جست‌وجوی استاد و پژوهشگر

• Information Security
• Cybersecurity
• Digital Privacy
• +۵ مورد دیگر

Gurpreet Singh Dhillon is a Professor at the Department of Management within Instituto Superior de Economia e Gestão (ISEG) , part of Universidade de Lisboa (ULisboa) . He holds a PhD in Management from the University of London (1995). His research focuses on information security, cybersecurity policies, digital privacy, and the societal implications of emerging technologies. He is actively involved in initiatives such as ISEG's Data Lab and Futures Lab, addressing cutting-edge topics like cyberattack analysis, policy design for digital crimes, and ethical technology use. His academic contributions include over 30 peer-reviewed publications in journals such as Journal of the Association for Information Systems , International Journal of Information Management , and Computers & Security . Key themes include organizational security compliance, behavioral factors in cybersecurity, and the intersection of social media addiction with privacy. His work bridges theoretical research and practical policy recommendations, particularly in developing economies. Prof. Dhillon teaches advanced courses on information systems security, policy design, and technology ethics. His teaching emphasizes real-world case studies, including recent modules on cloud privacy frameworks and digital wallet trust mechanisms. He has advised multiple PhD and Master’s students but no specific advisee names are listed in the provided texts. Awards and grants are not explicitly mentioned, though his extensive publication record and leadership in research labs indicate significant scholarly recognition. His current research explores digital emancipation, cybersecurity gaps in IoT devices, and the ethical dimensions of AI-driven systems.

Vivian Genaro Mottiمشاهده پروفایل

دانشیار

• Human Computer Interaction
• Wearable Computing
• Usable Privacy
• +۶ مورد دیگر

Dr. Vivian Genaro Motti is an Associate Professor at the Department of Information Sciences and Technology, George Mason University (GMU), where she leads the Human-Centric Design Lab (HCD Lab). Currently on sabbatical at the University of Lisbon's LASIGE until 2025, her research focuses on Human-Computer Interaction (HCI), Wearable Computing, and Usable Privacy. She investigates assistive smartwatches for neurodivergent adults, inclusive workplaces (NSF-funded), and smart home privacy. Her work combines participatory design, social media analytics, and qualitative analysis. Education: PhD in Computer Science, Catholic University of Louvain (Belgium) Masters in Computer Science, University of São Paulo (Brazil) Bachelor's in Biomedical Informatics, University of São Paulo Research Interests: Her expertise spans assistive technologies, mHealth, privacy in IoT, and inclusive design. She emphasizes participatory methods and has led projects funded by NSF, NIDILRR, and CCI. Recent work includes the NSF-funded "FW-HTF-RL" project fostering neurodiverse workplace success through wearables. Publications: Over 50 peer-reviewed articles, including work on wearable privacy, neurodivergent support systems, and smart home technologies. Recent trends highlight AI ethics, mental health monitoring via wearables, and inclusive employment frameworks. Awards: NSF Grant (2023) NIDILRR ACL Project Funding TeachAccess Award Commonwealth Cyber Initiative (CCI) Support Grants & Advising: Secured over $2M in grants; advised projects on accessible chatbots and privacy controls. Collaborates with industry and academia globally, including postdoc contributions to the NSF-funded Amulet project at Clemson University. Labs & Teams: Leads the HCD Lab, fostering interdisciplinary research in human-centric technology. Collaborates with institutions like Université catholique de Louvain and UFABC on neurodiversity and privacy initiatives.

• Cybersecurity
• Data Leak Prevention
• Steganography
• +۵ مورد دیگر

Dr. Abdulaleem Al-Othmani is a Senior Lecturer in Computer Science at De Montfort University (DMU), serving as Programme Manager for APU/DMU dual award computing programmes. He holds a PhD in Computer Science from Universiti Teknologi Malaysia (UTM) and has held academic roles at University Kuala Lumpur (UniKL) and Asia Pacific University (APU) in Malaysia. His research focuses on cybersecurity, including steganography, digital watermarking, data leak prevention, and machine learning applications in security. Education: BSc in Computer Engineering, University of Baghdad (2002) Master of Computer Science (Information Security), UTM (2010) PhD in Computer Science, UTM (2016) Research Interests: Data Leak Prevention frameworks for educational institutions Cybersecurity in IoT and telemedicine systems Machine learning-driven threat detection E-learning security during pandemics Biometric authentication systems for healthcare Awards & Grants: Principal Investigator: RM99,380 FRGS grant for data leak prevention (2020–2022) UTM International Doctoral Fellowship (2011–2012) Certificate of Excellence for PhD thesis (2016) Advising & Professional Roles: Supervised over 20 PhD/Master students and 50+ bachelor dissertations Current PhD supervision: Safari Ismail Mussa (web app vulnerability scanners) External Examiner for MSc programmes at Birmingham City University (2021) Member of IEEE, BCS, ACM, and AIS professional bodies He is affiliated with the Cyber Technology Institute (CTI) at DMU and contributes to editorial boards of journals/conferences.

Faezeh Nassajian Mojarradمشاهده پروفایل

پژوهشگر

• Cyber-Physical Systems
• Security & Privacy
• Social & Information Systems
• +۳ مورد دیگر

Faezeh Nassajian Mojarrad is a researcher at the Max Planck Institute for Informatics , focusing on the Cyber-Physical Systems department. Her research spans interdisciplinary areas including Algorithms, Theory & Logic, Programming Languages & Verification, Cyber-Physical Systems, Security & Privacy, and Social & Information Systems. Contact: Room 311, Building G 26, Campus Kaiserslautern, Germany Phone: +49 631 9303 8628 Fax: +49 631 9303 6019

Cynthia Matuszekمشاهده پروفایل

استادیار

• Robotics
• Machine Learning
• Human-Robot Interaction
• +۵ مورد دیگر

Cynthia Matuszek is an Assistant Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). She directs UMBC’s Interactive Robotics and Language lab, focusing on enabling robots to learn from human interaction using natural language. Her research spans robotics, machine learning, human-robot interaction (HRI), and natural language processing (NLP). Notably, she was recognized in IEEE's 2018 '10 to Watch in AI' list. Dr. Matuszek holds a Ph.D. and M.S. in Computer Science & Engineering from the University of Washington (2014, 2010) and a B.S. in Computer Science from the University of Texas at Austin (2000). Her work bridges theoretical and applied domains, addressing challenges in grounded language learning, multimodal data fusion, and ethical AI deployment. Her recent publications emphasize cybersecurity (e.g., malware detection using compact features), neurosymbolic reasoning, and the integration of large language models into robotics. The lab’s work often explores VR-based human-robot collaboration scenarios, leveraging photogrammetry and simulation for reproducible studies. Key thematic trends in her articles include: Advancing grounded language learning through cross-modal alignment and interactive labeling Developing ethical AI systems capable of moral reasoning and command rejection Pioneering domain-specific cybersecurity solutions using tensor factorization and vector stores Expanding multilingual and multimodal capabilities for robots in unstructured environments Her research also addresses societal impacts, including studies on gender stereotypes in AI datasets and privacy implications of pervasive robotics. The lab’s work often intersects with NSF-funded initiatives, such as the CAREER award for inclusive robotic learning environments.

• Blockchain Technology
• Cybersecurity
• Cloud Computing
• +۳ مورد دیگر

Wei-Tek Tsai is a Professor affiliated with Arizona State University's School of Computing, Informatics, and Decision Systems Engineering, and previously with Beihang University and the University of Minnesota. His research focuses on blockchain technology, cybersecurity, cloud computing, and software engineering. He has contributed significantly to areas such as blockchain-based systems, smart contract development, distributed testing methodologies, and crowdsourcing in software development. His work emphasizes practical applications like fraud detection, supply chain supervision, and decentralized financial systems. Research interests include permissioned blockchains, anomaly detection in cryptocurrency transactions, and optimizing consensus mechanisms. He has published extensively in top-tier journals and conferences, including IEEE Transactions and international workshops on software engineering and security. His work bridges theoretical advancements with real-world challenges in distributed systems and cybersecurity.

Asif Babaمشاهده پروفایل

دانشیار بالینی

• Computer Science
• Cybersecurity
• Internet of Things (IoT)
• +۷ مورد دیگر

Asif Baba is a Clinical Associate Professor in the Department of Computer Science and Engineering at the University of North Texas. His research focuses on cybersecurity, Internet of Things (IoT), and blockchain technology, with a particular emphasis on secure data transmission, phishing detection, and industrial networking. Research Keywords: Computer Science, Cybersecurity, IoT, Blockchain, Wireless Sensor Networks Email: Asif.Baba@unt.edu Dr. Baba’s recent publications highlight advancements in IoT security, including secure medical data transmission frameworks and fuzzy logic-based phishing detection systems. He has also contributed to blockchain applications in access control, accounting, and education records verification, alongside innovations in industrial IoT networking and RFID data cleansing. His work spans fog computing, drone simulation, and sensor localization, reflecting a multidisciplinary approach to solving real-world challenges through technology.

Javad Zarrinمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Distributed Systems
• Graph Neural Networks
• +۲ مورد دیگر

Javad Zarrin is Senior Lecturer in Artificial Intelligence at Abertay University's School of Design & Informatics. With a PhD in Computer Science from University of Aveiro, he specializes in distributed systems, AI, and machine learning applications. His research program focuses on: Graph neural networks for behavior analysis Cybersecurity threat detection AI applications in environmental monitoring Blockchain decentralization frameworks Deep learning for medical imaging Dr. Zarrin teaches courses on Data Structures, Algorithms, and Artificial Intelligence, and supervises postgraduate research in machine learning and distributed systems. He has contributed to EU and UK research projects including FP7, Horizon 2020, and EPSRC initiatives, maintaining collaborations with Cambridge University and Anglia Ruskin University.

Michael Kochمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Computer-Supported Cooperative Work (CSCW)
• Collaboration Technology
• +۳ مورد دیگر

Michael Koch is a Professor of Human-Computer Interaction (HCI) at the University of Bundeswehr Munich in Germany. He holds a doctorate (PhD) and Habilitation in Informatics from TU München. His research focuses on collaboration technologies, socio-technical systems design, and integrating user interface innovations for team and community support. He leads the Cooperation Systems Center Munich (CSCM) and chairs the HCI Special Interest Group in the German Computing Society (GI). He has held industry roles at Xerox Research Centre Europe and academic positions at TU München, University of Dortmund, and University of Bremen. Education: PhD in Informatics, TU München (1997) Habilitation in Informatics, TU München (2003) Research Interests: Designing usable systems for work and leisure contexts Computer-Supported Cooperative Work (CSCW) Socio-technical system integration for team collaboration Human-Computer Interaction innovations Professional Roles: Fellow of the German Computing Society (GI) Member of ACM SIGCHI Chapter and EUSSET boards Editorial roles in i-com Journal and Lecture Notes in Informatics Advising & Collaboration: Guided over 10 PhD/Master’s students Active in European cyber defense research through Forschungszentrum Cyper Operations His research bridges technical innovations with human-centric design principles, emphasizing real-world applicability in enterprise and community settings.

• Machine Learning
• Computer Vision
• Safety-Critical Systems
• +۷ مورد دیگر

Ran Wei is a researcher at the University of Science and Technology of China, Department of Chemistry, with extensive contributions across interdisciplinary domains. His work bridges Computer Science , Biomedical Imaging , and Transportation Systems , focusing on active inference models, digital twins, and multimodal learning. Academic Affiliation : University of Science and Technology of China, Department of Chemistry Research Themes : Ran Wei's research explores active inference for adaptive systems, multimodal fusion in computer vision, and domain-specific knowledge graphs for engineering applications. He also investigates federated learning on heterogeneous networks and automated safety analysis for cyber-physical systems. Recent Article Trends : His publications from 2025–2021 span AI-driven engineering (e.g., construction project management), biomedical imaging (lesion detection, radiomics), and transportation systems (driver behavior modeling). Methodologically, he integrates transformers , Bayesian inference , and active learning frameworks. Scientific Collaborations : Ran Wei collaborates with experts in autonomous vehicles (Alfredo García, Anthony D. McDonald), biomedical engineering (Qiaolin Ye, Yifan Cai), and safety-critical systems (Tim Kelly, Simon Foster).

Georgios Kornarosمشاهده پروفایل

دانشیار

• Digital Design
• Computer Architecture
• Embedded Systems
• +۵ مورد دیگر

Georgios Kornaros is an Associate Professor at the Department of Electrical and Computer Engineering (E.M.E.) of the Hellenic Mediterranean University (EL.ME.PA), specializing in Digital Design. He directs the ISCA Lab (Intelligent Systems and Computer Architecture Laboratory) under the School of Engineering. His teaching responsibilities include courses on Computer Organization, Digital Circuits, Computer Architecture, and Embedded Systems. Education: PhD, Electronic and Computer Engineering, Technical University of Crete (2013) Master's Degree, Computer Science, University of Crete (1997) Diploma in Engineering, Computer Engineering and Informatics, Technical University of Patras (1992) Research Interests: Multicore/heterogeneous architectures, embedded systems, cyber-physical systems, energy-efficient and secure processing. His work includes contributions to EU projects like VIRTICAL, SAVE, TRESCCA, DREAMS, TAPPS, and AVANGARD. He has published over 70 papers and edited the book “MultiCore Embedded Systems” (CRC Press). Professional Experience: Collaborated with the Institute of Informatics (ITE) on VLSI system design, led the Digital Integrated Systems group at ISD SA, and worked on network processor architectures at Ellemedia Technologies. He contributed to projects like EU/FP6 Micro2DNA and Lab-On-Chip-ATEI-CRETE. Labs/Teams: Director of the ISCA Lab, focusing on advanced embedded systems and cyber-physical systems design.

• Internet of Things (IoT)
• Wireless Sensor Networks
• Cyber-Physical Systems
• +۳ مورد دیگر

Fernando Boavida is a Professor at the University of Coimbra, Portugal, specializing in Internet of Things (IoT), Cyber-Physical Systems (CPS), and Human-in-the-Loop systems. His work focuses on integrating privacy-preserving technologies, sustainable smart city solutions, and industrial IoT frameworks. Research Interests : IoT and Wireless Sensor Networks Cyber-Physical Systems (CPS) Data Privacy and Security Human-in-the-Loop Systems Industrial IoT and Federated Learning Smart City Sustainability Key Contributions : Developed models for Human-in-the-Loop CPS, emphasizing privacy and edge computing. Advanced federated learning frameworks for LoRaWAN-enabled IIoT. Designed systems for unobtrusive healthcare sensing and pandemic response. Published extensively on IoT management protocols and industrial automation. Grants and Projects : Co-PI on projects addressing IoT integration in construction and healthcare sectors. Contributed to EU-funded initiatives on smart city sustainability and privacy preservation. Teams and Labs : Boavida leads interdisciplinary teams at the University of Coimbra, collaborating with industry partners to deploy real-world IoT solutions, including the iSenior elderly support system and iHorse equine monitoring platform.

Lianhua Chiمشاهده پروفایل

مدرس

• Big Data Analytics
• Artificial Intelligence in Healthcare
• Machine Learning
• +۷ مورد دیگر

Lianhua Chi is a Lecturer in the Department of Computer Science and Information Technology at La Trobe University, Melbourne, Australia, since February 2018. He holds a dual PhD in Machine Learning and Data Mining from the University of Technology Sydney (Australia) and Huazhong University of Science and Technology (China). Before joining academia, he worked as a Postdoctoral Researcher at IBM Research Australia on Watson Education and Health, and as a Data Specialist at the University of New South Wales (UNSW). His research focuses on big data analytics, particularly in healthcare applications, AI-driven Autism Screening, and hashing techniques for real-time data processing. Chi has received notable awards including the 'Young Global Changer' title from G20/T20 Germany, 'Top 200 Young Researchers Globally' by the Heidelberg Laureate Forum, and the IBM External Honors award. Education: PhD in Machine Learning and Data Mining (2015), University of Technology Sydney & Huazhong University of Science and Technology Previous roles: Postdoc at IBM Research Australia, Visiting Researcher at UTS Research Interests: Chi’s work emphasizes adaptive hashing algorithms, graph stream classification, geolocation prediction in social media, and time series analysis. He applies these techniques to healthcare challenges such as AI-based Autism Screening and medical imaging diagnostics. His methodologies prioritize scalability and real-time adaptability. Awards & Grants: Best Paper Award (PAKDD13) Romberg Grant (Heidelberg Laureate Forum, 2016) Innovation Connection Grant (NostraData, 2022–2023) Advising & Collaborations: Chi has collaborated with Harvard Medical School’s Gehlenborg Lab and led projects on healthcare AI and cybersecurity. His work integrates advanced hashing techniques with clinical data to improve diagnostic accuracy and patient care efficiency. Labs/Teams: Active in interdisciplinary teams focusing on AI ethics, healthcare analytics, and big data security at La Trobe University.

• Digital Transformation
• E-Learning and Technology-Enhanced Learning (TEL)
• Applied Artificial Intelligence
• +۴ مورد دیگر

Fisnik Dalipi is an Associate Professor of Informatics at Linnaeus University (LNU), Sweden, and holds an Associate Professorship in Information Systems at the University of South-Eastern Norway. He specializes in digital transformation, e-learning technologies, AI-driven solutions, and blockchain applications in education and industry. His research bridges computational methods with societal needs, focusing on sustainable data management, technology-enhanced learning, and privacy-preserving systems. Current Affiliations: Department of Informatics, Faculty of Technology at LNU Research Groups: Data-driven Business Innovation (DBI), Interaction Design Research Group, Linnaeus University Systems Community (LNU-STC) Key research areas include: - Digital transformation across agriculture, education, and manufacturing - Blockchain-based systems for academic credentials and product passports - AI applications in education, security, and healthcare - Human-computer interaction and inclusive technologies for special needs He leads EU/VINNOVA-funded projects like STELLA, APPEND, ENTRUST, and FOREST 4.0, aiming to enhance digital solutions in sectors like furniture industry and agriculture. His work emphasizes secure data practices and AI ethics.

• Information Security
• Information Quality
• Systems Thinking
• +۷ مورد دیگر

Dr. Patrik Elm is an Associate Professor at Linnaeus University specializing in information security and systems thinking. He holds a PhD in Computer Science from Blekinge Institute of Technology (2007). His research focuses on information security in public sector organizations, organizational complexity, and the interplay between human and technical factors in information systems. Dr. Elm has held leadership roles including department head and has led projects like RAPID (strengthening online education in Pakistan) and DI-PHDICTKES (developing ICT PhD programs in Kosovo). He co-supervises PhD students and reviews for international journals/conferences. His work bridges systems theory with practical governance models, particularly addressing GDPR compliance and data flow management. Education: PhD in Computer Science (2007) from Blekinge Institute of Technology. Leadership Experience: Department head roles, international university collaborations, and organizational development initiatives. Projects include: RAPID: Replicating pandemic-era distance learning practices in Pakistan. DI-PHDICTKES: Establishing ICT PhD programs in Kosovo. Seed Projects: Addressing challenges in lifelong learning and patient empowerment limits. Research Interests: Cybersecurity compliance, public sector IT governance, systems thinking pedagogy, and digital strategy inefficiencies. Publications emphasize secure data governance, pandemic-era educational shifts, and interdisciplinary systems approaches. Grants & Funding: Not explicitly listed but implied through project involvements. Labs/Teams: Involved in Linnaeus Knowledge Environments like Digital Transformations. Advising: Mentors multiple PhD students and participates in exam committees.