جست‌وجوی استاد و پژوهشگر

Antinisca Di Marcoمشاهده پروفایل

دانشیار

• Software Quality
• Software Adaptation
• IoT and WSN
• +۱۳ مورد دیگر

Antinisca Di Marco is an Associate Professor in the Department of Applied Clinical Science and Biotechnology at the University of L'Aquila, Italy. She has held this position since October 2017, having previously served as an Assistant Professor in the Department of Computer Science from 2008 to September 2017. Her research spans Software Engineering with specific focus on extra-functional properties and adaptation mechanisms. Key research areas include: Software modeling and performance analysis Performance antipatterns and model-based reconfiguration Context-aware systems and non-functional analysis Bio-inspired paradigms for self-adaptive systems Bioinformatics (since 2013) Dr. Di Marco's recent publications demonstrate a strong interdisciplinary approach, bridging software engineering with healthcare applications, particularly in mobile health systems for cancer treatment monitoring and symptom management. Her work also addresses fundamental challenges in context-aware mobile systems, performance optimization, and wireless sensor networks. She has received significant recognition including: Best Paper Award at FASE 2010 for performance modeling of context-aware mobile systems Best Poster Award at ECSA 2010 for bio-inspired self-adaptive paradigms Dr. Di Marco has advised multiple PhD students and has been actively involved in numerous research projects including iCARE (ERC Proof of Concept), VISION ERC, and CONNECT FET. She serves as Director of the University of L'Aquila Node of the InfoLife CINI Laboratory, focusing on Bioinformatics and Systems Biology research.

• Artificial Intelligence
• Computer Vision
• Data Science
• +۴ مورد دیگر

Dr. Hongda Tian is a Senior Lecturer at the University of Technology Sydney's Data Science Institute within the Faculty of Engineering and Information Technology. With a strong background in AI and data science, he focuses on translating research into practical solutions for real-world problems across multiple sectors including water, transport, energy, and retail. BSc and MEn from Beijing University of Posts and Telecommunications (2006, 2009) PhD from University of Wollongong, Australia (2015) Postdoctoral Fellow with DATA61 | CSIRO Computer Vision Scientist with Kandao Australia Pty Ltd Associate Research Fellow with University of Wollongong Dr. Tian's research spans artificial intelligence, computer vision, data science, and machine learning with a focus on practical applications. His work combines theoretical advancements with industry implementation, particularly in environmental sustainability, water management, and infrastructure monitoring. He excels at transforming real-world issues into data science problems and developing appropriate solutions that demonstrate industrial applicability to stakeholders. His publication record shows a clear trend toward applying AI to critical infrastructure and environmental challenges, with recent work focusing on water quality prediction, electricity price forecasting, carbon intensity modeling, and bushfire smoke detection. These publications appear in top journals including International Journal of Computer Vision, IEEE Transactions on Image Processing, and IEEE Transactions on Multimedia. 2025 The Australian Financial Review AI Awards (Sustainability category) 2024 NSW iAwards Winner for Sustainability & Environmental Solution 2024 NSW Merit iAwards for Government & Public Sector Solution 2024 Distilling Research Impact 2023 NSW Merit iAwards for Sustainability & Environmental Solution Chinese Government Award for Outstanding Self-financed Students Abroad Dr. Tian has secured approximately $1.07 million in external research funding as Chief Investigator since 2020 and has led or delivered over 15 research innovation projects with government and industry partners. His projects span multiple sectors including water (Dynamic Prediction of Raw Water Quality, Water Quality Prediction for Drinking Water Delivery Systems), transport (Structural Health Monitoring for Sydney Harbor Bridge, Computer Vision-Based Track Defect Detection), energy (Electrical Network-Related Incidents Prediction), and retail (Woolworths Endcap Compliance). He serves on thesis examination committees and as an editorial board member and reviewer for over 20 peer-reviewed journals and conferences.

Chua Tat Sengمشاهده پروفایل

استاد

• Multimedia Information Retrieval
• Social Media Analytics
• Unstructured Multimodal Data Analytics
• +۴ مورد دیگر

Professor Chua Tat Seng is a distinguished academic at the National University of Singapore's School of Computing, serving as KITHCT Chair Professor and Director of the NUS-Tsinghua Extreme Search Center (NExT). He also holds Distinguished Visiting Professorships at Tsinghua and Zhejiang Universities in China. PhD in Computer Science (University of Leeds, 1983) Founding Dean of School of Computing (1998-2000) Co-founded ViSenze and 6Estates technology startups His research focuses on unstructured multimodal data analytics, with particular emphasis on multimedia information retrieval, social media analytics, recommendation systems, and trustworthy AI. He has pioneered work in computational wellness and fintech applications, establishing the Lab for Media Search and leading NExT++ research initiatives. Over 300 publications in leading venues (CVPR, SIGIR, WWW, AAAI) Recipient of ACM SIGMM Technical Achievement Award (2015) Supervised 37 PhD students since 2004 Editorial leadership in ACM Transactions and IEEE Multimedia Recent work explores multimodal LLMs, knowledge editing techniques (AlphaEdit), and 3D generation frameworks, reflecting his commitment to advancing web intelligence and user empowerment.

Muhammad Muzammalمشاهده پروفایل

پژوهشگر

• Computer Science
• Artificial Intelligence
• Blockchain Technology
• +۱۱ مورد دیگر

Muhammad Muzammal is a researcher at Northumbria University , specializing in cutting-edge technologies at the intersection of computer science and decentralized systems. His work spans blockchain, IoT, and graph theory, with a focus on Security in 5G and IoT networks Efficient data fusion for medical applications Optimization of smart city infrastructure Privacy-preserving trajectory analysis Research trends in his publications highlight advancements in semi-supervised learning , signed network analysis , and blockchain-enabled decentralized solutions . Key themes include AI-driven anomaly detection, green energy distribution, and self-adaptive communication protocols for intelligent transportation systems. His collaborative work appears in journals like Information Fusion , Future Generation Computer Systems , and Knowledge and Information Systems , often addressing challenges in probabilistic data mining and spatio-temporal blockchain processing.

• Distributed Artificial Intelligence
• Sensor Networks
• Multi-Agent Systems
• +۳ مورد دیگر

Dr. Conor Muldoon is a Senior Lecturer in Software Engineering at the Department of Computing and Mathematics, Manchester Metropolitan University. His research focuses on distributed artificial intelligence, sensor networks, and multi-agent systems with applications in environmental monitoring and smart home technologies. Previously, he held postdoctoral positions at University College Dublin (UCD) and the University of Oxford, supported by prestigious fellowships including the INSPIRE Marie Curie and Government of Ireland Embark awards. He earned a Ph.D. in Computer Science from UCD, along with a first-class B.Sc. in Computer and Software Engineering and a Postgraduate Certificate in Higher Education Teaching. His research portfolio includes developing water quality forecasting systems, citizen science platforms (e.g., COBWEB), and autonomic energy management solutions. He has published extensively in journals and conferences, addressing topics such as sensor network optimization, incentive mechanisms for crowdsourcing, and adaptive middleware for ambient intelligence. Dr. Muldoon is a Fellow of the Higher Education Academy and supervises PhD candidates in areas like multi-agent systems and environmental informatics. Education: Ph.D. in Computer Science, University College Dublin B.Sc. (Honours) in Computer and Software Engineering, University College Dublin Postgraduate Certificate in Teaching and Learning in Higher Education His work bridges theoretical computer science with real-world applications, emphasizing sustainability and participatory technologies. Key projects include the Dublin Bay Water Quality Modelling and the MERA Data Extraction Toolkit. Awards include recognition for his contributions to agent-based systems and environmental data science.

Francesco Maurelliمشاهده پروفایل

دانشیار

• Marine Robotics
• Autonomous Systems
• Artificial Intelligence
• +۴ مورد دیگر

Prof. Francesco Maurelli is an Associate Professor of Marine Systems with a focus on Marine Robotics at the School of Computer Science and Engineering, Constructor University Bremen. His research applies robotics, AI, and algorithmic approaches to autonomous systems operating in marine environments, including underwater, surface, and aerial domains. His work spans ocean exploration, subsea infrastructure management, maritime automation, and lunar cave exploration through projects like the Daedalus mission. He leads a multidisciplinary team involved in both theoretical and applied research, collaborating with institutions globally. Education: PhD in AI & Robotics, University of Liverpool (2006–2007) Master's in Computer Engineering with AI & Robotics, Sapienza University of Rome (2002–2007) Research Interests: Autonomous Underwater Vehicles (AUVs) Sensor Fusion and Localization Energy-Efficient Robotics Robotics for Education and Outreach Space Robotics (e.g., lunar cave exploration) Key Projects: PANDORA Project: Persistent autonomy in AUVs MASK Initiative: Marine robotics education for high school students Daedalus: Lunar cave exploration with spherical robots Teaching Contributions: Developed online robotics curricula during the pandemic Advocated for global robotics education through initiatives like the RAS Young Professionals Committee Industrial Collaboration: Partnerships with companies like JetBrains for coding workshops German-Pakistani collaboration on freshwater canal robotics

Tim Quatmannمشاهده پروفایل

پژوهشگر

• Probabilistic Model Checking
• Multi-Objective Optimization
• Formal Verification
• +۳ مورد دیگر

Tim Quatmann is a researcher at RWTH Aachen University's Department of Computer Science, affiliated with the Faculty of Mathematics, Computer Science, and Natural Sciences. He focuses on probabilistic model checking, multi-objective optimization, and formal verification of parametric probabilistic systems. His work addresses challenges in systems with partial observability and parameter synthesis for Markov models. Quatmann is a core developer of the Storm probabilistic model checker, a widely used tool in formal verification. Education: He earned his Ph.D. in 2023 from RWTH Aachen University, with a dissertation titled Verification of multi-objective Markov models . Research Interests: Quatmann's research bridges theoretical foundations and practical tool development, emphasizing scalable algorithms for probabilistic systems. His work includes optimizing MDP model checking algorithms, parameter space exploration, and improving accuracy in computing probabilistic metrics like expected visiting times. He has contributed to the Storm project, QComp competitions, and tool benchmarking efforts. Teaching: He has taught courses such as Model Checking , Probabilistic Systems Verification , and Theoretical Foundations of UML , reflecting his expertise in formal methods and theoretical computer science. Labs/Teams: He collaborates with the MOVES group (Model-Based Software Verification and Self-Adaptive Systems) at RWTH Aachen, contributing to advancements in probabilistic verification and automated reasoning.

• Computational Statistics
• Machine Learning
• Bayesian Inference
• +۳ مورد دیگر

Saifuddin Syed is a Florence Nightingale Bicentenary Research Fellow at the University of Oxford's Department of Statistics, supervised by Arnaud Doucet and funded by the CoSInES project. His research focuses on computational statistics and machine learning, particularly scalable Bayesian inference, Monte Carlo methods, and non-reversible parallel tempering. He completed his PhD in Statistics at the University of British Columbia under Alexandre Bouchard-Côté. Currently, he contributes to the Next Generation Event Horizon Telescope (ngEHT) collaboration, improving algorithms for modeling and imaging supermassive black holes. Research interests include parallel tempering, sequential Monte Carlo, information geometry, and statistical physics. His work spans methodological development in MCMC schemes and applications in complex systems. He is affiliated with the Computational Statistics and Machine Learning research group and Statistical Theory and Methodology at Oxford. Key contributions include advancing non-reversible parallel tempering techniques to enhance computational efficiency in high-dimensional sampling, with applications to astrophysics and statistical mechanics. His recent work emphasizes scalable algorithms and rigorous theoretical analysis of MCMC performance.

Farshad Shamsمشاهده پروفایل

پژوهشگر

• Resource Allocation in Wireless Networks
• Fog-Based Networks
• Reconfigurable Intelligent Surfaces
• +۳ مورد دیگر

Farshad Shams is a Researcher at the French National Center for Scientific Research (CNRS), affiliated with the Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec, Paris, France. He holds a Ph.D. from IMT School for Advanced Studies Lucca, Italy (2012). His research focuses on resource allocation techniques for wireless networks, software-defined radio, and fog computing. He leads the REDESIGN project (Marie Skłodowska-Curie Actions H2020-MSCA-IF-2017), aiming to develop distributed, self-adaptable wireless fog networks for IoT applications. His work integrates reconfigurable intelligent surfaces (RIS) and deep learning to enhance energy efficiency and service latency. Research contributions include overhead-aware resource allocation frameworks, bi-objective optimization of energy and spectral efficiency, and game-theoretic approaches for resource management. He has published in top-tier journals like IEEE Transactions on Wireless Communications. Outreach activities include participation in EU Research Nights and training in entrepreneurship, patenting, and scientific writing. His current focus extends to 6G wireless technologies, smart cities, and sustainable network design.

Maben Rabiمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Networked Control
• Hybrid Systems
• +۵ مورد دیگر

Maben Rabi is a Professor at the Department of Information Technology and Communication, University of Southeast Norway. His work focuses on cyber-physical systems, networked control, and hybrid systems with applications in intelligent transportation and robotics. Current projects: CriSp (Research Council) and SafeSmart (KK Foundation). Research keywords: Cyber-Physical Systems, Networked Control, Hybrid Systems, Digital Society, DigiTech. Research Trends : His recent publications emphasize road friction estimation for autonomous vehicles, nonlinear control in relay feedback systems, probabilistic sampling for networked estimation, and packet loss modeling in vehicular networks. These works bridge control theory, cyber-physical systems, and transportation safety. Teaching : Courses include Technology Project (ITD25018) and Digital Control and Cyber-Physical Systems (ITD30019) .

Cong Shenمشاهده پروفایل

دانشیار

• Machine Learning
• Wireless Communications
• Federated Learning
• +۷ مورد دیگر

Cong Shen is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Virginia, where he leads a research group focused on machine learning, wireless communications, and networking. He is affiliated with the UVA Link Lab and serves as Deputy Director of Collaboration at SpectrumX, an NSF Spectrum Innovation Center. He has previously held faculty positions at the University of Science and Technology of China (USTC) and maintains strong industry ties with companies such as Qualcomm, SpiderCloud Wireless, Silvus Technologies, and Xsense.ai. Education: B.E. and M.E., Electronic Engineering, Tsinghua University, China Ph.D., Electrical Engineering, University of California, Los Angeles (UCLA), USA His research lies at the intersection of machine learning and communication systems, with a focus on in-context learning, transformers, federated learning, reinforcement learning, distributed optimization, multi-armed bandits, and AI for wireless . His work aims to bridge theoretical foundations with engineering applications in next-generation wireless networks and intelligent systems. His recent publications (2023–2025) reveal a strong trend toward integrating foundational models with communication constraints, particularly in federated and decentralized settings. Key themes include in-context learning with provable guarantees, efficient prompt optimization using bandit methods, privacy-preserving federated learning, and reinforcement learning for wireless resource management. His work frequently appears in top-tier venues such as NeurIPS, ICML, ICLR, AISTATS, and IEEE ICC. Scientific Awards: NSF CAREER Award (2022) Best Paper Award, IEEE ICC (2021) Excellent Paper Award, ICUFN (2017) Best Paper of 2024, Science Robotics Finalist for Best Student Paper Award, Asilomar (2024) Dr. Shen advises a dynamic group of graduate and undergraduate students, including PhD candidates Chengshuai Shi, Zhoubin Kou, Di Wu, and others. He leads multiple NSF-funded projects, including initiatives under the SWIFT, ECCS Core, MLWiNS, and CAREER programs, focusing on spectrum access, resource rationing in wireless FL, and domain-knowledge-enriched RL for network optimization. His lab actively contributes to open science through GitHub repositories and code releases. He also serves as an associate or editor for several IEEE Transactions journals and participates in program committees of major AI and communications conferences.

Mien Vanمشاهده پروفایل

مدرس ارشد

• Robotics and Control Engineering
• Autonomous Systems
• Human-Robot Interaction
• +۵ مورد دیگر

Dr. Mien Van is a Senior Lecturer (a.k.a. Associate Professor) in Robotics and Control Engineering at Queen's University Belfast, UK. He leads multiple research projects in autonomous systems, human-robot collaboration, and underwater robotics. His work spans resilient control for autonomous vehicles, in-process manufacturing quality control, and bio-inspired robotics design. Education: Research Fellowships at National University of Singapore (2015-2017) and University of Exeter (2018-2019). Research Interests: Resilient Autonomy, Human-Robot Interaction, Underwater Vehicles, Fault Diagnosis. Awards: IET Premium Award (2017), Best Paper Awards from BK21 and ICROS. Key Projects: ORCA (Dstl/MOD-funded), Digital Twins for Underwater Operations (EPSRC), Offshore Wind Turbine Blade Monitoring (Innovate UK). Dr. Van has authored/co-authored over 75 journal papers with an h-index of 34 and >3,700 citations. He serves as Associate Editor for multiple top-tier journals including IEEE Transactions on Automation Science and Engineering.

• Health Services Research
• E-health
• Educational Research
• +۳ مورد دیگر

Aslak Steinsbekk is a Professor at the Department of Community Medicine and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU). His research focuses on Health Services Research , E-health , Medical Education , and Health Communication , with a particular interest in Patient Education and Complementary Medicine . He leads the research group for Health Services Research and Health Communication and coordinates interdisciplinary teaching initiatives at NTNU. Health Services Research E-health Medical Education Health Communication Patient Education Complementary and Alternative Medicine Steinsbekk's recent publications span Virtual Reality (VR) medical training , patient portal design , chronic pain management , and interdisciplinary collaboration . His work often employs qualitative research and randomized controlled trials to assess interventions in primary care , mental health , and rehabilitation settings . Key projects include VR-based ISBAR training and the development of digital care plans for cross-organizational teams. He has been involved in multiple studies evaluating the Johns Hopkins Adjusted Clinical Groups System for risk stratification in Norwegian healthcare . His educational contributions include designing interdisciplinary courses like TverrSam and TverrPraks, integrating patient-centered communication and qualitative methods into medical school curricula. Although no scientific awards are listed, his work consistently addresses health equity , digital health innovation , and systematic clinical observation in Norwegian contexts.

Jamie Paikمشاهده پروفایل

استاد

• Soft Robotics
• Origami Robotics
• Wearable Technologies
• +۴ مورد دیگر

Prof. Jamie Paik is a Full Professor at the Swiss Federal Institute of Technology (EPFL), where she serves as Director of the Reconfigurable Robotics Lab (RRL) and is a core member of the Swiss NCCR robotics group. She holds multiple academic appointments across EPFL's School of Engineering, including positions in the Institute of Mechanical Engineering (IGM), STI-SMT SMT-ENS, and STI-SGM SGM-ENS. Additionally, she serves as a PhD program committee member for the Doctoral Program in Robotics, Control and Intelligent Systems. Her research focuses primarily on soft robotics , origami-inspired robotics , and wearable technologies . Prof. Paik's work leverages multi-material fabrication and smart material actuation to develop novel robotic designs that push the physical limits of materials and mechanisms. Her current research includes self-morphing Robogami (robotic origami) that transforms from planar shapes to 2D or 3D structures through predefined folding patterns, similar to traditional paper origami. Prof. Paik has published extensively on robotic origami, haptic feedback systems, and soft actuators, with her most recent work (2024-2025) focusing on vibration of soft twisted beams for locomotion, semi-autonomous surgical assistance, plug-and-play pneumatic systems, and data-driven kinematic modeling. Her research demonstrates a clear trajectory toward more adaptive, reconfigurable robotic systems with applications in surgery, human-robot interaction, and wearable technologies. Among her notable achievements, she developed a 7-DoF humanoid arm during her PhD at Seoul National University (sponsored by Samsung Electronics), which was the lightest in literature at that time (3.7kg including the 8-DoF hand). During postdoctoral work at Pierre Marie Curie University, she developed the internationally patented JAiMY laparoscopic tools now commercialized by Endocontrol-medical.com. PhD: Seoul National University (Humanoid Arm and Hand Design) Postdoc: Institut des Systems Intelligents et de Robotic, Université Pierre Marie Curie Postdoc: Harvard University's Microrobotics Laboratory Prof. Paik has supervised numerous PhD students, both current and past, including Bakir Alihan, Demirtas Serhat, Jiang Shaopeng, Kanno Ryo, Schüssler Alexander Michael, and Wang Ziqiao. Her teaching includes Topics in Autonomous Robotics, Mechanical Product Design and Development, and Advanced Design for Sustainable Future.

• Mobile and Ubiquitous Computing
• Internet of Things
• Context-Aware Applications
• +۵ مورد دیگر

Dr. Dirk Bade is a Researcher at the University of Hamburg , affiliated with the Department of Informatics under the Faculty of Mathematics, Informatics and Natural Sciences. His work focuses on Mobile and Ubiquitous Computing , Internet of Things , Context-Aware Systems , and Blockchain Applications . He is actively involved in projects such as SANE (Smart Networks for Urban Citizen Participation), CloudAware (Context-adaptive Middleware), and ContAgency (Context Data Brokerage). Research Guest at VSYS, University of Hamburg (since 2013) PhD in Informatics (2013), University of Hamburg Diploma (2007) and Bachelor (2003) in Informatics, University of Hamburg His research explores smart city infrastructures , context-aware computation offloading , and security implications of sensor data . Key contributions include CloudAware (middleware for mobile cloud adaptation) and Incolum (citizen-centric sensor data marketplaces). Publications highlight trends in mobile edge computing (2015-2016), smart cities (2019-2021), and context-aware middleware (2011-2013). His work bridges agent-oriented software engineering with blockchain-based information markets . Dirk has supervised over 50 theses, including studies on blockchain reputation systems , mixed-reality negotiation tools , and sensor-supported indoor localization . He teaches courses on mobile computing , smart cities , and context-aware systems , with a focus on practical software development and ubiquitous applications .