جست‌وجوی استاد و پژوهشگر

• Computer Vision
• Machine Learning
• Internet of Things
• +۳ مورد دیگر

Dr. Fernando J. Galetto serves as a Research Officer and Academic casual in the Department of Engineering at La Trobe University, Melbourne, Australia. His research focuses on developing intelligent systems that leverage Computer Vision, Machine Learning, and Internet of Things (IoT) technologies for real-time Edge device applications, with significant contributions in image restoration, defocus estimation, and infrastructure assessment. His expertise centers on practical implementations of deep learning and AI for resource-constrained environments. Key research areas include marine snow analysis, sewer infrastructure monitoring, and real-time PPE detection systems. His methodologies emphasize computational efficiency without sacrificing accuracy, particularly in underwater imaging and civil engineering applications where Edge deployment is critical. Analysis of his 2021-2025 publications reveals a consistent trajectory toward solving complex image processing challenges through novel filter designs and deep learning architectures. His work bridges theoretical advances in inverse problems and defocus estimation with tangible applications in environmental monitoring and infrastructure maintenance, demonstrating exceptional adaptability to Edge computing constraints. Dr. Galetto's scientific recognition includes: IEEE Award for Technical Innovation and Engineering Achievement (2019) for developing a real-time embedded system using Raspberry Pi and Intel Neural Compute Stick to detect personal protective equipment across four HD video streams at 60 fps. No documented information exists regarding graduate student supervision or externally funded research grants. His collaborative work primarily involves co-authors Deng G, Al-nasrawi M, and Stumpf A across multiple publications. While specific laboratory affiliations aren't detailed in available sources, his research outputs indicate active involvement in La Trobe University's engineering projects related to sewage pipe condition assessment and marine environment monitoring systems.

Lei Buمشاهده پروفایل

استاد

• Software Verification
• Software Testing
• Software Analysis
• +۸ مورد دیگر

Lei Bu is a Professor and Vice Dean of the Software Institute at Nanjing University, China. He has been with Nanjing University since 2010, progressing from Assistant Professor to his current position. His academic career includes a visiting position at Microsoft Research Asia through their StarTrack Program from 2014-2015. Professor Bu received his B.Sc. and Ph.D. degrees in Computer Science from Nanjing University, with additional research experience at Carnegie Mellon University and University of Texas at Dallas during his doctoral studies. His academic journey shows steady progression through the ranks at his alma mater. Lei Bu's research primarily focuses on software verification, testing, and analysis, with particular expertise in model checking, bounded model checking, formal methods, and cyber-physical systems. His work spans theoretical foundations to practical applications in safety-critical systems. Recent publications demonstrate growing interest in integrating machine learning techniques with traditional formal methods, as seen in works like SpecGen that leverage large language models for program specification generation. His research outputs show a consistent focus on verification techniques for complex systems, particularly addressing challenges in hybrid systems, cyber-physical systems, and IoT applications. Professor Bu has developed several verification tools including BACH (Bounded Reachability Checker for Linear Hybrid Automata) and BRICK (Bounded Reachability Checker of Numerically-Intensive C Code), which have been used in international verification competitions. 2023: Zhongchuang Software Talent Award 2022: CCF-IEEE CS Young Computer Scientist Award 2020: The Outstanding Teachers of Computing in Higher Education Award Program 2019: NASAC Young Software Innovation Award 2016: Young Talent Development Program 2014: StarTrack Program Visiting Young Faculty 2007: Full Scholarship under the State Scholarship Fund Professor Bu serves as a Principal Investigator on multiple significant research projects funded by the Natural Science Foundation of China, including a Key Program grant (2023-2027) on dynamic adjustment-control-fault tolerance theory. He has also advised numerous students and taught courses including Formal Languages and Automata, Theoretical Foundation of Software Engineering, and Preliminary Introduction to the Theory of Computation. His laboratory work focuses on developing practical verification tools for industrial applications in cyber-physical and IoT systems.

• 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.

Philipp Alexander Raithمشاهده پروفایل

پژوهشگر

• Edge Intelligence
• Edge Computing
• Serverless Edge Computing
• +۱ مورد دیگر

Philipp Alexander Raith is a PreDoc Researcher and PhD student at the Distributed Systems Group of the Institute of Information Systems Engineering at Vienna University of Technology (TU Wien). His research focuses on edge intelligence, serverless edge computing, and AI operations, with a strong emphasis on resource optimization and infrastructure management across the edge-cloud continuum. BSc in Software Engineering (2018) from TU Wien MSc in Software Engineering & Internet Computing (2021) from TU Wien Research Interests encompass: Edge Intelligence Serverless Edge Computing AI/ML Operations Resource-aware Scheduling Distributed Systems Computing Continuum Publication Trends highlight his work in edge-cloud orchestration, neural feature compression, and quantum computing integration. Key areas include elasticity, serverless frameworks, and energy-aware architectures. Scientific Awards : UCC 2022 Best Paper Award SEC 2019 Best Demo Award 2020 Netidee Grant Winner Shortlisted for TU Wien Distinguished Young Alumnus Advising : Supervised multiple Master’s theses on edge-cloud autoscaling, AI workloads, mobile edge computing, and resource-aware offloading. Projects : Key contributor to AUTO-Cloud (2013–2025) and RAINBOW (2020–2022) projects.

• Multimodal Machine Learning
• Natural Language Processing
• Computer Vision
• +۳ مورد دیگر

Rui Cao is a Researcher at the Department of Computer Science and Technology at the University of Cambridge, located in the William Gates Building. Their work focuses on multimodal AI systems, particularly addressing challenges in misinformation detection, hate speech moderation, and the analysis of internet memes. Rui's research integrates computer vision, natural language processing, and large language models to tackle real-world societal issues such as online toxicity and factual verification. Key research emphases include: Multimodal fact-checking systems (e.g., AVerImaTeC dataset) LLM-based hallucination mitigation in vision-language models Automated hate speech detection in memes and live video streams Zero-shot and few-shot learning for visual question answering Tools for meme analysis (e.g., Matk Toolkit) Recent work has explored adversarial data augmentation (HateGAN), modular neural architectures for hateful meme detection (Pro-CAP), and frameworks for resolving conflicting evidence in automated fact-checking. Their contributions span both technical advancements and ethical considerations in AI deployment. Research has been published in top-tier venues, with a focus on applications to social media content moderation and misinformation mitigation. No awards or grants are explicitly listed in the provided materials.

Tirado Franciscoمشاهده پروفایل

استاد

• Power Aware Computing
• Heterogeneous Computing
• Applications optimization
• +۴ مورد دیگر

Francisco Tirado is a Full Professor of Computer Architecture at Complutense University of Madrid since 1986. He has held leadership roles including Vice-Chancellor for Research (2012-2015), Dean of the Faculty of Physics (1994-2002), and Director of the Complutense Supercomputing Center (2002-2007). He is a founding member of the Spanish Society for Computer Science (SCIE) and Spanish Society for Computer Architecture (SARTECO). His research focuses on power-aware computing, heterogeneous systems, bioinformatics, and hardware design automation. He has authored over 242 publications and supervised 15 PhD theses. His professional service includes chairing 138 international conferences and serving on numerous committees for EUROMICRO, IEEE, and national research agencies. Education: No explicit details provided, but has been active at Complutense University since 1978. Affiliations: Member of COSCE Executive Board (2012), IEEE Senior Member (2005), and EUROMICRO Board (1991-2004). Research Interests: - Optimizing energy efficiency in high-performance computing systems - Design of heterogeneous architectures and accelerators - Bioinformatics applications through hardware/software co-design - Parallel programming models for emerging architectures - Automation tools for FPGA and embedded systems development Conference Contributions: Played multiple roles (General Chair, Program Chair) for major events like ParCo, HPCA, and EUROMICRO PDP conferences. Delivered 64 keynote/plenary lectures globally. Scientific Awards: Doctor 'Honoris Causa' from universities in Spain, Paraguay, and Peru 2013 National Computer Science Award IEEE Senior Membership Advising: Supervised 15 PhD students. Active in technology transfer contracts with industry. Labs/Teams: Founder and leader of the ArTeCS research group at Complutense University, specializing in computer architecture and high-performance computing innovations.

Simone Orcioniمشاهده پروفایل

دانشیار

• Sensor Systems
• Biomedical Engineering
• Signal Processing
• +۵ مورد دیگر

Prof. Simone Orcioni is an Associate Professor at the Department of Information Engineering, Università Politecnica delle Marche. His research focuses on sensor systems, biomedical engineering, nonlinear signal processing, and embedded systems. He leads projects in structural health monitoring, battery management, and telemedicine solutions. Orcioni's work integrates hardware design, algorithm development, and data analytics to address challenges in infrastructure maintenance, healthcare, and sustainable energy. Education: Not explicitly listed, but his role as an associate professor implies advanced academic credentials in electrical or biomedical engineering. Research interests include wearable sensors for healthcare monitoring, IoT-enabled environmental systems, and stochastic modeling of nonlinear processes. He collaborates on interdisciplinary projects involving robotics, circular economy, and smart infrastructure. His publications span journals and conferences in signal processing, biomedical engineering, and electronics. Notable areas include electrochemical impedance spectroscopy, sleep monitoring systems, and low-cost sensor networks. Orcioni's work emphasizes practical applications, such as non-invasive vital sign detection and sustainable battery recycling processes. Awards: None explicitly mentioned. Grants and collaborations are implied through his research projects but not detailed in the text. He contributes to academic governance via his teaching and administrative roles at the university. Labs/Teams: Affiliated with the Department of Information Engineering's research groups focused on embedded systems, biomedical instrumentation, and nonlinear signal analysis. Collaborates with industry partners on projects like smart EV charging systems and telemedicine platforms.

Hillol Karguptaمشاهده پروفایل

استاد

• Distributed Data Mining
• Ubiquitous Data Mining
• Privacy-Preserving Data Mining
• +۷ مورد دیگر

Professor Hillol Kargupta is a faculty member in the Department of Computer Science and Electrical Engineering at the University of Maryland Baltimore County. He received his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 1996 and co-founded AGNIK LLC, a ubiquitous data analytics company. His research spans distributed and ubiquitous data mining, sensor networks, privacy-preserving techniques, sustainable computing, and security applications. Research Interests : Mobile/distributed data mining, vehicular sensor networks, peer-to-peer systems, privacy-preserving algorithms, data stream analysis, and societal impacts of knowledge discovery Education : Ph.D. in Computer Science (1996), University of Illinois at Urbana-Champaign His work addresses privacy-preserving data mining with random perturbation techniques, distributed eigen-monitoring for astronomy data streams, and asynchronous P2P algorithms for clustering/classification. Recent publications focus on greenhouse emissions analysis , scalable outlier detection , and secure distributed inferencing . Scientific awards include: 2013 Frost & Sullivan Award (Agnik LLC) 2010 IEEE Fellow Top-10 Data Mining Case Study (ICDM'2010) 2008 IBM Innovation Award 2007 NSF Next Generation Data Mining Symposium 2003 IEEE Data Mining Best Paper Award

• Decision Agriculture
• Sustainable Agricultural Systems
• Data Analytics in Agriculture
• +۳ مورد دیگر

Dr. Matthew Knowling is a Senior Lecturer and Research Program Lead in Decision Agriculture at the University of Adelaide's School of Agriculture, Food and Wine, within the Faculty of Sciences, Engineering and Technology. His work focuses on developing decision support tools that integrate data from agronomy, hydrology, economics, and engineering to address agricultural sustainability challenges. He leads the $7.6M GRDC Farming Systems South program, evaluating profitability and sustainability in southern Australian farming systems, and previously directed the VitiVisor project, enhancing vineyard management through data assimilation and forecasting. He is eligible to supervise Master's and PhD students in agricultural systems analysis. Research Interests: Decision Agriculture, sustainable resource management, process-based modeling, data assimilation, climate risk assessment, and interdisciplinary approaches to agricultural decision-making. His work emphasizes translating complex data streams into actionable strategies for farmers, businesses, and policymakers. Grants & Programs: GRDC Farming Systems South ($7.6M): Evaluates strategic and tactical decisions in water-limited farming systems, focusing on profitability, sustainability, and emerging practices. VitiVisor ($5M): Developed decision support tools for Riverland vineyards, integrating sensors, financial benchmarks, and grapevine dynamics models. Labs & Teams: Part of the Decision Agriculture team at the Waite Campus, collaborating with multidisciplinary groups to advance precision agriculture and sustainable practices.

Jens Rettkowskiمشاهده پروفایل

استاد

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +۳ مورد دیگر

Prof. Jens Rettkowski is a leading academic specializing in advanced computing architectures, particularly focusing on multi-core systems, reconfigurable hardware (FPGAs), and networks-on-chip (NoC). His work bridges theoretical computer architecture with practical applications in embedded systems, real-time processing, and autonomous technologies. Research Interests: Multi-Core Architecture Design and Optimization Networks-on-Chip (NoC) for High-Performance Systems Reconfigurable Computing and FPGA-Based Systems Hardware-Software Co-Design for Embedded Applications Real-Time Systems and Energy Efficiency Sensor Data Fusion and Autonomous Driving Publications reflect a strong focus on optimizing communication and computation in heterogeneous systems, with recent work emphasizing power savings in multi-core architectures and event-based debugging frameworks. His contributions include frameworks like MPSoCSim for simulating reconfigurable systems, and software-defined FPGA approaches for adaptive computing. He has led research in robotics applications for assisted living environments, combining navigation algorithms with real-time sensor processing. His work also addresses security aspects of FPGA configuration and partial bitstream analysis using machine learning.

Deborah Robertsمشاهده پروفایل

استاد

• Environmental Microbiology
• Biological Treatment Processes
• Wastewater Treatment
• +۵ مورد دیگر

Deborah Roberts serves as the inaugural Dean of the Faculty of Science and Engineering at the University of Northern British Columbia (UNBC), bringing over 30 years of interdisciplinary expertise bridging microbiology and environmental engineering. A licensed Professional Engineer with EGBC, she holds leadership positions in multiple engineering and scientific societies while maintaining active research programs. Her academic foundation includes a BSc and PhD in Microbiology from the University of Alberta, complemented by immersive engineering training during her tenure as Assistant and Associate Professor in Civil and Environmental Engineering at the University of Houston. She played a pivotal role in establishing the School of Engineering in Kelowna before joining UNBC, where she integrates her dual expertise in biological systems and engineering design. Dr. Roberts' research program focuses on developing innovative biological treatment solutions for extreme environmental challenges, with particular emphasis on microbial fuel cell technology for waste-to-energy conversion, arsenic removal from mine drainage, and sulfur-oxidizing microbial processes affecting concrete infrastructure. Her laboratory trains students in advanced microbiological techniques, analytical chemistry methodologies, and the development of novel contaminant analysis protocols for water, soil, and air remediation. Recent publication trends reveal a strategic shift toward bioelectrochemical systems for sustainable wastewater treatment, with significant contributions to understanding microbial fuel cell performance in winery and food waste applications. Her work increasingly incorporates advanced sensing technologies, including microwave-based biosensors for real-time water quality monitoring and bacterial growth analysis, demonstrating interdisciplinary innovation across environmental engineering and analytical chemistry domains. Professional Engineering license with EGBC Member of multiple engineering and scientific societies Supervisor for MSc and PhD students in environmental engineering Active research collaborations across North America Dr. Roberts leads the Faculty of Science and Engineering while maintaining an active research laboratory focused on sustainable solutions for contaminated media. Her team develops practical applications for microbial processes in extreme environments, with particular attention to industrial wastewater challenges and resource recovery opportunities. Current projects emphasize scalable technologies for agricultural waste streams and mining-impacted waters, reflecting her commitment to translating fundamental research into field-deployable environmental solutions.

Marios C. Angelidesمشاهده پروفایل

استاد

• Multimedia Systems
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Marios C. Angelides is a prominent academic specializing in multimedia systems, artificial intelligence, and collaborative technologies. His work focuses on integrating machine learning, IoT, and game theory into applications such as autonomous systems, disaster response, and personalized gaming. He has authored over 90 publications, including influential papers on MPEG standards and AI-driven UAV coordination. His research bridges theoretical frameworks with practical implementations in telecommunications, emergency communications, and educational technologies. Angelides collaborates extensively with researchers like Faris A. Almalki and Harry W. Agius, advancing interdisciplinary solutions in intelligent tutoring systems and adaptive multimedia.

• Ontology
• Semantic Web
• IoT
• +۷ مورد دیگر

Stijn Verstichel is a Postdoctoral Researcher at Ghent University within the Faculty of Engineering and Architecture and the Department of Information Technology (EA05) . He is affiliated with IMEC , focusing on ontology-driven solutions for context-aware systems in healthcare, IoT, and railway domains. Research Interests: Ontology, semantic web technologies, IoT, eHealth, context-aware systems, and machine learning. Recent Trends: His 15 most recent articles emphasize semantic frameworks for IoT, predictive maintenance dashboards, time-series data on Solid pods, and ontology-enabled healthcare platforms. Scientific Awards: No awards explicitly mentioned in the provided data.

• Mathematics Education
• History of Mathematics
• Special Matrices
• +۷ مورد دیگر

Sandra Ricardo is an Assistant Professor at the University of Trás-os-Montes and Alto Douro (UTAD), Portugal, with a strong academic foundation in Mathematics, holding a PhD from the University of Rouen, France, and a Master’s from the University of Coimbra, Portugal. She is actively engaged in research and educational projects with international impact. PhD in Mathematics, National Institute of Applied Sciences of Rouen, University of Rouen, France (2008) Master's in Mathematics, University of Coimbra, Portugal (2000) Her research interests include Mathematics Education, History of Mathematics, Special Matrices, k-Bronze Fibonacci Numbers, and Mechanical Control Systems. She emphasizes innovative teaching strategies and the integration of historical context into mathematical instruction. Her work bridges theoretical mathematics with practical applications in education and biomedical signal analysis. The most recent publications reflect a dual focus: one stream on advanced algebraic structures such as quaternion Gaussian Bronze Fibonacci numbers and matrix theory, and another on pedagogical innovations in teaching fractions, statistics, and problem-solving in early education. These works highlight her commitment to both pure mathematical research and transformative educational practices. Sandra is involved in significant international projects: TeachersMOD (Erasmus+, EACEA): Modernizing elementary school teacher training in Kurdistan (2023–2025) Mais Conhecimento Melhor Futuro (Calouste Gulbenkian Foundation): Enhancing math, Portuguese, and digital literacy in Guinea-Bissau (2022–2023) These initiatives aim to improve educational access and quality in underserved regions, focusing on curriculum development and teacher capacity building. Sandra has advised and collaborated on numerous research projects, particularly in mathematics education reform and control theory. While no formal list of advisees is provided, her publications indicate strong mentorship and collaborative leadership. She has not received publicly listed scientific awards in the provided text. She contributes to academic outreach through the CIIE (Center for Research in Educational Innovation) and LabDERE (Laboratory of Digital Experimentation and Research in Education), promoting digital tools and innovative pedagogies in educational settings.

Muhammad Fermi Pashaمشاهده پروفایل

مدرس ارشد

• Computational Neuroimaging
• Intelligent Network Security
• Digital Health
• +۱۵ مورد دیگر

Muhammad Fermi Pasha is a Senior Lecturer at the School of Information Technology, Monash University, Malaysia. He holds a PhD in Brain-inspired Computing from Universiti Sains Malaysia and has been actively contributing to research and teaching since joining Monash. His academic roles include lecturing and serving as Chief Examiner for courses such as FIT1008, FIT2085, FIT9123, FIT5152, and FIT3175, focusing on computer science, business information systems, and usability. PhD in Brain-inspired Computing, Universiti Sains Malaysia (2010) MSc in Computer Science, Universiti Sains Malaysia (2006) BCompSc (Hons) in Software Engineering, Universiti Sains Malaysia (2003) Dr. Pasha's research spans computational neuroimaging, intelligent network security, digital health, and big data analytics. His work integrates artificial intelligence with healthcare applications, including Alzheimer's diagnosis, mHealth platforms, and secure medical data systems. He emphasizes evolving systems, machine intelligence, and neocortex memory modeling. His projects often involve interdisciplinary collaboration and community engagement. The recent publications highlight a strong trend in AI-driven healthcare solutions, secure data systems, and behavioral analysis using deep learning. His work combines computer vision, natural language processing, and cybersecurity to address real-world challenges in medicine and public health. Themes such as microexpression recognition, EHR clustering, blockchain for IIoT, and flood modeling using CNNs reflect his diverse yet cohesive research vision. Awards for software solutions and research projects as team lead or member (specific names not provided) Dr. Pasha supervises multiple PhD students and leads significant research grants, including projects on microexpression recognition, Alzheimer's prediction, and flood modeling. He collaborates with national and international researchers and contributes to UN Sustainable Development Goals, particularly in health and education. His lab work involves developing intelligent systems for medical and environmental applications. He leads or participates in key research labs and teams focused on AI in healthcare, network security, and sustainable computing. These teams develop frameworks for early disease detection, secure data sharing, and environmental resilience using advanced machine learning and blockchain technologies.