جستجوی استاد راهنمای دانشگاهی

• Computer Science
• Machine Learning
• Medical Imaging
• +۵ مورد دیگر

Hong Liu is a Professor at Shandong University's School of Computer Science and Technology, with an extensive publication record spanning multiple disciplines within computer science and engineering. His research spans computer vision, machine learning, medical imaging, robotics, and signal processing, with over 500 publications listed in the dblp database from 1993 to 2025. Dr. Liu's research interests focus on the intersection of artificial intelligence and practical applications across various domains. His recent work demonstrates expertise in deep learning architectures, medical image analysis, robotics navigation, and computer vision systems. He has made significant contributions to medical imaging techniques, particularly in segmentation methods using quaternion mathematics and self-attention mechanisms, as well as applications in liver disease diagnosis and pediatric fracture detection. The publication trends show increasing activity in recent years, with substantial contributions in 2023-2025 across IEEE journals and conferences. His work frequently appears in high-impact venues including IEEE Transactions on Medical Imaging, IEEE Access, and Pattern Recognition, demonstrating both theoretical rigor and practical applications. His research bridges theoretical computer science with real-world engineering and medical challenges, particularly in China's healthcare and technology sectors. Dr. Liu has collaborated extensively with researchers across Chinese institutions including Shandong University, Harbin Institute of Technology, and Huazhong University of Science and Technology, as well as international partners. His work shows strong interdisciplinary connections between computer science, electrical engineering, and medical applications.

Sangjin Hongمشاهده پروفایل

استاد

• Low-power VLSI Design
• Wireless Communication
• Digital Signal Processing
• +۲ مورد دیگر

Roles and Affiliations: Sangjin Hong is a Professor in the Department of Electrical and Computer Engineering at Stony Brook University (SUNY). He holds a Ph.D. from the University of Michigan and has prior industry experience at Ford Aerospace, Samsung, and as a research fellow at the University of Michigan. Education: B.S. and M.S. in Electrical Engineering and Computer Science, University of California, Berkeley Ph.D. in Electrical Engineering and Computer Science, University of Michigan, Ann Arbor Research Interests: Focuses on low-power VLSI design for multimedia and wireless communication systems, SOC design methodology, digital signal processing architectures, and hardware-aware system modeling. His work integrates algorithmic innovation with hardware optimization for real-world applications like surveillance, healthcare, and network systems. Teaching: Teaches core courses such as Discrete Mathematics for Engineers (ESE 122) , Digital Signal Processing Architectures (ESE 375) , and System Specification and Modeling (ESE 356/501) . Courses emphasize hands-on projects and SystemC-based system design. Awards and Affiliations: Senior Member of IEEE Member of Eta Kappa Nu and Tau Beta Pi Honor Societies Key Research Themes: Recent articles highlight work in real-time biomedical imaging, machine learning for education, and multi-sensor collaboration in surveillance systems. His publications span over two decades, reflecting expertise in both theoretical and applied aspects of signal processing and system design.

• Computer Networks
• Wireless Networks
• e-Health
• +۷ مورد دیگر

Polychronis Koutsakis is an Associate Professor in the School of Information Technology at Murdoch University's College of Science, Technology, Engineering and Mathematics. His research spans computer networks, wireless resource allocation, data science, and computational linguistics. He has received significant recognition including the Pro Vice Chancellor Education Citation for Excellence and multiple Exemplary Editor awards from IEEE. His research interests focus on network performance evaluation, e-health applications, traffic modeling, and mobile development. Recent publications demonstrate strong interdisciplinary work combining AI with network management, medical diagnostics, and urban infrastructure. Koutsakis has been honored with: Pro Vice Chancellor Education Citation for Excellence (2021) IEEE Exemplary Editor awards (2012, 2013, 2015, 2021-2023)

Abhishek Dubeyمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Cyber-physical Systems
• Distributed Computing
• +۴ مورد دیگر

Abhishek Dubey is an Associate Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He leads the SCOPE lab, focusing on AI-driven solutions for cyber-physical systems, resilient computing, and smart communities. His work integrates online learning algorithms and decision procedures to address challenges in energy systems, emergency response, and urban mobility. Key projects include partnerships with Nashville's fire department, transit agencies, and state transportation departments. Education: Ph.D. and M.S. in Electrical Engineering from Vanderbilt University (2009 and 2005), B.Tech. in Electrical Engineering from IIT Banaras Hindu University (2001). Research Interests: Resilient computational abstractions, energy-efficient transit systems, transactive energy systems, and AI for decision-making under uncertainty. Recent work emphasizes reinforcement learning, federated learning, and urban mobility optimization frameworks like NS-Gym and PDPTW-DB. Grants and Partnerships: Funded by NSF, NASA, DOE, ARPA-E, AFRL, DARPA, Siemens, Cisco, and IBM. Projects include grid-aware charging optimization, wildfire resilience, and equitable transit network design. Labs and Tools: SCOPE lab, NS-Gym simulation environment, E-Transit-Bench platform, and SmartTransit AI. His work bridges theory and practice, addressing real-world challenges in smart cities and critical infrastructure.

• Distributed communication networks
• Infrastructure-independent networks
• Aerial communication systems
• +۵ مورد دیگر

Dr. Julian Zobel is a postdoc researcher at the Adaptive Communication Systems research group within the Department of Electrical Engineering and Information Technology at the Technical University of Darmstadt. He completed his computer science studies at TU Darmstadt and worked as a research assistant from 2018-2022 before finishing his PhD in 2023 with a thesis focused on autonomous applications of aerial communication networks in disaster situations. His research interests include: Distributed and infrastructure-independent communication networks Aerial communication support and network monitoring Satellite networks Disaster response communication systems Wireless sensor networks for emergency scenarios Dr. Zobel's recent publications demonstrate a strong focus on improving communication resilience in disaster scenarios through innovative approaches involving UAVs, satellite communication, and network monitoring systems. His work bridges theoretical networking concepts with practical implementations for emergency response situations, with particular emphasis on infrastructure-independent solutions that can operate when traditional communication systems fail. His research spans multiple technical domains including protocol design, network resilience, and field testing of communication systems in realistic environments. He has supervised over 25 Master's and Bachelor's theses on topics related to his research. Notable students include Jakob Karg (KOM Award for Best Master's Thesis 2019) and Lukas Wehrstein (KOM Award for Best Bachelor's Thesis 2022). His advisees have worked on projects ranging from UAV-based network topology monitoring to low-power communication protocols for emergency crisis communication. Dr. Zobel maintains an active research profile with publications spanning conferences like ISCRAM, IEEE LCN, WONS, and journals like Global Change Biology. His collaborative work includes frequent partnerships with researchers such as Ralf Steinmetz, Björn Scheuermann, and Ralf Kundel. He is currently focused on advancing research in distributed communication networks that can operate independently of traditional infrastructure, with particular attention to satellite communication, UAV-based systems, and network monitoring approaches that can be deployed rapidly in emergency situations.

• Smart City
• Middleware
• Wireless Sensor Networks
• +۵ مورد دیگر

Félix Jesús Villanueva Molina is an Associate Professor at the University of Castilla-La Mancha, specifically in the Department of Information Technologies and Systems. His academic career demonstrates a strong focus on the intersection of computer science, smart technologies, and practical applications for improving urban and healthcare environments. His educational background includes a Ph.D. in Computer Science from the University of Castilla-La Mancha (2009), along with research stays at Friedrich-Alexander-Universität Erlangen-Nürnberg in Germany and the University of Twente in the Netherlands. These international experiences have contributed to his interdisciplinary research approach. Villanueva Molina's research spans multiple domains within computer science and technology. His primary interests focus on smart city infrastructure, middleware development, wireless sensor networks, and Internet of Things applications. More recently, his work has expanded into healthcare technologies specifically designed for elderly care and active aging. His publication record reveals a clear progression from foundational work in distributed systems and ambient intelligence toward increasingly applied solutions addressing real-world challenges. His scientific contributions demonstrate significant expertise in developing middleware solutions for smart environments, with a particular emphasis on creating practical implementations that bridge theoretical computer science with tangible applications. His work often involves interdisciplinary collaboration, particularly with healthcare professionals when developing technologies for elderly care. Throughout his career, Villanueva Molina has maintained an active research profile, with consistent publication output spanning over a decade. His recent work shows a strategic shift toward applications with direct societal impact, particularly in the domains of smart cities and healthcare technologies for aging populations. He has been involved in developing innovative solutions for urban management, environmental monitoring, and healthcare support systems. His technical expertise in distributed systems, sensor networks, and data processing frameworks has enabled the creation of comprehensive solutions addressing complex real-world problems.

Weiping Peiمشاهده پروفایل

استادیار

• Security and Privacy
• Crowdsourcing
• Machine Learning
• +۳ مورد دیگر

Weiping Pei is an Assistant Professor in the School of Cyber Studies at The University of Tulsa, specializing in security and privacy, crowdsourcing, machine learning, and human-computer interaction. Her work bridges technical security mechanisms with human behavioral aspects to develop practical privacy-preserving systems. Education: Ph.D. in Computer Science, Colorado School of Mines (2022) M.Eng. in Software Engineering, Sun Yat-sen University (2017) B.Eng. in Microelectronics, Sun Yat-sen University (2015) Dr. Pei's research centers on three interconnected pillars: secure and privacy-preserving crowdsourcing (with focus on receipt transcription systems and third-party privacy), robust machine learning (particularly adversarial attacks against vulnerability detection and content-preserving text manipulation), and usable security (including GDPR policy analysis and online grooming detection). Her approach uniquely integrates human behavioral modeling with cryptographic and machine learning techniques to address real-world security gaps in crowd-powered systems. Analysis of her 2023-2025 publications reveals a strategic shift toward AI-driven security solutions, particularly using LLMs for behavioral analysis in digital forensics and adversarial machine learning for vulnerability assessment. Her work consistently targets high-impact venues like IEEE S&P and ACM CCS, demonstrating both theoretical rigor and practical applicability in privacy policy compliance and crowdworker security. Scientific Awards: NSF CAREER Award (2025) for foundational cybersecurity research NSF SaTC 2.0 RES Award (2025) for privacy-preserving technologies NSF CRII Grant recipient (2023) Distinguished Rath Award nominee for societal-impact PhD thesis (2022) Outstanding CS Ph.D. Student Award at Mines (2021) Grace Hopper Celebration Scholarship (2018) Dr. Pei actively mentors four students across degree levels while leading multiple NSF-funded projects totaling $1.3+ million. Her research group develops tools for privacy policy analysis (PolicyChecker), adversarial vulnerability testing (AdVul), and online safety monitoring. She teaches core cybersecurity courses including Data Security and Cryptography, with future work focusing on AI security foundations through her NSF CAREER grant.

• Internet of Things
• Edge Computing
• Smart Cities
• +۶ مورد دیگر

Seng Loke is Professor in Computer Science at Deakin University, Australia, where he co-directs the Platforms and Applications Lab within the Centre for Internet-of-Things ECOsystems Research and Experimentation (CITECORE) at the School of Information Technology. He concurrently serves as Research Theme Leader for 'Intelligent Built Environments' in the Live+Smart Research Lab at Deakin’s School of Architecture and Built Environment, while holding adjunct professorships at La Trobe University (School of Engineering and Mathematical Sciences) and Southern Cross University (School of Business and Tourism). Education: PhD, University of Melbourne, 1998 His research pioneers Internet of Things architectures , edge-cloud computing integration , and human-machine cooperative systems for smart cities and transportation. Key contributions span context-aware pervasive systems (detailed in his 2006 CRC Press book) and crowd-powered mobile computing frameworks (2017 Springer publication), with emphasis on cooperative vehicles and urban IoT ecosystems. Professor Loke has authored over 300 publications including 70+ journal papers in IEEE Transactions, ACM Computing Surveys, and IEEE Internet of Things Journal. His academic leadership includes program committees for AAMAS (2003-2005), Percom (2010-2011), and MDM (2003-2006), workshop organization for AwareCities (Percom 2016) and IoCAT (Mobiquitous 2017), and editorial board membership for Sensors journal's IoT section. He actively disseminates research through public lectures on cooperative IoT algorithms and automated city futures.

Thomas Lauerمشاهده پروفایل

پژوهشگر

• Experimental Economics
• Behavioral Economics
• Experimental Methods
• +۵ مورد دیگر

Dr. Thomas Lauer serves as Scientific Managing Director of the Erfurt Laboratory for Empirical Research (ErfurtLab) at the University of Erfurt and holds the position of Deputy Data Protection Officer for the university. His academic work bridges empirical research infrastructure management and experimental economics scholarship. His research focuses on Experimental Economics , Behavioral Economics , and Experimental Methods , with significant contributions to understanding social dilemmas , time preferences , leadership dynamics , and incentive structures . Methodologically, he specializes in z-Tree and oTree programming for laboratory and field experiments, particularly examining conservation behavior, team performance, and climate change mitigation strategies. Analysis of his 15 most recent publications reveals consistent exploration of intergenerational cooperation and temporal discounting across environmental and organizational contexts. His work increasingly integrates field experiments with traditional laboratory settings, demonstrating practical applications in sustainable resource management and organizational design. Dr. Lauer has secured substantial research funding including a 54,000 Euro DFG project (2013-2015) on leadership determinants and multiple Center for Social and Economic Behavior grants (2015-2019) examining sustainable consumption, cooperation mechanics, and incentive effects. His teaching portfolio includes advanced courses in Behavioral Economics , Experimental Methods , and zTree/oTree programming . As head of the ErfurtLab, he oversees three physical laboratories (West, Central, East), mobile research infrastructure, and the Thüringen-Panel data collection system. The facility supports interdisciplinary empirical research across economics, psychology, and social sciences through standardized experimental protocols and technical resources.

• Economic History
• History
• Swedish Social Sciences
• +۶ مورد دیگر

Magnus Olofsson is an active Researcher in the Department of History at Lund University, concurrently serving as a Visiting Research Fellow at the Department of Economic History and a Profile Area Member for Human Rights. His work bridges historical scholarship with contemporary societal issues through Lund's interdisciplinary frameworks. Specializing in Economic History and Swedish Political Development , Olofsson's research examines democratization processes, contentious politics, and labor movements across Sweden's long 19th century (1789-1921). His current focus includes conflict repertoires, urban demonstrations, and welfare sector protests through projects like De stridbara svenskarna (DSS) and HALF: Historisk arbetslivsforskning . Methodologically, he integrates digital humanities approaches with traditional historical analysis. His publication trends reveal sustained engagement with political conflict (68% of recent works), democratization processes (52%), and Swedish social history (47%), with increasing digital methodology application since 2020. Key thematic clusters include labor movement evolution, republican political traditions, and provincial-national cultural dynamics. Nils Karlebys stiftelse för Skånsk kultur och historia (2010) Idéns Minnesfond (2009) Martin Weibulls Minnesfond (2009) Napoleonic Series Writing Contest, Best military paper (2008) As Principal Investigator for the DSS project (2024-2028) and coordinator for welfare sector strike research (2023-2025), Olofsson manages substantial research funding while contributing to the HALF collaborative research group. His academic service includes extensive peer review and conference organization within European historical networks. Olofsson contributes to Lund's Human Rights Profile Area through historical perspectives on political conflict and democratization, while his ContentiousGatherings.se platform demonstrates commitment to digital scholarly communication and public history engagement.

Gunter Bombaertsمشاهده پروفایل

استادیار

• Engineering Ethics
• Energy Justice
• Artificial Intelligence Ethics
• +۵ مورد دیگر

Gunter Bombaerts is an Assistant Professor at Eindhoven University of Technology , with dual affiliations in the Industrial Engineering and Innovation Sciences faculty and the Philosophy & Ethics department. He holds additional positions as EAISI Assistant Professor and EIRES Research Assistant Professor . His work focuses on interdisciplinary research at the intersection of engineering education, ethics, and societal challenges. Bombaerts has managed several high-impact projects, including Come-RES (2020–2023) and Scaling up Co-creation (2018–2021), both addressing energy justice and community-driven innovation. He also co-leads the ESDiT initiative (2019–2028), exploring ethics in disruptive technologies like AI and social media. Bombaerts has taught courses such as ITEC-Ethics of Technology and Engineering , Sociophysics 1 & 2 , and Research set-up . His educational philosophy emphasizes Challenge-Based Learning (CBL) as a tool to foster ethical reasoning and systemic thinking among engineering students. He has systematically restructured curricula using frameworks like Self-Determination Theory and Value Sensitive Design to prioritize student autonomy and societal impact. His research interests span engineering ethics pedagogy, energy transition justice, and the ethical implications of AI. He actively bridges disciplinary divides, collaborating with computer scientists, sociologists, and policymakers. Key themes include co-creation methodologies, mediation theory, and Buddhist-inspired ethical responses to attention-economy technologies. Recipient of the 2021 SEFI Maffioli Award for excellence in engineering education reform Co-winner of the 2023 Award for Best Poster and 2024 Best Formal Paper Prize Recognized for his work on Generative AI in academic writing (2023) Bombaerts oversees 7 supervised academic works and has published 113 research outputs. His grants include EU-funded initiatives on energy communities and AI ethics. He contributes to Philosophy and Technology , Ethics and Information Technology , and Organization Studies , and frequently engages in media commentary on topics like virtual power plants and energy justice frameworks. He participates in transnational research alliances such as EuroTeQ, emphasizing universities' role as societal transformers. His current projects explore normative frameworks for energy transitions, hybridization strategies for community initiatives, and the interplay between individual and collective values in decision-making.

Shane Gilroyمشاهده پروفایل

مدرس

• Autonomous Vehicles
• Image Sensors
• Automotive Engineering
• +۳ مورد دیگر

Shane Gilroy is a Lecturer in Electronic Engineering at the Department of Mechatronic Engineering, ATU Sligo. His research focuses on automotive systems, particularly autonomous vehicles, image sensor technology, and object detection challenges in occluded environments. He actively contributes to improving road safety through advancements in pedestrian detection, sensor validation, and cybersecurity in connected vehicles. His work aligns with UN Sustainable Development Goals, emphasizing innovation in urban mobility and sustainable infrastructure. Gilroy’s expertise spans computer vision, robotics, and automotive engineering, with notable contributions to occlusion classification methods and lifecycle validation of automotive components. He is currently accepting PhD students to further explore these interdisciplinary areas. Key research themes include: Autonomous vehicle perception systems Occlusion challenges in road safety Image sensor performance optimization Cybersecurity for connected vehicles Lean manufacturing methodologies His publications demonstrate a strong emphasis on practical applications, from improving pedestrian detection algorithms to evaluating sensor reliability under real-world conditions. Recent work explores urban mobility solutions and the integration of machine learning models for occlusion analysis.

Valentin Rakovicمشاهده پروفایل

دانشیار

• Wireless Networks
• Machine Learning
• Federated Learning
• +۵ مورد دیگر

Valentin Rakovic is an Associate Professor at the Faculty of Electrical Engineering and Information Technologies, Ss Cyril and Methodius University in Skopje. He is the head of the Laboratory for Wireless and Mobile Networks. His research focuses on wireless networks, machine learning, federated learning, and distributed systems, with applications in IoT, healthcare, and edge computing. He has co-authored over 80 publications and contributed to 10+ international research projects funded by the EU and NATO. Education: PhD in Electrical Engineering (2016) – Ss Cyril and Methodius University (Joint with RWTH Aachen, Germany) MSc in Wireless and Mobile Communications (2010) BSc in Telecommunications (2008) Research Interests: Wireless networks, federated learning, distributed learning, signal processing, optimization theory, and prototyping of wireless solutions. Recent work emphasizes synergies between wireless communications and machine learning, particularly in IoT and healthcare environments. Publications: Rakovic’s work spans federated learning optimization, edge computing, and network security. Recent trends include applications in healthcare, energy efficiency, and anomaly detection. Awards: Youngest recipient of the Ss Cyril and Methodius Award IEEE DySPAN Best Demo Award (2011, 2015) Supervised student teams to 1st/3rd place in IEEE competitions Labs & Teams: Heads the Laboratory for Wireless and Mobile Networks, collaborating on prototyping and system-level research.

Marta Marrón Romeraمشاهده پروفایل

دانشیار

• Intelligent Systems
• Embedded Systems
• Mobile Robotics
• +۹ مورد دیگر

Marta Marrón Romera is an Associate Professor at the Department of Electronics, School of Engineering, University of Alcalá. Her research focuses on intelligent systems, embedded systems, mobile robotics, computer vision, and assistive technologies. She holds a PhD in Electronics Technology (2008) and has over 25 years of research experience, including a 15-week stay at KTH Royal Institute of Technology in Sweden. Her work spans probabilistic algorithms for autonomous robots, machine learning, and applications in smart environments. She has led 33 research projects (19 national, 2 European, and 20 private) and holds 3 patents. She has authored 39 peer-reviewed journal articles (36 in JCR-indexed journals, 24 Q1-Q2), 5 book chapters, and over 70 conference communications. Her h-index ranges from 17 to 21, with over 1,200 citations. She has supervised 2 Cum Laude PhD theses (European), 4 ongoing PhDs, 19 master's, and 35 bachelor's theses. She actively participates as an evaluator for national research agencies, including the Spanish State Research Agency and Andalusian Quality Agency. She has organized 9 workshops and a Special Session on Multisensor Signal Processing. Her research is recognized by continuous 'sexenios' (research activity valuations) since 2015. Key contributions include the GEINTRA group's work on sensor fusion for intelligent spaces, autonomous wheelchairs, and human activity monitoring. She pioneers edge computing solutions for real-time surveillance and healthcare applications.

• Artificial Intelligence
• Automated Planning
• Machine Learning
• +۷ مورد دیگر

Dimitris Vrakas is an Assistant Professor at the Department of Informatics, School of Informatics, Aristotle University of Thessaloniki (AUTh). He holds a PhD in Intelligent Planning Systems and has conducted post-doctoral research focusing on Planning for the Semantic Web. His professional experience includes roles as a Lecturer (per Greek law 407/80), Informatics Instructor in multiple educational institutions, and IT consultant for medium-sized enterprises through the Go-online Project. Education: Bachelor of Science (1995–1999): Informatics, Aristotle University of Thessaloniki PhD (2000–2004): Intelligent Planning Systems, Dept. of Informatics, AUTh Postdoctoral Research (2005–2007): Planning for the Semantic Web, AUTh Research Interests: Automated Planning, Heuristic Functions, Intelligent Autonomous Systems, Machine Learning Applications (Energy Management, NILM), Semantic Web Services, and Smart Environment Technologies. His work bridges theoretical AI advancements with practical implementations in energy systems and emergency response. Publications: Over 45 papers (including 15 journal articles) and 5 book chapters, with a focus on energy disaggregation, evacuation algorithms, and semantic web composition. His work demonstrates expertise in applying advanced techniques like GANs for data generation and reinforcement learning for adaptive planning. Awards: 2025 ACM SIGMOD Test-of-Time Award for contributions to time-series clustering Advising & Grants: Active in guiding PhD candidates (as per recent calls) and coordinating projects like the IRIS RISK PARADIGM for industrial safety. His work involves developing smart university platforms for energy monitoring and collaborating on EU-funded initiatives. Labs & Teams: Member of the Intelligent Systems Lab at AUTh, contributing to projects like the BOnSAI ontology for smart buildings and the IRISPortal for risk management. He also coordinates the Hellenic Artificial Intelligence Society and chairs conferences like SETN 2016.