جست‌وجوی استاد و پژوهشگر

Alan Whiteمشاهده پروفایل

استاد

• Plant Cell Biology
• Science Education
• Cell Wall Structure
• +۳ مورد دیگر

Alan R. White is a Professor of Biological Sciences at the University of South Carolina's Department of Biological Sciences, affiliated with the McCausland College of Arts and Sciences. He previously served as Dean of the Thomas Harriot College of Arts and Sciences at East Carolina University (2005–2013) and Dean of the College of Science and Mathematics at North Dakota State University (2000–2005). Dr. White holds a BS in Biology and a PhD in Botany from the University of North Carolina at Chapel Hill. His research focuses on plant cell wall structure and synthesis, alongside contributions to the Virtual Cell project, an educational tool for cell biology. He has actively participated in funded initiatives to improve science education practices, emphasizing technology integration and interdisciplinary approaches. Key areas of research include plant cell biology, virtual learning environments, and STEM education reform. His work spans collaborations in academia, health promotion via sports (e.g., men’s health programs in football clubs), and technology-driven pedagogy. Dr. White has held faculty roles at multiple institutions, reflecting his commitment to both research and educational innovation. Labs/Teams: Core contributor to the Virtual Cell animation collection, a widely used resource for molecular and cellular biology education.

Nikos Spanoudakisمشاهده پروفایل

استادیار

• Multi-Agent Systems
• Artificial Intelligence
• Agent-Oriented Software Engineering
• +۱۱ مورد دیگر

Nikos Spanoudakis is an Assistant Professor at the Department of Electronic Engineering of Hellenic Mediterranean University , with concurrent research collaboration at Technical University of Crete . He holds a PhD in Computer Science (Artificial Intelligence) from Paris Descartes University (2009, "Très Honorable"), an MSc in Organization and Administration from Technical University of Crete, and a Diploma in Computer Engineering and Informatics from University of Patras. Research Focus: Multi-Agent Systems (AOSE, Computational Argumentation), Model-Driven Engineering , Smart Buildings , IoT , and Artificial Intelligence Applications in Ambient Intelligence, Finance, and Education Key Contributions: Created ASEME Methodology and AMOLA Language for agent modeling, developed Gorgias-B argumentation framework, and designed Kouretes Statechart Editor for robotic behavior specification His recent publications reveal a strong trend in Explainable AI (2023: Explainable Argumentation as a Service ), Smart Energy Systems (2025: Engineering IoT-Based Open MAS for Large-Scale V2G/G2V ), and EdTech Innovations (2024: Role Assignment in Programming Courses ). He has received prestigious ACM Senior Member (2023) and IEEE Senior Member (2012) distinctions, along with teaching recognition (2021) from Technical University of Crete. Academic Leadership: Serves as Editor for Springer Nature's Computer Science journal and has reviewed for 15+ top-tier publications including IEEE Intelligent Systems and Journal of Web Semantics Conference Involvement: Program Committee Member for 20+ international conferences (IJCAI, ECAI, AAMAS, AAAI) and organizer of multiple European Agent Systems Summer Schools

Henrik Beutherمشاهده پروفایل

دانشیار

• Star Formation
• Interstellar Medium
• Molecular Clouds
• +۲ مورد دیگر

Henrik Beuther is an Associate Professor at the University of Heidelberg and research scientist at the Max Planck Institute for Astronomy, focusing on Planet and Star Formation. He holds a PhD from Max Planck Institute for Radioastronomy and was an Emmy-Noether Fellow at Harvard-Smithsonian CfA. Research Focus: His group studies high-mass star formation using millimeter interferometry (ALMA/NOEMA) and JWST. Projects include CORE (fragmentation/disk formation), THOR (Galactic HI/OH survey), and RIMORPHIS (river morphology informatics). Publication Trends: Recent work explores magnetic fields in star formation, JWST-based protostellar chemistry, Galactic structure mapping, and accretion dynamics. His articles frequently combine multi-wavelength data to address star-formation physics across scales. Awards: ERC Consolidator Grant (2015) He mentors 12+ PhD students on projects ranging from molecular cloud formation to JWST protostellar analysis. Leads collaborative networks including CASCADE and the Puzzles of Star Formation conferences.

• Distributed Machine Intelligence
• Low-Power AI for IoT
• Indoor Localization
• +۳ مورد دیگر

Anuradha Ravi is a Research Assistant Professor in the Department of Information Systems at the University of Maryland, Baltimore County (UMBC). Previously, she served as a Research Scientist at the Living Analytics Research Center, Singapore Management University (2018-2023), and as an Assistant Professor at Shiv Nadar University (2016-2018). She holds a Ph.D. in Computer Science from the Indian Institute of Technology Roorkee, where her doctoral research focused on optimizing energy efficiency and latency reduction for mobile devices through intelligent offloading strategies in heterogeneous networks. Her research interests span multiple cutting-edge domains in computing and networking: Distributed machine intelligence at the edge Low-power AI systems for IoT devices Indoor localization and occupancy sensing Wireless networking protocols Mobile and ubiquitous computing Smart building management systems Analysis of her recent publications (2015-2025) reveals a consistent focus on efficiency optimization in constrained environments, with key themes including autonomous robotics, AI-driven compression techniques, multi-sensor localization, and energy-aware mobile systems. Her work increasingly emphasizes real-world applications in contested or resource-limited settings, leveraging machine learning for adaptive solutions. She actively mentors graduate students at UMBC in projects related to perception systems for unmanned vehicles, compression-aware federated learning, and network middleware development. During her tenure at Shiv Nadar University, she supervised undergraduate research on cooperative IoT strategies and 5G edge computing. She previously contributed to the Living Analytics Research Center's initiatives in smart building occupancy detection and collaborative machine intelligence frameworks for IoT devices.

Vlad Popescuمشاهده پروفایل

دانشیار

• Telecommunications
• Cognitive Radio Systems
• Software Defined Radio
• +۷ مورد دیگر

Vlad Popescu is an Associate Professor at the Department of Electronics and Computers, Faculty of Electrical Engineering and Computer Science, Technical University of Brasov. His research focuses on telecommunications, IoT, cognitive radio systems, and multimedia applications. He has authored numerous publications in top journals and conferences, including work on 6G-enabled smart cities, edge-cloud orchestration, and QoE-driven smart home systems. His research explores cutting-edge topics such as immersive multi-sensory experiences, real-time object detection, and energy-efficient architectures for Android TV integration. Popescu has contributed to open-source satellite simulators and pioneered studies on blockchain-based TV advertising systems. His work bridges theoretical advancements with practical implementations in smart home environments, IoT gateways, and next-generation wireless networks. Award-winning research includes innovations in SDR-based satellite gateways and hardware-software partitioning for embedded systems. His collaborative projects address challenges in distributed video applications, D2D communications, and social IoT frameworks for smart tourism management.

• Operations Research
• Healthcare Logistics
• Closed-Loop Supply Chains
• +۳ مورد دیگر

Pierre Desport is a Researcher in the Department of Computer Science at the University of Tours, affiliated with the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT, UR 6300). He is associated with the UFR of Sciences and Technology and the Polytechnic School of the University of Tours (EPU). His research focuses on optimization challenges in healthcare logistics, supply chain management, and telecommunications, emphasizing operational efficiency and sustainability. Key research areas include minimizing patient waiting times in outpatient settings, optimizing short local food supply chains, and developing combinatorial optimization methods for tactical distribution problems. His work often integrates advanced algorithms like Benders Decomposition and metaheuristics to address real-world logistical constraints. Desport’s publications span interdisciplinary applications of operations research, with a strong emphasis on practical solutions for healthcare systems, agricultural logistics, and telecommunications infrastructure. His research contributes to both theoretical advancements in optimization and actionable strategies for industry and public health sectors. He holds a position in the LIFAT laboratory, where his collaborations and projects address complex logistical challenges in dynamic environments. While no specific awards are listed, his prolific publication record highlights sustained contributions to optimization methodologies across multiple domains.

• Cloud Computing
• Machine Learning
• Edge Computing
• +۳ مورد دیگر

Zain Asgar is an Adjunct Professor at Stanford University . His research focuses on cloud computing, machine learning, edge computing, and systems engineering. He has published extensively on topics such as Kubernetes automation, edge ML deployment, privacy-preserving inference, and hardware-software co-design. His work bridges theoretical computer science with practical engineering challenges in distributed systems and embedded devices. Recent research trends include optimizing container orchestration for Kubernetes environments, improving model stability in edge deployments, and developing resilient image compression techniques for AIoT devices. His contributions span both software frameworks (e.g., ML-EXray) and hardware solutions (e.g., Starfish). No scientific awards or grants are explicitly mentioned. Advising and lab affiliations are not detailed in the provided text.

• Artificial Intelligence
• Machine Learning
• Cybersecurity
• +۳ مورد دیگر

Md. Ismail Hossain is an active academic researcher with a focus on Artificial Intelligence , Machine Learning , and Cybersecurity . His work spans both theoretical and applied domains, including Neural Network Pruning , Electric Vehicle Charging Systems , and Security Analysis of emerging technologies. Key Research Themes : Neural network optimization, deepfake detection, and energy systems integration Recent Trends : Articles from 2022-2025 show increasing focus on AI model efficiency and security frameworks

• Edge Computing
• Internet of Things
• Vehicular Networks
• +۵ مورد دیگر

Muhammad Bilal is an Associate Professor at Zhejiang University's School of Computer Science, Department of Computer Science and Technology. His research spans multiple cutting-edge domains in computer science and engineering, with a particular focus on edge computing, Internet of Things, and vehicular networks. His research interests include Edge Computing , Internet of Things , Vehicular Networks , Federated Learning , Digital Twins , and Cloud Computing . His work addresses critical challenges in resource allocation, latency optimization, privacy preservation, and intelligent decision-making in distributed computing environments. He has made significant contributions to developing novel frameworks for service caching, computation offloading, and secure data processing in next-generation networks. His recent publications reveal a strong trend toward integrating artificial intelligence with edge and cloud infrastructure, particularly focusing on privacy-preserving techniques and resource-efficient algorithms. His work spans applications from intelligent transportation systems to healthcare monitoring and meteorological services, demonstrating the versatility and real-world impact of his research. Dr. Bilal has established a prolific publication record with numerous high-impact papers in top-tier journals and conferences, reflecting his active engagement in the academic community. His collaborative approach is evident through extensive co-authorship networks, particularly with researchers in China, Pakistan, and internationally.

• Wireless Communications
• 5G/6G Networks
• Green Communications
• +۶ مورد دیگر

Md. Munjure Mowla is an active researcher at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences, with a strong publication record spanning from 2014 to 2024. His work primarily focuses on next-generation wireless communications, with particular expertise in 5G/6G networks, energy efficiency, and resource allocation strategies. Dr. Mowla's research interests center around sustainable wireless communications, with a growing emphasis on 6G technologies and cell-less network architectures. His work explores innovative approaches to resource management, energy efficiency in backhaul networks, and the integration of emerging technologies like Free Space Optics (FSO) and mmWave for next-generation wireless systems. Recent publications demonstrate an increasing focus on sustainability in 6G networks, workload prediction in virtualized RAN environments, and the application of machine learning techniques to wireless resource management. Analysis of his recent publications (2021-2024) reveals a clear research trajectory toward more sustainable and intelligent wireless network architectures. His work shows a significant shift from traditional cellular approaches to cell-less RAN architectures, with increasing attention to energy efficiency metrics and sustainability frameworks. The publications demonstrate strong collaboration patterns, particularly with researchers from Curtin University including Iftekhar Ahmad, Daryoush Habibi, and Quoc Viet Phung, as well as international collaborators from European institutions. Dr. Mowla has contributed significantly to the understanding of resource allocation challenges in heterogeneous wireless environments, with publications spanning top-tier journals like IEEE Access, IEEE Transactions on Green Communications and Networking, and Computer Networks, as well as prestigious conferences including GLOBECOM, CSCN, and PIMRC. His research output shows consistent growth and increasing impact in the wireless communications domain, with recent work exploring the integration of quantum technologies and machine learning in next-generation networks.

• Artificial Intelligence
• Smart Grids
• Machine Learning
• +۵ مورد دیگر

Carlos Ramos is a researcher affiliated with the University of Porto's Faculty of Engineering and the Polytechnic Institute of Porto's GECAD Research Group. He holds a PhD in Electrical Engineering and Computers from the University of Porto (1993). His work focuses on AI applications in energy systems, ambient intelligence, and agent-based systems. Ramos has collaborated extensively with researchers like Zita A. Vale and Sabah Mohammed on projects involving smart grids, manufacturing optimization, and cyber-physical systems. Research Interests : His primary areas include artificial intelligence, smart grids, machine learning, agent-based systems, and ambient intelligence. Recent work emphasizes explainable AI models in building energy management and genetic algorithms for industrial scheduling. Publications : Ramos has over 138 publications spanning journals like Engineering Applications of Artificial Intelligence and IEEE Transactions on Intelligent Systems . Key themes include AI-driven energy optimization, IoT applications in smart cities, and multi-agent systems for market simulation. His work often bridges theoretical AI with practical industrial and healthcare applications. Labs/Teams : Active in the GECAD Research Group, focusing on intelligent engineering solutions. Collaborates with international partners on projects like the Mascem electricity market simulator and the ISEM agent-based marketplace.

Nicos Kasenidesمشاهده پروفایل

مدرس

• Software Engineering
• Distributed Systems
• Real-time Systems
• +۳ مورد دیگر

Nicos Kasenides is a Lecturer in Computing at the University of Central Lancashire Cyprus (UCLan Cyprus), associated with the School of Sciences. He holds a PhD in Computing (2023) and BSc (Hons) in Computing (2018) from UCLan UK and UCLan Cyprus respectively. His research focuses on Software Engineering, Distributed Systems, Real-time Systems, Cloud Computing, and Game-Based Learning Environments. He has contributed to over 8 peer-reviewed publications in conferences like IEEE COMPSAC and International Conference on Human-Computer Interaction, exploring topics ranging from educational robotics integration to sustainable development goal frameworks in gaming. Kasenides has held roles including Lecturer (2024–present), Associate Lecturer (2019–2024), and Research Associate (2018–2019) at UCLan Cyprus. He leads modules such as The Computing Challenge , Mobile Computing , and Distributed Enterprise Systems , while teaching foundational courses in programming and computing exploration. His work combines academic rigor with practical applications, emphasizing scalable cloud frameworks for gaming and pedagogical innovations in technology-enhanced learning.

Rouskas Angelosمشاهده پروفایل

استاد

• Wireless Communication Networks
• Edge Computing
• 6G Networks
• +۴ مورد دیگر

Rouskas Angelos is a Professor at the Department of Digital Systems, University of Piraeus. He holds a Diploma in Electrical Engineering from the National Technical University of Athens (NTUA), a Master's in Communications and Signal Processing from Imperial College London, and a PhD in Electrical and Computer Engineering from NTUA. Previously, he served as Lecturer, Associate Professor, and Head of the Computer Systems and Communications Laboratory at the University of the Aegean (2000–2009). His research focuses on next-generation wireless networks, edge computing, and energy-efficient network design. He has led multiple national and EU-funded projects and worked as a network designer at CosmOTE (1999–2000). He chaired the Technical Committee for European Wireless 2006 and served on numerous international conference committees. Education: BEng: Electrical Engineering, NTUA MSc: Communications & Signal Processing, Imperial College London PhD: Electrical & Computer Engineering, NTUA Research Interests: His work centers on optimizing wireless networks, particularly in edge computing environments and 6G/IoT connectivity. Key areas include energy efficiency, heterogeneous network architectures, and latency reduction through adaptive resource allocation. Recent trends in his publications emphasize non-terrestrial networks and federated edge-cloud IoT systems. Grants & Leadership: He has coordinated国家级 and European projects focusing on green networks and edge computing. His technical leadership extended to roles in industry partnerships and academic administration. Labs & Collaboration: Past leadership at the Computer Systems & Communications Lab (University of the Aegean) and current involvement in edge-cloud research initiatives.

Hans-Wolfgang Loidlمشاهده پروفایل

دانشیار

• Functional Programming
• Parallel Programming
• Program Analysis
• +۷ مورد دیگر

Hans-Wolfgang Loidl is an Associate Professor at the School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh. His primary research areas include functional programming, parallel computation, program analysis, symbolic computation, and high-performance machine learning with applications in embedded systems, FinTech, and health informatics. He leads the dependable systems group and serves as Senior Programme Director for Computer Science, chairing the Undergraduate Board of Studies and leading the 2025 Academic Review. Member of dependable systems group Coordinated SICSA MultiCore Challenge Hosted 2nd International Summer School on Advances in Programming Languages in 2014 He designs and implements programming languages for easy-to-use parallelism (Glasgow Parallel Haskell, Glasgow Distributed Haskell, mobile Haskell) and focuses on formal guarantees for resource bounds. Recent expansions include computer security (Secrious project EP/T017511/1) via serious games, high-performance machine learning for FinTech (BA grant + industry PhD), and Brain-Computer Interfaces (EPSRC proposal). His research output spans 1999–2025, including 64 peer-reviewed publications and 5 datasets. Notable works include articles on parallel Haskell dialects (PAEAN), NUMA performance analysis, unikernel benchmarking, and playful learning exercises for security education. He offers PhD projects in functional programming, parallel programming, and high-performance machine learning applications. His teaching vision emphasizes strategic focus in software engineering education, with courses on industrial programming, hardware-software interfaces, and parallel/distributed technology.

Muhammad Majid Hussainمشاهده پروفایل

استادیار

• Smart Grid
• Power System Analysis
• Grid Integration
• +۷ مورد دیگر

Muhammad Majid Hussain serves as an Assistant Professor at Heriot-Watt University within the School of Engineering and Physical Sciences, United Kingdom. His research directly contributes to UN Sustainable Development Goals related to affordable and clean energy, with over 50 publications spanning power systems, smart grid technologies, and renewable energy integration. He actively collaborates internationally and accepts PhD students for advanced research in electrical engineering domains. Dr. Hussain's academic foundation includes: BSc in Electrical and Electronic Engineering (2005) from Pakistan MSc in Electrical Engineering (2009) from Pakistan PhD in Electrical Engineering (2018) from Glasgow Caledonian University, focusing on salt deposition mechanisms and surface flashover on outdoor insulators near shorelines His research portfolio centers on smart grid technologies and power system resilience , with critical work in cyber-physical security of power networks, EV-grid integration, and advanced energy management systems. Recent projects address real-time grid stability through AI-driven optimization and secure communication architectures, emphasizing practical implementation for modernizing aging infrastructure. His work bridges theoretical modeling with field applications, particularly in harsh environmental conditions affecting power components. Analysis of his 15 most recent publications (2022-2025) reveals three dominant research thrusts: (1) Software-defined networking for dynamic grid control, (2) AI/optimization techniques for microgrid energy management, and (3) Material science applications for power system component durability. This trajectory demonstrates increasing interdisciplinary convergence between power engineering, computer science, and materials engineering to solve grid modernization challenges. Professional recognition includes: Chartered Engineer status from The Institution of Engineering & Technology (UK) Fellowship in The Higher Education Academy (Advance HE, UK) Dr. Hussain has secured competitive funding as Principal Investigator for multiple projects, including two University of South Wales Partnership & Engagement Programme grants focused on grid integration challenges. His supervision extends to PhD candidates developing next-generation grid technologies, with strong industry partnerships facilitating technology transfer. Current research initiatives explore blockchain-based energy trading and second-life battery applications for grid stabilization. His laboratory work emphasizes experimental validation of theoretical models, particularly in insulator performance under coastal conditions and real-time grid simulation environments. Collaborative networks span European and Asian institutions, with recent projects examining cross-border renewable integration and EV charging infrastructure resilience.