جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Robotics
• Systems Engineering
• +۳ مورد دیگر

Peter Pavel Arthur Petráš is a Tutor at the Institute for Intelligent System Technologies within the Faculty of Technical Sciences at the University of Klagenfurt. His research focuses on interdisciplinary applications of artificial intelligence, robotics, and systems engineering, with contributions to fields like swarmalator dynamics, automated systems design, and media literacy in digital environments. He is actively engaged in collaborative projects involving industry partners such as Infineon Technologies Austria AG and the Austrian Research Promotion Agency (FFG), emphasizing practical innovations in technology and education. While not listed as a project head, his role supports cutting-edge research in areas like radar simulation frameworks, garment sorting automation, and multi-agent localization systems. His work bridges theoretical advancements with real-world implementation, particularly in edge-cloud computing and interdisciplinary methodological innovations. Recent publications highlight his expertise in AI-driven solutions, robotics, and the societal implications of digital media. Notable themes include analyzing online political microtargeting avoidance, improving multi-robot exploration algorithms, and exploring poetry workshops in migration research. His contributions align with the University of Klagenfurt’s focus on fostering innovation through its Third Mission initiatives, emphasizing knowledge transfer to regional industries and public sectors. Petráš collaborates on projects addressing societal challenges, such as promoting media literacy through the #NoFakeFacts! Citizen Science initiative and enhancing wind turbine blade inspection via multimedia drones. His work reflects a commitment to both technical innovation and addressing ethical and educational dimensions of emerging technologies.

Maciej Malawskiمشاهده پروفایل

دانشیار

• Parallel and Distributed Computing
• Cloud Computing
• Data Science
• +۵ مورد دیگر

Maciej Malawski is an Associate Professor at the Department of Computer Science, AGH University of Science and Technology, and Research Team Leader at the Sano Centre for Computational Medicine in Kraków, Poland. He holds a PhD in Computer Science (2009) and MSc degrees in Computer Science (2001) and Physics (2004). His research focuses on parallel/distributed computing, cloud technologies, and biomedical applications, with contributions to federated learning, serverless computing, and scientific workflow optimization. Education: PhD in Computer Science, AGH University (2009) MSc in Physics, Jagiellonian University (2004) MSc in Computer Science, AGH University (2001) Research Interests: Parallel computing, cloud infrastructures, serverless systems, federated learning, biomedical data analysis, and workflow scheduling. His work bridges computational methods with healthcare, such as federated learning for medical imaging and sensitivity analysis in cardiovascular models. Publications & Awards: Over 50 international publications, including top-tier venues like SC, IPDPS, and IEEE Cluster. Recognitions include the 2018 AGH Rector’s Award, Publons Peer Review Award (2018), and 1st place in the Executable Paper Grand Challenge (2011). Labs & Affiliations: Director of Sano, senior researcher at ACC Cyfronet AGH, and collaborator with CERN. Leads projects on HPC/Cloud integration and scientific computing for medicine.

Bartosz Baliśمشاهده پروفایل

دانشیار

• scientific workflows
• data science
• e-Science
• +۲ مورد دیگر

Bartosz Baliś serves as Associate Professor at the Institute of Computer Science, AGH University of Science and Technology, and holds a Senior Postdoctoral position in Extreme-scale Data and Computing at the Sano Centre for Computational Medicine. He actively contributes to the CERN ALICE experiment as a core team member. His educational foundation includes dual degrees from AGH University and Jagiellonian University, culminating in both PhD and DSc (habilitation) qualifications in Computer Science from AGH University. These advanced credentials underpin his specialized expertise in computational methodologies. Dr. Baliś pioneers research in scientific workflows, data science, and distributed computing systems , with particular emphasis on cloud-native architectures and e-Science infrastructures. His innovative work bridges theoretical computer science with practical applications in large-scale data processing, advancing methodologies for scientific computing environments through novel workflow management solutions. Recent publications demonstrate a clear trajectory toward serverless computing paradigms and comprehensive observability frameworks for scientific applications, reflecting his commitment to solving scalability challenges in modern computational research through cutting-edge cloud technologies. He has secured substantial research funding through participation in major European initiatives including CrossGrid, CoreGRID, K-Wf Grid, ViroLab, Gredia, UrbanFlood, PaaSage, and WATERLINE across FP5-FP7 and Horizon 2020 programs. His leadership extends to conference organization as Euro-Par 2020 General Co-chair, HPCS 2018-19 Tutorials Co-chair, and IEEE/ACM SC committee roles. Within institutional frameworks, Dr. Baliś contributes to the Extreme-scale Data and Computing research group at Sano Centre while maintaining active collaboration with the international CERN ALICE collaboration, where his computational expertise supports high-energy physics research infrastructure.

• Project management
• Organizational psychology
• Educational psychology
• +۷ مورد دیگر

Karin Lackner is an Assistant Professor (retired) affiliated with the Institute for Teaching and School Development at the University of Klagenfurt. Her work focuses on educational and organizational psychology, project management, and intercultural dynamics within institutional settings. Research Areas: Organizational and educational psychology Healthcare management Team development strategies Sociodynamic design Sports research Intercultural project management Her scholarly contributions span interdisciplinary research methodologies and practical applications in educational systems. Recent work emphasizes innovation in teaching methodologies and institutional frameworks. Publications include analyses of digital media behavior ( Political Microtargeting Avoidance ), robotics applications ( Swarmalator Systems ), and sustainable business models ( Entrepreneurial Ecosystems ). These reflect her interdisciplinary approach bridging social sciences and technical fields. Grants & Projects: Collaborative research initiatives in education innovation and organizational dynamics (funding sources include Austrian Research Promotion Agency and Carinthian Economic Development Fund). She leads initiatives promoting inclusive educational practices and advises on institutional transformation strategies.

Eric Kellerمشاهده پروفایل

دانشیار

• Computer Networks
• Software-Defined Networking
• Network Security
• +۲ مورد دیگر

Eric Keller is an Associate Professor in the Department of Electrical, Computer & Energy Engineering at the University of Colorado's College of Engineering. His research focuses on computer networks, network security, and cloud/edge computing, with particular emphasis on software-defined networking and efficient resource allocation in distributed systems. Keller's research spans several interconnected domains including network virtualization, hardware acceleration, container-based computing, and security protocols. His work often bridges the gap between theoretical networking concepts and practical system implementations. Through his publications, Keller demonstrates consistent focus on optimizing network performance and security, particularly in cloud and edge computing environments. His recent work shows growing interest in hardware-level acceleration and AI-enhanced networking solutions.

Paarijaat Adityaمشاهده پروفایل

استاد

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۴ مورد دیگر

Paarijaat Aditya is a faculty member at the Max Planck Institute for Software Systems (MPI-SWS) , focusing on interdisciplinary research at the intersection of theoretical computer science and applied systems. Their work spans algorithms, programming languages, security, and distributed systems , with a particular emphasis on serverless computing, federated learning, and privacy-preserving urban sensing. Research Areas : Machine Learning Security (e.g., model hijacking, federated learning) Serverless Computing (e.g., GPU sharing, high-performance frameworks) Privacy Engineering (e.g., urban sensing, image capture, mobile compliance) Distributed Systems (e.g., NFV, peer-assisted content delivery) Their publications reflect a trajectory of advancing scalable AI training, secure collaborative systems, and privacy-compliant infrastructures. Recent works address challenges in public cloud adaptability, while earlier contributions explore mobile privacy risks and secure resource management.

• Computer Science
• Distributed Systems
• Blockchain Technology
• +۴ مورد دیگر

Pezhman Nasirifard is a researcher at the Technical University of Munich, specializing in distributed systems and blockchain technology. He earned his PhD from the same institution in 2023, focusing on reducing coordination in permissioned blockchains using Conflict-free Replicated Data Types (CRDTs). His work bridges computer science and energy systems, addressing challenges in blockchain scalability, distributed ledgers, and grid inference through crowdsourced data. Key contributions include the OrderlessChain framework, which eliminates global transaction ordering in blockchains, and the FabricCRDT approach for permissioned blockchain systems. He has also explored energy grid modeling using drone imagery and crowdsourcing, as well as serverless computing architectures. His publications span venues like Middleware, e-Energy, and IEEE Transactions, highlighting interdisciplinary research in distributed systems, blockchain applications, and energy infrastructure. Collaborations with co-authors like Hans-Arno Jacobsen and Ruben Mayer emphasize his engagement with cutting-edge technologies and distributed computing paradigms.

• Serverless Computing
• Cloud Computing
• Business Process Management
• +۵ مورد دیگر

Vatche Isahagian is a researcher with affiliations at Bentley University's McCallum School of Business in the Computer Information Systems department and IBM Research (Cambridge, MA and Yorktown Heights, NY). He completed his PhD in Strategic and operational services for workload management in the cloud from Boston University in 2013. His research focuses on serverless computing, business process management, and the application of artificial intelligence in enterprise settings. He has published extensively on topics including Function-as-a-Service (FaaS), workflow automation, deep learning platforms, and cloud resource management. His work bridges theoretical computer science with practical enterprise applications, particularly in automating business processes through AI technologies. Recent research shows a strong trend toward applying large language models to business process automation, with publications in 2023-2025 focusing on conversational interfaces for workflow generation, security policy automation using LLMs, and business process-specific foundation models. His work demonstrates how AI can be integrated into enterprise systems to improve efficiency and decision-making. As a highly collaborative researcher, he has worked extensively with Vinod Muthusamy (54 joint publications), Yara Rizk (22), Aleksander Slominski (20), and Praveen Venkateswaran (17), among others. His research has been published in top venues including AAAI, KDD, Middleware, BPM, and IEEE conferences. His contributions to serverless computing were particularly influential, with early work helping define the field through publications like 'The rise of serverless computing' (Communications of the ACM, 2019) and 'Serverless Computing: Current Trends and Open Problems' (2017). This foundational work helped establish serverless architecture as a significant paradigm in cloud computing.

• Computer Architecture
• Distributed Systems
• Cloud Computing
• +۵ مورد دیگر

Randy H. Katz is a distinguished Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley's College of Engineering. With an extensive publication record spanning over two decades, he has established himself as a leading researcher in computer systems, distributed computing, and energy-efficient architectures. His work bridges theoretical foundations with practical implementations in cloud computing, networking, and smart infrastructure systems. Professor Katz's research interests span a broad spectrum of computer systems topics, with particular emphasis on energy-efficient computing, distributed systems design, and infrastructure for emerging applications. His work on FireSim represents a major contribution to FPGA-based system simulation, while his research on energy-aware datacenters and smart grids addresses critical sustainability challenges in computing infrastructure. He has pioneered approaches in serverless computing, blockchain systems, and mobile augmented reality that balance performance with energy constraints. Analysis of Professor Katz's recent publications reveals a strong focus on hardware-software co-design for emerging computing paradigms. His work consistently addresses the tension between performance and energy efficiency across multiple domains including cloud infrastructure, smart buildings, and mobile systems. A notable trend is his focus on making complex systems more accessible and manageable through innovative abstractions like FireSim for hardware simulation and Cirrus for serverless machine learning workflows. Scientific Awards: IEEE James H. Mulligan, Jr. Education Medal (2010) - Recognizing his exceptional contributions to engineering education Professor Katz has advised numerous PhD and Master's students who have gone on to influential positions in both academia and industry. His research has been supported by major grants from NSF, DARPA, and industry partnerships with leading technology companies. His work on Mesos, a cluster resource management system, has had significant industry impact, and his energy-efficient computing research has informed datacenter design practices across the industry. His research group at UC Berkeley has been instrumental in developing frameworks like FireSim for hardware acceleration and FirePerf for performance profiling. These tools have become important resources for the computer architecture community, enabling researchers to explore new hardware designs with unprecedented efficiency. His work on smart buildings through projects like SnapLink demonstrates his commitment to applying computing research to solve real-world sustainability challenges.

• High-Performance Computing
• Performance Modeling
• Parallel Computing
• +۳ مورد دیگر

Alexandru Calotoiu is a Researcher in the Department of Computer Science at ETH Zürich, affiliated with the Professorship for Scalable Parallel Computing. His work focuses on performance modeling, high-performance computing (HPC), serverless systems, and cloud computing. He leads research in empirical performance modeling for complex applications, optimization of parallel algorithms, and scalable cloud architectures. Key research areas include noise-resilient performance models, serverless computing frameworks, and compositional parallel programming. He has contributed to benchmarking tools like SeBS and developed techniques for loop scheduling, static analysis, and resource disaggregation in HPC environments. His publications from 2023–2025 emphasize serverless systems (e.g., FaaSKeeper, Cppless), performance embeddings for optimization, and specialized supercomputing for climate science. These studies address scalability, reproducibility, and cross-platform performance portability in data-centric workloads. No scientific awards are explicitly listed, but his work has been presented at leading conferences such as ISCA and IEEE/ACM events. He collaborates on projects like rFaaS (RDMA-enabled serverless platforms) and Process-as-a-Service frameworks. His research bridges theoretical models with practical implementations in distributed systems and cloud infrastructure.

• Computer Science
• Distributed Systems
• Caching Algorithms
• +۳ مورد دیگر

Dr. Yazhuo Zhang is a researcher at the Department of Computer Science, ETH Zürich, focusing on distributed systems, caching algorithms, and cloud infrastructure. Their work addresses core challenges in resource elasticity and web performance optimization. Key research contributions include: Advancing cache eviction algorithms beyond traditional LRU Developing causal models for latency analysis in distributed systems Improving elasticity in cloud-native environments Recent publications explore cache optimization using FIFO queues (2023), causal latency modeling (2023), and cloud-native resource management (2025).

Christos Kozyrakisمشاهده پروفایل

استاد

• Computer Architecture
• Computer Systems
• Cloud Computing
• +۶ مورد دیگر

Christos Kozyrakis is a Professor in the Departments of Electrical Engineering and Computer Science at Stanford University. His research focuses on computer architecture, computer systems, and cloud computing, with contributions to energy-efficient systems, machine learning infrastructure, and database-oriented operating systems. He leads the MAST research group and directs the Stanford Platform Lab. Education: Bachelor's Degree in Computer Science, University of Crete PhD in Electrical Engineering and Computer Sciences, University of California, Berkeley Research Interests: Kozyrakis explores cloud management, machine learning systems, energy-efficient architectures, and hardware-software co-design. Notable projects include DBOS (a database-oriented OS), the MAST group's work on serverless computing and storage systems, and energy-proportional data center design. Awards: ACM SIGARCH Maurice Wilkes Award ISCA Influential Paper Award NSF Career Award Okawa Foundation Research Grant ACM and IEEE Fellowships Advising & Grants: Supervised over 20 PhD and master's students, with notable alumni contributing to academia and industry. Supported by NSF, DARPA, SRC, Google, Microsoft, and other industry collaborations. Labs & Teams: Leads the MAST research group and directs the Stanford Platform Lab, focusing on cutting-edge systems research and prototyping.

Mladen Veinovićمشاهده پروفایل

استاد

• Cybersecurity
• Network Security
• Data Protection
• +۷ مورد دیگر

Mladen Veinović is a Professor at Singidunum University, affiliated with the Faculty of Informatics and Computing. He holds a Doctorate in Systems Theory from the School of Electrical Engineering, University of Belgrade (1996), along with postgraduate and bachelor's degrees in Automatic Control and Electronics from the same institution. His research focuses on cybersecurity, network security, signal processing, and machine learning. Key contributions include work on malware C2 infrastructure, IoT security, steganography, and robust speech processing algorithms. He has authored/co-authored over 40 books and numerous peer-reviewed articles in journals like IEEE Access, Sensors, and Computers & Security. Veinović is actively involved in education technology, developing secure communication tools and problem-based learning approaches. His work spans cloud forensics, blockchain applications, and pandemic-era teaching strategies. He has been a key contributor to projects like the WIDE web development framework and cybersecurity tools for sensor networks. Professional affiliations include Singidunum University's research institute and participation in international conferences like Sinteza and TELSIKS. His expertise bridges theoretical research and practical applications in digital systems, IoT, and information security.

André van Hoornمشاهده پروفایل

استاد

• Software Performance Engineering
• Distributed Systems
• Software Architecture
• +۴ مورد دیگر

Prof. Dr.-Ing. André van Hoorn was a distinguished academic at the University of Hamburg , leading the Software Development and Construction Methods group in the Department of Computer Science since 2023. His research focused on quantitative analysis of performance and quality attributes in complex distributed systems, contributing significantly to software engineering and architecture communities. He held leadership roles in SPEC Research and organized ICPE and ECSA conferences. Education and Career: He previously worked at Oldenburg, Kiel, and Stuttgart universities. His academic rank was Professor, reflecting his expertise and leadership in software systems research. Research Interests: His work emphasized resilience engineering, microservices, cloud computing, and performance optimization. He developed tools like Kieker for performance monitoring and frameworks like Radon for serverless computing analysis. Teaching and Outreach: He actively mentored students and pioneered the SeaSchool project to introduce students to non-programming aspects of computer science. His pedagogical innovations included tablet-based e-exams in large courses. Legacy: His contributions span academic leadership, impactful research, and community engagement. Condolence books are available at the University of Hamburg’s Department of Computer Science, and a fundraising campaign supports his family.

Hong Zhangمشاهده پروفایل

استادیار

• Large-scale data analytics
• Distributed ML training and serving systems
• Application and network scheduling
• +۵ مورد دیگر

Hong Zhang is an Assistant Professor at the University of Waterloo, specializing in large-scale data analytics, distributed machine learning systems, and cloud computing. His research focuses on advancing robust and efficient methods for modern AI systems, including topics like adversarial robustness, zero-knowledge proofs for deep learning, and scalable inference techniques for large language models. He holds a Ph.D. in Computer Science from the Hong Kong University of Science and Technology and dual bachelor's and master's degrees in Electronics and Communications Engineering from Huazhong University of Science and Technology. Education: Ph.D., Computer Science and Engineering, Hong Kong University of Science and Technology (2019) B.Sc. and M.Sc., Electronics and Communications Engineering, Huazhong University of Science and Technology, China (2013) Research Interests: Hong's work bridges theoretical foundations and practical applications in distributed ML systems, data center networking, and secure AI. Key areas include optimizing large-scale training/serve pipelines, mitigating adversarial vulnerabilities, and developing privacy-preserving techniques like zero-knowledge proofs for deep learning. His contributions span both algorithmic innovations and real-world system implementations. Publications Trends: Recent work emphasizes scalable inference acceleration (e.g., Eagle series), trustworthy AI (e.g., generative model guidelines), and cryptographic safeguards for ML (e.g., zkdl/zkllm frameworks). He frequently explores intersections between security, efficiency, and scalability in modern AI systems. Awards/Grants: No specific awards or grants mentioned in available texts. Advising & Labs: While student names aren't listed, his research group likely focuses on distributed systems and secure ML. Active collaborations likely involve cloud computing and adversarial machine learning domains.