details provided in current text Labs & Teams: Part of UW’s Distributed Systems Lab Collaborates with industry on data center innovations Personal: Music enthusiast with background in violin, electronic music production, and DJing Outdoor activities include skiing and hiking Former Demoscene participant in Germany

Yiming ZengView profile

Assistant Professor

• Quantum Networking
• Quantum Computing
• Edge Computing
• +3 more

Yiming Zeng is an Assistant Professor at the School of Computing, Binghamton University. He holds a PhD from Stony Brook University and a BS from Shanghai Jiao Tong University. His research focuses on quantum networking, quantum computing, edge computing, distributed systems, differential privacy, and decentralized optimization. He has been recognized with awards including the 2023 Sigcomm Workshop Travel Grant and the 2017 Stony Brook Academic Excellence Fellowship. Education: PhD in Electrical and Computer Engineering, Stony Brook University (2024 expected) BS in Engineering, Shanghai Jiao Tong University Research Interests: Quantum Networking: designing protocols for entanglement routing and management in quantum internets Edge Computing: optimizing edge caching, data offloading, and privacy-preserving techniques in 5G networks Decentralized Optimization: applying game theory to blockchain systems and distributed resource allocation Differential Privacy: developing methods for federated learning and data marketplaces Teaching Experience: Teaching Assistant for courses including Digital Logic Design, Electronics Laboratory, and Introduction to Electrical and Computer Engineering Labs/Teams: Active in quantum internet research and edge computing systems development, though specific lab affiliations are not explicitly stated.

Todd MowryView profile

Professor

• Computer Architecture
• Systems
• Databases
• +3 more

Todd Mowry is a Professor in the Computer Science Department at Carnegie Mellon University, affiliated with the School of Computer Science. His research focuses on enhancing microprocessor-based system performance through parallelism exploitation, including single-chip multiprocessing and latency mitigation strategies. He leads initiatives like the STAMPede project, addressing challenges in compiler-driven parallelization and hardware-software co-design. His work spans computer architecture, systems, and databases, with a strong emphasis on compiler optimization, memory management, and scalable computing. Mowry has advised students including Sam Arch, Patrick Coppock, Hongyi Jin, Ruihang Lai, and Eliot Solomon. He teaches advanced courses such as 15745 (Fall 2025) and 15418 (Spring 2025), contributing to graduate-level education in computer systems. Recent research highlights include innovations in machine learning optimization (e.g., Relax framework), efficient LLM microservices, and architectural solutions for thread-safe metadata management. His publications address topics like UDF optimization, auto-batching in neural networks, and energy-minimal dataflow systems. Mowry's projects often involve collaboration across academic and industrial partners, driving advancements in both theoretical and applied computer systems. He has contributed to frameworks like CORA for tensor compilation and NVOverlay for non-volatile memory systems, emphasizing practical scalability and efficiency.

Faisal NawabView profile

Professor

• Distributed Data Management
• Blockchain
• Edge-Cloud Computing
• +2 more

Faisal Nawab is a Professor at the University of California, Irvine , where he leads the EdgeLab (established in 2018). His research focuses on enabling technologies for Edge-Cloud Data Management and Blockchain Systems in Internet of Things (IoT) applications. The lab addresses challenges in distributed coordination, decentralization, and energy efficiency for edge environments. His work emphasizes hierarchical localization for distributed consensus, asymmetric transaction processing across edge-cloud boundaries, and memory-aware data structures to optimize edge device energy consumption. Publications span top venues in distributed systems and database research , including studies on Byzantine fault tolerance and blockchain-based trust mechanisms. Scientific contributions include foundational research on consensus protocols, as detailed in the co-authored monograph "Consensus in Data Management: From Distributed Commit to Blockchain" (Now Publishers, 2023). The lab has produced innovations like the AnyLog database , which integrates edge-cloud dynamics with blockchain immutability for real-world IoT deployments.