جست‌وجوی استاد و پژوهشگر

• Computer Arithmetic
• RISC-V
• Cyber-Physical Systems
• +۴ مورد دیگر

Federico Rossi is an Assistant Professor at the Department of Information Engineering, University of Pisa, and a Research Fellow (RTD-A) in H2020 projects. His research focuses on computer arithmetic, RISC-V open platforms, cyber-physical systems (CPSs), and digital twins. He explores interdisciplinary applications of AI in digital twins for environmental and engineering systems. His work integrates machine learning, sensor data analysis, and low-precision computing to enhance system efficiency and autonomy. Research Interests: Computer Arithmetic & RISC-V Architecture Cyber-Physical Systems (CPS) Design AI-Driven Digital Twins for Environmental Monitoring Low-Precision Inference for Edge Computing Publications Trends: His recent work emphasizes biological soil crusts' role in ecosystem resilience, cyanobacterial applications for soil restoration, and exopolysaccharide dynamics in dryland environments. These studies bridge computational engineering with environmental microbiology, addressing challenges in desertification and sustainable land management. Grants & Collaborations: Federico contributes to H2020-funded projects, focusing on open-source platforms and AI integration in critical infrastructure systems. His research often involves cross-disciplinary collaborations between engineering and environmental science domains. Labs/Teams: While no specific lab is mentioned, his affiliations suggest involvement in the Department of Information Engineering's CPS and embedded systems research groups, alongside ecological engineering initiatives.

• High-Performance Computing
• Distributed Systems
• Parallel Computing
• +۱۲ مورد دیگر

Juan Jose Costa Prats is a researcher in the Department of Computer Architecture at the Universitat Politècnica de Catalunya (UPC), affiliated with the Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona. He is a key member of the CRAAX - Centre de Recerca d'Arquitectures Avançades de Xarxes, contributing to advanced research in computing systems and network architectures. His work is deeply integrated into competitive R&D projects, including Horizon Europe and national initiatives focused on digital innovation and infrastructure. Research Interests: Costa Prats specializes in high-performance and distributed computing, with a strong focus on parallel programming models (especially OpenMP), software distributed shared memory (SDSM), cloud computing, virtualization, and cybersecurity. His recent work emphasizes secure and resilient computing systems, particularly through RISC-V-based architectures, hypervisor extensions, and runtime malware detection using opcode analysis and machine learning. He also contributes to educational innovation through remote datacenter laboratories. Publication Trends: His recent publications (2021–2024) reflect a shift toward secure, trustworthy computing environments, especially in cloud and IoT contexts. Themes include RISC-V virtualization, intrusion detection using transfer learning, GPS spoofing detection, and secure development frameworks like Vitamin-V. These works highlight a convergence of system architecture, security, and machine learning. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While no formal students are listed, Costa Prats collaborates extensively with leading researchers such as Beatriz Otero, Ramon Canal, and Javier Verdú. He participates in numerous competitive R&D+i projects funded by the Spanish government and the European Union, including Horizon Europe, RIS3CAT, and national research programs, focusing on cloud resilience, intelligent cloud management, and RISC-V ecosystem development. Labs and Teams: He is an active member of the CRAAX research group at UPC, which works on advanced computing architectures. His research often involves collaboration with the Barcelona Supercomputing Center. His projects, such as Vitamin-V and Remote DasaLAB, indicate involvement in both secure computing environments and innovative educational platforms.

Ramon Canal Corretgerمشاهده پروفایل

استاد

• Microarchitecture
• Processor Design
• Memory Design
• +۱۵ مورد دیگر

Ramon Canal Corretger is a Full Professor in the Department of Computer Architecture at the Faculty of Informatics of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC). He previously served as Vice Dean of Postgraduate Studies at FIB and leads the VirtuOS (Virtualization and Operating Systems) research group. His work bridges computer architecture, hardware security, and system-level reliability. Doctorate from UPC, co-supervised at the University of Wisconsin-Madison Sabbaticals at Harvard University (2006–2007) and the University of Cyprus (2019–2020) Active leadership in EU-funded projects such as Vitamin-V (Horizon Europe) His research focuses on microarchitecture, processor and memory design, reliability under variability, and security at the hardware-software interface. He explores low-power multicore architectures, virtualization optimizations, and secure RISC-V-based systems. His recent work integrates AI for intrusion detection and privacy-preserving federated learning in fog computing environments. The most recent publications demonstrate a strong trend toward security, reliability, and trustworthy computing , particularly in RISC-V ecosystems and cloud/edge infrastructures. There is increasing emphasis on hardware-software co-design , attack detection via performance monitoring , and energy-efficient secure accelerators using emerging technologies like neuromorphic and photonic computing. Scientific Awards: HiPEAC Paper Awards (2017, 2010) IEEE Senior Member (2016) Fulbright Award (2006) IBM Faculty Award (2000) Best Student Paper at HPCA-6 (2000) Multiple teaching excellence recognitions from UPC and AQU Catalunya First Prize in Epson Foundation Rosina Ribalta Award (2001) He has advised several PhD students including Manish Rana, Zoran Jaksic, and Shrikanth Ganapathy, many of whom received honors such as the Intel Doctoral Student Programme recognition. His research is supported by competitive grants from the Spanish government, EU Horizon programs, and industry collaborations. He is actively involved in the design of secure, reliable, and efficient computing systems for future cloud and embedded applications. He leads the VirtuOS research group, which focuses on virtualization, operating systems, and hardware-software interface optimization. The group contributes to open-source RISC-V initiatives and participates in large-scale European R&D projects targeting trustworthy computing infrastructures.

Tobias Grosserمشاهده پروفایل

دانشیار

• Compilers
• Programming Languages
• Performance Programming
• +۷ مورد دیگر

Tobias Grosser is an Associate Professor in the Department of Computer Science and Technology at the University of Cambridge. His research focuses on rethinking performance programming by bridging the gap between developers and compilers. He holds a PhD from École Normale Supérieure Paris and has held positions including Reader at the University of Edinburgh and Ambizione Fellow at ETH Zurich. His research interests span compilers, programming language design, static/dynamic analysis, and the integration of machine learning into compiler development. He emphasizes making compilation more modular, automatic, and trustworthy, with applications in quantum computing, climate science, and open-source hardware. Key projects include xDSL (a Python-native compiler framework), LoopOpt, and the Open Earth Compiler for climate simulations. Recent publications highlight advancements in multi-level intermediate representations (IR), formal verification in MLIR, and performance optimization for GPUs and FPGAs. His work often addresses barriers between programmers and compilers, aiming for intuitive collaboration between developers and automated systems. Tobias mentors a dynamic team of PhD students, postdocs, and researchers, including notable contributors like Siddharth Bhat, Arjun Pitchanathan, and Mathieu Fehr. His lab focuses on compiler toolchains for domain-specific hardware accelerators, quantum computing ecosystems, and verified compilation techniques.

• Performance Measurement
• Operating Systems
• Virtualization
• +۳ مورد دیگر

Manuel Alejandro Pajuelo González is a researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture and the School of Computer Science. His research focuses on Performance measurement Operating systems Virtualization Thread assignment in multithreaded processors Recent publications show strong trends in RISC-V architectures, cybersecurity, and performance optimization. Key themes include Hardware virtualization Intrusion detection frameworks Statistical thread assignment approaches Spin-lock overhead analysis Scientific awards include BDigital Global Congress 15ª Edició Computación de Altas Prestaciones VI HiPEAC Paper Award He participated in multiple competitive R&D projects, including the DRAC project focused on RISC-V accelerators for next-generation computing.

Dustin Richmondمشاهده پروفایل

استادیار

• Computer Architecture
• FPGA
• RISC-V
• +۴ مورد دیگر

Dustin Richmond is an Assistant Professor in the Department of Computer Science and Engineering at the Baskin School of Engineering, University of California, Santa Cruz. His work focuses on secure, usable hardware systems with applications in FPGA acceleration, RISC-V architectures, and side-channel analysis. Email: drichmond@ucsc Office: Engineering 2, Room 221 Research Interests: Secure hardware systems FPGA-based computing Manycore processors High-level synthesis Side-channel vulnerabilities Notable Article Trends: Recent publications emphasize cloud FPGA security, manycore design optimization, and hardware security. Earlier works focus on RISC-V acceleration, OpenCL compiler enhancements, and heterogeneous computing systems. GitHub Contributions: Maintains open-source projects like RISC-V-On-PYNQ and PYNQ-HLS, addressing FPGA programming challenges and RISC-V integration. Active in resolving community issues related to toolchain compatibility and hardware-software interfaces.

• Cybersecurity
• Digital Rights Management
• Internet of Things Security
• +۵ مورد دیگر

Eva Rodríguez is an Associate Professor in the Department of Network Engineering at Pompeu Fabra University's School of Engineering, specializing in cybersecurity, digital rights management, and IoT security. With over 50 publications since 2003, she has established herself as a leading researcher in secure network architectures and privacy-preserving technologies. Her research focuses on applying machine learning techniques to cybersecurity challenges, particularly in mobile and IoT environments. Rodríguez has published extensively on deep learning for intrusion detection, privacy protection mechanisms, and security frameworks for next-generation networks (5G/6G). She has also made significant contributions to RISC-V processor security through the Horizon Europe Vitamin-V project. Recent work shows a strong emphasis on federated learning approaches for privacy preservation in fog computing environments and the development of security management architectures for resilient wireless ecosystems. Her publication record demonstrates consistent leadership in both theoretical frameworks and practical implementations of security solutions. Among her notable contributions are comprehensive surveys on deep learning techniques for mobile network security and machine learning methods for IoT privacy protection, which have become important references in these rapidly evolving fields. As a research supervisor, she has mentored several doctoral students including Norma Gutiérrez and Beatriz Otero, who now appear as co-authors on her recent publications. Her collaborative work extends across multiple European research projects, demonstrating strong integration within the international cybersecurity research community.

Björn Lundellمشاهده پروفایل

پژوهشگر

• Open Source Software
• ICT Standards
• Public Sector IT
• +۳ مورد دیگر

Björn Lundell is a Researcher at the School of Informatics, University of Skövde, Sweden. His work centers on Open Source Software (OSS), ICT standards, and digital governance in public sector contexts. He investigates sustainable software practices, interoperability, and policy compliance. Research Interests: Lundell explores: OSS adoption in government and industry Digital preservation (e.g., PDF/A conformance) Software ecosystems and standardization SaaS licensing risks and open alternatives His 158 publications reflect a focus on practical challenges in public IT, including accessibility, procurement, and cross-border data governance. Recent trends show emphasis on IoT standards and reproducible builds. Affiliations: Lundell is exclusively affiliated with the University of Skövde. No lab, awards, or supervised students are mentioned in the source material.

Jie Liuمشاهده پروفایل

استاد

• Big Data Intelligent Analysis
• Machine Learning Systems
• Intelligent Software Engineering
• +۳ مورد دیگر

Jie Liu is a Researcher at the Institute of Software, Chinese Academy of Sciences and a Professor and Doctoral Supervisor at University of Chinese Academy of Sciences. He is also a Member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences and an Executive Committee Member of the System Software Committee of the CCF Computer Society. His research is conducted within the Software Engineering Technology R&D Center. Dr. Liu received his Ph.D. from the University of Science and Technology of China in 2011 and his B.A. from the same institution in 2004. He has progressed through the ranks at the Institute of Software, CAS, starting as an Assistant Research Fellow (2011-2014), then Associate Research Fellow (2014-2024), and currently as a Researcher (since 2024). His research spans Big Data Intelligent Analysis Models and Systems at the intersection of AI, Software Engineering, and System Software. Specifically, his work covers three main areas: Big Data and Machine Learning Systems (statistics and AI algorithm model libraries, data quantitative analysis tools, LLM reasoning optimization, Earth Big Data); Intelligent Software Engineering (code model constraint decoding, data science agents, system log analysis agents); and Knowledge-Enhanced Intelligent Model Construction (knowledge extraction, knowledge graphs, domain AI model design). His research has resulted in innovative approaches to handling complex data analysis challenges across multiple domains. Dr. Liu's research has produced significant outcomes including EarthDataMiner, which supports SDG indicator calculations and won the 2024 Beijing Municipal Science and Technology Progress First Prize. His work on RISC-V software migration technology has been integrated into the Ruiqian tool (https://rvpt.top/), demonstrating practical applications of his research in emerging computing architectures. Beijing Science and Technology Progress Award, First Prize, 2024 2023 Surveying and Mapping Science and Technology Award, Special Prize, 2023 DASFAA Best Paper Runner-up, Second Prize, 2013 Dr. Liu has successfully guided numerous graduate students who have secured positions at major technology companies including Alibaba, ByteDance, Southern Power Grid, and Agricultural Bank of China. He has secured funding through multiple National Natural Science Foundation projects, National Key R&D Program projects, and over ten other research initiatives. His research collaborations span industry leaders like Huawei, JD.com, and TravelSky, as well as academic institutions within the Chinese Academy of Sciences. He teaches graduate courses such as 'Machine Learning Systems' and 'Cloud Computing and Big Data Technology' at University of Chinese Academy of Sciences, and has established a research group focused on developing innovative solutions at the intersection of AI and software engineering with real-world applications in earth sciences, healthcare, and intelligent systems.