جست‌وجوی استاد و پژوهشگر

Felix Naumannمشاهده پروفایل

استاد

• Data Profiling
• Data Quality
• Data Integration
• +۴ مورد دیگر

Professor Felix Naumann is Chair for Information Systems at the Hasso Plattner Institute (HPI) at the University of Potsdam in Germany, where he leads the Information Systems research group. He is also Coordinator for MSc. Data Engineering and for the Data and AI track for MSc. Computer Science, and Speaker of the Research School on Data Science and Engineering. His extensive academic career includes visiting positions at CIRES Centre in Brisbane (2024-2025), SAP's Innovation Center (2020), AT&T Research (2016), and QCRI (2012). Professor Naumann's research focuses on data profiling, data cleansing, data integration, and data quality assessment with over 200 scientific publications. His work spans theoretical foundations and practical applications, with significant contributions to data quality metrics, metadata extraction, and AI-driven data preparation techniques. His research group develops prominent systems like Metanome for data profiling and Metis for data quality assessment. His recent publications demonstrate continued innovation in data management, with a growing intersection between traditional database research and AI applications. The 15 most recent papers show increasing focus on data quality for AI applications (KITQAR), multimodal data analysis (MELArt), and practical data cleaning frameworks that bridge database systems with machine learning pipelines. GI Dissertationspreis 2000 for best computer science PhD thesis IBM Research Division Award, 2002 Distinguished ACM member since 2021 Distinguished Reviewer Award - SIGMOD 2023 Best paper award at EDBT 2024 for Tasheeh paper Professor Naumann has successfully advised over 30 PhD students who now hold prominent positions at institutions like MIT, Google, Snowflake, and universities worldwide. His research has been funded by major grants including DFG Nachwuchsforschergruppe (2003-2008), IBM SUR Grant (2007), and DFG Forschergruppe Stratosphere (2010-2016). He leads the Information Systems research group at HPI, which includes PostDocs, PhD students, and student assistants working on projects like Metanome, Metis, KITQAR, and Janus, focusing on data profiling, quality assessment, and change exploration in data systems.

• CMOS integrated circuits
• Computer architecture
• Electrical and electronic engineering
• +۱۲ مورد دیگر

Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.

Xiaoyang Wangمشاهده پروفایل

مدرس ارشد

• Graph Processing
• Graph Neural Networks
• Spatial Data Processing
• +۱۰ مورد دیگر

Xiaoyang Wang is a Senior Lecturer in the School of Computer Science and Engineering (CSE) at the University of New South Wales (UNSW). He holds a Bachelor's and Master's degree in Computer Science from Northeastern University, China, and earned his PhD from CSE UNSW. Dr. Wang's research focuses on database systems with a special emphasis on query processing and data mining on large-scale graph, spatial, and streaming data. His expertise extends to data-driven machine learning, smart contract analysis on blockchain, and FinTech with financial network analysis. His work spans Graph Processing, Graph Neural Networks, Spatial Data Processing, AI for Databases (AI4DB), Database for AI (DB4AI), and FinTech applications. His publication record shows significant contributions to the field with 7 book chapters, 56 journal articles, 61 conference papers, 7 edited conference proceedings, and 4 conference abstracts. Recent publications (2022-2025) demonstrate his strong research trajectory in advanced graph processing techniques, neural network applications, and innovative database approaches. Key themes include hierarchical contrastive learning, robust attack frameworks, temporal graph processing, influence maximization, knowledge graph-enhanced reasoning, and rumor mitigation. Dr. Wang actively recruits PhD students interested in pursuing research in related fields and encourages current undergraduate and master's students at UNSW to contact him about research opportunities. He maintains an active research agenda with practical implications for industries dealing with large-scale network data, financial technology applications, and data-intensive systems. He can be reached at xiaoyang.wang1@unsw.edu.au and is located in Engineering building K17-501D at UNSW.

Mahbubur Rahmanمشاهده پروفایل

استادیار

• Internet of Things (IoT)
• Cyber-Physical Systems (CPS)
• Wireless Networks and Communication
• +۳ مورد دیگر

Mahbubur Rahman is an Assistant Professor in the Department of Computer Science at Queens College and the Graduate Center, City University of New York (CUNY). He earned his PhD in Computer Science from Wayne State University in 2020 and a BSc in Computer Science & Engineering from Bangladesh University of Engineering and Technology in 2012.

• Cyber Security
• Federated Learning
• Network Security
• +۵ مورد دیگر

Jonathan White serves as a Senior Lecturer in Cyber Security within the College of Arts, Technology and Environment at the University of the West of England (UWE). With over 23 years of prior industry experience in telecommunications critical infrastructure systems, he joined UWE in January 2020 after transitioning from roles as software developer, product specialist, and management leader in real-time embedded systems. His educational background includes an M.Sc. in Cyber Security (with Distinction) and B.Sc. in Computing for Real-time Systems, both from UWE, where he is currently pursuing a PhD focused on Federated Learning security tradeoffs. White's research centers on Federated Learning applications for IoT security, container security analysis, and machine learning-driven threat detection in home networks. Analysis of his publication record reveals a strong focus on practical security implementations, particularly in containerized environments (Docker security analysis, cyber ranges) and Federated Learning security frameworks. His work consistently bridges theoretical machine learning concepts with tangible security applications for IoT and edge devices, emphasizing privacy-performance tradeoffs in distributed systems. Scientific Recognition: Fellow of the Higher Education Academy (FHEA) White actively contributes to cyber security education through innovative teaching methods including the 'Cyber Funfair' immersive learning platform and Scalextric-based physical system hacking demonstrations. His industry background in telecommunications critical infrastructure informs his practical approach to security education and research, particularly regarding real-time system vulnerabilities and high-availability network security requirements. His technical expertise spans C and Python programming, network security protocols, and specialized knowledge in securing containerized environments and IoT ecosystems. Current research includes longitudinal analysis of container image vulnerabilities and development of modular cyber range infrastructure for security training.

Stavros Vologiannidisمشاهده پروفایل

استادیار

• Control Theory
• Robotics
• Machine Learning
• +۳ مورد دیگر

Stavros Vologiannidis serves as an Assistant Professor in the Department of Informatics, Computer and Telecommunications Engineering at the International University of Greece. His academic career spans both teaching and research in control theory, robotics, and machine learning applications. Previously, he was associated with the Mathematics Department at Aristotle University of Thessaloniki where he completed his education and conducted postdoctoral research. Education: B.Sc. in Mathematics from Aristotle University of Thessaloniki (1997) Ph.D. in Control Theory from Aristotle University of Thessaloniki (2005) with dissertation titled 'ALGEBRAIC-POLYONYMICAL COMPUTING METHODS IN CONTROL THEORY' Dr. Vologiannidis' research focuses on Classical and Intelligent Control Theory, Robotics, and Machine Learning, with particular expertise in polynomial matrices and automatic control systems. His work bridges theoretical mathematics with practical engineering applications, especially in educational robotics and industrial control systems. He has developed several educational platforms including EUROPA, a ROS-based educational robot for teaching sensor integration and data acquisition. His publication record shows a clear evolution from theoretical control systems research toward applied machine learning and educational technology. Recent work demonstrates increasing focus on practical applications of AI in education, urban feature recognition, industrial monitoring, and robotics education across multiple educational levels from middle school through university. His research combines mathematical rigor with real-world implementation. Scientific Recognition: Excellence Scholarship in the 'Excellence Scholarships 2010' program of the Research Committee Total citations exceeding 250 with Scopus H-index of 9 Dr. Vologiannidis has secured numerous research grants and led multiple projects including 'Rapid Earthquake Damage Assessment Consortium – REDACt', 'Predictive Maintenance 4.0', and 'Development of computational methods for optimization of eigenvalue assignment problems'. He has collaborated extensively with institutions across Europe including UTIA Foundation in Prague and has participated in EU-funded projects like GALENOS and GN4-1 GÉANT Research and Education Networking. His laboratory work centers around the EUROPA educational robotics platform and the StreetScouting urban feature detection system, both of which integrate hardware, software, and educational applications. These projects demonstrate his commitment to translating theoretical research into practical educational and industrial tools.

Philipp Weissمشاهده پروفایل

پژوهشگر

• Automotive Systems
• Internet of Things (IoT)
• Fail-Operational Systems
• +۵ مورد دیگر

Philipp Weiss is a Researcher at the Technical University of Munich (TUM), affiliated with the Department of Electrical and Computer Engineering and the Chair of Embedded Systems and Internet of Things. Holding an M.Sc. degree, he actively contributes to research and teaching in embedded systems and IoT with a strong focus on automotive applications. His research spans Automotive Systems , Internet of Things (IoT) , Fail-Operational Systems , Reliability Analysis , Agent-Based Systems , and Distributed Systems . Weiss specializes in fail-operational automotive software design, dynamic agent-based mapping methods, and run-time reliability analysis, addressing critical challenges in autonomous vehicle safety and resilience through publications in DATE and DSD conferences. Analysis of his 2020-2021 publications reveals consistent focus on fail-operational architectures for automotive systems, with recurring themes in distributed agent-based modeling, timing analysis, and energy optimization within hybrid cloud environments. His work bridges theoretical reliability frameworks with practical automotive implementations. Weiss has supervised multiple Master's theses and final projects from 2019-2021 on topics including dynamic agent-based reliability analysis and fail-over timing for neural networks. As an educator, he serves as tutor for System Design for the Internet of Things and seminar manager for Advanced Seminar Embedded Systems and Internet of Things . Embedded within Prof. Sebastian Steinhorst's research team, Weiss contributes to major initiatives including Security for IoT and Autonomous Systems , Time-Sensitive Networking , and 6G Research Hub "6G-Life" , operating within TUM's IoT Remote Lab infrastructure for hands-on experimentation with industrial IoT systems.

• Internet Governance
• Public Policy
• Cybersecurity
• +۵ مورد دیگر

Jesse Sowell is an Associate Professor at the University College London (UCL) in the STEaPP (Science, Technology, Engineering and Public Policy) department. His work intersects internet governance , cybersecurity policy , and public policy analysis , with a focus on emerging technologies like artificial intelligence and the Internet of Things. He contributes to the Sustainable Development Goal 11 (Sustainable Cities and Communities) through digital policy research. Email: j.sowell@ucl.ac.uk Collaboration Network: Active in international policy and cybersecurity research Research interests span: AI-driven policy crafting and systematic review methodologies Security lifecycle of IoT devices and networks Adaptive governance frameworks for digital risks Competition dynamics in internet infrastructure Transnational cybersecurity norms and incident response IPv4-IPv6 transition policy comparisons Publication trends reveal a focus on internet governance , cybersecurity , and AI policy , with increasing attention to IoT security (2017-2021) and AI integration in policymaking (2025). His work bridges technical and policy dimensions, emphasizing network resilience and multi-stakeholder collaboration .

Lorenzo Striginiمشاهده پروفایل

استاد

• Dependability Assessment
• Fault Tolerance
• Defense in Depth
• +۵ مورد دیگر

Lorenzo Strigini is a Professor of Systems Engineering at City St George's, University of London , where he has been affiliated since 1995 and served as Director of the Centre for Software Reliability from 2012–2024. His research focuses on dependability assessment , fault tolerance , and defense in depth for safety, security, and reliability in computer-based and socio-technical systems. He has also explored high-speed networking during his earlier career at the Italian National Research Council (IEI-CNR) and as a visiting scientist at UCLA and Bell Communications Research.

Nathalia Costaمشاهده پروفایل

پژوهشگر ارشد

• Low Back Pain Research
• Qualitative Health Research
• Pain Management
• +۵ مورد دیگر

Dr. Nathalia Costa is a Senior Research Fellow at the University of Queensland's cLinical TRials cApability (ULTRA), located within the Centre for Clinical Research in Herston, and affiliated with the Centre for Innovation in Pain and Health Research (CIPHeR). She holds appointments in the School of Health and Rehabilitation Sciences within the Faculty of Health, Medicine and Behavioural Sciences. Her research focuses on theoretically grounded qualitative and mixed methods approaches to understanding low back pain, pain management, and healthcare systems. Costa is particularly known for her groundbreaking work on low back pain flares, which established the first rigorous definition of pain flares through stakeholder engagement with over 70 experts and consumers. Her methodological expertise spans systematic reviews, qualitative methodologies (interviews, ethnography, Delphi studies), embedding qualitative research in clinical trials, and systems-thinking frameworks. Costa's recent publications demonstrate a growing focus on culturally responsive care, healthcare access for migrant populations, and the intersection of legal services with mental health. Her work bridges micro-level patient experiences with macro-level healthcare systems, aiming to make pain care more nuanced, equitable, and evidence-based. She has published over 55 papers spanning musculoskeletal conditions, pain research, health policy, and qualitative methodologies. Her scientific achievements include the 2021 ISSLS Prize for Lumbar Spine Research, recognition from the International Society for the Study of the Lumbar Spine. Her research has influenced international pain frameworks, including adoption by the International Association for the Study of Pain (IASP) in their online Fact Sheet (July 2023). Costa actively supervises multiple PhD students, serves as Associate Editor for Qualitative Health Research and the Journal of Humanities in Rehabilitation, and has taught across disciplines including research methods, musculoskeletal physiotherapy, and health policy. She has secured over AUD$7.5M in research funding, currently leading the FORENSIC trial investigating lumbar fusion surgery effectiveness for persistent severe low back pain.

Fabian Monroseمشاهده پروفایل

استاد

• Cybersecurity
• Computer Systems
• Software Security
• +۷ مورد دیگر

Fabian Monrose is a Professor at the Georgia Institute of Technology, holding the Julian T. Hightower Chair in Cybersecurity. His career spans leadership roles at the University of North Carolina at Chapel Hill (UNC), Johns Hopkins University, and Bell Labs. He earned his Ph.D. in Computer Science from New York University's Courant Institute in 1999. Dr. Monrose specializes in cybersecurity, with research focusing on malware analysis, network security, and hardware threats. His work has earned Best Paper Awards at IEEE and USENIX conferences, along with the AT&T Best Applied Security Paper Award . He has published over 100 papers and led collaborative efforts at institutions like RENCI. Dr. Monrose's recent publications include studies on TLS certificate risks, hardware trojans, and AI-aided malware evasion. Best Paper Award at IEEE Symposium on Security & Privacy Best Paper Award at USENIX Security Symposium Outstanding Research in Privacy Enhancing Technologies Award AT&T Best Applied Security Paper Award Best Student Paper Award (2013) His research trends emphasize practical security solutions , including defensive registration strategies, automated bug analysis, and IoT threat mitigation. Dr. Monrose has also contributed to cybersecurity education through gamified platforms and secure autograding systems.

Fendy Santosoمشاهده پروفایل

عضو هیئت علمی

• cyber-physical systems
• cybersecurity
• artificial intelligence
• +۶ مورد دیگر

Dr. Fendy Santoso is a Visiting Fellow at UNSW Canberra's School of Engineering and Information Technology, where he conducts cutting-edge research at the intersection of cyber-physical systems, cybersecurity, and artificial intelligence. His work focuses on developing robust security mechanisms for autonomous systems, particularly UAVs and robotics operating in adversarial environments. His educational background includes a PhD in Electrical Engineering from UNSW Sydney and a Master of Engineering (Electrical and Computer Systems) from Monash University. Dr. Santoso's research interests span cyber-physical systems security, adversarial machine learning, trustworthy autonomy, and AI-driven cybersecurity for autonomous platforms. His work specifically targets penetration-resistant architectures and secure decision-making frameworks for UAVs and robotic systems operating in dynamic, threat-prone environments. His approach integrates advanced fuzzy logic systems with deep learning techniques to create resilient control mechanisms that can withstand cyberattacks and operational uncertainties. Analysis of his recent publications reveals a consistent focus on applying type-2 fuzzy systems, deep learning, and negative imaginary control theory to solve critical challenges in autonomous systems security and control. His work demonstrates strong interdisciplinary connections between cybersecurity, control theory, and artificial intelligence, with particular emphasis on real-world implementation and experimental validation. Distinguished Early Career Travel Fellowship 2019, University of Wollongong ARC Linkage Project: Robust Defenses Against Adversarial Machine Learning for UAV Systems (2023) CSIRO Next Generation Grant for AgriTwins: Bridging Cyber-Secure Emerging Technologies and Data-Centric Twin Tech for Resilient Agriculture of the Future (2024) Dr. Santoso has secured over AUD 3 million in competitive research funding from prestigious sources including the Australian Research Council, U.S. Army Ground Vehicle Systems Centre, and Defence Science and Technology Group. He leads multi-disciplinary research teams and maintains strategic partnerships with defense and government agencies to translate theoretical advances into practical cybersecurity frameworks. His laboratory work centers around the Autonomous System Laboratory at UNSW Canberra, where he conducts experimental validation of security protocols for military ground robots and UAVs under realistic cyberattack scenarios.

Carole Dalinمشاهده پروفایل

دانشیار

• Sustainable Food Systems
• Water Resources Management
• Food Security
• +۵ مورد دیگر

Dr. Carole Dalin is Associate Professor in Sustainable Food Systems at University College London's Bartlett School of Environment, Energy & Resources, where she leads the Sustainable Food Systems research team at the Institute for Sustainable Resources. She also holds a dual appointment as CNRS Researcher at École normale supérieure in Paris, leading the European Research Council Starting Grant FLORA project on 'Sustainable and healthy food solutions: system dynamics and trade-offs'. Her academic journey began with a Diplôme d'Ingénieur from Ecole Centrale Paris in 2011, followed by a Ph.D. in Environmental Engineering & Water Resources from Princeton University in 2014 under the supervision of Ignacio Rodriguez-Iturbe. Her research bridges environmental engineering and policy, with a primary focus on the environmental sustainability of global food production and trade. Dr. Dalin's work specifically addresses water resources management within food systems, the water-food-energy nexus, and biodiversity conservation impacts. She has developed integrated environmental sustainability indicators for global food production and has made significant contributions to understanding virtual water trade and groundwater depletion embedded in international food commerce, with particular attention to vulnerable regions like Southern Africa. Dr. Dalin's scholarly output demonstrates a consistent trajectory toward understanding the complex interconnections between food systems, environmental sustainability, and human health. Her work has increasingly integrated biodiversity considerations with water sustainability metrics, and she has become a key contributor to the Lancet Countdown reports that examine health implications of climate change. Recent publications highlight her expanding focus on developing practical solutions for sustainable food systems that balance environmental protection with food security needs. NERC Independent Research Fellowship (2016-2021) ERC Starting Grant FLORA (2022-2027) Multiple contributions to The Lancet Countdown on health and climate change reports Dr. Dalin actively mentors a diverse research team comprising both current and former Ph.D. students and postdoctoral researchers who investigate various dimensions of sustainable food systems. Her research has secured funding from prestigious organizations including NERC, the European Research Council, and the Wellcome Trust. She maintains strong collaborative relationships across institutions, particularly with UCL's Centre for Biodiversity and Environment Research and French research institutions through her CNRS position at École normale supérieure. She facilitates the Water and Food Resource Nexus research theme at UCL's Institute for Sustainable Resources, which integrates multiple projects addressing different aspects of food system sustainability, including the FOODIES project on environmental indicators, ADVENT on energy and nature valuation, and research on climate change impacts on food security.

Andrew Elliottمشاهده پروفایل

مدرس ارشد

• Statistics
• Data Analytics
• Modeling in Space and Time
• +۸ مورد دیگر

Dr Andrew Elliott is a Senior Lecturer in the School of Statistics at the University of Glasgow. His research bridges Statistics , Computational Statistics , and Machine Learning & AI , with applications in Social & Urban Studies and Imaging, Image Processing & Image Analysis . Education: Not explicitly detailed in the text. Dr Elliott's work focuses on modeling in space and time , synthetic data generation , and network analysis . His recent publications explore fairness constraints in AI , agent swarms , and temporal network modeling , reflecting interdisciplinary applications in urban analytics and environmental science. His publications from 2014–2024 span network science , machine learning , image analysis , and geospatial studies . Key trends include privacy auditing , counterfactual explanations , and deep learning for network time series . Dr Elliott supervises doctoral students and has advised Zhengduo Zhao and Weiyue Zheng . He actively contributes to research groups in Statistics & Data Analytics and Machine Learning . Notable collaborations include work with Mihai Cucuringu and Gesine Reinert .

Sirojan Tharmakulasingamمشاهده پروفایل

مدرس

• Machine Learning
• Artificial Intelligence
• Data Science
• +۶ مورد دیگر

Dr. Sirojan Tharmakulasingam serves as a Lecturer and Research and Development Coordinator at the Signals, Information & Machine Intelligence lab within the Faculty of Engineering at the University of New South Wales (UNSW) Sydney. His work bridges theoretical machine learning with practical applications in edge computing and high-performance systems. His research spans multiple cutting-edge domains including machine learning, artificial intelligence, data science, edge computing, and high-performance computing. Dr. Tharmakulasingam specializes in developing next-generation inference models by integrating machine learning, signal processing, mathematical modeling, and computing across diverse data types including images, video, audio, and quantum molecular data. His work has significant implications for scientific computing, telecommunications, and healthcare applications. Analysis of his publication trends reveals a strong focus on practical AI implementations, with increasing emphasis on edge computing solutions, quantum applications, and energy-efficient models. His recent work demonstrates progression from foundational machine learning techniques toward specialized applications in scientific computing and real-time systems. Dr. Tharmakulasingam holds a Doctor of Philosophy from UNSW Sydney and a Bachelor of Science of Engineering from the University of Moratuwa in Sri Lanka. His academic journey reflects a strong foundation in both theoretical and applied engineering principles. As Research and Development Coordinator for the Signals, Information & Machine Intelligence lab, he oversees critical research infrastructure and collaborations. His work location in Room 447 of the EE&T Building (G17) places him at the heart of UNSW's engineering research ecosystem, with access to the Mark Wainwright Analytical Centre's extensive facilities.