جست‌وجوی استاد و پژوهشگر

Christopher Chenمشاهده پروفایل

دانشیار

• Space Plasma Physics
• Solar Wind
• Plasma Turbulence
• +۵ مورد دیگر

Dr. Christopher Chen is a Reader in Space Plasma Physics at Queen Mary University of London, holding a UKRI Future Leaders Fellowship. He is affiliated with the School of Physical and Chemical Sciences within the Department of Physics and Astronomy. Chen earned his PhD in Space Physics from Imperial College London in 2011 and has held research positions at the University of California, Berkeley and Imperial College before joining QMUL in 2017, where he progressed from Lecturer to Senior Lecturer in 2021 and then to Reader in 2022. Chen's research focuses on space plasma physics, particularly solar wind turbulence and its fundamental properties. His work bridges theoretical models, spacecraft data analysis, and laboratory experiments to understand complex plasma behavior. He is actively involved in several major space missions including Parker Solar Probe (as a member of FIELDS and SWEAP teams), Interstellar Probe mission study, and Magnetospheric Multiscale mission (as a member of the Science Working Team). His publication record shows a strong focus on solar wind turbulence, Alfvén wave interactions, and plasma dynamics in the inner heliosphere. The most recent work emphasizes forecasting techniques for solar wind parameters, laboratory experiments of wave interactions, and detailed analysis of turbulence properties using data from Parker Solar Probe. His research demonstrates a clear progression toward understanding the kinetic-scale processes that govern energy transfer in space plasmas. Royal Astronomical Society Fowler Award (2017) American Geophysical Union Macelwane Medal (2021) Conferred Fellow of the American Geophysical Union (2021) American Physical Society Landau-Spitzer Award (2022) Chen actively supervises a large research group including multiple postdoctoral researchers and PhD students, and has secured significant research funding through an STFC Ernest Rutherford Fellowship (2016-21), UKRI Future Leaders Fellowship (2022-26), and multiple STFC Consolidated Grants. His teaching responsibilities include organizing and lecturing the Astrophysical Plasmas module and supervising Masters and undergraduate research projects. He is also engaged in extensive public outreach through media interviews, public talks, and participation in science festivals.

Stephen Taylorمشاهده پروفایل

استاد

• Cybersecurity
• Distributed Computing
• Computer and Network Security
• +۴ مورد دیگر

Stephen Taylor is a Professor of Computer Engineering at Dartmouth College's Thayer School of Engineering. His research focuses on cybersecurity, distributed computing, and embedded systems security. He has held leadership roles including DARPA Program Manager and Air Force Research Laboratory IPA. Taylor's work includes foundational contributions to the National Cyber Range and Air Force Cyber Experimentation Environment. Education: BSc in Computer Systems from Essex University (1982), MSc in Computer Science from Columbia University (1985), and PhD in Computer Science from the Weizmann Institute (1989). Research emphasizes resilient operating systems for cloud computing, security mechanisms for embedded systems, and large-scale experimentation infrastructure. Awards include the USAF Exemplary Civilian Service Medal and Secretary of Defense Medal for Public Service. Teaches courses on microprocessors, software design, and cyberspace technology. Advises on multi-disciplinary projects and has authored 4 books and over 25 journal articles. His lab explores hardware-software co-design for cyber resilience and soil-based sustainable computing.

Niko Mäkitaloمشاهده پروفایل

استادیار

• Cyber-Physical Systems
• AI/ML Software Engineering
• IoT Architectures
• +۳ مورد دیگر

Niko Mäkitalo is an Assistant Professor at the University of Jyväskylä's Faculty of Information Technology and a member of the University Consortium Chydenius. His research focuses on advancing cyber-physical systems through innovative software architectures for AI, IoT, and the Cloud-Edge Continuum, with significant emphasis on hardware and network infrastructures. He teaches and mentors graduate students in these areas. Research Interests: Mäkitalo's work centers on creating intelligent environments via novel software frameworks, engineering methodologies for distributed AI/ML applications, and addressing ethical/privacy challenges in edge computing. He explores the intersection of agile development practices, third-party code management, and industry standards like IDSA/GAIA-X for AI integration. Key Contributions: His recent work includes studies on software ownership dynamics, regulatory-aware AI deployment, and liquid AI systems. He leads the Empirical Software Engineering Research group and collaborates on initiatives like 6GSoft for edge-cloud software solutions. Advising & Grants: Mäkitalo supervises Master's and Ph.D. candidates in software engineering and systems architecture. His projects often involve industry partnerships to address real-world challenges in smart manufacturing, autonomous systems, and networked environments. Labs/Teams: Active in the Empirical Software Engineering Research group, contributing to cross-disciplinary projects at the University of Jyväskylä's tech innovation ecosystem.

David Bellمشاهده پروفایل

پژوهشگر

• Atmospheric Chemistry
• Environmental Science
• Secondary Organic Aerosol (SOA)
• +۵ مورد دیگر

Dr. David Bell is a Scientist at the Paul Scherrer Institute (PSI) within the Center for Energy and Environmental Sciences and Laboratory of Atmospheric Chemistry . Since 2017, he has conducted research on aerosol formation and aging processes, particularly focusing on secondary organic aerosol (SOA) from biomass burning and complex combustion sources. He transitioned to a Tenure Track position at PSI in 2021. Education : B.Sc. in Chemistry and Mathematics from University of Wisconsin-Stevens Point (2008); Ph.D. in Chemistry from University of Utah (2013); Postdoctoral Researcher at Pacific Northwest National Laboratory (2013-2017). His research systematically investigates aerosol source profiles using atmospheric simulation chambers and real-time chemical composition analysis. Key areas include secondary organic aerosol formation , oxidative potential of combustion aerosols , and humidity effects on aerosol behavior . He employs advanced instrumentation like extractive electrospray ionization mass spectrometry (EESI-TOF) for molecular-level insights. The 15 most recent publications (2023-2025) highlight his work on biomass burning emissions , α-pinene oxidation , NO3 radical impacts , and instrument development for aerosol analysis. His studies emphasize the interplay between inorganic-organic interactions (e.g., ammonia effects) and climate-relevant processes (e.g., cloud formation).

Marta Catilloمشاهده پروفایل

پژوهشگر

• Cybersecurity
• Machine Learning
• Intrusion Detection Systems
• +۳ مورد دیگر

Marta Catillo is a Researcher at the Department of Engineering (DING) of the University of Sannio (UNISANNIO) . She specializes in Cybersecurity , with focus on Machine Learning applications for intrusion detection , IoT security , and cloud auto-scaling mechanisms . Her research addresses challenges in Denial of Service (DoS) mitigation , anomaly detection , and deep learning architectures for security. Teaching: [803004] PROGRAMMING 1 for Electronic and Biomedical Engineering students (2025 cohort) Contact: Office hours: Thursdays 3-5 PM, Room 23, Bosco Lucarelli Palace Research trends: From 2019-2025 publications, her work spans adversarial attack resistance , collective anomaly detection , outlier-aware architectures , and empirical analysis of defense mechanisms , with recurring collaborations with Antonio Pecchia , Umberto Villano , and Massimiliano Rak . Key methodologies include deep autoencoders , hybrid detection systems , and measurement-based security evaluation . Technical Contributions: Developed the ZED-IDS framework for zero-day threat detection, MultiCIDS for multivariate time series intrusion detection, and DEFEDGE for edge-cloud security testing.

• Internet of Things (IoT)
• Cloud Computing
• Edge Computing
• +۶ مورد دیگر

Devki Nandan Jha is a researcher specializing in Internet of Things (IoT) , Cloud/Edge Computing , and Cybersecurity . His work focuses on runtime monitoring, security frameworks, and deployment optimization in heterogeneous environments. Collaborations include institutions across Europe and Asia, with frequent co-authorship with Rajiv Ranjan, David Wallom, and David Blundell.

• Robot Vision
• Robot Navigation
• Computer Vision
• +۷ مورد دیگر

Helder Araujo is a Professor at the Department of Electrical and Computer Engineering, University of Coimbra. His research focuses on Robot Vision , Computer Vision , and Medical Imaging , with applications in Capsule Endoscopy , Autonomous Driving , and Sensor Fusion . Recent publications highlight advancements in 3D Object Detection using transformer networks (e.g., RetSeg3D , DDet3D ), Medical Robotics (e.g., Self-supervised monocular pose estimation ), and Federated Learning (e.g., FAIR-FATE ). Key subfields include Transformer Models , Deep Learning , and Autonomous Navigation . His projects span Medical Imaging (e.g., Multi-Cam Capsule Endoscopy ), Autonomous Robotics (e.g., Learning to Navigate Endoscopic Capsule Robots ), and Edge Computing (e.g., Benchmarking CNN Inference on Low-Power Devices ). Grants include funding from Fundação para a Ciência e a Tecnologia (e.g., PTDC/EEI-ROB/1155/2020) and the European Commission (e.g., AdvanCed Hardware/Software Components for Embedded Vision). He has served as an invited researcher at Université Blaise Pascal (2012–2014). Peer review activities cover journals like IEEE Transactions on Pattern Analysis and Machine Intelligence and Autonomous Robots . His work bridges Medical Imaging , Autonomous Systems , and AI Fairness .

Rider W. Foleyمشاهده پروفایل

دانشیار

• Science and Technology Studies
• Sustainability Science
• Ethical STEM Education
• +۵ مورد دیگر

Rider W. Foley is an Associate Professor in the Science, Technology & Society program at the University of Virginia's Department of Engineering and Society. He directs the Policy Internship Program and leads the '4C Project' on Cultivating Cultures of Ethical STEM education, collaborating with institutions like Notre Dame and Arizona State University. His research focuses on societal-technology intersections, including ethical STEM education, innovation governance, sustainability challenges, and urban techno-politics. Foley holds a Ph.D. in Sustainability from Arizona State University, a Master's in Environmental Management from Harvard, and a B.S. in Environmental Science from the University of New Hampshire. Prior to academia, he worked in environmental consulting and emergency response for Triumvirate Environmental Inc. His work spans themes like responsible innovation, wicked problems, and policy interventions for equitable technological development. Education: Ph.D. in Sustainability, Arizona State University M.S. in Environmental Management, Harvard University B.S. in Environmental Science, University of New Hampshire His research interests emphasize 'wicked problems' requiring interdisciplinary solutions, such as nanotechnology governance, smart city equity, and energy infrastructure ethics. He co-leads the 'Nano and the City' thematic cluster at Arizona State's Center for Nanotechnology in Society and collaborates with the Sustainability Science Education program at the Biodesign Institute. Recent projects include evaluating innovation ecosystems for wearable medical devices and analyzing the Atlantic Coast Pipeline's societal impacts through public values theory. Foley's academic contributions bridge theory and practice, with a focus on pedagogy (e.g., concept mapping for learning outcomes) and participatory methods (e.g., community-governed network commons). He explores how education and policy can align technological advancements with societal needs, particularly in marginalized communities. His work on anticipatory governance frameworks aims to preempt ethical challenges in emerging technologies like geoengineering and synthetic biology. His advising and grants include collaborations on the '4C Project' and 'Nano and the City,' leveraging partnerships between academia, industry, and policymakers. Current efforts involve refining methodologies for assessing student learning in engineering ethics and advancing frameworks for sustainable innovation in arid regions. Foley is affiliated with the Center for Nanotechnology in Society and contributes to initiatives like the Secure Affordable Sustainable Edge Clouds (SASEC) for smart cities.

• Information Systems
• Big Data
• Cloud Computing
• +۱۲ مورد دیگر

Norman H. White is a Clinical Professor in the Department of Information, Operations, and Management Sciences at the Leonard N. Stern School of Business, New York University. He has been a faculty member since 1973 and currently serves as the Faculty Director of the Stern Center for Research Computing, where he supports advanced computational research across the school. His research spans big data, cloud computing, distributed computing, data science, decision support systems, and mobile applications . He has published in areas including data mining, computer networking, and simulation. His work bridges technology and business applications, particularly in marketing and financial engineering. Professor White holds a Ph.D. in Economics and Statistics from NYU Stern (1974) and a B.A. in Engineering and Applied Physics from Harvard University (1966). He previously served as Deputy Chair of the Information Systems Department and Acting Chief Technology Officer of the Stern School. He has been actively involved in university-wide computing initiatives and has consulted for major organizations including Anheuser-Busch, Kraft, Toyota, Ford, Goldman Sachs, and the U.S. State Department. The Stern Center for Research Computing, under his leadership, provides a high-performance computing grid, private cloud infrastructure, and Hadoop-based big data clusters to support research. He teaches courses such as Dealing with Data , Designing and Developing Web and Mobile Apps , and Computational Approaches to Financial Engineering .

• Computer Architecture
• High-Performance Computing
• Distributed Systems
• +۱۲ مورد دیگر

Yolanda Becerra Fontal is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the Barcelona School of Informatics (FIB). She is actively involved in research projects and collaborations, notably with the Barcelona Supercomputing Center, and is a member of prominent research groups such as the High Performance Computing Group (CAP) and CROMAI (Computing Resources Orchestration and Management for AI). Research Interests: Her research spans a broad spectrum of computer systems, with a consistent focus on performance, efficiency, and scalability. Key areas include Computer Architecture , High-Performance Computing (HPC) , Distributed and Cloud Systems , Resource and Energy Management in virtualized environments, and Data-Intensive Computing . More recently, her work has centered on innovative time-series database systems and data management for edge and cloud analytics. Publication Trends: Her recent scholarly output (2020-2022) shows a strong emphasis on time-series data management, proposing novel database architectures like NagareDB and strategies for polyglot persistence. Earlier work (2009-2013) was pivotal in MapReduce workload management, energy accounting for virtualized systems, and optical data center networks, demonstrating a long-standing contribution to foundational distributed computing challenges. Scientific Contributions: Her work has been published in top-tier journals and conferences such as Future Generation Computer Systems , IEEE Transactions , and Nucleic Acids Research . She has also contributed to significant competitive R&D projects and holds patents related to data flow management and distributed indexing. Advising and Grants: Dr. Becerra Fontal has served as a thesis advisor for doctoral students. Her research has been funded through competitive grants from national and regional programs, including Spanish State Research Plans (Plan Estatal de Investigación) and Catalonia's RIS3CAT strategy, supporting projects on high-performance computing and data management. Research Groups and Labs: She is a core member of the CAP - High Performance Computing Group and the CROMAI - Computing Resources Orchestration and Management for AI group at UPC. Her work is closely associated with the Barcelona Supercomputing Center (BSC) , one of Europe's leading supercomputing facilities, indicating access to advanced computational infrastructure.

Martin Wulf Gerdesمشاهده پروفایل

دانشیار

• eHealth
• Artificial Intelligence
• Machine Learning
• +۹ مورد دیگر

Martin Wulf Gerdes is an Associate Professor at the Department of Information and Communication Technology, University of Agder, Norway. With a Ph.D. in eHealth and over two decades of experience in telecommunications and healthcare technology research, he focuses on developing user-friendly, interoperable eHealth solutions using ICT and IoT. His career spans roles at Ericsson Eurolab and academic leadership in Norway. Education: M.Sc. equivalent in General Electrical Engineering (1998) from RWTH Aachen, emphasizing ICT. Ph.D.: Information and Communication Technologies with eHealth specialization (2019) from University of Agder. Research Interests: Gerdes explores AI-driven decision support systems, distributed eHealth infrastructure, telemedicine, and assistive technologies for chronic disease management. His work bridges IoT, data privacy, and user-centered design in healthcare robotics. Teaching: Since 2014, he has taught at bachelor's and master's levels, currently leading courses in Communication & Cooperation, Technology Understanding, and seminar projects in eHealth. Scientific Publications: His 15 most recent articles (2020-2024) span AI in dental radiology, blood glucose prediction, digital twins, and ethical considerations in healthcare algorithms. Topics include IoT integration, data privacy, and pandemic analytics.

• Database Systems
• Distributed Data Management
• Concurrency Control
• +۵ مورد دیگر

Alan D. Fekete is a Professor at the University of Sydney's Department of Computer Science, specializing in database systems, distributed data management, and consistency models. His work spans transaction processing, cloud computing, and query optimization, with recent focus on enhancing database concurrency and serializable execution. Key Research Areas: Database Concurrency & Transaction Isolation Multicore Scalability & Distributed Systems Cloud Data Consistency & Replication Query Optimization & NoSQL Performance Recent publications (2023-2025) explore transactional frameworks for analytical interfaces, DB-OS co-design for data ingestion, and mixed isolation levels for serializable execution. Earlier works (2018-2014) address scalable lock managers, coordination avoidance in databases, and consistency properties in cloud storage. He has contributed to educational initiatives, including a data-centric computing curriculum (2021) and teaching threading concepts (2008). Collaborations include co-authors like Nancy Lynch, Uwe Röhm, and Joseph Hellerstein.

Dessislava Georgieva Petrova-Antonovaمشاهده پروفایل

استاد

• Service-Oriented Architectures
• Web Services
• Distributed Systems
• +۲ مورد دیگر

Dessislava Georgieva Petrova-Antonova is a Professor at Sofia University's Faculty of Mathematics and Informatics , specializing in the Department of Software Technologies . Her work focuses on service-oriented architectures, web services, and big data systems for smart cities. She holds a PhD in Software Technologies from Technical University of Sofia (2007) and an MSc in Computer Systems and Control (2000). PhD: Technical University of Sofia, Faculty of Computer Systems and Control (2007) MSc: Technical University of Sofia, Faculty of Computer Systems and Control (2000) Research Interests: She pioneers methodologies for testing web service compositions (e.g., TASSA ), develops big data platforms for smart governance, and explores digital twin modeling for urban environments. Her projects integrate IoT, quality of service (QoS) frameworks, and data-driven policy tools. Projects: Leads initiatives like National CogniTwin (National Science Fund, 2019–2022) and Big4Smart (NSF, 2017–2020). Collaborates in EU programs such as Digital Twin Cities Centre (2020–2025) and People Network+ (FP7, 2012–2013). Labs & Collaborations: Affiliated with the GATE Center of Excellence and contributes to international teams in big data and smart city research. Her work bridges academia and industry through tools like TESSI (Web Service Testing Tool) and faultInjector (BPEL Fault Injection Tool).

• Computer and networked systems security
• Systems security and privacy
• Trusted execution environments
• +۶ مورد دیگر

Nuno Santos is an Associate Professor in the Department of Computer Science and Engineering at Instituto Superior Técnico (IST), University of Lisbon, and a senior researcher at INESC-ID Lisbon, where he leads the SysSec team within the Distributed, Parallel and Secure Systems (DPSS) group. He is an active member of the international security community, serving as Program Vice Co-Chair for USENIX Security 2025 and on program committees for top venues such as IEEE S&P, CCS, and USENIX Security. Education: Ph.D. in Computer Science, 2013 – Max Planck Institute for Software Systems (MPI-SWS) & Saarland University Research internships at Microsoft Research Redmond (2010), Vrije Universiteit Amsterdam (2018), and Technical University of Munich (2024) Research Interests Nuno Santos’s research centers on the security and privacy of computer and networked systems, with particular emphasis on trusted execution environments, secure systems design, and the intersection of machine learning with security. His group investigates vulnerabilities and defenses in widely deployed platforms, including TrustZone, JavaScript runtimes, and cloud infrastructures. Additional themes include censorship-resistant communication, privacy-preserving analytics, and automated exploit generation. Recent Publication Trends Over the past five years, his work has increasingly targeted emerging threat models in confidential computing (AMD SEV-SNP, Intel TDX), large-language-model integration into web applications, and automated security analysis of JavaScript ecosystems. These publications consistently appear in the most selective venues (PLDI, SIGMETRICS, ICSE, NDSS, S&P, USENIX Security), evidencing strong empirical evaluation and real-world impact. Awards & Honors IST Outstanding Teaching Award (2019/2020) ISOC.PT Best Portuguese Internet Research Award (2024) Prémio Científico Universidade de Lisboa / Caixa Geral de Depósitos (2024) Multiple IST Teaching Excellence Awards Advising & Service Nuno Santos has supervised numerous MSc and PhD students whose theses span secure systems, network privacy, and trustworthy computing. Recent defenses include Bernardo Ribeiro, Cristi Savin, Hugo Mantinhas, João Aragonez, João Sá, and Tomás Tavares. He actively participates in doctoral committees and mentors junior researchers within the DPSS group. Labs, Teams & Collaborations He leads the SysSec team inside the Distributed, Parallel and Secure Systems (DPSS) group at INESC-ID Lisbon. The team maintains strong collaborative ties with MPI-SWS, VUSec at VU Amsterdam, the Systems Research Group at TU Munich, and multiple industry partners including Microsoft Research.

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Prof. Fabio Galasso is a Full Professor in the Department of Computer Science at Sapienza University of Rome, where he heads the Perception and Intelligence Lab (PINLab). His research focuses on fundamental innovation in computer vision and machine learning, with particular emphasis on distributed intelligent systems, perception frameworks, and general intelligence within sustainable and interpretable AI contexts. His research interests span multiple domains of computer vision including video segmentation , motion forecasting , distributed intelligent systems , and shape reconstruction . Galasso's work emphasizes sustainable AI approaches that operate within constrained computational resources while maintaining interpretability and verifiability. His research bridges theoretical foundations with practical applications across retail, smart cities, and industrial settings. His recent publications demonstrate a clear progression toward increasingly complex human motion understanding and forecasting, with a strong emphasis on real-world applications. The research trajectory shows movement from foundational video segmentation techniques toward sophisticated motion prediction systems and anomaly detection frameworks that integrate multiple modalities. Key themes include temporal consistency, computational efficiency, and practical deployability in resource-constrained environments. His scientific achievements have been recognized with prestigious awards: 2019 IoT/WT Innovation World Cup 2019 Digital Champions Award 2018 Deutscher Digital Award Galasso has coordinated significant research initiatives including a Marie Sklodowska-Curie Actions project (Horizon 2020) and served as Principal Co-Investigator in multiple German-funded projects from the Ministry of Education and Ministry of Economics. His industry experience includes founding and directing OSRAM's Computer Vision Department in Munich, where he led R&D efforts connecting AI research with smart lighting applications, resulting in successful innovation transfers like the award-winning VISN product. He leads the Perception and Intelligence Lab (PINLab) at Sapienza University of Rome, fostering research that spans fundamental computer vision techniques to practical implementations in retail, smart cities, and industrial applications. The lab maintains strong connections with both academic institutions (including previous collaborations with University of Cambridge and Max Planck Institute) and industry partners.