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Kerrianne HarringtonView profile

Researcher

• Optical Fibre Technology
• Laser Physics
• Medical Applications of Light
• +3 more

Kerrianne Harrington is a Researcher in the Department of Physics at the University of Bath, focusing on developing hollow core optical fibres for advanced applications. Her work contributes to the 'u-Care' interdisciplinary project, aiming to create compact UV-C light sources for medical therapies targeting drug-resistant pathogens and precision cancer surgery. She also leads the 'Robotic microscopy for globally accessible science and healthcare' project, advancing fibre-based imaging and diagnostic tools. Her research expertise spans optical fibre fabrication, splicing, and simulation, with a focus on anti-resonant fibres enabling UV light transmission below 220 nm—unachievable in traditional fibres. Key contributions include Axi-Stack manufacturing techniques and methods to minimize interconnection losses in hollow-core fibres. Collaborations involve projects funded by EPSRC and The Royal Society, addressing quantum communication, low-loss fibre integration, and biomedical applications. Her work aligns with UN SDGs, particularly in advancing health and innovation. Recent publications highlight achievements in supercontinuum generation, UV light guidance, and multi-core fibre designs. Harrington’s research bridges fundamental physics with practical innovations in healthcare, photonics, and quantum technologies.

Per StenströmView profile

Professor

• Computer Architecture
• Memory Systems Optimization
• Energy-Efficient Computing
• +3 more

Professor Per Stenström is affiliated with the Department of Computer Science and Engineering at Chalmers University of Technology . His research focuses on computer architecture , memory systems optimization , and energy-efficient computing , with significant contributions to DNN accelerator design and cache management . Research Trends : His recent publications emphasize Memory compression techniques for energy efficiency Hardware-software co-design for DNN acceleration Security in microarchitectural optimizations Hybrid memory systems for near-memory computing These works span both theoretical and applied aspects of computer architecture, with a particular focus on data redundancy elimination , parallel processing , and quality-of-service constraints . His work has influenced the development of energy-aware resource management frameworks and resilient EU HPC systems , as evidenced by his long-standing contributions to the field since the early 2010s.

• Distributed Systems
• Cloud Computing
• Fault Tolerance
• +3 more

Rodrigo Miragaia Rodrigues is a full professor at the Instituto Superior Técnico (ULisboa) and a researcher at INESC-ID since 2015. He previously held roles as an associate professor at Universidade Nova de Lisboa, tenure-track faculty at MPI-SWS, and completed his PhD at MIT in 2005 under Barbara Liskov. Education: PhD in Computer Science, MIT, 2005 Research Interests: Focuses on distributed systems, fault-tolerant computing, cloud infrastructure, and consistency models. His work bridges theoretical foundations and practical implementations, addressing challenges in geo-replication, secure analytics, and resource allocation in serverless environments. He emphasizes scalable systems and resilient data management. Awards: Best Paper Award at SOSP ERC Starting Grant Google Faculty Research Award Advising & Grants: Has advised 7 PhD students as main advisor, with graduates in top institutions like Purdue, TU Munich, and USTC. Secured funding from the European Research Council (ERC) and Google, focusing on projects like DependableCloud (ERC Grant 307732). Labs & Teams: Leads research at INESC-ID and previously directed the Dependable Systems Group at MPI-SWS. Active in academic leadership roles, including President of the Scientific Council at IST.

Nabil J. SarhanView profile

Associate Professor

• Computer Systems
• Deep Learning
• Video Streaming
• +5 more

Dr. Nabil J. Sarhan is an Associate Professor of Electrical and Computer Engineering at Wayne State University , where he directs the Computer Systems and Deep Learning Research Laboratory and the interdisciplinary M.S. Program in Artificial Intelligence (Systems and Hardware Track) . He previously served as Graduate Program Director and College of Engineering Faculty Assembly Chair. Education : Ph.D. and M.S. in Computer Science and Engineering from Pennsylvania State University (GPA 4.0), B.S. in Electrical Engineering from Jordan University of Science and Technology Internationally recognized for expertise in computer systems , deep learning , video streaming , and AI hardware accelerators , Dr. Sarhan's research bridges theoretical and applied domains in automated video surveillance and medical AI systems . His work includes novel approaches to epileptic seizure prediction , energy-efficient neural network accelerators , and mixed-signal circuit design for edge computing. Recent grant highlights include a $418,907 National Science Foundation award for reconfigurable AI accelerator development. His patent (US Patent 9,313,463) on automated video surveillance systems demonstrates practical technology impact. Scientific Awards IEEE SEM Outstanding Professional of the Year Wayne State President's Excellence in Teaching Award College of Engineering Excellence in Teaching Award WSU Academy of Teachers (2022) IEEE Senior Member (2016) As an educational reform leader , he has chaired over 20 ABET accreditation panels in Saudi Arabia and Palestine, evaluating programs in electrical engineering, computer science, and software engineering. His intellectual property expertise spans significant patent infringement cases including ACQIS v. ASUSTek and VideoShare v. Google .

• Informatics Engineering
• Serious Games
• Virtual Reality
• +10 more

Hugo Barbosa is an active faculty member in Informatics Engineering, affiliated with Lusófona University – Porto University Center and Porto Polytechnic (IPP). He teaches both theoretical and practical aspects of informatics and collaborates with the Social Innovation and Interactive Systems (SIIS) R&D unit at ISEP, focusing on applied research in interactive technologies for education and healthcare. Master’s in Informatics Engineering – Graphics and Multimedia Systems Bachelor’s in Informatics Engineering – Computers and Systems Professional Aptitude Certificate (CAP) PhD candidate in Informatics Engineering at FEUP (60 ECTS completed) Senior Member, Portuguese Engineers Association (OE) Hugo Barbosa's research lies at the intersection of technology and education, with a strong emphasis on serious games , virtual reality , and interactive simulation for training and rehabilitation. His work explores how adaptive digital environments can enhance learning, particularly in medical and engineering contexts, and investigates the integration of cybersecurity and network optimization in these systems. He focuses on user-centered design, aiming to create accessible and effective solutions for diverse populations, including the elderly and individuals with mobility or cognitive challenges. His publication record from 2009 to 2020 reveals a consistent trajectory in applied informatics, with a recent concentration on serious games for rehabilitation , cybersecurity in healthcare , and digital privacy . These works reflect a multidisciplinary approach, bridging computer science with health sciences and education. His research often addresses real-world challenges such as data protection in national health systems, adaptable therapeutic environments, and immersive training simulations. Hugo Barbosa has been recognized as a Senior Member of the Portuguese Engineers Association (OE), a professional distinction reflecting his contributions and expertise. While no additional awards are explicitly mentioned, his active participation in conferences and publications in research journals underscores his scholarly engagement. He is involved in research advising and project development through his work with SIIS at ISEP/IPP, though no named students are listed. His academic and professional activities suggest involvement in research grants and collaborative projects, particularly within R&D units focused on social innovation and interactive systems. His dual teaching role across institutions also indicates a broad educational impact. Hugo Barbosa is actively involved with the Social Innovation and Interactive Systems (SIIS) research unit at ISEP, Porto Polytechnic. This lab focuses on developing innovative interactive applications for social good, particularly in healthcare, education, and rehabilitation. His work there involves designing and evaluating multimedia and simulation-based tools that support learning and therapy, leveraging technologies like serious games and virtual environments.

Yong ChenView profile

Professor

• Data-Intensive Computing
• Parallel and Distributed Computing
• High-Performance Computing
• +3 more

Dr. Yong Chen is a Professor and Interim Department Chair in the Computer Science Department at Texas Tech University (TTU), where he founded the Data-Intensive Scalable Computing Laboratory (DISCL). He also serves as Co-Director of the NSF Cloud and Autonomic Computing Center (CAC@TTU), focusing on data-intensive computing, high-performance computing (HPC), cloud systems, and parallel/distributed architectures. His research bridges hardware-software co-design for scientific and enterprise applications. Ph.D., Computer Science, Illinois Institute of Technology (2009) M.S., Computer Science, University of Science and Technology of China (2003) B.E., Computer Engineering, University of Science and Technology of China (2000) Dr. Chen's research spans data-intensive computing, HPC, cloud systems, and parallel architectures. He develops scalable solutions for scientific discovery and enterprise computing, emphasizing systems software, storage optimization, and hardware-software co-design. His work addresses challenges in metadata management, 3D-stacked memory, and efficient resource allocation in distributed environments. Recent publications include studies on 3D-stacked memory optimization (IEEE TC), metadata indexing (SC), and parallel file system reliability (ICS). His work is characterized by interdisciplinary collaboration and practical applications in HPC domains. NSF-TCPP Early Adopter Status Award Best Paper Award (IPDPS'21) Outstanding Teaching Assistant, IIT (2006) Dr. Chen advises students through graduate and undergraduate research assistantships at DISCL and CAC@TTU, offering financial support for qualified candidates. He has contributed to major conferences as Program Co-Chair (ICPP) and Committee Member (IPDPS, CCGrid, ISC, HPCAsia). Labs/Teams: Data-Intensive Scalable Computing Laboratory (DISCL), NSF Cloud and Autonomic Computing Center (CAC@TTU).

Bingyao LiView profile

Assistant Professor

• Computer Architecture
• High-Performance Computing
• Multi-GPU Systems
• +4 more

Bingyao Li is an incoming tenure-track Assistant Professor at the University of California, Riverside's Computer Science and Engineering Department, starting Fall 2025. She is currently a fourth-year Ph.D. student at the University of Pittsburgh, advised by Dr. Xulong Tang. Her research focuses on computer architecture, particularly multi-GPU systems, virtual memory management, and address translation for high-performance computing. Educational Background: She holds a B.E. (2017) and M.S. (2020) from Tianjin University's College of Intelligence and Computing. Her Ph.D. work at Pitt emphasizes GPU architecture and system-level optimizations for large-scale applications. Research Interests: Her work spans advanced computer architectures, multi-GPU optimization, and parallel computing systems. She explores solutions like object-aware page management (OASIS), TLB enhancements (STAR), and dynamic page placement (GRIT) to improve multi-GPU performance. She also investigates system-level optimizations for large language models and GPU ecosystems from hardware to applications. Awards: She has received the CS50 Outstanding Research Fellowship (2022, 2023) and the SCI Fellowship from the University of Pittsburgh. Her contributions include internships at NVIDIA's Architecture Research Group and talks on multi-GPU computing at NVIDIA and Tianjin University. Future Work: As a faculty member, she plans to mentor PhD students in Winter/Spring/Fall 2026, focusing on next-generation GPU systems and high-performance computing challenges. Her lab will address scalability, efficiency, and emerging applications in parallel computing.

Zhu ZhichunView profile

Associate Professor

• Computer architecture
• Performance modeling and evaluation
• Energy-efficiency computer designs

Zhu Zhichun is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago, College of Engineering. His primary research focuses on computer architecture, performance modeling, and energy-efficient designing of computer systems. Ph.D. in Computer Science from College of William and Mary (2003) B.Sc. in Computer Engineering from Huazhong University of Science and Technology, China (1992) His research interests center around computer architecture , particularly in performance modeling and evaluation , energy-efficiency computer designs , and memory system optimization . He investigates techniques for improving power efficiency, thermal management, and bandwidth utilization in DRAM and PCM memory systems, with a focus on multicore processors and low-power designs. Zhu's publications demonstrate consistent work in memory architecture and power-efficient computing . Key trends include thermal modeling , DRAM optimization , and hybrid memory systems . His collaborations with Zhao Zhang, Jiang Lin, and other researchers highlight interdisciplinary approaches to solving computer architecture challenges.

• Computer Architecture
• Embedded Systems
• High-Performance Computing
• +9 more

Zapater Sancho Marina is an Associate Professor at the ReDS Institute (Institute of Reconfigurable and Embedded Digital Systems) within the School of Engineering and Management Vaud (HEIG-VD), part of the University of Applied Sciences and Arts Western Switzerland (HES-SO). She holds dual master's degrees in Electronic and Telecommunication Engineering from Universitat Politècnica de Catalunya (2010) and a PhD in Computer Science from Universidad Politécnica de Madrid (2015). Her career includes postdoctoral work at EPFL (2016-2020) and assistant professorship at Universidad Complutense de Madrid (2015-2016). Education BSc & MSc in Electronic Engineering (UPC 2010) PhD in Computer Science (UPM 2015) Research Focus spans cross-layer optimization of heterogeneous architectures for performance and energy efficiency, with emphasis on: Embedded systems (IoT/edge computing) High-performance compute architectures Analog in-memory computing for AI Thermal/power management in 3D chips Cloud-edge AI workload orchestration Publication Trends show expertise in RISC-V simulation frameworks, analog computing tiles for CNNs, virtual memory redesign, and AI-driven cloud performance prediction. Her recent work explores thermal-aware 3D chip management, hybrid-cache reliability optimization, and open-source teaching platforms for radio theory. Awards include a Spanish government PhD fellowship. She has led 4 European H2020 projects since 2016 and currently serves as PI for 4 industrial collaborations (Facebook/Intel/Huawei), Innosuisse projects, and HES-SO initiatives. Labs & Teams include the ReDS Institute, EPFL's Embedded Systems Laboratory, and collaborations with Yale/Edinburgh. She co-developed the ALPINE simulation framework and SO3 operating system modifications for Midgard project validation.

• Systems
• Concurrency
• Memory Management
• +5 more

Christoph Kirsch is a Professor and Chair of the Department of Computer Science at the University of Salzburg. He also serves as Chair of the Programming Research Laboratory at the Faculty of Information Technology, CTU Prague. His research focuses on systems, concurrency, memory management, and formal methods, with notable contributions including the Selfie educational software project and work on symbolic execution. He is a prolific author with over 50 publications in top venues like LCTES and EMSOFT. Education: Ph.D. in Computer Science (details not specified). His teaching includes courses on elementary computer science concepts and curricula development. He advises students such as Anna Bolotina and has graduated over a dozen PhD students. Research highlights include the Selfie system (self-referential C compiler and emulator), work on concurrency primitives like Scal and Timestamped Stack, and contributions to real-time systems (Logical Execution Time, Variable-Bandwidth Servers). His recent focus includes teaching digital thinking and evaluating eval in R programs. He has organized conferences like MPLR’24 and served on program committees for EuroSys and RTNS. His book Elementary Computer Science emphasizes foundational concepts for broad audiences.

Gurindar S. SohiView profile

Professor

• Computer Architecture
• Parallel Computing
• Memory Systems
• +3 more

Gurindar S. Sohi is a Vilas Research Professor , John P. Morgridge Professor , and E. David Cronon Professor of Computer Sciences at the University of Wisconsin-Madison , affiliated with both the College of Engineering (Department of Electrical and Computer Engineering) and the Department of Computer Sciences . He served as Department Chair of Computer Sciences from 2004 to 2008 and has been a faculty member since 1985. Education: Ph.D. in Electrical and Computer Engineering from the University of Illinois (1985) Sohi's research focuses on high-performance computer architecture , particularly instruction-level parallelism (ILP) , multiscalar processing , and speculative execution techniques . His work has influenced commercial microprocessor design through innovations like non-blocking caches , memory dependence prediction , and trace caches . Key publications represent 15+ years of research in dynamic scheduling , parallel computing paradigms , and processor simulation tools (e.g., Simplescalar). Industry collaborations span major manufacturers like Intel , IBM , and HP . Scientific recognition includes: ACM SIGARCH Maurice Wilkes Award (1999) Vilas Associate (1997) WARF Kellett Mid-Career Award (2000) WARF Named Professor (2007) ACM and IEEE Fellow National Academy of Engineering member Teaching contributions include advanced courses on computer architecture (CS/ECE 752, 757) and foundational computer organization classes (CS/ECE 354, 552). He has graduated 18 Ph.D. students , including six NSF CAREER awardees and a Sloan Research Fellow.

Hoai Phuong HaView profile

Professor

• Green and energy-efficient computing
• Parallel and distributed computing systems
• Cyber-physical systems
• +3 more

Professor Hoai Phuong Ha is affiliated with UiT The Arctic University of Norway's Department of Computer Science. A leading expert in green computing and cyber-physical systems, they contribute to Arctic research through the Distributed Arctic Observatory (DAO) and Arctic Green Computing (AGC) group. Founded ARC (Arctic Center for Sustainable Energy) PI in EU FP7 EXCESS and H2020 TAILOR projects WP-leader in EEA POLNOR HAPADS and RCN PREAPP projects Their research focuses on energy-efficient computing, including IoT systems, edge computing, and parallel algorithms. Recent work addresses wireless charging trajectories (eU2U, 2025), smart grid networks (GridWatch, 2024), and pollution monitoring (2024). Publications span cyber-physical observatories, sensor calibration, and distributed systems optimization. Key trends in their 15 most recent articles (2017-2025) include: energy-aware data structures, Arctic-adapted IoT deployments, and sustainable computing methods. Collaborations span EU and Norwegian grants with applications in smart grids, environmental sensing, and high-performance computing. Co-founder of Arctic Center for Sustainable Energy (2017) Active in EEA POLNOR (2019-2023) and RCN eX3 infrastructure project Their lab (Realfagbygget A237) develops systems for Arctic tundra monitoring, including UAV-powered networks and energy-harvesting protocols. Students include researchers from multiple international collaborations.

• Microelectronics
• Circuit Design
• Analog-to-Digital Converters
• +3 more

Zhangming Zhu is a Professor at Xidian University in the School of Microelectronics . He specializes in Microelectronics and Circuit Design , with a focus on Analog-to-Digital Converters (ADCs) , CMOS Technology , and Low-Power Electronics . His work addresses challenges in high-speed, high-precision, and energy-efficient circuit design. Research Interests: His publications highlight expertise in ADCs, PLLs, energy harvesting, biomedical sensors, and RF systems. Recent Publications: 2025 papers include a 12-bit 1.5-GS/s ADC , a 5-18-GHz Quadrature Receiver , and 20-bit SAR ADC with thermal error suppression. Collaborations: Frequently co-authors with Shubin Liu, Yi Shen, Ruixue Ding, and others. Applications: Work spans consumer electronics, IoT, biomedical devices, and energy-efficient systems.

David Black-SchafferView profile

Professor

• Computer Architecture
• Memory Systems
• Parallel Programming
• +4 more

David Black-Schaffer is a Professor at Uppsala University's Department of Information Technology, specializing in computer systems research. As of 2023, he serves as Dean of Research for the Faculty of Science and Technology. His work bridges software and hardware innovations to enhance data movement efficiency in computer systems, with applications commercialized through a startup and integrated into industry standards like OpenCL. Black-Schaffer earned his PhD in Electrical Engineering from Stanford University in 2008, focusing on many-core processor programming. His career spans roles at Apple Inc. (contributing to OpenCL standards), postdoctoral research at Uppsala University, and academic progression from assistant to full professor (2010–2017). He has held leadership roles including Head of the Division of Computer Systems (2022) and department representative on the faculty Advisory Committee for Research (2021). His research spans computer architecture, memory systems, parallel programming, and simulation techniques. Recent publications (2024–2020) explore garbage collection, cache optimization, memory contention, NUMA systems, and instruction scheduling. Key trends include software-hardware co-design for power efficiency, reuse-aware data placement, and machine learning for performance modeling. Knut & Alice Wallenberg Foundation: Wallenberg Academy Fellowship Prolongation (2020–2025), Wallenberg Academy Fellow (2016–2021) Swedish Research Council (VR): Project Grant (2019–2024), Young Researcher Grant (2015–2018), Framework Grant (2012–2017) European Research Council: ERC Starting Grant (2017–2022) Teaching Awards: Uppsala Engineering and Science Student Union Pedagogical Prize (2012), Uppsala University Pedagogical Prize (2016), Uppsala Technical Physics Students' Teaching Award (2019) Other Grants: ScalableLearning flipped classroom project (2012–2020), Arm Ltd. collaborations on memory system designs He pioneered flipped-classroom teaching through the ScalableLearning project, impacting over 80,000 students. His research is conducted in collaboration with institutions like Arm Ltd., with past contributions to Apple's OpenCL implementation and UPMARC research center.

Tilmann RablView profile

Professor

• Stream Processing
• Big Data Management
• End-to-End Machine Learning Pipelines
• +1 more

Tilmann Rabl is a Professor at the Digital Engineering Faculty of the University of Potsdam and holds the chair for Data Engineering Systems at the Hasso Plattner Institute. He is a cofounder and scientific director of the startup bankmark. Rabl earned his PhD at the University of Passau in 2011 and spent four years as a postdoc at the University of Toronto's Middleware Systems Research Group (MSRG). From 2015 to 2019, he served as senior researcher and visiting professor at Technische Universität Berlin's Database Systems and Information Management (DIMA) group and as Vice Director of the Intelligent Analytics for Massive Data (IAM) Group at DFKI. Rabls research interests center on stream processing, big data management, end-to-end machine learning pipelines, and benchmarking data processing systems. His recent work explores hardware-conscious database design, GPU memory optimization, and CPU cache prefetching strategies. EDBT Best Experiments and Analysis Paper Award (2025) ICDE Outstanding Meta-Reviewer (2024) SIGMOD Distinguished Reviewer (2024) EDBT Best Paper Award (2019, 2022) ACM SIGMOD Research Highlight (2022) VLDB Distinguished Reviewer (2022) ICDE Best Paper Award (2021) SIGMOD Best Paper Award (2020) DEBS Grand Challenge & Audience Awards (2020) SIGMOD Distinguished Reviewer (2020, 2024) EDBT Best Demonstration Award (2017) Rabls advising includes Clemens Schielicke, Finn Schöllkopf, and Tobias Jordan, who are working on master's theses in areas like memory bandwidth expansion, SIMD-accelerated sort-merge joins, and probabilistic filters for intermediate data processing. His group also includes PhD students and postdocs across ongoing projects.