جست‌وجوی استاد و پژوهشگر

Shen-Shyang Hoمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Artificial Intelligence
• +۷ مورد دیگر

Shen-Shyang Ho is a Full Professor in the Department of Computer Science at Rowan University's College of Science & Mathematics. His work spans machine learning, data mining, and edge computing with applications in urban mobility, precision agriculture, and data privacy. He leads NSF-funded research projects on dynamic graph analysis and spatiotemporal anomaly detection. Ph.D. in Computer Science, George Mason University Post-Doctoral Associate, Caltech & NASA JPL B.S. in Mathematics with Computational Science, National University of Singapore Research expertise includes graph-based machine learning, conformal prediction, cooperative inference, and privacy-preserving ML. Current work focuses on federated learning for edge devices and anomaly detection in evolving systems. He has developed tools like SplitTracer for cooperative inference evaluation and ParkGauge for urban mobility monitoring. Recent publications highlight his contributions to 2026 Pattern Recognition journal (martingale-based graph analysis), 2025 IEEE ICAIC conference (blockchain gas optimization), and 2024 ACM SAC symposium (shared mobility systems). His work integrates machine learning with real-world constraints across energy grids, transportation, and agricultural technology. NSF Grant (2022) for Dynamic Graph Anomaly Detection NSF Grant (2018) for Spatiotemporal Analysis Google Scholar Classic Paper Recognition (2017) for 2006 Radar Micro-Doppler Study Professional memberships include the Association for Computing Machinery (ACM). His teaching portfolio ranges from introductory programming to advanced ML courses. He previously held positions at Nanyang Technological University before joining Rowan in 2016.

Jeff Dixمشاهده پروفایل

استادیار

• Analog/Mixed-Signal Integrated Circuit Design
• Neural Network Integrated Circuit Design
• Low Power Integrated Circuit Design
• +۶ مورد دیگر

Jeff Dix is an Assistant Professor in the Department of Electrical Engineering at the University of Arkansas, College of Engineering. He received his B.S., M.S., and Ph.D. in Electrical Engineering from the University of Tennessee at Knoxville in 2013, 2015, and 2018, respectively. He leads the Integrated Systems Laboratory for ANalog Design (ISLAND), focusing on analog/mixed-signal integrated circuits for energy-efficient applications. B.S., Electrical Engineering, University of Tennessee at Knoxville M.S., Electrical Engineering, University of Tennessee at Knoxville Ph.D., Electrical Engineering, University of Tennessee at Knoxville His research spans four key areas: (1) Neural network/neuromorphic hardware for IoT/edge computing; (2) Extreme environment IC design (radiation-hardening, temperature extremes); (3) Subthreshold/weak inversion IC design for ultra-low power; and (4) Power electronics for electric vehicles and micro-grids. His work emphasizes energy efficiency and robustness in specialized operational contexts. Recent publications highlight trends in radiation-hardened analog circuits (2021), RF energy harvesting (2022), and neuromorphic hardware (2023). Key keywords include Integrated Circuit Design, Machine Learning Hardware, and Low Power Electronics. He teaches courses in analog/digital IC design, microelectronics, and neural network hardware, including Circuits I (ELEG 2103), Electronics II (ELEG 3223), and IC Design Lab I (ELEG 4243L/5253L).

Azzam Al-nahariمشاهده پروفایل

دانشیار

• Backscatter Communications
• Massive MIMO Systems
• Physical Layer Security
• +۴ مورد دیگر

Azzam Al-nahari is an Associate Professor in the Department of Electrical Engineering at Ibb University, Yemen, since 2017. He holds a B.Sc. in Electronics and Communications Engineering from the University of Technology, Iraq, and M.Sc. and Ph.D. in Electrical Communications from Menoufia University, Egypt. He has held postdoctoral positions at Lund University, Sweden (2012), University at Buffalo, USA (2014), and is currently a Visiting Scholar at Aalto University, Finland (since 2019). Education: B.Sc., Electronics and Communications Engineering, University of Technology, Iraq M.Sc. & Ph.D., Electrical Communications, Menoufia University, Egypt Research Interests focus on Backscatter Communications , Massive MIMO Systems , Physical Layer Security , Cognitive Radio Networks , and Signal Processing for Wireless Communications . His work explores UAV-assisted systems, energy-efficient protocols, and covert communication techniques. Recent Publications highlight advancements in Ambient IoT , UAV-Backscatter Integration , Reconfigurable Intelligent Surfaces (RIS) , and Secure Beamforming , reflecting trends in low-power networking, AI-driven resource allocation, and wireless security. Affiliation: Research groups in Communication Engineering at Aalto University.

• Computer Security
• Network Security
• Internet of Things (IoT) Security
• +۳ مورد دیگر

Dr. Abdelrahman Abuarqoub is a Senior Lecturer in Computer Security at the Cardiff School of Technologies , Cardiff Metropolitan University . He holds a PhD in Computer Science (2014) from Manchester Metropolitan University and an MSc (Distinction) in Data Telecommunications and Networks (2011) from the University of Salford . Research focuses on Computer Security , IoT Networks , and Lightweight Encryption Active member of IEEE TSUSC , MTAP-Springer , and other technical program committees Published extensively in IEEE , Springer , and ACM venues

Petri Vuorimaaمشاهده پروفایل

استاد

• Web Engineering
• Web Development
• Multimedia Systems
• +۱۳ مورد دیگر

Professor Petri Vuorimaa is a faculty member at the Department of Computer Science, Aalto University. His research spans web technologies, digital television, and human-computer interaction. Research Interests: Web Engineering and Development Edge Computing and Serverless Architectures Smart Home Systems and Semantic Interoperability Blockchain Applications in E-commerce Publication Trends: Recent work focuses on serverless edge computing, resumability in web applications, disappearing frameworks, and blockchain-based reputation systems. Earlier research includes declarative languages, XML frameworks for digital TV, and mobile computing.

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

Stefan Forsström is an Associate Professor at Mid Sweden University, affiliated with the Department of Computer and Electrical Engineering (DET) and the STC Research Centre. His work focuses on distributed systems, IoT, and educational innovations for lifelong learning. Academic Rank: Associate Professor Department: Computer and Electrical Engineering (DET) Research Centres: STC Research Centre Location: Sundsvall, Sweden Research interests include IoT, edge computing, machine learning, and educational technology. He has led projects like DRIVEN, DAWN, and GRIT while exploring secure and scalable IoT architectures. Recent publications analyze trust in edge AI systems, task offloading in vehicular networks, and intrusion detection for IIoT. His work often involves real-world implementations and performance evaluations. Teaching initiatives emphasize flipped classroom models, MOOCs, and generative AI education for professionals.

• Edge-Cloud Computing
• Resource Optimization
• Applied Machine Learning
• +۵ مورد دیگر

Jia Hu is an Associate Professor in Computer Science at the University of Exeter. He holds a PhD in Computer Science from the University of Bradford (2010), and M.Eng/B.Eng degrees in Electronic Engineering from Huazhong University of Science and Technology. His research specializes in edge-cloud computing, federated learning, and AI-driven optimization for networks and IoT systems. Research Interests: Hu's work spans resource optimization, applied machine learning (particularly in distributed settings), network security, blockchain integration, and intelligent systems for electric vehicles and Industry 4.0. His recent projects focus on federated edge AI, 6G-enabled industrial IoT, and real-time federated learning via hardware-algorithm co-design. Publications: His 150+ papers emphasize federated learning, edge computing, and reinforcement learning applications. Recent works (2020–2025) show a strong trend toward optimizing AI at the network edge, with themes like digital twins, blockchain security, and EV-integrated systems dominating. Awards & Recognition: Best Paper Awards: IEEE SOSE'16, IUCC'14 Outstanding Service & Leadership Awards for IEEE conferences Top 4% contributor to EPSRC Peer Review Fellow of the Higher Education Academy (HEA) Grants & Projects: Secured €4.7M+ funding from EU Horizon, EPSRC, and Royal Society for projects including: SAILING (Secure AI for Smart Internet-of-Energy, €3.6M) REFINE (Real-time Air Quality Monitoring with UAVs, €897K) SustainAIRA6G (Energy-Efficient AI for 6G Networks, £118K) Advising: Supervised 12 PhD students to completion; currently mentoring 7 students in federated learning, edge computing, and AIoT.

• Construction Logistics
• Digital Twin Frameworks
• Building Information Modeling (BIM)
• +۴ مورد دیگر

Stephan Kessler is a researcher at the Technical University of Munich , affiliated with the Department of Mechanical Engineering and the Chair of Conveying Technology, Material Handling, and Logistics . His work focuses on construction logistics, digital twins, and IoT integration in building processes. Contact: stephan.kessler@tum.de Key research areas: Digital Twin, BIM, DEM simulations, IoT in construction Collaborates with Prof. Johannes Fottner on construction automation projects His research emphasizes digitalization of construction processes through technologies like RFID, machine learning, and simulation tools. Recent publications address tower crane planning, co-robot integration, and bulk material handling standards. Article trends show consistent focus on construction automation (IoT, digital twins, BIM), material flow optimization (DEM simulations, screw conveyor standards), and equipment lifecycle management (telematics, RFID identification). Kessler contributes to industry-university collaborations through projects like BauFlott (fleet management systems) and TEP (Tower Crane Deployment Planner). His work bridges theoretical research with practical implementations in construction site logistics.

Stephen B. Wickerمشاهده پروفایل

استاد

• Information Networks
• Privacy and Security in Wireless Systems
• Wired and Wireless Telephony
• +۱۱ مورد دیگر

Stephen B. Wicker is a Professor in the Department of Electrical and Computer Engineering at Cornell University, with affiliations in the graduate fields of Computer Science, Information Science, and Applied Mathematics. He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and has received multiple teaching awards at Cornell, including the College of Engineering Teaching Award (2012) and the Douglas Whitney '61 Excellence in Teaching Award (2010). Education: B.S., Electrical and Communications Engineering, University of Virginia (1982) M.S., Electrical and Communications Engineering, Purdue University (1983) Ph.D., Electrical and Communications Engineering, University of Southern California (1987) Wicker's research spans privacy and security in information networks , wireless systems , and network science . His work integrates game theory and mechanism design to address privacy challenges in consumer internet models. He has pioneered frameworks to balance data collection with user rights , influencing policy discussions on digital surveillance and Fifth Amendment protections . Research Trends: Recent publications highlight intersections between 5G/IoT and healthcare systems , blockchain applications in IoT, and algorithmic fairness . His 2022 work on 5G in Healthcare explores network optimization, while 2018–2020 studies focus on surveillance ethics and cyber-physical security . Scientific Awards: 2012 IEEE Fellow College of Engineering Teaching Award (2012, 2000, 1998) Douglas Whitney '61 Excellence in Teaching Award (2010) Cornell School of ECE Teaching Award (2009) Wicker has mentored prominent researchers like Dipayan Ghosh , whose work on digital privacy builds on Wicker’s earlier studies. His contributions include six books , Cellular Convergence and the Death of Privacy (2013), and over 50 peer-reviewed articles, reflecting his focus on privacy-aware design and policy reform in technology.

Robert Hsuمشاهده پروفایل

استاد

• Parallel and Distributed Computing
• Cloud Computing
• Big Data Analytics
• +۴ مورد دیگر

Robert Hsu is Chair Professor and Dean of the College of Information and Electrical Engineering at Asia University, Taiwan, and holds concurrent appointments as Professor at National Chung Cheng University. He serves as President of the Taiwan Association of Cloud Computing and Research Consultant at China Medical University Hospital. His research spans parallel and distributed computing , cloud and edge systems , AI , and medical applications , with over 350 publications in top venues like IEEE TPDS, IEEE TSC, and ACM TOMM. Editor-in-Chief of International Journal of Grid and High Performance Computing Founding Editor-in-Chief of International Journal of Big Data Intelligence Advisory roles in 10+ journals including IEEE Transactions on Cloud Computing His research focuses on cloud-edge collaboration , AI for medical imaging , IoT security , and big data analytics . Key projects include federated learning frameworks for multi-institutional healthcare, optimization techniques for UAV-assisted MEC, and blockchain-based security solutions. His 15 most recent articles highlight advancements in malware detection, resource orchestration in edge environments, and lightweight AI models for retail and rural applications. Scientific accolades include: Stanford University's World's Top 2% Scientists (2020-2023) Best Paper Awards at IEEE ICEIB 2023 and SysCom 2021 Over 25 grants from Ministry of Science and Technology and Ministry of Education Leadership roles as IEEE TCCLD Chair and Steering Committee member He has supervised 30+ PhD/Master's students , including Shih-Chang Chen (2010), Tai-Lung Chen (2010), and Nithin Melala Eshwarappa (2020). His laboratory focuses on edge computing , cloud systems , and AI-driven solutions for healthcare and urban infrastructure.

Jose Paolo Talusanمشاهده پروفایل

پژوهشگر

• Smart Transportation Systems
• Cyber-Physical Systems
• Middleware
• +۴ مورد دیگر

Dr. Jose Paolo Talusan is a Research Scientist at the Department of Computer Science and Computer Engineering , Vanderbilt University, specializing in smart transportation systems , distributed computing , and cyber-physical systems . He is affiliated with ScopeLab , a research group focused on smart cyber-physical systems. Education: PhD from Nara Institute of Science and Technology, Japan (2020) Research Interests: His work addresses challenges in urban mobility through middleware architectures, optimization algorithms, and machine learning. Key areas include incident detection in transportation systems, privacy-preserving route planning, and vehicle-to-building charging optimization. Publication Trends: Recent publications focus on real-time transit optimization (2024-2025), leveraging reinforcement learning for heterogeneous agents in vehicle-to-building systems, and privacy-aware route planning in smart cities. His work integrates IoT , edge computing , and graph neural networks to tackle imbalanced data and sparsity issues in transit analytics. Labs & Teams: Actively contributes to ScopeLab at Vanderbilt University, collaborating on interdisciplinary projects with researchers in computer science, electrical engineering, and urban planning.

Tiantai Dengمشاهده پروفایل

مدرس

• FPGA-based Hardware Acceleration
• Sparse Processing Architecture for CNN and GEMM
• Number System and Approximation Computing
• +۳ مورد دیگر

Dr. Tiantai Deng is a Lecturer in Electronics and Digital Systems at the School of Electrical and Electronic Engineering , University of Sheffield (since 2021). His industrial background includes a senior research engineer role at HiSilicon/Huawei , where he focused on hardware architecture design for CNN, GEMM, and image/video processing on FPGAs/ASICs. Education: BEng, MSc, PhD Research interests span FPGA-based hardware acceleration , sparse processing architecture for CNN/GEMM, number system design , approximation computing , and high-level design environments . His work integrates algorithm-hardware co-optimization for efficiency in AI and mathematical computing. Recent publications emphasize neurodynamic systems for opinion modeling, parallel processing elements for ODE/AI acceleration, and low-power FPGA implementations for clustering/modulation classification. Earlier work addressed combustion dynamics and image processing pipelines. Contact: t.deng@sheffield.ac.uk | Office: G108, Sir Frederick Mappin Building, Sheffield S1 3JD | ORCID 0000-0003-4507-5746

• Optical Networks
• 6G Communications
• Quantum-Classical Networks
• +۷ مورد دیگر

Paolo Monti is a Professor and Head of the Optical Networks Unit at Chalmers University of Technology's Department of Communications, Antennas and Optical Networks. With extensive expertise in optical communication infrastructures, he leads research focusing on energy efficiency, network resiliency, programmability, automation, and techno-economics of optical networks. His work spans multiple international collaborations with funding from major research bodies across EU, USA, and Asia. Professor Monti's research interests center around next-generation optical networking technologies. His work explores the integration of artificial intelligence and machine learning with optical networks, quantum-classical network convergence, 6G infrastructure development, and network automation. His research addresses critical challenges in network energy consumption, reliability under failure conditions, and cost-effective deployment strategies for emerging communication technologies. The research group under his leadership develops frameworks for optical network monitoring, security, and resource optimization using advanced computational techniques. Analysis of his recent publications reveals a strong trend toward AI/ML integration with optical networking, with significant focus on quality of transmission estimation, network automation, and 6G readiness. His work increasingly combines quantum technologies with classical optical networks while addressing practical implementation challenges in multi-band elastic optical networks. The publications demonstrate a progression from theoretical network design to practical implementations with real-world validation. Professor Monti has received recognition as a Senior Member of IEEE, highlighting his contributions to the field of communications and networking. As an academic leader, Professor Monti has been involved as Principal Investigator, co-PI, and main technical leader in numerous national and international projects. His educational contributions include teaching courses at undergraduate, Master's, and PhD levels, as well as developing ICT-focused education programs. His research has been supported by major funding bodies including the European Commission, VINNOVA, and Wallenberg Centre for Quantum Technology. The Optical Networks Unit under Professor Monti's leadership operates as a vibrant research environment focusing on both theoretical and experimental aspects of next-generation optical communications. The unit maintains strong collaborations with industry partners and academic institutions worldwide, participating in multiple EU-funded projects and national initiatives focused on quantum communications and 6G infrastructure.

Aryan Pasikhaniمشاهده پروفایل

مدرس

• Intrusion Detection and Prevention Systems
• Reinforcement Learning
• Machine Learning
• +۹ مورد دیگر

Dr. Aryan Pasikhani is a Lecturer in Cybersecurity at the University of Sheffield , affiliated with the Security of Advanced Systems research group . Holding a PhD from the same institution, his research focuses on Intrusion Detection Systems , Reinforcement Learning , and Quantum Computing applications in security. Specializes in securing Embedded Systems and Internet of Things architectures Active in Adversarial Machine Learning and Privacy-Preserving Technologies Peer-reviewer for IEEE Internet of Things Journal and IEEE Transactions on Industrial Informatics His recent work explores 6LoWPAN security through reinforcement learning and Federated Learning frameworks for privacy-preserving data analysis. Awards include Fellow of the Higher Education Academy . Current grants involve real-time ransomware detection (CipherGrit) and automated threat modeling for AI systems. He supervises four PhD students and teaches Security of Control and Embedded Systems .

Andrea Vinciمشاهده پروفایل

پژوهشگر

• Quantum Computing
• Edge-Cloud Computing
• Internet of Things (IoT)
• +۵ مورد دیگر

Andrea Vinci is an accomplished researcher with 66 publications and 1,261 citations, specializing in the intersection of quantum computing, edge-cloud architectures, and Internet of Things (IoT) systems. His work demonstrates significant contributions to solving complex computational problems through innovative approaches that bridge theoretical quantum algorithms with practical distributed computing applications. His research interests span quantum computing applications for resource management, multi-density clustering techniques for urban analytics, and platform-independent IoT application development. Vinci has pioneered work in variational quantum algorithms for cloud/edge resource allocation, quantum kernels for IoT data classification, and distributed AI for cognitive building systems. His research demonstrates a consistent focus on addressing NP-hard problems through quantum-classical hybrid approaches. Analysis of Vinci's publication trends reveals a strategic research trajectory moving from foundational work in smart city analytics and crime prediction toward cutting-edge quantum computing applications for IoT and edge-cloud systems. His recent publications (2023-2025) show increasing focus on quantum machine learning techniques specifically tailored for IoT data processing, with significant attention to practical implementation challenges. Vinci maintains an extensive collaborative network, frequently publishing with researchers including Fabrizio Marozzo, C. Mastroianni, J. Settino, and Antonio Guerrieri across multiple high-impact venues including IEEE Transactions, ACM conferences, and specialized journals in quantum computing and distributed systems. His technical contributions include the development of the COGITO platform for cognitive buildings, novel approaches to multi-density crime prediction, and significant advancements in quantum kernel methods for IoT data analysis. Vinci's tutorial publications indicate his role in educating the broader research community about emerging quantum computing applications for distributed systems.