جست‌وجوی استاد و پژوهشگر

Ivan Beschastnikhمشاهده پروفایل

دانشیار

• Distributed Systems
• Software Engineering
• Cloud Computing
• +۵ مورد دیگر

Ivan Beschastnikh is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Faculty of Science. He leads research in distributed systems, software engineering, and formal methods, with a focus on privacy-preserving technologies, blockchain systems, and machine learning. His work bridges theoretical foundations and practical system implementations, emphasizing empirical validation and real-world deployment. Research Interests: His primary areas include distributed systems (e.g., consensus algorithms, transaction processing), formal methods for system correctness (e.g., PGo compiler for verified implementations), and privacy in federated learning and blockchain. He also explores interdisciplinary topics like AI ethics, human-computer interaction for developers, and system security. Key Projects: Includes PGo (formal specification to Go compiler), Biscotti (decentralized federated learning), Erlay (Bitcoin transaction relay optimization), and Teleoscope (text corpus analysis tool). His work has practical impact in blockchain scalability, secure multi-party ML, and distributed system validation. Awards: Recognized with the ASPLOS Distinguished Artifact Award, UBC Faculty Teaching Award, and ESEM Best Paper Award. His contributions span academic excellence, pedagogy, and collaborative research. Lab Affiliations: Active in the Systopia Lab and Software Practices Lab (SPL) , and collaborates with UBC’s Data Science Institute and Blockchain@UBC. He emphasizes interdisciplinary research, mentoring students in both theoretical and applied systems work.

Christopher McCombمشاهده پروفایل

دانشیار

• Sociotechnical Systems
• Machine Learning for Engineering Design
• Human-AI Collaboration
• +۱۷ مورد دیگر

Christopher McComb is an Associate Professor in the Department of Mechanical Engineering at Carnegie Mellon University's College of Engineering. He leads research in sociotechnical systems, machine learning for engineering design, and human-AI collaboration. He is affiliated with the Block Center for Technology and Society, Manufacturing Futures Institute, NextManufacturing Center, and Wilton E. Scott Institute for Energy Innovation. Previously, he was an assistant professor at Penn State, where he directed the Center for Research in Design and Innovation and led the Technology and Human Research in Engineering Design Group. Ph.D., Mechanical Engineering, Carnegie Mellon University M.S., Mechanical Engineering, Carnegie Mellon University B.S., Civil Engineering and Mechanical Engineering, California State University-Fresno His research centers on human-AI teaming , sociotechnical systems , and computational design , with applications in additive manufacturing, STEM education, and energy systems. He explores how machine learning can enhance engineering design processes, particularly through human-centered AI, generative design, and agent-based modeling. His work emphasizes the integration of human cognition and behavior into AI systems to improve collaboration and innovation. The 15 most recent publications (2025) demonstrate a strong trend in AI-driven design automation , neural surrogate modeling , human-AI interaction , and data generation for engineering simulations . Topics span from using large language models for material selection and design concept generation to developing datasets and benchmarks for advanced manufacturing and CAD systems. There is a clear emphasis on real-world applications in aerospace, finance, and global manufacturing, particularly in Africa. National Science Foundation Graduate Research Fellow McComb has received research funding from NSF, DARPA, and private corporations, and has collaborated with Boeing through their Visiting Professorship Program. He advises students in mechanical engineering and design, and leads the Human+AI Design Initiative and the Design Research Collective. His research has been applied in partnerships with NASA and in addressing manufacturing challenges in Africa. He leads or contributes to interdisciplinary research teams focused on AI in design, additive manufacturing, and energy systems. His labs and initiatives include the Human+AI Design Initiative and the Design Research Collective, which foster collaboration between human-centered design and artificial intelligence.

• Privacy-Preserving Machine Learning
• Reinforcement Learning
• Data Privacy and Security
• +۵ مورد دیگر

Associate Professor Kee Siong Ng is affiliated with the School of Computing at the Australian National University (ANU). His research focuses on privacy-preserving technologies, reinforcement learning, distributed systems, and blockchain applications. He has contributed extensively to areas such as privacy-preserving machine learning, federated learning, entity resolution, and scalable database systems. His work emphasizes balancing computational efficiency with privacy guarantees in data-driven environments. Key research contributions include methodologies for secure data processing in federated learning frameworks, privacy-preserving reinforcement learning for population-level systems, and blockchain-based digital identity solutions. He has led projects like Integrated Graph Analytics and contributed to initiatives involving the Australian Medicare dataset. His research often intersects theoretical foundations with practical implementations, addressing challenges in scalability and real-world applicability. Ng has published over 24 peer-reviewed articles, with notable works appearing in venues like IEEE Transactions on Parallel and Distributed Systems and Transactions on Machine Learning Research . His articles frequently explore cutting-edge topics such as differential privacy, approximation algorithms, and multi-agent systems. Collaborations include industry partnerships and interdisciplinary efforts involving health informatics and financial intelligence. His projects include Integrated Graph Analytics (2018–2021): Focused on scalable graph-based data analysis. Translational Fellowship (2018–2022): Bridging theoretical research with practical applications. Research on Data Sets for Health and Pharmaceutical Schemes (2020): Analyzing Medicare and pharmaceutical data with privacy safeguards. Ng's work prioritizes ethical AI and privacy-by-design principles, with a focus on real-world deployment challenges in distributed and federated systems.

Zbigniew T Kalbarczykمشاهده پروفایل

استاد پژوهشی

• Computer Security
• Fault Tolerance
• Reliable Systems
• +۷ مورد دیگر

Zbigniew T. Kalbarczyk is a Research Professor at the Coordinated Science Laboratory and the Department of Electrical and Computer Engineering (ECE) at the University of Illinois at Urbana-Champaign (UIUC), holding this position since 2004. He holds M.S. degrees in Mechanical Engineering (Technical University of Warsaw, 1981) and Electronic Engineering (Technical University of Sofia, 1984), as well as a Ph.D. in Computer Science from the Bulgarian Academy of Sciences (1992). His research focuses on reliable and secure computing systems , including fault tolerance, cybersecurity, and cyberphysical systems. He leads the DEPEND Group, which investigates trustworthy systems, health analytics, and big-data applications. Key projects include securing supercomputing infrastructure against environmental attacks, improving IoT security, and advancing healthcare systems through AI-driven solutions. Recent collaborations involve industry partners like IBM, Mayo Clinic, and the National Science Foundation (NSF), with notable funding such as a $500K NSF grant for cybersecurity research. His work bridges theoretical concepts and practical implementations, emphasizing real-world testing on systems like Blue Waters supercomputers and smart grids. Notable students include Krishnakant Saboo (Ph.D. 2023), Homa Alemzadeh (William Carter Award recipient), and Arjun Athreya (best paper award winner). The DEPEND Group also collaborates internationally, including with Singapore’s VinUniversity and the National University Hospital.

Andrew Nereمشاهده پروفایل

استادیار

• Machine Learning
• Computer Architecture
• Embedded Systems
• +۳ مورد دیگر

Andrew Nere serves as Assistant Professor of Computer Science in the Math & Computer Science Department at Western Colorado University, teaching courses including Introduction to Web Design, Computer Science I, and Software Entrepreneurship since joining the faculty in Fall 2022. His industry background includes co-founding Thalchemy (2013), a startup specializing in embedded machine learning for wearable and environmental sensor applications, alongside prior internships at IBM and Qualcomm. His educational credentials feature: PhD in Electrical Engineering from University of Wisconsin-Madison (2013) MS in Electrical Engineering from University of Wisconsin-Madison (2010) B.S. in Computer Engineering from St. Cloud State University (2007) Nere's research centers on hardware-software co-design for efficient AI deployment, with dual focus on neuromorphic computing architectures and practical embedded systems implementation. He bridges theoretical neuroscience with engineering solutions, particularly for resource-constrained environments like fitness trackers and environmental sensors where computational efficiency is paramount. His work emphasizes translating academic research into real-world applications rather than pure theoretical exploration. Analysis of his 2010-2013 publications reveals consistent innovation in brain-inspired computing hardware, with recurring themes of GPU-accelerated neural simulations, specialized cache architectures for AI workloads, and energy-efficient neuromorphic designs. The research demonstrates strong interdisciplinary collaboration across computer architecture, neuroscience, and machine learning communities, frequently targeting hardware acceleration for cognitive computing tasks. Scientific recognition includes: Best Paper Nomination at IEEE International Symposium on Workload Characterization (2012) Best Paper in Track at International Parallel and Distributed Processing Symposium (2011) Nere brings substantial industry experience to academia, having served as university collaborator on the DARPA/IBM SyNAPSE project modeling brain functionality in computing systems. His startup Thalchemy exemplifies his commitment to applied research translation, while his current Software Entrepreneurship course provides students with practical business development frameworks for technology ventures. He actively leverages Gunnison Valley's natural environment for both recreation and potential research applications, noting particular interest in environmental sensing opportunities afforded by the region's wilderness proximity and diverse ecosystems.

• Internet Computing
• Network-Centric Systems
• Cloud Computing
• +۳ مورد دیگر

Professor Marios Dikaiakos is a full-time faculty member at the University of Cyprus (UCY), Department of Informatics. He holds a Ph.D. in Computer Science from Princeton University (1994) and has been at UCY since 1998. His roles include serving as Chair of the Department of Informatics (2010-2014) and Founding Director of the Entrepreneurship Center (2014-2021). He leads the Internet Computing Laboratory, focusing on Network-Centric Systems, Cloud Computing, and Social Media Analysis. His research has resulted in over 160 publications and 22 funded projects. Research interests include edge computing, cloud systems, IoT energy modeling, and polarization detection in news media. He has developed open-source tools like Fogify and BenchPilot for edge computing emulation. Active in academic governance, he has reviewed proposals for EU, national, and Chinese institutions. His work bridges theoretical computer science with practical applications in telemedicine, smart grids, and entrepreneurship ecosystems.

• Fog Computing
• 6G Networks
• Container Orchestration
• +۵ مورد دیگر

José Pedro Pereira dos Santos is a Senior Postdoctoral Fellow at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology (EA05). His work focuses on advancing cloud-native architectures for next-generation networks, particularly through machine learning and reinforcement learning techniques. Current role: FWO Fellow (2022-2025) for 'Predictive orchestration and distributed networking for low-latency applications in future 6G Networks' Past role: Doctoral researcher (2017-2022) at Ghent University Research interests center on Fog Computing , 6G Networks , and Container Orchestration , with emphasis on: Reinforcement Learning applications Low-latency service delivery Network-aware resource provisioning Compute Continuum optimization Recent publications demonstrate expertise in Kubernetes auto-scaling, 6G edge-cloud orchestration, and energy-efficient containerized systems. Awards and student advising details are not explicitly mentioned in the provided texts.

Djob Mvondoمشاهده پروفایل

دانشیار

• Virtualization
• Cloud Computing
• Operating Systems
• +۳ مورد دیگر

Djob Mvondo is an Associate Professor at the University of Rennes 1, France, affiliated with the IRISA laboratory and the WIDE Team. He previously held a postdoctoral position at the University of Edinburgh, focusing on virtualization and cloud computing under Antonio Barbalace. His Ph.D. from the University of Grenoble Alpes (2020) explored resilience and sizing in virtualized environments under Prof. Noel De Palma and Prof. Alain Tchana. His research interests span virtualization, cloud computing, and operating systems. Notable achievements include the 2021 ASF and GDR RSD Thesis Prize for his dissertation. He advises two Ph.D. students and collaborates with institutions like Inria and Blacknut. Recent grants include a 300K€ French National Research Agency award (2023) and a 40K€ Rennes Metropole grant for heterogeneous CPU architectures. Teaching includes courses on cloud security, network security in IoT, and ACM programming at ENS Lyon. Active in the academic community, he serves on program committees for conferences such as Eurosys, Middleware, and DSN. He organizes hackathons and contributes to open-source projects like Unikraft. His work addresses challenges in distributed systems, hypervisor optimization, and cloud resilience.

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.

Paul Townendمشاهده پروفایل

دانشیار

• Energy-efficient distributed systems
• Sustainable computing
• Cloud computing
• +۷ مورد دیگر

Paul Townend is an Associate Professor at Umeå University , Sweden, with a Docent qualification. He leads the Green Distributed Computing group and serves as Research Leader for the Autonomous Distributed Systems (ADSLab) lab. Scientific Coordinator for Horizon Europe COGNIT Co-Manager & Scientific Advisor for WASP WARA-Ops Member of WASP Graduate School Management Team His research focuses on energy-efficient and sustainable distributed systems , with a current emphasis on Edge-Cloud integration . Additional areas include fault tolerance, provenance, data center optimization, and simulation . He has supervised 5 PhD students and 2 postdocs , with expertise in IoT, machine learning for cloud management, and microservices . Best Paper Awards at SOSE 2013 and ISORC 2012 Principal Investigator for grants totaling over $5.8M , including projects like Adaptive Monitoring of Streaming Data and Energy-Aware Cloud-Edge Management

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.

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.

Xiaoyi Luمشاهده پروفایل

دانشیار

• Parallel and Distributed Computing
• High-Performance Communication and I/O Technologies
• Big Data Analytics
• +۴ مورد دیگر

Dr. Xiaoyi Lu is an Associate Professor in the Department of Computer Science & Engineering at the University of California, Merced (UC Merced), where he founded and directs the Parallel and Distributed Systems Laboratory (PADSYS Lab). He is affiliated with the AgAID Institute since 2023 and has authored over 170 publications, including ten Best Paper Awards or Nominations (e.g., SC 2019, IPDPS 2024). His research outcomes like OpenDOTA and MVAPICH2-Virt are used by hundreds of organizations globally. Research Interests: He focuses on scalable parallel systems for HPC, Big Data, AI, Cloud, and Edge Computing, leveraging advanced technologies like RDMA/PMEM/NVMe/GPU/DPU. His work bridges high-performance computing with applications in precision agriculture, biostatistics, and digital twin technology. Article Trends: Recent publications emphasize DPU offloading, compression-optimized collective communication, error detection in HPC, and scalable Bayesian group testing. Topics span GPU clusters, NVMe-over-Fabrics, and adaptive networks for LLM training, reflecting his expertise in heterogeneous architectures and distributed systems. Scientific Awards: NSF CAREER Award (2024) Amazon Research Award (2023) Google Research Award (2022) Meta Faculty Research Award (2022) Multiple Best Paper Nominations Professional Activities: He serves as Associate Editor for Frontiers in High Performance Computing and organizes tracks at SCAsia and HiPC. His leadership in PADSYS Lab drives innovation in systems for social good.

• Database Systems
• Cloud Computing
• Machine Learning Integration
• +۳ مورد دیگر

Carlo Curino is a researcher at Microsoft Research , focusing on database systems, cloud computing, and machine learning integration. He has collaborated extensively with institutions including MIT, Microsoft, and the University of Wisconsin-Madison. His research spans Geo-distributed data analytics Automated configuration tuning Tensor-based database systems Data lake optimization Spark performance engineering Recent publications highlight his work on AI-driven systems like MotherNet and Rockhopper , alongside contributions to query processing over compressed data and log-structured tables. Collaborators include prominent figures such as Raghu Ramakrishnan and Jesús Camacho-Rodríguez . Key projects involve LST-Bench (cloud storage benchmarking), AutoComp (data compaction), and PyFroid (commodity workstation analytics). His work bridges database optimization with modern machine learning demands in enterprise environments.

Luís Antunes Veigaمشاهده پروفایل

دانشیار

• Distributed systems
• Cloud computing
• Grid computing
• +۵ مورد دیگر

Luís Antunes Veiga is an Associate Professor in the Department of Computer Science and Engineering at Instituto Superior Técnico (IST), Universidade de Lisboa, and a Senior Researcher at INESC-ID Lisboa, where he is Vice-Coordinator of the Computing Systems and Communication Networks Laboratory and of the Distributed Systems Group. He has held roles such as Scientific Coordinator of the Distributed, Parallel and Secure Systems research area, Vice-Head of Department for Academic Matters, and Coordinator of the MSc programme in Information Systems and Computer Engineering (MEIC). Education: Details of degrees not explicitly listed, but career progression from Teaching Assistant (2001) to Associate Professor (2015) indicates completion of PhD and other qualifications. Research Interests: His work lies at the intersection of distributed systems and cloud computing, with a focus on: Virtualization & Cloud Infrastructure: Virtual machines, container technologies, and serverless (FaaS) platforms. Data Management & Consistency: Replication strategies, consistency models, and garbage collection for large-scale systems. Edge & P2P Computing: Extending cloud abstractions to edge devices and community networks, peer-to-peer middleware, and mobile computing. Recent Publication Trends: Over the last three years, his research output has concentrated on serverless computing at the edge , analyzing performance, cost, and scheduling strategies. Key contributions include novel utility-driven placement algorithms and lightweight orchestration frameworks that reduce cold-start latency while respecting edge resource constraints. Scientific Awards: Nominated for Best Researcher Award 2019, INESC-ID Lisboa. Advising & Grants: He has successfully supervised more than nine PhD students as primary advisor (including joint programmes with UCLouvain, UPC, and University of Maryland) and numerous MSc students. Funding has been secured through: EU Programmes: CloudStars (MCSA), MoTiV (H2020), CloudForEurope (FP7), TIMBUS (FP7). National FCT Projects: novaVM, ContexTWA, PROSOPON, Synergy, RepComp, GINGER. Labs & Teams: He leads activities within the Distributed Systems Group , coordinates the INESC-ID Computing Systems and Communication Networks Laboratory , and is a member of the IST Scientific Council (2023–).