جست‌وجوی استاد و پژوهشگر

Christopher L. Barrettمشاهده پروفایل

استاد

• Biocomplexity
• Computational Science
• Dynamical Networks
• +۷ مورد دیگر

Christopher L. Barrett is the Executive Director of the Biocomplexity Institute and Distinguished Professor of Computer Science at the University of Virginia. He holds a joint appointment in the School of Engineering and Applied Science. His interdisciplinary work spans computational science, dynamical networks, and AI-driven modeling. He leads large-scale research initiatives for federal agencies and has advised organizations like the Department of Defense and the European Commission. Education: Ph.D. in Bioinformation Systems (Caltech, 1985), Post-Ph.D. in Aerospace Experimental Psychology (U.S. Navy, 1986) Awards: 2021 Virginia Academy of Science Award, Jubilee Professorship (Chalmers University, 2012–2013), Distinguished International Professor (Royal Institute of Technology, 1997–1998) Research focuses on multi-scale systems, including RNA evolution, pandemic modeling, and sociotechnical infrastructure resilience. His work bridges computational methods with real-world problems like disaster preparedness and vaccine distribution strategies. He has published over 100 articles and holds seven patents. Recent publications emphasize agent-based frameworks for migration modeling, genomic surveillance, and HPC-driven epidemic analysis. His interdisciplinary approach unifies mathematical, biological, and social science methods to address complex global challenges.

Rohan Basu Royمشاهده پروفایل

استادیار

• Parallel Computing
• Distributed Systems
• Cloud Computing
• +۳ مورد دیگر

Rohan Basu Roy is an Assistant Professor (tenure-track) at the University of Utah, affiliated with the Kahlert School of Computing and the SCI Institute. His research focuses on optimizing parallel and distributed computing systems, including cloud, serverless, and HPC environments, with an emphasis on sustainability and cost-effectiveness. He holds a Ph.D. in Computer Engineering from Northeastern University, advised by Prof. Devesh Tiwari. Affiliations: University of Utah (Kahlert School of Computing), SCI Institute. His research interests include scheduling algorithms, energy efficiency, and environmental sustainability in computing systems. He has pioneered open-source tools like GreenMix and ECOLIFE , widely adopted in the systems research community. Awards: ACM-IEEE CS George Michael Memorial HPC Fellowship (2023), MLCommons ML and Systems Rising Star (2023), Northeastern University Excellence in Research Award (2023). Rohan has served as a program committee member for top-tier conferences (ASPLOS, HPCA, SC) and co-chaired tracks such as AI/ML for Systems at HiPC 2025. He has also delivered invited talks at Google Brain and ParslFest 2023.

Samuel Kounevمشاهده پروفایل

استاد

• Software Engineering
• Performance Engineering
• Autonomic Computing
• +۴ مورد دیگر

Samuel Kounev is a Professor and Chairholder of the Chair of Software Engineering (Computer Science II) at the University of Würzburg's Department of Computer Science. He has held leadership roles, including Faculty Dean (2019-2021) and Head of the Department of Computer Science (2016-2017). His research focuses on software engineering, performance engineering, and autonomic computing, with contributions to cloud computing, cybersecurity, and machine learning. He actively participates in international conferences, including co-chairing the ACM/SPEC International Conference on Performance Engineering (ICPE) and leading initiatives like the DFG Research Unit SOS and bidt Consortium Project ROOT. His work emphasizes real-time systems, benchmarking, and interdisciplinary applications in earth observation and healthcare. Education: Not explicitly listed in provided text. Research Interests: Software Engineering, Performance Engineering, Autonomic Computing, Cloud Computing, Cybersecurity, Machine Learning, High-Performance Computing. His recent articles explore topics like homomorphic encryption, time series forecasting, and AI in healthcare. He is an editorial board member of journals like Elsevier's Performance Evaluation and co-founder of the ICPE and ACSOS conferences. Awards and recognitions are listed on separate pages, but his leadership roles and extensive conference involvement highlight his academic impact.

Erik Elmrothمشاهده پروفایل

استاد

• Distributed Systems
• Cloud Computing
• Edge Computing
• +۳ مورد دیگر

Erik Elmroth is a Professor at the Department of Computing Science, Umeå University. He leads research in distributed systems, cloud/edge computing, and autonomous resource management, directing a 30+ member research group. His leadership includes transformative roles as department head (2009-2021) and Deputy Director at High Performance Computing Center North (HPC2N). Elmroth serves on executive committees for the SEK 6.2B Wallenberg AI program (WASP) and SEK 390M eSSENCE initiative, and leads multiple Kempe Foundation projects. Research interests center on: Autonomous control of cloud/edge infrastructures Software-defined systems and federated clouds AI-driven resource optimization High-performance computing architectures Robust machine learning for distributed environments His publications emphasize adaptive cloud systems, anomaly detection, and federated learning, with consistent focus on scalability and resilience in edge/cloud deployments. Awards and honors: Member of Royal Swedish Academy of Engineering Sciences (IVA) Nordea Scientific Prize (2011) SIAM Linear Algebra Prize (2000) National HPC Lecturer appointment He has supervised 40+ PhD students and secured major grants including the Swedish Research Council's second-largest award for the Cloud Control project. Elmroth founded the Control Workshops series and co-founded Elastisys AB, a cloud security firm with 50+ employees recognized as Umeå's Spin-off Company of the Year.

Josep Lluís Berral Garcíaمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Cloud Computing
• Deep Learning
• +۴ مورد دیگر

Josep Lluís Berral García is an Associate Professor in the Department of Computer Architecture at the Barcelona School of Informatics (FIB), Polytechnic University of Catalonia · BarcelonaTech (UPC). He is actively engaged in teaching and research, with a strong focus on Artificial Intelligence, Cloud Computing, and sustainable computing practices. He leads innovative educational initiatives and is affiliated with the CROMAI research group and the Barcelona Supercomputing Center (BSC-CNS). Research Interests: Artificial Intelligence and Deep Learning Cloud and High-Performance Computing Resource Orchestration and Management Sustainable and Ethical AI AI Education and Pedagogy His recent research and teaching projects center on integrating sustainability and ethical responsibility into AI education, using active learning methodologies. The trend in his work shows a consistent focus on optimizing computing resources through AI, particularly in cloud and HPC environments, with increasing emphasis on environmental impact and responsible innovation. Scientific Awards: UPC Award for Quality in University Teaching 2025 (Teaching Initiative for Newly Recruited Professors) Advising and Grants: While specific students are not listed, his leadership in competitive R&D+i projects and innovation initiatives indicates active supervision and grant-funded research. His involvement in multiple competitive and non-competitive R&D projects demonstrates sustained funding and research leadership. Labs and Teams: He is a key member of the CROMAI (Computing Resources Orchestration and Management for AI) research group at UPC and maintains a strong collaborative link with the Barcelona Supercomputing Center (BSC-CNS), leveraging the MareNostrum supercomputing infrastructure for AI and systems research.

Bin Renمشاهده پروفایل

استادیار

• Parallel Computing
• High-Performance Computing
• Compiler Techniques
• +۷ مورد دیگر

Bin Ren is an Assistant Professor in the Department of Computer Science at the College of William & Mary, where he has been a faculty member since Fall 2016. He holds a Ph.D. in Computer Science and Engineering from The Ohio State University (2014) and was a postdoctoral research associate at Pacific Northwest National Laboratory from 2014 to 2016. Research Interests: His work centers on high-performance computing, compiler techniques, and machine learning systems, with a focus on enabling real-time and energy-efficient deep neural network execution on mobile and edge devices. He explores compiler optimizations, DNN pruning, neural architecture search, and GPU memory management to improve system performance and efficiency. Publication Trends: His recent publications (2023–2025) reveal a strong focus on compiler-aware deep learning systems, mobile and edge AI, and performance optimization across heterogeneous platforms. Key themes include DNN acceleration, memory efficiency, real-time inference, and hardware-software co-design. His work frequently appears in top-tier venues such as ASPLOS, SC, CVPR, and PLDI. Scientific Awards: NSF CAREER Award, 2021 Best Paper Award, SC 2020 Best Student Paper Nomination, SC 2020 Jeffress Trust Award, 2020 ISLPED Design Contest First Place, 2020 Student Cluster Reproducibility Challenge Paper, SC 2019 Best Paper Award, CGO 2013 SIGPLAN Research Highlights, 2013 Advising and Grants: Bin Ren has advised numerous Ph.D. and master’s students, many of whom have co-authored influential papers. His research has been supported by competitive grants, including the NSF CAREER Award. He actively mentors students in areas of parallel computing, compiler design, and machine learning systems. He has also received funding from the Jeffress Trust Awards and other sources to support interdisciplinary research. Professional Service: He has served in leadership roles such as Program Co-Chair for PPoPP'25 and HIPS'21, Track Co-Chair for ICPP'24 and HiPC'24, and Artifact Evaluation Co-Chair for PPoPP'24 and ALENEX'25. He is a frequent reviewer for top journals and conferences including TPDS, TACO, NeurIPS, and SC. Teaching: He teaches courses such as CS304 (Computer Organization) and CS642 (Compiler Techniques for High Performance Computing), contributing to both undergraduate and graduate education in systems and programming. Lab and Team: His research group focuses on system-software co-design for efficient AI deployment. Collaborators include researchers from institutions like Pacific Northwest National Laboratory and The Ohio State University. His team works on real-world applications in healthcare, autonomous systems, and scientific computing.

• High-Performance Interconnection Networks
• Computer Architecture
• Network Simulation
• +۷ مورد دیگر

Francisco J. Andújar Muñoz is an Associate Professor at the University of Valladolid in the Department of Computer Science since January 2024. His career spans multiple institutions including Universidad de Castilla-La Mancha (2008-2015) and Universitat Politècnica de València (2017-2018), with academic roles ranging from Research Assistant to Juan de la Cierva Formación Researcher. PhD in Advanced Computer Science Technologies (2011-2015) MsC in Advanced Computer Science Technologies (2010-2011) Computer Science Engineering (2008-2010) Computer Science Technical Engineering (2004-2008) His research focuses on high-performance interconnection networks , with significant contributions to quality-of-service mechanisms, energy-efficient network topologies, and heterogeneous programming optimization. He maintains the open-source VEF Traces framework for network workload modeling. Recent publications (2023-2025) demonstrate expertise in FPGA high-level synthesis portability, SYCL-based GPU optimization, and machine learning applications for Twitch streaming analysis. His work combines theoretical network design with practical implementations in the Journal of Supercomputing and IEEE Transactions on Computers .

Tomás Fernández Penaمشاهده پروفایل

استاد

• High Performance Computing (HPC)
• Parallel and Distributed Systems
• Quantum Computing
• +۵ مورد دیگر

Tomás Fernández Pena is a Full Professor at the University of Santiago de Compostela (USC) and Senior Researcher at the Research Center in Intelligent Technologies (CiTIUS) . With a career spanning over three decades, he has held academic positions since 1990 and contributed extensively to High Performance Computing (HPC), Big Data, and emerging quantum computing fields. Ph.D. in Physics from USC (1994) Senior Member of IEEE Associate Editor for IEEE Transactions on Computers and IEEE Access Research Contributions : His work focuses on parallel systems architecture, cloud computing middleware, and quantum simulation optimization. He has pioneered methods for NUMA systems, LiDAR data processing, and Big Data applications in bioinformatics/cheminformatics. His recent articles show increasing emphasis on quantum computing frameworks and distributed quantum processing. Scientific Recognition : Holds four Spanish Ministry of Education six-year research excellence periods (sexenios de investigación) and has served as Principal Investigator in 3 public projects and co-investigator in 31 EU/Xunta de Galicia funded initiatives. Supervised 7 Ph.D. theses and published 43+ international journal papers. International Collaborations : Maintains academic connections through funded research stays at Loughborough University, University of Tennessee, and University of Illinois Urbana-Champaign. Active in IEEE and participates in global conferences like Euro-Par and CHEP.

Enrico Tronciمشاهده پروفایل

استاد

• Model Checking
• Cyber-Physical Systems
• Software Engineering
• +۷ مورد دیگر

Enrico Tronci is a Full Professor in the Department of Computer Science at Università degli Studi di Roma La Sapienza , Italy. His research focuses on model checking, formal verification, and synthesis of cyber-physical systems, with applications to mission-critical and safety-critical domains such as space systems, smart grids, and healthcare. He leads the Model Checking Lab (MCLab) and has coordinated numerous national and international research projects funded by organizations including the European Community (EC), European Space Agency (ESA), and Italian Ministry of University and Research (MUR). Research Highlights : Automatic control software synthesis from closed-loop specifications Model checking algorithms for hybrid and stochastic systems Technology transfer in sectors like energy, transportation, and aerospace Teaching : Undergraduate: Software Engineering (Fall 2024) Graduate: Automatic Verification of Intelligent Systems (Fall 2024), Verification and Validation of Intelligent Systems (Spring 2025) Scientific Awards : Recipient of the IBM-Italia 1987 prize for best thesis in Artificial Intelligence Publications Trends : 2024: Scaling up model checking for cyber-physical systems via HPC 2023: Hormonal impact on behavior and fault-tolerant sensor deployments 2021-2022: In silico clinical trials, smart grid management, and scenario enumeration 2020: AI-guided diabetes patient modeling and forensic psychiatry applications Software Tools : QKS (Quantized Kontrol Synthesizer) NashMV (MAD systems verification) CMurphi (Hybrid systems model checker) FHP-Murphi (Probabilistic verification) BSP (Boolean symbolic programming)

Dolores Modicمشاهده پروفایل

پژوهشگر

• Technology Transfer
• Intellectual Property Rights (IPR)
• University-Industry Collaboration
• +۲ مورد دیگر

Dolores Modic is a researcher at the Division of Innovation and Entrepreneurship at Nord University. Her primary research interests include technology transfer, intellectual property rights (IPR) management, university-industry collaboration, patent informatics, and circular economy. She has led numerous projects sponsored by funding agencies across Europe, USA, and Asia, serving as a project author, PI, team member, and coordinator. Her work focuses on understanding complex systems in innovation, particularly in circular economy and data-driven IPR management. She contributes to the field through interdisciplinary collaboration and international team coordination. Scientific Awards: JSPS Fellow in Japan (2016-2018) Fulbright Scholar in U.S.A. (2015) She actively participates in projects involving public procurement, patent data, and innovation ecosystems, with recent publications in journals like Environmental Technology & Innovation, IEEE Transactions on Engineering Management, and Research Policy.

Michael Gerndtمشاهده پروفایل

استاد

• Cloud Computing
• Internet of Things (IoT)
• High Performance Computing (HPC)
• +۱۱ مورد دیگر

Prof. Dr. Michael Gerndt is a Full Professor at the Chair of Computer Architecture and Parallel Systems , School of Informatics, Technische Universität München (TUM). His research focuses on cloud and IoT systems, high-performance computing (HPC), and performance analysis tools for parallel/distributed systems. Current projects: SEANERGYS , PlasmaPEPS , OpenCUBE , and MUNIQC-ATOMS Past projects: AutoTune , READEX , InvasIC , and CrossGrid Research Highlights: Developed the Periscope Tuning Framework and iOMP (OpenMP extension for invasive computing) Pioneering work in performance analysis, energy efficiency, and resource management in HPC and cloud systems Focus on AI-driven cloud operations, quantum-HPC integration, and hardware accelerators for machine learning Scientific Awards: Outstanding Paper Award, IEEE SC2 Symposium (2017) Teaching Contributions: Lectures: Parallel Programming Systems , Advanced Computer Architecture , Cloud Computing Lab courses: Efficient Programming of Multicore Processors , IoT Sensor Nodes Seminars: Hardware Accelerators for AI , Quantum Computing Integration Education & Career: PhD in Computer Science (1989, University of Bonn), postdoc at University of Vienna (1990-1991), habilitation at TUM (1998), Professor at TUM since 2000.

Swarnendu Biswasمشاهده پروفایل

استادیار

• Programming Languages
• Compilers
• Runtime Systems
• +۷ مورد دیگر

Swarnendu Biswas is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur. He teaches courses including Programming for Performance (CS 610), Analysis of Concurrent Programs (CS 636), and Compiler Design (CS 335), demonstrating his expertise across multiple areas of computer systems. His research interests center on Programming Languages, Compilers, Runtime Systems, and Parallel Software Systems. He leads the PROSPAR (Programming Languages and PARallel Systems) research group, which focuses on developing techniques to build efficient and correct parallel software through program analysis, compiler optimizations, and runtime systems. His recent publications reveal a strong trend in addressing fundamental challenges in parallel computing, with work spanning cache coherence, false sharing detection, data race analysis for GPUs, verification of neural networks, and thermal-aware management of heterogeneous systems. His research bridges theory and practice with significant contributions to both hardware and software aspects of parallel systems. His scientific achievements have been recognized through multiple prestigious awards: Google India Research Award 2021 Google Explore CSR 2022 Research Grant from Intel Corporation SERB Start-up Research Grant 2019 Google Cloud Platform Research Credits (2019, 2020) IITK Initiation Grant 2019 As an advisor, he mentors several PhD and MTech students working on cutting-edge research in parallel systems. His PROSPAR group has secured significant funding from industry and government sources, supporting innovative research in programming languages and parallel systems. The group actively collaborates with industry partners including Google and Intel, addressing real-world challenges in parallel computing. He leads the PROSPAR research group at IIT Kanpur, which brings together faculty, PhD students, and MTech researchers to tackle challenging problems at the intersection of programming languages, compilers, and parallel systems. The group maintains strong industry connections and focuses on practical solutions that can be deployed in real systems.