جست‌وجوی استاد و پژوهشگر

Christian Poellabauerمشاهده پروفایل

استاد

• Mobile Sensing
• Data Analytics
• Healthcare Technology
• +۷ مورد دیگر

Christian Poellabauer is a Professor at Florida International University (FIU) in the Knight Foundation School of Computing and Information Sciences, serving as Interim Associate Dean for Research and Graduate Studies in the College of Engineering & Computing. He holds a Ph.D. from Georgia Institute of Technology (2004) and a Diplom-Ingenieur from TU Vienna (1998). His research focuses on mobile sensing, data analytics, and healthcare technologies, leading the MOSAIC Lab which develops solutions for healthcare, IoT, and smart cities. He previously led the Mobile Computing Lab at the University of Notre Dame and held leadership roles in data science institutes. Research Interests: His work spans digital biomarkers for neurodegenerative diseases, speech analysis for mental health, wearable device authentication, and wireless sensor networks. The MOSAIC Lab addresses challenges like real-time sensor data analysis on constrained devices and translating insights into clinical applications. Teaching: He has taught courses on Operating Systems, Mobile Computing, and Smart Health at both FIU and Notre Dame. Recent courses include COP4610 (Operating Systems Principles) and COP5614 (Graduate Operating Systems) at FIU. Service: He serves as Associate Editor for IEEE Transactions on Network Science and Engineering, and has organized conferences like ICNC 2023 and IEEE MASS 2021. His academic service includes roles on editorial boards and technical program committees for major conferences in distributed computing and networking. Advising & Labs: Advises current Ph.D. students in areas like multi-modal sensing for affective computing and mental health crowdsensing. Past students have pursued roles in academia and industry (e.g., Rose-Hulman Institute of Technology, Facebook, Microsoft). The MOSAIC Lab collaborates on projects like digital clinical outcome assessments and motor impairment detection.

Xiaodong Linمشاهده پروفایل

استاد

• Information Security
• Privacy-Enhancing Technologies
• Digital Forensics
• +۴ مورد دیگر

Dr. Xiaodong Lin is a Professor at the University of Guelph's School of Computer Science and an IEEE Fellow (2017) for contributions to secure vehicular communications. He leads the Blockchain Technology and Cybersecurity (BTC) lab, focusing on privacy-enhancing technologies, digital forensics, wireless network security, blockchain applications, and DeFi security. PhD, Beijing University of Posts and Telecommunications, China PhD, University of Waterloo, Canada His research bridges theoretical and applied domains in cybersecurity, particularly vehicular networks, smart grids, and decentralized systems. Recent work examines blockchain security, privacy-preserving protocols for IoT, and secure data aggregation in wireless networks. Key publication trends include secure fog computing for vehicular crowdsensing, privacy-preserving authentication in 5G, and cryptographic solutions for smart grids. Awards highlight multiple Best Paper recognitions at IEEE conferences. IEEE Fellow (2017) Best Paper Awards (IEEE INFOCOM 2018, GLOBECOM 2017, SECURECOMM 2016) Dr. Lin supervises graduate students in blockchain security, AI security, and digital forensics. His lab provides financial support to qualified students.

• Smart Sustainable and Resilient Cities
• Energy Efficient Communities & Cities
• Crowdsensing-based Infrastructure Monitoring (CbIM)
• +۴ مورد دیگر

Mustafa Gül is a Professor in the Department of Civil and Environmental Engineering at the University of Alberta’s Faculty of Engineering. He also serves as Director of Internationalization at the Faculty of Engineering’s Deans Office. His research focuses on smart, sustainable, and resilient cities, with an emphasis on infrastructure monitoring and energy-efficient systems. Education: PhD in Civil Engineering (University of Central Florida, 2009), MSc in Electrical Engineering (University of Central Florida, 2011), MSc in Civil Engineering (Boğaziçi University, 2004), BSc in Civil Engineering (Boğaziçi University, 2002). Dr. Gül’s research spans two primary domains: Crowdsensing-based Monitoring of Built and Natural Environments (CoMBiNE) using AI, signal processing, and data analytics for infrastructure health; and Energy-Efficient Smart Cities through solar PV integration, IoT applications, and net-zero energy homes. His work bridges structural engineering, machine learning, and sustainable urban development. Recent publications highlight advancements in smartphone-based damage detection, UAV-assisted disaster assessment, and AI-driven energy systems. His team’s work on crowdsensing bridges, solar PV optimization, and smartphone analytics has been widely recognized in journals like Structural Control and Health Monitoring and Energy and AI . Notably, his 2017 paper earned the Best Paper Award at ISARC. Students supervised include Azim, R. , Keskin, M. , and Do, N. T. , among others. Scientific Awards: Best Paper Award, 34th International Symposium on Automation and Robotics in Construction (ISARC 2017) Dr. Gül’s projects often involve interdisciplinary collaboration, leveraging sensor networks, computer vision, and optimization algorithms to address urban resilience and energy sustainability. His leadership extends to course CIV E 779 and ongoing research initiatives in Alberta, Canada.

Yu Xiaoمشاهده پروفایل

دانشیار

• Edge Computing
• Extended Reality (XR)
• Wearable Computing
• +۷ مورد دیگر

Yu Xiao is an Associate Professor at the Department of Information and Communications Engineering, Aalto University, specializing in edge computing, extended reality (XR), wearable computing, and crowdsensing. Their research contributes to the UN Sustainable Development Goals, particularly in education and technology innovation. Active in mobile cloud computing and decentralized systems Principal Investigator in EU-funded projects (EMIL, TUTL) Expert in 5G networks, autonomous systems, and human activity recognition Yu Xiao's work spans interdisciplinary domains, including healthcare (cardiovascular resuscitation devices) and urban mobility (autonomous vehicle interactions). They have received multiple awards, including Best Paper Awards and Nokia Foundation Scholarships. Focus on low-latency communication and multiagent reinforcement learning Developed frameworks like FediLive for decentralized social networks Contributed to 128+ publications and software tools Recent collaborations include institutions like Pontificia Universidad Católica de Chile and participation in IEEE committees. Their research integrates blockchain for secure IoT communication and advanced AR applications.

Siqi Maمشاهده پروفایل

مدرس ارشد

• Automated Vulnerability Detection and Repair
• Mobile Security
• IoT Security
• +۴ مورد دیگر

Dr. Siqi Ma is a Senior Lecturer at the UNSW Institute for Cyber Security (IFCYBER) within the School of Systems & Computing at the University of New South Wales (UNSW). He previously served as a Lecturer at the University of Queensland's School of Information Technology and Electrical Engineering (ITEE). He holds a Ph.D. in Information Systems from Singapore Management University (2018) and was a Postdoctoral Research Fellow at Data61, CSIRO. He also visited Carnegie Mellon University (CMU) in 2015. Current Role: Senior Lecturer, UNSW Institute for Cyber Security Former Role: Lecturer, University of Queensland Education: Ph.D. (Singapore Management University), Postdoc (Data61, CSIRO) His research spans automated vulnerability detection, mobile security, IoT security, network authentication, and graph-based adversarial robustness. Recent work focuses on drone configuration bugs, Android malware analysis via GNNs, federated learning privacy, and credential leakage in open-source projects. Key trends in his 2024-2025 publications include automated security analysis for embedded systems, deepfake detection in multimedia, and privacy-preserving mechanisms for distributed networks. He collaborates with institutions like Purdue University, Singapore Management University, and CSIRO Data61.

Lu Suمشاهده پروفایل

دانشیار

• Internet of Things
• Cyber-physical Systems
• Wireless and Mobile Sensing
• +۷ مورد دیگر

Lu Su is an Associate Professor at the School of Electrical and Computer Engineering , Purdue University , with prior appointments at SUNY Buffalo . His research spans Internet of Things , cyber-physical systems , mmWave sensing , and crowd-sourced data validation , focusing on quality-of-information aware distributed sensing and security in autonomous systems . Ph.D. in Computer Science (2013) and M.S. in Statistics (2012) from University of Illinois at Urbana-Champaign M.E. and B.E. from Harbin Institute of Technology Research Interests: IoT , cyber-physical systems , crowd sensing , security and privacy , and machine learning for sensor networks. His work addresses quality-aware information integration , adversarial attacks in autonomous vehicles , and privacy-preserving crowd-sourced systems . Recent publications focus on mmWave-based sensing (e.g., 3D pose reconstruction), federated learning (driver monitoring), and data poisoning attacks in crowd-sourced systems. His research also extends to traffic optimization and human activity recognition using wireless networks. Professional Roles: Workshop Chair (INFOCOM 2023, 2022) TPC Vice Chair (INFOCOM 2021) Program Committee Member for top conferences Editorial Board, ACM Transactions on Sensor Networks Teaching: Courses on Embedded Systems , Internet of Things , and Network Concepts at both undergraduate and graduate levels.

Reza Curtmolaمشاهده پروفایل

استاد

• Cybersecurity
• Cloud Computing
• Network Security
• +۷ مورد دیگر

Reza Curtmola is a Professor in the Department of Computer Science at NJIT. His research focuses on cybersecurity, distributed systems, and network security with an emphasis on secure routing, cloud computing, and privacy-preserving technologies. He holds a Ph.D. in Computer Science from Johns Hopkins University (2007), an M.S. from the same institution (2003), and a B.S. from the Politehnica University of Bucharest (2001). Dr. Curtmola’s work addresses challenges in wireless mesh networks, vehicular communication systems, and mobile-cloud integration. His contributions include innovative solutions for secure network coding, distributed resource management (e.g., parking assignment systems), and auditable data storage mechanisms. He has developed middleware frameworks like Moitree for mobile-cloud applications and has explored defenses against side-channel attacks, cache leaks, and entropy-based network vulnerabilities. His research also extends to privacy in vehicular DSRC protocols, dynamic traffic optimization, and verifiable code review systems. He has published extensively on topics ranging from cryptographic defenses in distributed systems to practical implementations of remote data checking in untrusted clouds. Current research activities include advancing secure cloud infrastructure, improving mobile crowdsensing reliability, and mitigating threats in IoT-enabled urban environments. His work often bridges theoretical foundations with practical system implementations, emphasizing real-world applicability in smart cities and critical infrastructure systems.

Edith C. H. Ngaiمشاهده پروفایل

دانشیار

• Internet-of-Things
• mobile crowdsensing
• network security
• +۱۲ مورد دیگر

Edith C. H. Ngai is an Associate Professor in the Department of Information Technology at Uppsala University, Sweden. She leads the Smart City Arena initiative and serves as project leader for the national GreenIoT project on energy-efficient IoT for sustainable city development funded by Vinnova. Her academic career spans multiple prestigious institutions including Chinese University of Hong Kong, Imperial College London, Simon Fraser University, UCLA, and Tsinghua University. Dr. Ngai's research focuses on Internet-of-Things, mobile crowdsensing, network security and privacy, cloud computing, and data analytics, with particular applications in smart cities and healthcare. Her work bridges theoretical foundations with practical implementations for sustainable development. She has pioneered research in energy-efficient IoT systems, data privacy in participatory sensing, and mobile health monitoring applications. Her recent publications demonstrate strong trends in IoT for smart cities, privacy-preserving techniques in social sensing, and energy-efficient data collection systems. The research spans both theoretical contributions and practical implementations, with applications ranging from urban environmental monitoring to healthcare solutions. Her work consistently addresses the tension between functionality and privacy in connected systems. Professional recognition includes: ACM Senior Member (2016) IEEE Senior Member (2015) ACM/IEEE IPSN Best Paper Runner-Up (2013) IEEE IWQoS Best Paper Runner-Up (2010) VINNMER Fellow from Swedish government agency (2009) Dr. Ngai actively mentors PhD and Master's students, with numerous graduates working at leading technology companies including Google. She serves as Associate Editor for IEEE Access, IEEE Transactions on Industrial Informatics, and IEEE Internet-of-Things Journal. Her current research projects include EU SimpliCITY, EU CRUNCH, and the GreenIoT platform for sustainable development, with funding from European Commission, Swedish Research Council, and Vinnova. She leads the Uppsala Urban Computing Lab, which focuses on IoT and mobile crowdsensing for smart cities, network security and data privacy, and smart sensing for healthcare applications. The lab develops integrated decision support tools for smart cities and citizen engagement platforms.

• Structural Health Monitoring
• Civil Engineering
• IoT/Edge Computing
• +۵ مورد دیگر

Dr. Zhen Peng is a Research Fellow at Curtin University's School of Civil and Mechanical Engineering, part of the Faculty of Science and Engineering. He holds an ARC Early Career Industry Fellowship (2025–2028), focusing on developing cost-effective bridge monitoring systems using computer vision and edge computing in collaboration with Main Roads WA. His work bridges structural engineering, IoT/edge computing, and machine learning to enhance infrastructure safety. Dr. Peng earned his PhD from Curtin University (Chancellor's Commendation, 2022). His research emphasizes structural dynamics, nonlinear damage detection, and mobile crowdsensing frameworks for infrastructure monitoring. He has published extensively in top journals like Engineering Structures and Structural Control and Health Monitoring , receiving notable awards such as the 2023 Best Paper Award and a Gold Medal in the China Postdoctoral Innovation Competition. His current projects include deploying IoT-driven systems for real-time bridge condition assessment and training students via available 2025 PhD scholarships. Dr. Peng teaches courses in civil engineering and structural analysis, contributing to both academia and industry through innovation in smart infrastructure technologies.

Wei Songمشاهده پروفایل

استاد

• Mobile Social Networks
• Internet of Things
• Vehicular Networks
• +۱۰ مورد دیگر

Dr. Wei Song is a Professor and the Coordinator of Software Engineering at the Faculty of Computer Science, University of New Brunswick (UNB) in Fredericton, New Brunswick, Canada. She has been with UNB since 2009, after completing her postdoctoral studies at UC Berkeley, and has established herself as a leading researcher in mobile networking and wireless communications. Her office is located in room ID419 and she can be reached at wsong@unb.ca. Education Ph.D. in Electrical and Computer Engineering, University of Waterloo (2003-2007) Postdoctoral Fellow, Department of Electrical Engineering and Computer Sciences, University of California, Berkeley (2008-2009) Research Focus Dr. Song's research spans multiple cutting-edge areas in mobile and wireless networking, with a strong emphasis on integrating artificial intelligence and machine learning techniques. Her work addresses fundamental problems in mobile social networks, Internet of Things, vehicular networks, and mobile cloud computing. She explores how cooperative intelligence and distributed AI can enhance network performance while addressing practical constraints such as energy efficiency and user incentives. Her recent work particularly focuses on intelligent edge computing, mobile crowdsensing with deep reinforcement learning, and social-aware data dissemination through device-to-device communications. She investigates how to turn decentralized mobile "crowds" into coherent working groups and how social connections can be leveraged to improve data dissemination efficiency. Publication Trends Dr. Song's recent publications (2016-2023) demonstrate a clear evolution from traditional wireless networking to AI-driven approaches. While her earlier work focused on fundamental problems in device-to-device communications and resource allocation, her recent publications increasingly incorporate deep reinforcement learning, graph neural networks, and other AI techniques to solve complex optimization problems in mobile crowdsensing and edge computing. This shift reflects broader trends in the field toward intelligent, adaptive networking solutions. Scientific Recognition Best Paper Award from IEEE ICC (2018) UNB Merit Award (2014) Best Student Paper Award from IEEE CCNC (2013) Top 10% Award from IEEE MMSP (2009) NSERC postdoctoral fellowship (2008) Best Paper Award from IEEE WCNC (2007) Professional Service and Mentoring Dr. Song serves as Senior Member of IEEE and has held significant leadership roles, including Chair of the Joint Computer and Communications Chapter of IEEE New Brunswick Section (2014-2020). She has chaired symposia at major conferences including IEEE VTC Fall 2023, 2017, and 2016. As a supervisor, she mentors graduate students in areas including intelligent edge computing and deep learning for networking, and is currently recruiting students for Winter 2024 and Fall 2025.

Alexander Kocianمشاهده پروفایل

استادیار

• Machine Learning
• Internet-of-Things (IoT)
• Agro Informatics
• +۳ مورد دیگر

Alexander Kocian is an Assistant Professor at the Department of Computer Science, University of Pisa. He holds a Ph.D. in Electrical and Electronic Engineering from Aalborg University (Denmark) and a Master's in Electrical Engineering from TU Vienna (Austria). His research focuses on Machine Learning, IoT, Agro Informatics, Health Informatics, and Real-time embedded systems. He has led major projects like AGRITECH (€40M funded by PNRR) and FuorisuoloSmart, advancing smart agriculture and healthcare technologies. Dr. Kocian serves as IEEE Senior Member (since 2024) and EAI Fellow (since 2022). He is Associate Editor of IEEE Access (2025–present), and Editorial Board member of Stats (2019–present) and Signals (2020–present). He has organized conferences like the EAI Int. Conf. on Intelligent Transport Systems (INTSYS) as General Chair (2024) and Steering Committee Member (2023). His work includes 50+ peer-reviewed publications, 4 patents, and contributions to telemedicine platforms like TESHEALTH (ESA-funded). Key projects span precision farming, IoT-based greenhouses, and AI-driven healthcare solutions. Current efforts emphasize data spaces for agritech and health informatics interoperability.

Brent Lagesseمشاهده پروفایل

دانشیار

• Cybersecurity
• Machine Learning
• Pervasive Computing
• +۶ مورد دیگر

Brent Lagesse is an Associate Professor at the University of Washington - Bothell , affiliated with the Division of Computing & Software Systems under the School of Science, Technology, Engineering & Mathematics . His research focuses on security in emerging environments , particularly secure machine learning and privacy in sensor-rich systems . Ph.D. in Computer Science from the University of Texas at Arlington (2009) Research Interests include: Detecting and locating hidden webcams Scalable AI/ML defense mechanisms Privacy-preserving video sharing AI systems for air quality prediction Automated yeast cell analysis CRISPR/CAS9 guide-donor libraries Article Trends : Recent publications emphasize secure machine learning for smart city applications, privacy-preserving technologies , and resource-constrained security in crowdsensing environments . Collaborative work spans cybersecurity education , environmental monitoring , and context-aware systems . Scientific Awards : Cybersecurity Fulbright Scholar (University of Cambridge, 2018) Johann-von-Spix International Guest Professorship (University of Bamberg, 2019-20) Advising & Grants : Advises current research students Neil Prakasam and Nicholas Handaja NSA grant ($96k) for GenCyber curriculum development (2022) NSF grant ($300k) for AI-enhanced cybersecurity workforce studies (2021) T-Mobile grants for ML security metrics and dataset anonymization (2020-2022) Laboratory : Leads the Security of Emerging Environments (SEE) Lab , developing practical and theoretical frameworks for smart city security and privacy-preserving technologies .

• Cybersecurity
• IoT Security
• Blockchain
• +۲ مورد دیگر

Muhammad Ajmal Azad is a Senior Lecturer in Computing at the University of Derby's College of Science and Engineering specializing in cybersecurity for distributed systems. His research develops privacy-preserving architectures for IoT, vehicular networks, and pandemic response technologies. Research focuses on: Privacy-enhancing technologies for mobile health applications Blockchain implementations in vehicular networks Trust management systems for machine-to-machine communication Security frameworks for next-generation networks Publications demonstrate consistent innovation in security protocols for emerging technologies including COVID-19 contact tracing apps and blockchain-enabled IoT ecosystems.

Pietro Manzoniمشاهده پروفایل

استاد

• Internet of Things (IoT)
• Mobile Wireless Networks
• LPWAN Technologies
• +۷ مورد دیگر

Pietro Manzoni is a Professor of Computer Engineering at the Polytechnic University of Valencia (UPV), Spain. He holds a Master's from the University of Milan (1989) and a Ph.D. from Politecnico di Milano (1995). His research focuses on IoT, edge computing, and wireless networks, with emphasis on TinyML, LPWAN, and edge-cloud systems. He coordinates the Computer Networks Research Group (GRC) and is active in IEEE committees. Education includes a Master's in Computer Science (Università degli Studi di Milano, 1989) and a Ph.D. in Computer Science (Politecnico di Milano, 1995). He interned at Bellcore Labs (USA, 1992–1993) and ICSI (USA, 1994). Research interests span IoT applications, resource-constrained devices, and distributed systems. His work prioritizes empirical validation through prototypes. Teaching includes courses on Networks and Security, Intelligent IoT Systems, and IoT fundamentals in Spanish programs. Publications emphasize IoT protocols, UAV swarms, and TinyML. No scientific awards listed, but over 130 theses advised. Coordinates GRC projects and contributes to editorial boards and conferences.

• Mobile Generative AI
• Edge General Intelligence
• Quantum Computing and Networking
• +۳ مورد دیگر

Roles & Affiliations: Professor and President's Chair Professor in Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. Member of the IEEE and IET, with roles in editorial boards of major journals like IEEE Transactions on Network Science and Engineering and IEEE Communications Surveys & Tutorials. Current positions: Editor-in-Chief of IEEE Transactions on Network Science and Engineering, Area Editor in multiple journals including IEEE Communications Surveys and Tutorials. Education: Ph.D. (2008) and M.Sc. (2005) in Electrical and Computer Engineering from the University of Manitoba, Canada. B.Eng. (1999) in Computer Engineering from King Mongkut's Institute of Technology Ladkrabang, Thailand. Research Interests: Focuses on mobile generative AI, edge general intelligence, quantum networking, incentive mechanisms, and wireless communication systems. Explores applications in 6G, IoT, UAV networks, and secure communication. Recent Articles & Trends: 15 most recent articles highlight advancements in generative AI for wireless networks, quantum computing integration, secure communication protocols, and AI-driven network optimization. Key themes include semantic communication frameworks, RIS-aided systems, and federated learning in edge networks. Awards: Over 20+ prestigious awards including IEEE Fellow (2017), IET Fellow (2022), Stuart Meyer Memorial Award (2024), and multiple best paper awards at top conferences like IEEE WCNC and IEEE ICC. Advising & Grants: Advisor to numerous students (not listed explicitly). Active in funding initiatives for AI in wireless systems, quantum networks, and low-altitude economy networking. Leads projects on GenAI for networking and 6G innovations. Labs & Teams: Research focuses on CCDS labs at NTU, collaborating on projects like GenAI for ISAC, mobile edge computing, and secure federated learning systems.