جست‌وجوی استاد و پژوهشگر

• Digital Piracy
• Information Security
• Computer Security
• +۶ مورد دیگر

Rahul Telang is a Professor of Information Systems and Management at the H. John Heinz III School of Public Policy and Management at Carnegie Mellon University. His work spans digital piracy , computer security , and the economics of information systems , with a focus on policy implications of technology. His research examines the interplay between online piracy and cybersecurity , including how malware propagates through infringing sites. He also investigates privacy regulation (e.g., app privacy labels ), search engine advertising , and the economics of software vulnerabilities . Recent papers analyze artificial intelligence in copyright policy and workforce analytics using occupational skill embeddings . While Telang’s articles frequently use empirical methods and natural experiments , no formal scientific awards are listed in the available data. His collaboration network includes scholars from Carnegie Mellon, Emory, Chapman University, and Indian School of Business, covering topics like ride-hailing congestion and data breach impacts . No student advising or lab affiliation details are explicitly mentioned.

• Signal Processing
• Medical Imaging
• Computer Vision
• +۴ مورد دیگر

Benoît Macq is a distinguished professor at the ICTEAM Institute , Université catholique de Louvain, Belgium. With over 350 publications spanning 1990–2025, his work bridges signal processing , medical imaging , machine learning , and data security . Key collaborators: Christophe De Vleeschouwer Simon K. Warfield Jean-François Delaigle Mathieu De Craene Research interests include: Adaptive algorithms for real-time model deployment and domain adaptation 3D reconstruction and medical image segmentation for radiation therapy Security in blockchain-based distributed learning systems Transformers for EEG classification and proton radiography Recent publications focus on foundation models in cytology and remote sensing, holonic multi-agent systems for VR, and secure codestreams for UAV object detection. His work emphasizes scalable architectures and privacy-preserving techniques in dynamic environments. Advising: Dani Manjah Antoine Aspeel Maxime Zanella

Slavisa Aleksicمشاهده پروفایل

استاد

• Communication Technology
• Network Infrastructure and Cloud
• Data Science
• +۷ مورد دیگر

Dr. Slavisa Aleksic is a Professor for Network Technologies and Network Management at the Faculty of Digital Transformation , Leipzig University of Applied Sciences (HTWK Leipzig) since February 2021. Previously, he held academic roles at Hochschule für Telekommunikation Leipzig (2015-2021), TU Wien (2010-2015), IBBT, Ghent University (2011), and TU Wien in various capacities since 1999.

• Machine Learning
• Cloud Computing
• Fault Diagnosis
• +۳ مورد دیگر

Chao Yin is a researcher at Shanghai University , Department of Computer Engineering and Science. His work spans multiple domains including Machine Learning, Cloud Computing, Fault Diagnosis, and Supply Chain Optimization. Key research areas: Machine Learning , Cloud Computing , Quantum Computing , Supply Chain Systems , Network Security Scientific Contributions (2024-2025): Developed heterogeneous graph neural networks for automotive supply chain analysis Created MSDF-VAE cloud-edge fault diagnosis framework using transfer learning Proposed quantum metrology methods with Heisenberg-limited precision Designed LARP pseudonym protocol for V2X communication Optimized fog computing resource scheduling with hybrid metaheuristics Prior Work (2012-2023): Contributed to fluid animation feature preservation from single images Developed label distribution learning for facial age estimation Designed erasure coding storage systems for big data Created multi-agent manufacturing networks in cloud environments

Henry Hoffmannمشاهده پروفایل

استاد

• Self-aware Computing
• Adaptive Computing
• Computer Systems
• +۵ مورد دیگر

Henry Hoffmann is Professor and Liew Family Chair of the Department of Computer Science at the University of Chicago. He serves as Chair of the department and leads research in self-aware and adaptive computing systems. His work bridges traditional computer systems areas with control theory and machine learning to create systems that automatically adapt to meet high-level goals. Hoffmann received his Ph.D. from MIT in 2013 under advisors Anant Agarwal and Srinivas Devadas, with his dissertation titled "SEEC: a framework for self-aware management of goals and constraints in computing systems." He earned an S.M. from MIT in 2003 and a B.S. with highest honors and distinction from UNC-Chapel Hill in 1999. Hoffmann's research focuses on developing self-aware computing systems that understand high-level goals and automatically adapt their behavior to meet those goals optimally. His recent work has shifted toward applying these techniques to control machine learning and AI systems, building learning systems that dynamically adapt their internal structure and resource usage to meet accuracy, energy, performance, and security goals at inference time. His interdisciplinary approach combines operating systems, computer architecture, control theory, and machine learning. Analysis of Hoffmann's recent publications reveals a clear trajectory toward increasingly sophisticated applications of self-aware computing principles. His work has evolved from foundational resource management to cutting-edge applications in AI/ML systems, quantum computing, and security. The publications demonstrate a consistent theme of using control theory and machine learning to create adaptive systems that optimize multiple competing objectives like performance, energy efficiency, and reliability. Recent papers show expanding applications into large language models, quantum algorithms, and privacy-preserving techniques. Presidential Early Career Award for Scientists and Engineers (PECASE) 2019 DOE Early Career Award 2015 Samsung Security Hall of Fame recognition IEEE Micro Top Picks Honorable Mention awards FSE Test of Time Honorable Mention ASPLOS Hall of Fame recognition Hoffmann has mentored numerous PhD and Master's students who have gone on to successful careers in academia and industry. His research has secured over $19 million in funding for the University of Chicago. He co-founded Config Dynamics in 2019 to commercialize aspects of his self-aware computing research. His work has practical applications across data centers, edge computing, AI systems, and quantum computing. Hoffmann leads the SEEC (Self-aware, Energy-Efficient Computing) research group at the University of Chicago. The group focuses on developing frameworks and techniques for building self-aware computing systems that can dynamically adapt to changing conditions and requirements. The group maintains strong collaborations with industry partners and other academic institutions, particularly in the areas of quantum computing, AI systems, and energy-efficient computing.

Federico Olmedoمشاهده پروفایل

استادیار

• Program Verification
• Probabilistic Programming
• Language-Based Security
• +۵ مورد دیگر

Federico Olmedo is an Assistant Professor at the Computer Science Department of the University of Chile, where he teaches courses like Program Analysis and Verification ( CC4101 ) and Discrete Mathematics for Computer Science ( CC3101 ). His research focuses on the semantics and verification of probabilistic programs , with applications in language-based security , differential privacy , and formal verification of cryptographic systems . Previously, he was a postdoctoral researcher at RWTH Aachen University and earned his PhD from the Technical University of Madrid in 2014. Research Interests : Program Verification Probabilistic Programming Language-Based Security Theorem Provers Quantum Computing Cryptographic Proofs Publications span formal methods for probabilistic programs, including weakest precondition calculi , runtime analysis of quantum programs , and machine-checked proofs for cryptographic protocols . Notable works include the Best Theory Paper Award at ECOOP 2016 and foundational research on conditioning in probabilistic programming . He co-developed the CertiCrypt and CertiPriv frameworks for verifying cryptographic proofs and differential privacy in Coq. Scientific Awards : ECOOP 2016 Best Theory Paper Award

Vasyl Kvartiukمشاهده پروفایل

پژوهشگر

• Local/Rural Governance
• Inclusive Local Economic Development
• Behavioral Economics
• +۴ مورد دیگر

Dr. Vasyl Kvartiuk is a Research Associate at the Leibniz Institute of Agricultural Development in Transition Economies (IAMO), specializing in Agricultural Policy . His work focuses on land reform, institutional quality, political economy of agricultural subsidies, and rural development in transition economies, particularly Ukraine, Russia, and Kazakhstan. PhD in Economics (2014) from Martin Luther University Halle-Wittenberg MA in Economics and Politics (2011) from Freiburg University Research interests include localized governance, behavioral economics, and international labor migration. He has contributed extensively to studies on farmland rental and sales markets, regulatory capture in agricultural subsidies, and post-war land policy digitalization. His recent work analyzes how institutional frameworks affect land market efficiency, including wartime challenges in Ukraine and subsidy dynamics in Russia. Key projects involve AG-InstitutionsNaturalResources , GUCE-SAFE , and UaAgriDialog , with a focus on sustainable agricultural systems and stakeholder engagement.

Martina Zitterbartمشاهده پروفایل

استاد

• Multimedia Communication Systems
• Mobile and Ubiquitous Communication
• Ambient Technologies
• +۷ مورد دیگر

Martina Zitterbart is a Professor of Computer Science at the Karlsruhe Institute of Technology (KIT) , with a career spanning over 30 years in telematics research. She leads the Institute of Telematics , focusing on multimedia communication systems , mobile networking , and wireless sensor networks . Current C4 Professor at KIT since 2001 PhD in Computer Science (University of Karlsruhe, 1990) Visiting scientist at IBM Research (USA/Switzerland, 1989-1992) Her research now integrates artificial intelligence into network security and 6G automation . Key projects include: KIWI : Federated machine learning for cross-domain attack detection Open6GHub : 6G infrastructure development (€66.8M BMBF grant) 6G-ANNA : Network automation for next-gen mobile systems Recent publications focus on: DDoS attack detection through machine learning QUIC protocol performance in long-term use energy packet transmission for smart grids autonomic network management She has received multiple awards including: Alcatel SEL Research Prize (2002) Best Paper Awards (EI.A 2024, NoF 2023) Teaching Excellence Recognition (2003, 2008) As a member of IEEE, ACM, and the German Society for Informatics, she actively contributes to academic discourse through conferences like SIGCOMM and workshops on blockchain technology.

• Formal Methods
• Graph Databases
• Property Graph Schema
• +۵ مورد دیگر

Ştefania-Gabriela Dumbravă is an Associate Professor at Institut Polytechnique de Paris (ENSIIE/Samovar Laboratory). Her research focuses on formal methods for graph database algorithms , including schema design, query processing, and verification. She contributes to international standards through co-chairing VLDB 2026 Demonstration Track and organizing workshops like VLDB Summer School 2025 . Dumbravă serves on editorial boards (e.g., ACM Transactions on Database Systems ) and program committees for top-tier conferences ( SIGMOD , ICDE ). Research Interests include formal verification of graph databases , property graph schema constraints , certified inference engines , and distributed graph systems . She integrates proof assistants (Coq, Isabelle) with practical database development, emphasizing reliability and mechanical correctness . Her work spans theoretical foundations (e.g., category theory , type theory ) and real-world applications (e.g., transit accessibility analysis , SDN controllers ). Selected Scientific Awards : EASST Best Software Science Paper Award (ICGT 2025) SIGMOD Best Paper Award (2023) VLDB Best Regular Paper Runner-Up (2022) D4Gen Hackathon 3rd Prize Teaching includes Graph Databases , Functional Programming , and Formal Languages at ENSIIE, with additional roles at Université Paris-Saclay, ENS Lyon, and Université Rennes 1. She supervises research internships and participates in gender parity initiatives (e.g., Paris-Saclay Women & Science Mentorship Program).

• Data Privacy
• Cybersecurity
• Internet of Things (IoT)
• +۴ مورد دیگر

Vincent Naessens is a researcher at Ghent University, Belgium, with a focus on data privacy, cybersecurity, and IoT systems. His work spans privacy-preserving data publishing, security analysis of industrial control systems, and secure IoT applications. Research Interests: Data Privacy, Cybersecurity, IoT, eHealth Systems, Machine Learning. His recent articles (2023-2025) explore advanced anonymization pipelines, Linux-based IoT benchmarks, and reverse engineering of IoT ecosystems. These works emphasize balancing privacy utility, detecting firmware vulnerabilities, and improving location masking in colluding environments. Dr. Naessens has collaborated extensively with researchers like Jorn Lapon, Jan Vossaert, and Michiel Willocx, contributing to conferences such as ARES, SEC, and WOOT. His projects include cloud pricing analysis, IoT security seminars, and eHealth system privacy mechanisms.

• Software Security
• Complex Systems
• Artificial Intelligence
• +۶ مورد دیگر

Pierre Parrend is a researcher at INSA de Lyon's College of Engineering, focusing on software security, complex systems, and artificial intelligence applications. He has published extensively on topics including OSGi platform security, graph-based attack detection, and biologically inspired computing models. His research bridges cybersecurity with machine learning, emphasizing explainable AI for threat detection. Recent work includes Agentic AI frameworks for offensive security Graph processing methodologies for ML Multilayer architectures in cyber-physical systems Key collaborations include Pierre Collet, Stéphane Frénot, and Julio Navarro. While no formal education details appear in the data, his work spans 2006-2025 with significant contributions to zero-day attack detection and security architecture.

• Computer Science
• Education
• Machine Learning
• +۳ مورد دیگر

Brian Broll is a Vanderbilt University researcher in the College of Engineering with a focus on computer science education , distributed computing , and machine learning accessibility . He has collaborated extensively with Dr. Ákos Lédeczi and other researchers to develop educational tools like NetsBlox and DeepForge for K-12 and higher education contexts.

Gordon Fraserمشاهده پروفایل

استاد

• Software Engineering
• Software Testing
• Automated Testing
• +۹ مورد دیگر

Gordon Fraser is a Professor and holds the Chair of Software Engineering II at the Faculty of Computer Science and Mathematics, University of Passau, since 2017. His academic journey includes a doctorate from Graz University of Technology and research experience at Saarland University and the University of Sheffield. Research Interests: His work centers on software analysis, software development, and programming education. Key themes include preventing software errors through automated testing, improving developer productivity using AI-based tools, and enhancing programming training—especially for beginners and children. He actively explores the role of gamification, large language models, and search-based techniques in software testing and education. Recent Research Trends: His recent publications (2023–2024) show a strong focus on flaky tests in Python, automated test generation for Android and block-based environments (Scratch), gamification of testing in IDEs, and educational studies on pair programming, gender dynamics, and feedback mechanisms in primary computing education. The integration of AI and machine learning in software testing is a recurring theme, especially in the context of large language models and neuroevolution. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: He leads several research projects, including DFG-funded TYPES4STRINGS and DeepMBT , and the DeepCode project which explores AI for code quality. He mentors a large number of students and researchers, particularly in the areas of automated testing and programming education. His advising spans PhD and Master’s students, many of whom are co-authors on his publications. Labs and Teams: He leads a research group at the University of Passau focused on software testing, analysis, and education. The team develops tools like Pynguin for automated Python testing and Code Defenders for gamified software testing education. They also work on LitterBox , a linter for Scratch programs, and various gamification plugins for IDEs and educational platforms.

• Energy meteorology
• Smart grids
• Photovoltaics
• +۷ مورد دیگر

Professor Gerd Heilscher holds the endowed professorship for "Energy Data Management of Decentralized Renewable Energy Systems" at Ulm University of Applied Sciences, where he heads the Smart Grids Research Group within the Institute of Energy and Drive Technology. His office is located in room W3204 at Albert-Einstein-Allee 53-55, 89081 Ulm. His research concentrates on: Integration of high solar power proportions into distribution grids Energy meteorology applications for photovoltaics Development of planning procedures for energy infrastructure Creation of standards for secure "energy information networks" Professor Heilscher previously served as Managing Director of meteocontrol GmbH – Energy and Weather Services in Augsburg from 1991 to 2006 before his 2006 academic appointment. During a 2011/12 research semester in Hawaii, he analyzed rapid irradiance changes and their grid impacts. Professional memberships: VDI, VDE, IEEE, ISES, DGS, DMG and SmartGridsBW Operating Agent of IEA PVPS Task 14 "Solar PV in a 100% RE Power System" Awards: Ulm Science Prize (2014) He teaches Energy Data Management, Electrical Networks, Renewable Energy Systems, Energy Economics Seminar, Photovoltaics, and Energy Meteorology courses.

• Sensor Networks
• Middleware Systems
• Federated Learning
• +۵ مورد دیگر

Eleftheria Katsiri is a researcher with extensive contributions to computer science , focusing on sensor networks , middleware systems , and serious games . Her work bridges privacy-preserving machine learning with IoT applications in healthcare and environmental monitoring. Collaborations with Alexandros Gazis, Pavlos S. Efraimidis, and other researchers highlight her interdisciplinary approach. Key publication venues: Frontiers Robotics AI , ICR , CoRR , Communications of the ACM Research trends since 2022 include federated learning for health apps, blockchain middleware, and edge intelligence for air quality monitoring. Her articles demonstrate expertise in abstract reasoning, sensor data fusion, and scalable middleware design. No formal awards or academic appointments are mentioned in available data.