جست‌وجوی استاد و پژوهشگر

• Software Defined Networking
• Network Security
• Cloud Computing
• +۲ مورد دیگر

Simon Jouet is Research Fellow at the University of Glasgow's School of Computing Science specializing in software-defined networking and network security. Research focuses on: Programmable data planes using eBPF technology Distributed anomaly detection systems Network function virtualization DDoS mitigation strategies Cloud data center resource management Publications show emphasis on SDN/NFV technologies (70%) and network security (30%), with recent work expanding into operational technology resilience. Developed Glasgow Network Functions framework for virtual network function management. Research addresses challenges in cloud computing infrastructures and critical network protection during disasters. Collaborates with industry partners through European research projects on resilient networking.

Anna Lackingerمشاهده پروفایل

پژوهشگر

• Edge Intelligence
• Distributed Inference
• Federated Learning
• +۵ مورد دیگر

Anna Lackinger is a PreDoc Researcher and PhD student in the Distributed Systems Group at TU Wien's Faculty of Informatics. Holding a Diplom-Ingenieur (Master's) and BSc from TU Wien, she specializes in edge intelligence and distributed machine learning systems with applications in cloud infrastructure optimization. Education: Diplom-Ingenieur (Master of Science in Engineering), TU Wien, 2023 Bachelor of Science, TU Wien Her research centers on Edge Intelligence and Federated Learning architectures, developing communication-efficient orchestration frameworks for hierarchical learning systems. She pioneers time series prediction techniques for cloud workload forecasting, enabling proactive resource scaling while addressing challenges in heterogeneous IoT environments and communication-constrained distributed systems. Analysis of her publication record reveals consistent focus on adaptive federated learning systems that optimize communication costs while maintaining model accuracy. Her work bridges theoretical AI advancements with practical distributed systems implementations, particularly in edge-cloud continuum scenarios where resource constraints demand innovative orchestration solutions. Professional Service: Reviewer for IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS) Reviewer for International Web Information Systems Engineering Conference (WISE) Reviewer for ACM Transactions on Internet Technology (TOIT) Reviewer for IEEE Transactions on Services Computing (TSC) Reviewer for IEEE Internet Computing (IC) Reviewer for IEEE Open Journal of the Computer Society (OJCS) Anna co-advises bachelor's and master's theses in distributed systems and machine learning. She actively contributes to major research initiatives including AloTwin (2023–2025) on reactive federated learning orchestration, INTEND (2024–2026) developing adaptive inference agents, and TEADAL (2022–2025) focused on load-aware federated learning systems. As a core member of TU Wien's Distributed Systems Group, she collaborates on cutting-edge research in edge intelligence and IoT swarm coordination, advancing the RainCloud framework for decentralized heterogeneous IoT systems while contributing to the group's leadership in distributed AI infrastructure.

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

Aaron Elmore is an Associate Professor in the Department of Computer Science at the University of Chicago, affiliated with The College. His research focuses on elastic databases, cloud computing, and distributed systems, with an emphasis on database-as-a-service, resource-efficient systems, and collaborative analytic platforms. Education : PhD in Computer Science, University of California, Santa Barbara (2015) MS in Computer Science, University of Chicago (pre-PhD) Industry experience prior to academia Research Interests : Cloud computing, distributed systems, database systems, IoT analytics, edge computing, and data management. He develops systems like CrocodileDB (resource-efficient query execution), VergeDB (IoT analytics), and CodecDB (data-driven encoding). His work also explores compression techniques ( DenseStore , EdgeTSD ) and collaborative tools ( DataHub , Decible ). Labs & Groups : ChiDATA: Research on large-scale video analysis and data economics Systems Group: Focus on systems, programming languages, and software engineering CERES Center: Unstoppable computing and system resilience Awards include the NSF CAREER Award (2021), multiple Google DANI Awards (2024–2023), and ACM SIGMOD recognitions. Grants & Advising : Active in securing industry grants (e.g., J.P. Morgan, Google) and has advised numerous PhD students and postdocs, including Dixin Tang (now Assistant Professor at UT Austin) and Chunwei Liu (MIT postdoc). Labs/Teams : ChiDATA, Systems Group, and the CERES Center for collaborative and resilient computing initiatives.

Shay Solomonمشاهده پروفایل

دانشیار

• Design and analysis of algorithms
• Graph compression problems
• Dynamic graph algorithms
• +۴ مورد دیگر

Shay Solomon is an Associate Professor in the School of Electrical & Computer Engineering at Tel Aviv University. His research focuses on theoretical computer science, particularly in the design and analysis of algorithms for graph problems, distributed systems, and computational geometry. He coordinates the EE-Systems Department Colloquium and has received funding from prestigious organizations including the European Research Council (ERC), the Israel Science Foundation (ISF), and the US-Israel Binational Science Foundation (NSF-BSF). Professor Solomon's research interests span several key areas in theoretical computer science. He has made significant contributions to dynamic graph algorithms, developing novel techniques for problems like set cover and graph coloring. His work on Euclidean spanners and metric embeddings has advanced our understanding of geometric data structures. In distributed computing, he has explored locality-sensitive approaches to network representation. His research on sublinear algorithms addresses fundamental questions about what can be computed efficiently with limited resources. Across all these areas, his work is characterized by mathematical rigor and practical significance for algorithm design. Analysis of Professor Solomon's recent publications (2023-2025) reveals a strong focus on advancing the state-of-the-art in graph algorithms. His work frequently appears in top theoretical computer science venues including STOC, FOCS, and SODA. A notable trend is his exploration of dynamic algorithms that can efficiently update solutions as input changes, with applications to set cover and graph coloring problems. He has also made significant contributions to the theory of graph spanners in Euclidean and metric spaces, establishing new bounds and constructions. His collaborative work with researchers like Hung Le and Sayan Bhattacharya demonstrates the interdisciplinary nature of modern theoretical computer science research. Professor Solomon acknowledges support from several prestigious funding sources: European Research Council (ERC) Israel Science Foundation (ISF) US-Israel Binational Science Foundation (NSF-BSF) As the coordinator of the EE-Systems Department Colloquium, Professor Solomon plays an active role in academic community building at Tel Aviv University. While specific information about his advisees isn't provided in the source material, his research group likely includes graduate students working on theoretical computer science problems. His extensive publication record suggests an active research program with numerous collaborations across the global theoretical computer science community.

Michalis Kokologiannakisمشاهده پروفایل

استادیار

• Programming Languages
• Compilers
• Software Verification
• +۵ مورد دیگر

Michalis Kokologiannakis is an Assistant Professor in the Department of Computer Science at ETH Zurich, Switzerland. Previously, he was affiliated with the Max Planck Institute for Software Systems (MPI-SWS) in Germany where he completed his PhD. His research focuses on programming languages, compilers, and software verification, with particular emphasis on: Automated verification and testing of concurrent programs Weak memory models employed by modern microprocessors Stateless model checking techniques Formal methods for program analysis His work has led to the development of several verification tools including GenMC (a stateless model checker for C/C++ programs under weak memory models) and Kater (a tool that automates weak memory model metatheory and consistency checking). Dr. Kokologiannakis has published extensively at top-tier programming languages and verification conferences including PLDI, POPL, OOPSLA, and CAV. His research has pioneered advances in stateless model checking, partial order reduction, and verification under weak memory consistency models. He completed his MEng at the National Technical University of Athens (NTUA) before earning his PhD from MPI-SWS.

Heikki Ailistoمشاهده پروفایل

استاد پژوهشی

• Artificial Intelligence
• Software Engineering
• Smart Buildings
• +۴ مورد دیگر

Heikki Ailisto serves as a Research Professor at VTT Technical Research Centre of Finland within the BA5A Management and Support department. With a research career spanning from 1985 to present, he maintains active involvement in cutting-edge technology research and development projects. His research interests focus on Artificial Intelligence applications , Software Engineering methodologies , Smart Building technologies , and Digital Governance frameworks . A significant portion of his work addresses the practical implementation of AI systems in public sector contexts and industrial applications, with particular attention to Finnish societal needs and environmental considerations. Analysis of his recent publications reveals a strong trend toward interdisciplinary research connecting technology development with policy implications and sustainability goals. His work consistently bridges theoretical concepts with practical implementations, particularly in energy management systems and manufacturing data integration. Dr. Ailisto actively contributes to major research initiatives including: Future of Software Engineering (2025-2027) GOWELL: Governance of new technologies towards sustainability and well-being (2024-2026) His media presence includes contributions to discussions about AI development in Finland, such as the 2021 media appearance "Kohti tekoälyn kesää?" (Toward the Summer of AI).

Nagarajan Kandasamyمشاهده پروفایل

استاد

• Computer Engineering
• Embedded Systems
• Self-Managing Systems
• +۵ مورد دیگر

Nagarajan Kandasamy is a Professor and Interim Department Head in the Department of Electrical and Computer Engineering at Drexel University. His research focuses on computer engineering, with expertise in neuromorphic computing, embedded systems, fault-tolerant architectures, and distributed systems. Prior to Drexel, he worked as a research scientist at Vanderbilt University's Institute for Software Integrated Systems. PhD, University of Michigan (2003) MS, University of Connecticut BE, Guindy Engineering College, Anna University, Chennai, India His research interests include neuromorphic computing, spiking neural networks, and reliable system design. He has contributed to fields like deformable image registration, self-testing hardware, and wireless security frameworks. Kandasamy's publications emphasize neuromorphic architectures, medical imaging algorithms, and secure communication protocols. His work often intersects hardware-software co-design and machine learning applications. National Science Foundation Early Faculty (CAREER) Award (2007) Best Paper Award, IEEE International Conference on Autonomic Computing (2006) He collaborates across disciplines in neuromorphic engineering, with grants from NSF and industry partners. His team develops tools for radiation oncology, low-power AI systems, and FPGA-based security protocols.

• Knowledge Graphs
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Sareh Aghaei serves as a Research Fellow at the Institute of Management Sciences within the Faculty of Mechanical Engineering and Industrial Management at Vienna University of Technology (TU Wien), focusing on knowledge-driven solutions for industrial maintenance and healthcare systems. Her academic credentials include: Ph.D. in Computer Science from the University of Innsbruck (2023) M.Sc. in Computer Science from the University of Isfahan Dr. Aghaei's research integrates knowledge graphs with natural language processing and machine learning to develop explainable AI systems. Her work spans industrial maintenance optimization, clinical decision support, and tourism information systems, emphasizing ontology engineering and question-answering frameworks that transform unstructured data into actionable knowledge. Analysis of her 2021-2025 publications reveals a strategic shift toward domain-specific knowledge graph applications, particularly in maintenance management (2022-2025) and health informatics (2023-2024). This evolution demonstrates increasing specialization in medical knowledge representation while maintaining foundational contributions to semantic web technologies established in earlier works like her 2011 Web services architecture research. Her scholarly recognition includes: netidee Grant Call 17: Austria's award for most innovative doctoral theses Dr. Aghaei's doctoral research was funded through the netidee scholarship. Current documentation indicates no active student supervision or major grant leadership beyond her postdoctoral position at TU Wien. Within TU Wien's Institute of Management Sciences, she contributes to research bridging production engineering and artificial intelligence, developing knowledge-based systems for predictive maintenance and industrial process optimization through interdisciplinary collaboration.

Hai Dongمشاهده پروفایل

مدرس ارشد

• Service-Oriented Computing
• Edge Intelligence
• Blockchain
• +۴ مورد دیگر

Dr. Hai Dong is a Senior Lecturer at the School of Computing Technologies, RMIT University in Melbourne, Australia, with promotion to Associate Professor scheduled for 2026. He serves as the Founding Director of the CloudTech-RMIT Green Cryptocurrency Joint Research Laboratory (GreenCryptoLab) and Leader of the Smart Sensing and Services Research Area. Previously, he held research fellow positions at both RMIT University and Curtin University. Dr. Dong is a Senior Member of IEEE and chairs the IEEE Computational Intelligence Society Task Force on Deep Edge Intelligence. Dr. Dong's research spans several cutting-edge domains including Service-Oriented Computing, Edge Intelligence, Blockchain, AI Security, Cyber Security, and Machine Learning. His work bridges theoretical foundations with practical applications, particularly in secure and efficient computing systems. He has developed innovative approaches for smart contract security, edge computing optimization, federated learning, and blockchain applications with a strong focus on sustainability and real-world impact. His publication record demonstrates consistent high-impact contributions across top venues including AAAI, ASE, ICML, TSE, and TSC. Dr. Dong's research shows a clear trajectory toward increasingly sophisticated integration of AI with edge computing and blockchain systems, with growing emphasis on security, privacy, and resource efficiency. Recent work highlights his leadership in addressing emerging challenges in LLM-generated smart contracts and secure federated learning systems. Best Research Paper Award at ICSOC 2016 Best Paper Award at IEEE ICBC 2025 2023 RMIT Award for Research Engagement and Impact - Industry Engagement in Graduate Research Dr. Dong has successfully supervised numerous PhD and Master's students to completion, with many going on to prestigious positions. He has secured over $5 million in research funding as Chief Investigator from sources including ARC, CRC, QNRF, and industry partners like ANZ, CloudTech, and Telstra. His GreenCryptoLab research facility represents a significant industry-academic partnership focused on sustainable blockchain technologies. Dr. Dong maintains active collaborations with researchers worldwide and serves on committees for over 100 international conferences.

Patrick Basمشاهده پروفایل

استاد پژوهشی

• Steganography
• Steganalysis
• Digital Watermarking
• +۲ مورد دیگر

Patrick Bas serves as Research Director and Thematic Group Facilitator for the Data Intelligence Group (DatInG) at the University of Lille, France, where he leads the Signal and Images team within the CRISTAL laboratory. His office is located at ESPRIT in Lille's Scientific City, and he holds membership on the institution's Scientific Council. Bas earned his Electrical Engineering degree (1997) and Ph.D. in Signal and Image Processing (2000) from the Institut National Polytechnique de Grenoble. His academic journey includes postdoctoral work at Université Catholique de Louvain, CNRS research at Gipsa-Lab (2001-2009), and a visiting position at Helsinki University of Technology (2005-2008). His primary research centers on steganography, steganalysis, and digital watermarking, with significant contributions to image manipulation detection and neural network applications in multimedia security. He has organized major initiatives including the BOSS steganalysis contest (2010) and served as co-coordinator for the Ecrypt European NoE's watermarking virtual lab (2004-2008). While his Google Scholar profile indicates recent publications in graph theory and combinatorics (2021-2025), these appear inconsistent with his documented research focus on multimedia security as evidenced by his thesis supervision and professional activities. Bas has supervised seven doctoral theses including Rony Abecidan's work on robust image manipulation detection (2024) and Solène Bernard's research on neural network steganography (2021). He has held editorial roles for the Eurasip Journal on Information Security (since 2011) and IEEE Transactions on Information Forensics and Security (2013-2016), and co-organized the International Workshop on Information Hiding (IH07).

Tej Chajedمشاهده پروفایل

استادیار

• Formal Verification
• Systems Software
• Concurrency
• +۴ مورد دیگر

Tej Chajed is an Assistant Professor in the Department of Computer Science at the University of Wisconsin-Madison. His research focuses on formal verification of systems software, particularly addressing concurrency and crash safety in file systems and distributed protocols.

Greg van Andersمشاهده پروفایل

دانشیار

• Condensed Matter Physics
• Soft Condensed Matter
• Inverse Materials Design
• +۵ مورد دیگر

Greg van Anders is an Associate Professor in the Department of Physics, Engineering Physics & Astronomy at Queen's University. His research focuses on the intersection of condensed matter physics, soft condensed matter, and systems physics, with a particular emphasis on inverse materials design, self-assembly, and statistical mechanics. He leads the Greg van Anders Group, which explores emergent phenomena in complex systems, including colloidal crystals, hierarchical materials, and distributed system design. Education: BSc in Applied Math from the University of Western Ontario (2003), PhD in Physics from the University of British Columbia (2008). Before joining Queen's, he held positions at the University of Michigan, including postdoctoral and research faculty roles in Chemical Engineering and Physics. Research interests include entropy-driven organization, robust design principles for engineered systems, and the application of statistical mechanics to industrial design challenges. His group develops novel methods for predicting and controlling material properties through computational and theoretical approaches, such as digital alchemy and inverse design. Recent work highlights include studies on colloidal pre-assembly, neural network training optimization, and the role of shape in material phase transitions. Students and collaborators in the group work on projects ranging from computational morphogenesis to nanocrystal assembly, with funding support from NSERC, Mitacs, and the Vanier Canada Graduate Scholarship program. The group actively promotes diversity and inclusivity in scientific training, welcoming members from varied academic and cultural backgrounds. Key research themes include understanding how entropy promotes local order, designing materials with targeted mechanical properties, and analyzing system robustness through materials-inspired metrics. Recent publications emphasize applications in photonic crystals, self-assembly of anisotropic particles, and the interplay between geometry and thermodynamics in complex systems.

Hani Ragab Hassenمشاهده پروفایل

دانشیار

• Cybersecurity
• Deep Learning Applications
• Natural Language Processing (NLP) in Cybersecurity
• +۷ مورد دیگر

Hani Ragab Hassen is an Associate Professor leading the Cybersecurity with AI Research Group at the School of Mathematical & Computer Sciences, Heriot-Watt University. He specializes in cybersecurity, particularly in applying machine learning and NLP to address challenges such as malware analysis, intrusion detection, and access control systems. His roles include Associate Director of PGR Studies, Academic Integrity Officer, and former leadership in Learning & Teaching and Research programs. Research interests focus on cybersecurity fundamentals, including deep learning for malware detection, NLP-driven vulnerability assessment, and P2P systems. He has supervised numerous PhD students, currently advising three candidates on airport cybersecurity, NLP-based vulnerability detection, and network intrusion systems. His work contributes to UN Sustainable Development Goals related to innovation and infrastructure security. Publications span malware detection frameworks (e.g., ActDroid, Droiddissector), network security tools (NTFA), and machine learning optimization (D2TS). He has developed datasets like SI22 for DDoS analysis and contributed to open-source tools. His research emphasizes practical applications of AI in securing networks and cloud environments. Notable contributions include advancing Android malware detection via control flow graphs and text analysis, and pioneering cloud security protocols like Stick for social platforms. His interdisciplinary work bridges cybersecurity with machine learning and data science, addressing real-world threats through innovative solutions.

• Distributed Systems
• Distributed Computing
• Persistent Memory
• +۳ مورد دیگر

Anatole Lefort is a Postdoctoral Researcher at the Systems Research Group of the Technical University of Munich, hosted by Prof. Pramod Bhatotia. His current research focuses on CXL-based disaggregated memory systems for heterogeneous compute architectures. Dr. Lefort's educational background includes: Ph.D. in Computer Science from Institut Polytechnique de Paris (2023), advised by Pierre Sutra and Gaël Thomas. Diplôme d’Ingénieur (M.S. Eng.) from Télécom SudParis (2018), where he graduated first in his class. His research interests encompass Distributed Systems, Distributed Computing, Persistent Memory, Concurrency, Language Runtimes, and Cloud Infrastructures. During his doctoral studies, he investigated persistent memory programming, particularly for managed languages like Java, addressing challenges in memory management and concurrency. His recent publications demonstrate a strong focus on persistent memory systems, with contributions such as J-NVM for off-heap persistent objects in Java and the WB-amcast protocol for fault-tolerant atomic multicast, reflecting expertise in both systems and distributed algorithms. Dr. Lefort has been recognized with several awards: Laureate of Engineers of the Future Awards, Engineers for Research category (December 2022). Best student publication in ICTs at Institut Polytechnique de Paris (September 2022). He has not advised any students to date. His funding includes an NVMW Student Travel Grant for the 2022 workshop and a Fully-Funded Ph.D. Scholarship from Institut Mines-Télécom awarded in 2018 based on academic excellence. Currently, Dr. Lefort is part of the Systems Research Group at TUM. Previously, he was a member of the Parallel and Distributed Systems Group at Télécom SudParis during his Ph.D. studies.

Christopher Eibelمشاهده پروفایل

پژوهشگر

• Energy-Aware Systems
• Distributed Systems
• Operating Systems
• +۵ مورد دیگر

Christopher Eibel is a Researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander University Erlangen-Nuremberg (FAU). He specializes in energy-aware systems, distributed computing, and middleware design. His work focuses on optimizing energy efficiency in dynamic applications, heterogeneous computing environments, and real-time systems. His research includes projects such as BATS (tracking wildlife via sensor networks), E³ (energy-aware execution environments), and SEEP (symbolic execution for energy optimization). He has contributed to frameworks like Empya (energy-efficient middleware) and Albatross (profit-driven HPC runtime systems). Eibel has published extensively on topics like energy-aware programming, cloud computing, and heterogeneous cluster management. Notably, his work on Strome (energy-aware data-stream processing) won the Best Paper Award at DAIS 2018. He has supervised multiple theses on energy-efficient systems and middleware. He has taught courses on distributed systems and cloud computing since 2013, focusing on practical exercises and master’s seminars. His lab collaborates on projects involving high-performance computing, sensor networks, and operating system-level optimizations.