جستجوی استاد راهنمای دانشگاهی

• Machine Learning
• Data Mining
• Pattern Recognition
• +۹ مورد دیگر

Associate Professor Zhidong Li is a prominent researcher at the Data Science Institute within the Faculty of Engineering and Information Technology at University of Technology Sydney (UTS), Australia. With over a decade of experience in data science and machine learning, he leads impactful research bridging theoretical advancements with practical applications across multiple critical infrastructure domains. Dr. Li earned his PhD from the University of New South Wales, Sydney, Australia, and previously served as a senior engineer at Data61, CSIRO (Commonwealth Scientific and Industrial Research Organisation), Australia's federal government agency for scientific research. His research spans machine learning, data mining, pattern recognition, image processing, and human-computer interaction with applications in water, gas, traffic, urbanization, visitor economy, agriculture, environment, finance, property market, railway, law, electric and health sectors. His work particularly focuses on developing interpretable AI models, temporal point processes, and practical applications for smart infrastructure management. His extensive publication record reveals strong thematic consistency in applying advanced machine learning techniques to infrastructure management problems, with particular emphasis on water systems. His research demonstrates progression from fundamental algorithm development toward increasingly sophisticated applications with real-world impact, especially in temporal modeling, graph neural networks, and fairness in AI systems. Scientific Awards 2022 R&D Excellence Award NSW Water Award 2021 UTS Medal for Research Impact for the Vice-Chancellor's Awards for Research Excellence 2018 Australian Museum Eureka Prize for Excellence in Data Science 2019 Victorian iAwards - Industrial & Primary Industries Merit for 'Predictive Analytics for Water Pipe Maintenance' Multiple AWA research innovation awards (NSW, National, QLD) Dr. Li actively supervises Masters and PhD students and leads numerous funded research projects across diverse sectors. His collaborative approach is evident through partnerships with water utilities, transport agencies, and various CRC projects focusing on Food Agility, Digital Finance, and Smartcrete. His work on the world's first independently-audited ethical talent AI in partnership with Reejig demonstrates his commitment to translating research into real-world solutions that address societal challenges while maintaining ethical standards.

• Cyberphysical systems
• Internet of Things (IoT)
• Distributed systems
• +۷ مورد دیگر

Prof. Dimitrios Georgakopoulos is a Professor of Computer Science at Swinburne University of Technology's School of Science, Computing and Emerging Technologies. He serves as Director of the ARC Industrial Transformation Research Hub for Future Digital Manufacturing and Swinburne's IoT Lab. Previously, he was Research Director at CSIRO's ICT Centre and a Professor at RMIT University. Affiliations: CSIRO Adjunct Fellow since 2014 Leadership: Directed 7 large cross-disciplinary initiatives with $100M+ funding Research Focus: IoT, Cyber-Physical Systems, Digital Manufacturing, Machine Learning Funding: Secured $77.1M in external grants; $59.7M at Swinburne Research Interests: Digital twins and AI for manufacturing IoT sensor sharing ecosystems 5G-enabled smart cities Autonomic IoT systems Quality assurance in Industry 4.0 Awards: 2023 National iAward (Public Sector), Vice Chancellor’s Innovation Award (2018), and multiple industry and academic recognitions. Grants & Projects: Lead researcher on ARC-funded initiatives in digital manufacturing, cybersecurity, and steel innovation. Collaborates with industry partners like Bega Cheese and FIA on IoT-driven solutions. Labs & Teams: Oversees Swinburne's IoT Lab and the ARC Future Digital Manufacturing Hub, advancing Industry 4.0 applications in manufacturing, healthcare, and smart infrastructure.

• Cybersecurity
• Data Security and Privacy
• Context-Aware Access Control
• +۵ مورد دیگر

Dr ASM Kayes serves as Senior Lecturer in Cybersecurity and Cyber Curriculum Lead at La Trobe University's Department of Computer Science and Information Technology, where he shapes cybersecurity education programs including Master's, Bachelor's, and Double Degrees. His academic journey began with a PhD from Swinburne University of Technology in 2015, followed by postdoctoral research at La Trobe before joining as Lecturer in 2019 and promotion to Senior Lecturer in 2022. His research spans critical cybersecurity domains including data security, privacy preservation, context-aware access control, malware/ransomware defense, and IoT/fog/cloud security leveraging AI/ML techniques. Dr Kayes has established himself as a leading voice in blockchain security frameworks, privacy policy analysis, and cyber incident response through publications in top-tier venues like ACM Computing Surveys, IEEE Internet of Things Journal, and Computers & Security. His recent publications reveal a strong trajectory toward integrating AI with traditional security frameworks, particularly in blockchain risk assessment (2025), cross-domain access control (2025), and IoT behavior prediction (2024). The research demonstrates consistent focus on practical security solutions addressing ransomware mitigation, privacy breaches, and emerging threats in decentralized systems. Over $880,000 secured as Chief Investigator for cybersecurity projects Australian Government Department of Social Services grant (2023-2026) for cyberbullying prevention AustCyber research funds with industry partners (2020-2023) SmartSat CRC and ASCRIN PhD scholarship grants (2021) Dr Kayes has successfully supervised 5 PhD candidates to completion and currently mentors 5 doctoral students across diverse topics including AI-driven threat hunting, satellite network security, and blockchain risk frameworks. His collaborative network spans UK, USA, Europe, and Asia, with active industry partnerships through Westpac, BHP, and Quantum Victoria. He serves on editorial boards for leading cybersecurity journals and has examined HDR dissertations globally, reflecting his significant standing in the academic community.

Benjamin Turnbullمشاهده پروفایل

دانشیار

• Cyber Security
• Simulation
• Digital Forensics
• +۶ مورد دیگر

Associate Professor Benjamin Turnbull is Deputy Head of School at UNSW Canberra's School of Systems & Computing. His research focuses on cybersecurity, simulation, and emerging technologies, aiming to develop decision support systems for cyber resilience. He leads large-scale research projects funded by organizations like CSIRO, Australian Defence Force, and the US Naval Research Laboratory, totaling over $3 million AUD in grants. Teaching contributions include co-creating the Bachelor of Cyber Security program and directing multiple postgraduate cybersecurity offerings. His educational design emphasizes industry-relevant courses, from undergraduate to executive programs like the UNSW Online Cyber Security Masters. He has extensive experience in curriculum design, content development, and online education. Research interests span cyber situation awareness, secure simulation platforms, and automated learning from big datasets. Notable projects include the UNSW-MG24 microgrid cybersecurity dataset and frameworks like OQFL (quantum-based federated learning) for intelligent transportation systems. His work bridges theory and practice, with outputs including software tools and policy recommendations for cyber resilience in critical infrastructure. Key collaborations include the Cyber Cooperative Research Centre and DST Group. He has authored over 100 peer-reviewed publications, focusing on IoT security, blockchain-enabled learning, and cyber-physical-social systems resilience. His grants emphasize applied research with direct societal impact, such as mitigating supply chain cyber risks and enhancing microgrid cybersecurity.

• Computer Vision
• Autonomous Systems
• Robotics
• +۱۲ مورد دیگر

Dr Lounis Chermak is a Lecturer in Computer Vision and Autonomous Systems at the Centre for Electronic Warfare, Information and Cyber, part of Cranfield Defence and Security at Cranfield University, UK. He leads the Joint Autonomy Lab and is actively involved in research and education in autonomous systems with applications in defence and space. Research Interests: His work focuses on situational awareness in autonomous platforms, with core expertise in computer vision, sensor fusion, artificial intelligence, robotics, and navigation. He investigates perception, decision-making, and mobility across aerial, ground, maritime, and space systems, developing robust solutions for challenging environments including low visibility and extreme illumination. The recent publications reflect a strong trend in autonomous navigation, particularly for space and defence applications, using advanced computer vision techniques such as thermal stereo odometry, HDR imaging, stixel-based scene understanding, and lightweight 3D descriptors. Research also extends to cybersecurity of autonomous systems, including impersonation attack detection and optical countermeasures. Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: Dr Chermak leads research activities supported by postdoctoral researchers, PhD, and MSc students. His work is funded and applied in collaboration with major clients including aerospace organizations (ESA, UK Space Agency, Thales Alenia Space), defence agencies (MoD, DSTL, BAE Systems, MBDA), and technology companies (Samsung, Astroscale). He supervises research students in robotics and autonomous systems across civilian and defence domains. Labs and Teams: He leads the Joint Autonomy Laboratory, a 200 m² indoor facility equipped with drone netting, motion capture systems, virtual reality test benches, UAV and ground robot fleets, electric vehicles, and multiple sensors for vision, ranging, and motion. This lab supports both educational and cutting-edge research in autonomous systems.

• Human Factors Engineering
• Neuroergonomics
• Robotic Surgery
• +۳ مورد دیگر

Denny Yu is an Associate Professor at the Edwardson School of Industrial Engineering, Purdue University. His work bridges human factors, neuroergonomics, and healthcare safety through advanced sensor systems and AI. Primary Affiliation : Edwardson School of Industrial Engineering, Purdue University Research Themes : Surgical ergonomics, autonomous vehicle human factors, cognitive workload assessment, multimodal physiological sensing Dr. Yu's research focuses on neuroergonomics and human-robot interaction , particularly in surgical and transportation contexts. His team develops sensor-based systems for workload monitoring, including: EEG-eye tracking fusion for situation awareness Wearable exoskeletons for surgical posture support Computer vision tools for lifting task risk analysis Smart infusion pump usability frameworks AI-driven surgical coaching systems Recent publications emphasize deep learning applications in soft tissue deformation estimation and real-time adaptive systems for robotic surgery augmentation. His work spans both occupational health (veterinary surgeons, airport workers) and medical device innovation domains.

• Machine Learning
• Cybersecurity
• IoT
• +۳ مورد دیگر

Pedro Miguel Sanchez Sanchez is a researcher affiliated with the University of Murcia , specializing in Machine Learning , Cybersecurity , and IoT . He earned his doctorate in 2024 with the thesis Identical IoT device identification via hardware performance fingerprinting and Machine Learning , supervised by Dr. Alberto Huertas Celdrán and Dr. Gregorio Martínez Pérez. Research Interests Pedro's work focuses on applying Machine Learning and Federated Learning to solve critical challenges in Cybersecurity and IoT environments. His research includes: Developing decentralized federated learning frameworks (e.g., Flighter, ProFe) for secure and efficient model training. Designing malware detection systems using system call data and large language models . Enhancing IoT device authentication via hardware fingerprinting techniques. Exploring moving target defense strategies to counter zero-day attacks on IoT networks. Building knowledge graphs for cyber defense applications. Recent Publications Pedro's 2025–2024 publications demonstrate a strong focus on decentralized federated learning , malware mitigation , and hardware-based security . Key trends include: Advancements in zero-shot learning for multilingual tasks on edge devices. Security frameworks (e.g., Cyberforce, Sentinel) for military reconnaissance and industrial IoT . Behavioral analysis techniques for ransomware detection and continuous authentication . Robustness studies on federated learning architectures under adversarial conditions. Creation of benchmarks like LwHBench for hardware performance evaluation. Collaborations He has collaborated with researchers in the Intelligent Systems and Telematics group, contributing to projects in 5G security , crowdsensing platforms , and trusted execution environments .

Jo Herstadمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Universal Design
• Inclusive Technology
• +۴ مورد دیگر

Jo Herstad is an Associate Professor in the Department of Information Systems Design at the University of Oslo , where she has worked since 2002. With a background in industry at Ericsson (1990-2003), Herstad bridges technical expertise with academic rigor. She teaches courses including: IN1030 - Introduction to Design, Use, Interaction (since 2017) IN2000 - Software Engineering with Project Work IN5480 - Interaction with AI and Autonomous Systems Research Focus: Her work explores Human-Computer Interaction through: Universal Design principles in digital environments Human-Robot Interaction for domestic applications Inclusive Technology across diverse populations Participatory Design methodologies Privacy Dynamics in smart homes Multimodal Systems for elderly care Key Publications (2017-2024) examine motion profiling in robotics, equitable digital feedback, and socio-technical systems. Her supervision includes 15+ master's theses on topics ranging from chatbot ethics to universal design in education. Current projects focus on: Artificial Intelligence and Sensor Technology Multimodal Elderly Care Systems (MECS) Podcast Accessibility (PUD) RHYME: Music Technology for All

Michelle Zhuمشاهده پروفایل

استاد

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

Dr. Michelle Zhu is a Professor and Associate Director for Faculty and Academic Affairs at the School of Computing, Montclair State University. She previously held roles as Associate Professor and Director of Undergraduate Programs at Southern Illinois University Carbondale. Dr. Zhu holds a Ph.D. in Computer Science from Louisiana State University and a B.S. in Biomedical Engineering from Zhejiang University. Her research focuses on parallel/distributed computing, big data analytics, and high-performance networking, supported by grants from NSF, DOE, and NVIDIA. She has authored over 150 peer-reviewed publications. Education: Ph.D., Computer Science, Louisiana State University (2005) M.Sc., Computer Science, Louisiana State University (2002) B.S., Biomedical Engineering, Zhejiang University (1996) Her research interests span parallel computing architectures, cloud workflow scheduling, and cybersecurity. She has led initiatives integrating computational thinking into STEM education and developed robotics-based learning tools. Her work has been funded through NSF grants such as the $1.1M "Assimilating Computational and Mathematical Thinking into Earth and Environmental Science" project (2017–2022). Dr. Zhu’s articles explore topics like blockchain-based cloud security, GPU-accelerated Gibbs sampling, and edge computing deployment strategies. She actively contributes to academic governance, serving on Montclair State’s Middle States accreditation committee and the University Academic Assessment Council. Key Grants: NSF MRI: Multimodal Collaborative Robot System (MCROS), $321,737 (2021–2024) DOE: Scalable Application Support Platform for E-Sciences, $389,398 (2009–2013) Service Roles: Curriculum Committee Chair, Computer Science Department Blue Ribbon Task Force for Gen Ed Redesign (2019–2020) She collaborates on robotics projects like MCROS and leads outreach efforts to engage pre-university communities in AI and robotics education.

Lynne Greweمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Lynne Grewe serves as a Professor in the Department of Computer Science at California State University, East Bay, where she maintains active research and teaching responsibilities with current office hours and contact information. Her work bridges theoretical computer science with real-world applications across healthcare, education, and emergency response domains. Her research portfolio centers on three interconnected thrusts: Medical Technology : Development of computer vision systems for stroke detection through facial pattern analysis (StrokeChange), infrared-based disease monitoring, and assistive navigation tools for the visually impaired (Seeing Eye Drone) Educational Innovation : Creation of multimodal systems like ULearn that detect student frustration using deep learning, alongside community college partnerships to broaden participation in computing Sensor Fusion Applications : Integration of multi-modal data for disaster response, infrastructure monitoring, and mobile health platforms using advanced machine learning techniques Publication analysis reveals consistent evolution toward real-time, deployable systems—particularly mobile health applications and educational tools—while maintaining foundational work in sensor fusion. Her 2020-2024 output shows increasing emphasis on healthcare applications (40% of recent work) and educational technology (25%), often combining computer vision with mobile platforms. Grewe demonstrates significant commitment to educational equity through the Faculty in Residence program, collaborating with community colleges to prepare underrepresented students for computing careers. Her Google partnership and focus on practical applications indicate strong industry engagement, though specific grant details aren't documented in source materials. Current projects suggest ongoing expansion into in-situ health monitoring and AI-driven educational support systems.

• Wireless transmission
• Wireless relay networks
• Software-defined radio
• +۷ مورد دیگر

Aggelos Bletsas Aggelos Bletsas is a Professor at the School of Electrical and Computer Engineering (ECE) at the Technical University of Crete (TUC). He holds a PhD from MIT and has expertise in wireless communication, backscatter radio, and IoT. His research focuses on ultra-low-cost sensor networks and ambiently-powered systems. Education PhD in Media Arts and Sciences, MIT (2005) MSc in Media Arts and Sciences, MIT (2001) 5-year Diploma in Electrical & Computer Engineering, Aristotle University of Thessaloniki (1998) Research Interests Bletsas' work spans scalable wireless networks, backscatter radio, RFID systems, and energy harvesting. He pioneers batteryless IoT devices and environmental sensing technologies. His lab develops hardware and algorithms for low-cost, long-range communication. Awards & Recognition IEEE Fellow (2023) 2012-2013 TUC Research Excellence Award Multiple Best Paper Awards (ISWCS, RFID-TA, SENSORS) IEEE ComSoc and RFID Council Distinguished Lecturer (2022-2025) Labs & Projects Bletsas leads the Telecommunications Laboratory at TUC, focusing on batteryless sensors, scatter radio, and robotic inventory systems. Key projects include 'Internet of Plants' and ambiently-powered inference networks.

Robert Godwin-Jonesمشاهده پروفایل

استاد

• Computer-Assisted Language Learning
• Second Language Acquisition
• Artificial Intelligence in Language Education
• +۳ مورد دیگر

Robert Godwin-Jones is a Professor in the Department of Foreign Language at Virginia Commonwealth University's College of Humanities and Sciences, where he has served since 1979. He holds the position of Foreign Language Liaison and maintains active scholarly contributions through his "German Stories" digital repository and "Communicating Across Cultures" blog, focusing on technology-enhanced language pedagogy and intercultural communication. His educational background includes: B.A. in French and German from Franklin and Marshall College (1971) M.A. in Comparative Literature (German, French, and English) (1973) Ph.D. in Comparative Literature from the University of Illinois Urbana-Champaign (1977) Dr. Godwin-Jones specializes in Computer-Assisted Language Learning (CALL), with research spanning artificial intelligence applications, virtual reality environments, and digital literacies for language learners. His work examines how emerging technologies transform second language acquisition through ecological semiotics, distributed agency models, and multimodal communication frameworks. He investigates pedagogical translanguaging strategies for less commonly taught languages and analyzes authenticity in AI-mediated language interactions, particularly in pragmatics and writing development. Analysis of his 2021-2025 publications reveals three dominant trajectories: (1) generative AI integration in language instruction with emphasis on ethical implementation and threat mitigation; (2) extended reality applications creating immersive language spaces in the metaverse; and (3) ecological approaches connecting smart devices, ambient intelligence, and situated learning contexts. His scholarship consistently bridges theoretical frameworks with practical classroom applications across 19th-century German literature studies and contemporary language education. He maintains active professional engagement through memberships in: Delta Phi Alpha German Honorary Society Phi Kappa Phi Honorary Society Modern Language Association American Association of Teachers of German American Association of Teachers of French Foreign Language Association of Virginia As director of the "German Stories" project since 1994, he has curated verified editions of 19th-century German narratives with English translations under Creative Commons licensing, creating what has become a foundational resource for literary study and language acquisition. His blog extends this work through contemporary analyses of intercultural communication challenges, while his scholarly leadership in organizations like CALICO shapes national discourse on technology in language education. His laboratory functions as the "German Stories" digital ecosystem, which has evolved into a comprehensive platform hosting annotated texts, pedagogical resources, and research archives. This environment supports both formal classroom instruction and informal learning communities, demonstrating his commitment to porous classroom models that integrate physical and digital learning spaces.

Mathias Fischerمشاهده پروفایل

استاد

• IT and network security
• Resilient distributed systems
• Network monitoring
• +۴ مورد دیگر

Mathias Fischer is Professor for Computer Networks at the University of Hamburg since December 2021, affiliated with the MIN Department of Informatics. He previously served as an assistant professor at Universität Hamburg (2016-2021), University Münster (2015-16), and held postdoctoral positions at the International Computer Science Institute/UC Berkeley (2014-15) and the Center for Advanced Security Research Darmstadt/TU Darmstadt (2012-14). His educational background includes a PhD in Computer Science from TU Ilmenau (2012) and a diploma in Computer Science from the same institution (2008). He also served as Head of Data Literacy Education in IT Support at the University of Hamburg's ISA Center. Professor Fischer's research spans critical areas of modern network infrastructure, with particular emphasis on IT and network security , resilient distributed systems , and network monitoring . His work addresses fundamental challenges in cybersecurity including botnet monitoring, intrusion detection, and critical infrastructure protection. His research group actively investigates P2P networks and develops innovative approaches to network security that balance functionality with privacy preservation. Analysis of his recent publications reveals a strong focus on privacy-enhancing technologies, network security protocols, and resilient distributed systems. His research trajectory shows increasing attention to practical implementations of security solutions for edge computing environments, digital twin networks, and time-sensitive networking applications. The work demonstrates sophisticated integration of cryptographic techniques with network architecture design to address emerging security challenges in distributed systems. Among his notable recognitions are the Claussen-Simon Competition for Universities (2019), the University Prize of the Claussen-Simon Foundation (2019), and an Outstanding Paper Award at ACSAC (2018). Claussen-Simon Competition for Universities (2019) University Prize of the Claussen-Simon Foundation 2019 Outstanding Paper Award at ACSAC (2018) Professor Fischer leads multiple significant research projects including SOVEREIGN (Technologically sovereign security monitoring), RESISTANT (Resilient zero-trust platform for aircraft), and Dynamic situational awareness for rescue teams. His research group comprises numerous doctoral and master's students working on cutting-edge network security challenges. Current projects focus on developing resilient data and AI platforms for crisis situations, security monitoring for critical infrastructures, and innovative home network security solutions. The Computer Networks research group at the University of Hamburg, led by Professor Fischer, maintains active collaborations with industry and academic partners. The group operates specialized laboratories focused on network security testing, intrusion detection systems, and resilient network architectures. Current research directions include QUIC protocol security, federated learning security, and privacy-preserving network analytics, with strong emphasis on practical implementations that address real-world security challenges.

• Business Model Development
• Software Ecosystems
• Virtual Reality
• +۵ مورد دیگر

Sebastian Gottschalk is a researcher at Paderborn University, Germany, specializing in business model development within software ecosystems, virtual reality applications, and model-driven software engineering. His research focuses on creating situation-specific approaches to business model development, with particular emphasis on tool support, method composition, and knowledge provision. His research interests span business model innovation, virtual reality applications for education and collaboration, model-driven development, and end-user programming. He has made significant contributions to understanding how business models can be developed in context-aware ways within software ecosystems, with practical applications in tool development and method engineering. His publication record shows a clear progression from foundational work on business model development to innovative applications in virtual reality and gamification. Recent work demonstrates increasing focus on practical implementations, particularly in educational contexts using VR technology to teach UML and software modeling concepts. Gottschalk has collaborated extensively with Gregor Engels (27 publications together), Enes Yigitbas (20 publications), and Alexander Nowosad (7 publications), indicating strong research partnerships that have driven much of his recent work in business model development and virtual reality applications.

• Maritime Navigation
• Marine Engineering
• Human Factors in Maritime Systems
• +۳ مورد دیگر

Reto Weber is a Lecturer in Technology at Chalmers University of Technology, specializing in Maritime Studies . With a professional background as a sea captain and pilot on the Swedish west coast, he brings practical maritime expertise to his academic work in bridge simulators and e-navigation systems. Education : Sea Captain's Degree, Master's from World Maritime University (Switzerland, England, Sweden) Affiliations : Chalmers University, Lighthouse - Swedish Maritime Competence Center, Swedish Transport Administration (Trafikverket) His research focuses on maritime navigation systems , particularly examining human factors in automated environments. Key areas include: Algorithmic decision support in maritime traffic Collision avoidance mechanisms Impact of automation on vessel traffic services Development of web-based simulation tools Route exchange protocols and e-navigation solutions Remote ship monitoring ergonomics Reto's publications reveal trends in SMART ship technologies and Lighthouse projects , emphasizing the integration of artificial intelligence with traditional maritime practices. His work spans simulation-based training tools, COLREG compliance, and physics-informed machine learning architectures for wind propulsion optimization. As an examiner for courses like MManeuvering and Navigation in Confined Waters and Bridge Service , he bridges academic research with practical maritime education through Chalmers' Full Mission Bridge Simulator . Collaborations with institutions like Lighthouse and Trafikverket demonstrate his commitment to advancing maritime safety and efficiency through technology.