جست‌وجوی استاد و پژوهشگر

Bradley Reavesمشاهده پروفایل

دانشیار

• Cyber Security
• Network Security
• Mobile Security
• +۲ مورد دیگر

Bradley Reaves serves as an Associate Professor in the Department of Computer Science at North Carolina State University and is a core member of the Wolfpack Security and Privacy Research (WSPR) Lab and the Secure Computing Institute. His work focuses on real-world security and privacy challenges across cellular networks, mobile platforms, and software systems. Education: Ph.D. in Computer Engineering, University of Florida (2017) M.S. in Computer Science, Georgia Institute of Technology (2015) Research Interests: Dr. Reaves pioneers interdisciplinary security solutions combining signal processing, machine learning, and cryptography to combat robocalls, mobile fraud, and software vulnerabilities. His work spans telephone network security (e.g., call authentication systems), mobile money security in developing economies, and software secret leakage in repositories. He emphasizes practical impact through industry collaboration and deployable tools. Publication Trends: Recent work (2023-2024) shows concentrated focus on telecom security (call traceback, SMS phishing), software vulnerability management (LLM-assisted patching, secret leakage), and network policy systems . His research consistently bridges theoretical innovation with real-world data collection, including analysis of 1.5 million robocalls and mobile money transaction fraud. Awards: Best Paper at ACM WiSec (2013) Advising and Collaborations: Dr. Reaves mentors Ph.D., Master's, and undergraduate researchers through structured pathways: Ph.D. applicants must demonstrate specific interest in his publications; Master's students typically engage via courses like CSC 574; undergraduates require CSC 230 completion and 10+ weekly hours. Industry partnerships include data sharing under confidential agreements, student hiring pipelines, and commissioned research for telecom fraud analysis. Labs and Teams: He leads the Wolfpack Security and Privacy Research (WSPR) Lab, which operates within NC State's Secure Computing Institute. The lab specializes in large-scale security measurement studies and develops tools like SNORCall for robocall analysis and SecretBench for secret leakage detection.

Petr Kuznetsovمشاهده پروفایل

استاد

• Distributed Systems
• Algorithms
• Synchronization
• +۳ مورد دیگر

Petr Kuznetsov is a Professor at Telecom Paris (Institut Polytechnique de Paris), affiliated with the Department of Computer Science and Networks (INFRES). He leads the Autonomous Critical Embedded Systems (ACES) research team at the Information Processing and Communication Laboratory (LTCI). His work bridges theoretical foundations and practical applications in distributed systems. Research Focus: Kuznetsov specializes in distributed algorithms, synchronization protocols, failure detection mechanisms, and the application of algebraic topology to distributed computing. His recent work explores Byzantine fault tolerance, blockchain consensus, and concurrency in networking infrastructures. Recent Publication Trends (2015-2025): His articles predominantly focus on scalability and resilience in distributed systems, with emerging themes in blockchain technologies, Byzantine fault tolerance, and concurrency optimization. Theoretical contributions include computability theorems and complexity bounds, while applied work targets payment systems and distributed ledgers. Awards & Honors: Best Paper Award at DISC 2019 for Scalable Byzantine Reliable Broadcast Best Student Paper Award at PODC 2018 for An Asynchronous Computability Theorem for Fair Adversaries Projects & Advising: He directs the TrustShare Innovation Chair (large-scale data synchronization) and DISCMAT (mathematical foundations of distributed computing). Actively seeks PhD candidates for projects on distributed algorithms and concurrency. Laboratory & Teams: Heads the ACES team at LTCI, focusing on critical embedded systems and fault-tolerant distributed architectures. Collaborates internationally through workshops like SPTDC.

• Human-Machine Interaction
• Neuroergonomics
• Physiological Computing
• +۳ مورد دیگر

Raphaëlle N. Roy is a Professor at ISAE-SUPAERO, part of the University of Toulouse, France. Her academic career spans multiple institutions, including the Gipsa-Lab in Grenoble and the University of British Columbia. She specializes in Neuroergonomics and Physiological Computing, focusing on Human-Machine Interaction in aerospace contexts. PhD in Cognitive Neuroscience & Signal Processing, Université Grenoble Alpes/CEA-Leti (2015) Habilitation à Diriger des Recherches (HDR), Université de Toulouse (2022) Certified Lecturer in Neuroscience (2016) Her research interests include Neuroergonomics , Brain-Computer Interfaces , and Neuroadaptive Technology , with applications in aerospace systems. She leads the Neuroergonomics and Human Factors research group and coordinates the Certificate in Human Factors & Neuroergonomics for Aeronautics and Transportation . Roy has organized major conferences like the International Neuroergonomics Conference (Paris 2016, Munich 2021, Bordeaux 2024) and co-founded the French BCI association CORTICO , serving as Vice-President since 2023. She is an Associate Editor for Frontiers in Neuroergonomics and has reviewed for over 30 journals and conferences, including NeurIPS and IEEE Transactions. Ministerial fellowship for PhD thesis She supervises PhD and Master’s students, including Mathias Rihet , Elena López-Contreras González , and Pauline Dreyer , and collaborates with institutions like INRIA, TU Delft Robotics Institute, and LAAS-CNRS. Her work is supported by ANR, ESA, and CNES grants, including the EPIIC project (ANR).

• Financial Mathematics
• Stochastic Processes
• Risk Management
• +۳ مورد دیگر

Prof. Dr. Francesca Biagini is a full Professor at the Department of Mathematics, University of Munich (LMU Munich) , leading the Stochastics and Financial Mathematics working group. She serves as Vice President for International Affairs and Diversity at LMU Munich since October 1, 2019, and as President of the Bachelier Finance Society (2022–2023). She is also a Correspondent of the Deutsche Aktuarvereinigung (DAV) and a member of the Executive Board of the Munich Risk and Insurance Center (MRIC) since 2017. Her research focuses on stochastic processes in financial markets , particularly asset price bubbles , default risk modeling , and robust hedging under model uncertainty. Recent work includes deep learning applications to bubble detection and non-linear affine processes for market dynamics. She actively contributes to academic leadership through teaching and publications, including 15+ recent articles on topics like liquidity-induced bubbles, machine learning calibration, and systemic risk transfer equilibrium. Her workgroup collaborates on quantLab initiatives and DAV certificate programs .

Heyuan Shiمشاهده پروفایل

دانشیار

• Software Quality Assurance
• Kernel Fuzz Testing
• Operating System Security
• +۳ مورد دیگر

Heyuan Shi is an Associate Professor at the School of Electronic Information, Central South University since 2023. He earned his B.S. (2015) and Ph.D. (2020) from Central South University and Tsinghua University respectively. His research focuses on software quality assurance with emphasis on kernel fuzz testing , open source software security , and AI application security . Presided over 10+ projects including NSFC General Program (No.62472448) and National Key R&D Sub-Project Published 30+ CCF-A/B papers across software security, machine learning, and quantum testing Supervised 15+ graduate students in software quality assurance areas His recent 2024-2025 publications demonstrate expertise in: LLM-enhanced patch classification Quantum neural network verification Hypergraph adversarial attacks RTOS fuzzing techniques Scientific recognition includes: 2024 Beijing Science & Technology Progress Award (First Prize) Hunan Province Xiaohe Sci-Tech Talent (2023) China Association for Science & Technology Young Talent (2025-2027) Active in academic service as PC member for FM2024 and reviewer for IEEE Transactions journals. Leads industry collaborations with Alibaba and Beijing Institute of Aerospace Metrology.

Ayşe İLGÜN KAMANLIمشاهده پروفایل

مدرس

• Management
• Strategy
• Organizational Behavior
• +۷ مورد دیگر

Dr. Ayşe İLGÜN KAMANLI is a Lecturer at the Faculty of Economics and Administrative Sciences of Doğuş University, Turkey, with academic roles since 2016. She holds a PhD in Management and Organization from Marmara University and has an extensive record in business administration. Education : BSc in Business Administration (Doğuş University), MSc in Business Administration (Doğuş University), PhD in Management and Organization (Marmara University) Her research focuses on organizational commitment , family business institutionalization , leadership styles , and corporate social responsibility . She has supervised 14+ theses on topics ranging from employee motivation to family business sustainability. The trends in her publications emphasize: Organizational performance in SMEs Workplace stress and retention CSR in education and healthcare sectors Political marketing discourse Transactional leadership impacts Institutional theory applications She received the Journal Best Paper Certificate in 2016. Her work spans both national and international publications, including a 2024 book chapter on green transformation in business.

• MIMO communications
• Reconfigurable intelligent surfaces
• Radio resource allocation
• +۴ مورد دیگر

Emil Björnson is a Professor of Wireless Communications and Head of the Communication Systems Department at KTH Royal Institute of Technology since 2024. He received his Master of Science in Engineering Mathematics from Lund University (2007) and PhD in Telecommunications from KTH (2011). After postdoctoral work at SUPELEC, France (2012-2014), he held faculty positions at Linköping University (2014-2021) before returning to KTH in 2020. Research Focus: MIMO communications, reconfigurable intelligent surfaces, radio resource allocation, machine learning for communications, and energy efficiency Editorial Roles: Editor for multiple IEEE transactions and magazines His research has significantly advanced wireless communication technologies, particularly in Massive MIMO and cell-free systems. He has authored four textbooks, including Massive MIMO Networks (2017) and Introduction to Multiple Antenna Communications and Reconfigurable Surfaces (2024). Scientific awards include: IEEE Fellow Clarivate Highly Cited Researcher Wallenberg Academy Fellow Digital Futures Fellow Multiple IEEE and EURASIP awards (2014-2024)

Alberto Rosمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Processing
• Multicore Processors
• +۵ مورد دیگر

Alberto Ros is a Full Professor at the University of Murcia , Spain, in the Computer Engineering Department (DITEC) . His work focuses on cache coherence , memory hierarchy designs , memory consistency , and processor microarchitecture , with over 100 peer-reviewed publications. Dr. Ros earned his MS (2004) and PhD (2009) in Computer Science from the University of Murcia. He interned at the School of Informatics, University of Edinburgh , and held postdoctoral positions at the Technical University of Valencia and Uppsala University . He is an IEEE Senior Member . Research interests include optimizing hardware for multicore systems. His work spans cache coherence protocols, transactional memory, speculative execution, and data/instruction prefetching techniques. He led the ERC Consolidator Grant (2018) and ERC Proof of Concept Grant (2023) to improve multicore architecture performance. Recent publications emphasize hardware transactional memory efficiency, speculative execution, and secure cache systems. Notable works include cache locking, memory dependency prediction, and fine-grain coherence protocols. Scientific awards : Inducted into the MICRO Hall of Fame ISCA Hall of Fame 27 HiPEAC paper awards (MICRO, ISCA, HPCA, ASPLOS) Winner, ML-based Data Prefetching Competition Winner, 1st Instruction Prefetching Championship IEEE MICRO TopPicks for ISCA'17, MICRO'21 (honorable), MICRO'16 (honorable) Best paper awards at HiPC'16, FORTE'16 Honorable mention at HPCA'24 Nomination at ISCA'22 Grants as Principal Investigator include ERC Proof of Concept (2023) ERC Consolidator (2018) Europe Excellence (2018) Seneca Foundation, Young Leaders in Research (2014) . Dr. Ros is affiliated with the Computer Architecture and Parallel Systems Group (CAPS) at the University of Murcia and previously with UPMARC at Uppsala University.

Daniel Romeroمشاهده پروفایل

استاد

• UAV Communications
• Wireless Communications
• Time-Series Analysis
• +۵ مورد دیگر

**Daniel Romero** is a **Professor** in the **Department of Information and Communication Technology** at the **University of Agder**, Norway. His research focuses on UAV communications, time-series analysis using machine learning and network science, and decentralized processing for sensor networks. He holds a Ph.D. in Signal Theory and Communications from the University of Vigo (2015), an M.Sc. in Signal Theory (2011), and a Telecommunication Engineering degree (2009). **Education**: Ph.D. in Signal Theory and Communications, University of Vigo (2015) M.Sc. in Signal Theory and Communications, University of Vigo (2011) Telecommunication Engineering, University of Vigo (2009) **Research Interests**: His work spans UAV communication systems (focusing on low-latency, high-reliability networks), time-series analysis for complex systems (using ML and network science), and decentralized computation in sensor networks to improve robustness and hardware efficiency. Recent projects include radio map estimation for mmWave beam alignment, spoofing detection via graph neural networks, and aerial base station placement optimization. **Publications**: Over 30+ peer-reviewed articles in top venues like IEEE Transactions on Wireless Communications and ICC. Recent trends emphasize radio map estimation (2023–2024), UAV-enabled spectrum surveying (2022), and robust D2D communications (2022). **Advising & Grants**: Teaches PhD courses (Statistical Signal Processing, Advanced Optimization) and leads the **Advanced Signal Processing Lab (ASL)**. Collaborates with the **CIEM (Center for Integrated Emergency Management)** on crisis-related communication systems. **Labs/Teams**: Directs the Advanced Signal Processing Lab (ASL.uia.no) and contributes to CIEM, applying ML and signal processing to emergency management challenges.

• Artificial Intelligence (AI)
• Machine Learning Algorithms
• AI Ethics
• +۴ مورد دیگر

Daswin De Silva is a Full Professor of AI and Analytics at La Trobe University, Australia, and Deputy Director of the Centre for Data Analytics and Cognition (CDAC). He also holds an Adjunct Professor position at Lulea University of Technology, Sweden. His expertise spans AI ethics, algorithm development, and applications in healthcare, energy, and education. He leads major initiatives like the La Trobe Energy AI Platform for net-zero emissions and the OptusU AI Micro-credentials program. Education: PhD in AI (Monash University, 2011). Awards include the Australian Awards for University Teaching (2021), Vice-Chancellor’s Teaching Award (2019), and Mid-Career Research Excellence Award (2018). Editor of five journals including IEEE Transactions on Industrial Informatics and Springer Discover AI. Research focuses on generative AI, ethical AI systems, and vector symbolic architectures. Recent work includes AI applications in healthcare diagnostics, energy efficiency, and smart cities. He has secured AU$14M in research funding and supervised 15 PhD completions with 10 current students. Leadership roles include Deputy Chair of La Trobe’s Research & Graduate Studies Committee and chairmanship of IEEE committees on Responsible AI and Web/Information Systems. Keynote speaker at global conferences like IEEE HSI, INDIN, and ETFA. Media engagements include ABC News, Forbes, and The Conversation.

Prashant Shenoyمشاهده پروفایل

استاد

• Distributed Systems
• Networking
• Cloud Computing
• +۷ مورد دیگر

Prashant Shenoy is a Distinguished Professor and Associate Dean in the College of Information and Computer Sciences at the University of Massachusetts Amherst. He has been on the faculty since 1998 and heads the Laboratory for Advanced Systems Software while directing the Center for Smart and Connected Society. His research focuses on systems issues for distributed systems ranging from large server clusters to networks of small sensors. Shenoy received his PhD in Computer Science from the University of Texas at Austin in 1998, following an MS from the same institution in 1994. He earned his BTech in Computer Science and Engineering from the Indian Institute of Technology, Bombay in 1993. His academic progression at UMass Amherst has been from Assistant Professor (1998-2004) to Associate Professor (2004-2009) to Professor (2009-2020) to Distinguished Professor (2020-present). His primary research interests include distributed systems, networking, cloud and edge computing, mobile computing and Internet of Things, and energy and sustainability. Over the past decade, his work has increasingly focused on computational decarbonization, as evidenced by his recent $12 million NSF Expedition award in this area. His research group maintains several important resources including the UMass Trace Repository, UMass CS Weather Station, BenchLab, and Smart* Dataset. Shenoy's publications reflect a progression from foundational distributed systems work to increasingly sustainability-focused research. His recent work centers on carbon-aware computing, energy optimization, and computational decarbonization across various computing domains including cloud, edge, and IoT systems. ACM Fellow (2019) AAAS Fellow (2018) IEEE Fellow (2013) ACM Sigmetrics Test of Time Award (2016) NSF Career Award recipient Conti Research Fellowship recipient Lilly Foundation Teaching Fellow As an educator, Shenoy has consistently taught Distributed and Operating Systems (Compsci 677) and has mentored numerous PhD students who have received awards and gone on to successful careers. He serves as the founding Chair of the ACM Special Interest Group on Energy (SIGEnergy) and has organized numerous conferences including serving as PC chairs for the ACM Symposium on Edge Computing in 2025. His research has secured significant funding, including a recent $12 million NSF Expedition in Computational Decarbonization awarded in May 2024. Shenoy leads the Laboratory for Advanced Systems Software at UMass Amherst and directs the Center for Smart and Connected Society. He serves on editorial boards of several journals including ACM Transactions on IOT (TIOT), ACM Modeling and Performance Evaluation of Computing Systems (TOMPECS), and ACM Transactions on the Web (TWEB).

Bettina Kemmeمشاهده پروفایل

استاد

• Distributed Systems
• Cloud Computing
• Database Systems
• +۵ مورد دیگر

Bettina Kemme is a Professor in the School of Computer Science at McGill University, Montreal, Canada. She leads the Distributed Information Systems Lab (DISL) and specializes in large-scale data management, distributed systems, and cloud computing. Her academic roles include teaching COMP 512 (Distributed Systems) and COMP 421 (Database Systems). Education: Diplom (M.Sc. equivalent) in Computer Science, Friedrich-Alexander University, Erlangen, Germany (1996) PhD in Computer Science, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland (2000) Research Interests: Distributed systems, cloud-native data management, in-database analytics (AIDA project), monitoring-as-a-service frameworks, and scalable pub/sub systems for online games. Current projects focus on integrating machine learning with databases, cloud performance monitoring using SDN, and sustainable data systems for data science. Lab & Collaborations: Leads the Distributed Information Systems Lab (DISL) with active projects in distributed databases, cloud computing, and game systems. Collaborates on EU-Canada initiatives like the SustainSys program for sustainable data infrastructure. Advising: Supervises PhD and M.Sc. students in topics like monitoring frameworks (Mona ElSaadawy), in-database ML (Winnie He), and distributed systems (Maximilian Schiedermeier). Alumni include over 50 researchers from PhD candidates to undergraduate researchers.

Ellen Muirمشاهده پروفایل

استادیار

• Economic Theory
• Market Design
• Mechanism Design
• +۳ مورد دیگر

Ellen Muir is an Assistant Professor of Applied Economics at the MIT Sloan School of Management. Her research focuses on the behavior of firms with market power, employing mechanism design to analyze pricing, labor procurement, and regulatory interventions. She holds a PhD in Economics from Stanford University (2022) and a PhD in Mathematics and Statistics from the University of Melbourne, alongside MSc and BSc degrees from the same institution. Educational Background: PhD in Economics, Stanford University, 2022 PhD in Mathematics and Statistics, University of Melbourne MSc in Mathematics and Statistics, University of Melbourne BSc in Mathematics and Statistics, University of Melbourne Research Interests: Ellen’s work addresses classic economic questions through mechanism design, including optimal pricing strategies, labor market dynamics under monopsony power, and regulatory frameworks. Her studies shed light on phenomena such as involuntary unemployment, opaque pricing, and market rationing. Key areas include property rights, auction design, and market thickness optimization. Recent Publications: Her recent work includes studies on optimal Hotelling auctions, mechanism-design approaches to property rights, and labor procurement under minimum wage policies. These contributions appear in top journals like the Journal of Political Economy and the Journal of Economic Theory. Professional Background: Before MIT Sloan, Ellen was a Prize Fellow in Economics, History, and Politics at Harvard University. She has authored numerous working papers and maintains affiliations with the MIT Sloan School of Management.

• Geomatics Engineering
• Remote Sensing
• Civil Infrastructure Monitoring
• +۳ مورد دیگر

Mostafa Arastounia is an Assistant Professor of Geospatial Sciences at Kennesaw State University (KSU). He holds a PhD in Geomatics Engineering from the University of Calgary (Canada) and an MSc in Geo-Information Science from the University of Twente (Netherlands). He is licensed as a Professional Engineer in Geomatics in British Columbia and holds a Project Management Professional (PMP) certification. His research focuses on automated processing of LiDAR and Unmanned Aircraft (UA) data for infrastructure monitoring, including railroads, tunnels, and electrical substations. He develops algorithms for object recognition, 3D modeling, and workflow optimization in geospatial applications. He serves as a Topic Editor for Remote Sensing Journal and is a reviewer for journals like IEEE Transactions on Geoscience and Remote Sensing and Sensors . His teaching includes undergraduate courses in surveying, civil engineering, and geography at KSU. His work bridges geomatics, remote sensing, and civil engineering to enhance infrastructure resilience and maintenance through advanced data analytics. Key research areas include automated mapping of civil infrastructure, LiDAR-based asset recognition, UAS data workflows, and interdisciplinary applications of geospatial technologies. His peer-reviewed publications span journals like ISPRS Journal of Photogrammetry and Infrastructures , with a focus on advancing automation in geospatial data processing.

Frédéric PASCALمشاهده پروفایل

استاد

• Statistical Signal Processing
• Machine Learning
• Adaptive Radar Detection
• +۵ مورد دیگر

Frédéric Pascal is a Full Professor at CentraleSupélec, part of the University of Paris-Saclay, and a member of the Laboratoire des Signaux et Systèmes (L2S). His research focuses on statistical signal processing, machine learning, and robust estimation techniques, with applications in radar detection, covariance matrix estimation, and information geometry. He has held roles including Coordinator of AI activities at CentraleSupélec and Head of the "Signals and Statistics" group at L2S. His academic journey includes a PhD from University Paris X – Nanterre (2006) and an HDR (2012) from University Paris-Sud. His work emphasizes adaptive signal processing in non-Gaussian environments, with contributions to robust covariance estimation, M-estimators, and applications in radar systems and biomedical signal processing. He has authored over 100 journal/conference papers and serves as an Associate Editor for IEEE Transactions on Signal Processing and Elsevier Signal Processing. Current research interests include AI transparency, data-driven methods for industry 4.0, and health-related signal analysis.