جست‌وجوی استاد و پژوهشگر

Hanna Kurniawatiمشاهده پروفایل

استاد

• Robotics
• Decision-Making Under Uncertainty
• Motion Planning
• +۴ مورد دیگر

Hanna Kurniawati is a Professor at the ANU School of Computing and holds the SmartSat CRC Professorial Chair for System Autonomy, Intelligence, and Decision-Making. She leads the ANU Node and Planning & Control theme of the ARIAM Hub, and founded the Robot Decision Making group. Her research focuses on scalable algorithms for decision-making under uncertainty, particularly in robotics and autonomous systems. She has received prestigious awards, including the RSS 2021 Test of Time Award and multiple best-paper recognitions. She is an active conference organizer and editorial board member for journals like IEEE Transactions on Robotics. Education: BSc Computer Science, University of Indonesia PhD Computer Science (Robot Motion Planning), National University of Singapore (2008) Research Interests: Planning under uncertainty and POMDP frameworks Robot motion planning and computational geometry Integration of planning and reinforcement learning Autonomous system assurance and safety Service and Leadership: Former President of the Australian Robotics and Automation Association (2019–2020) Keynote speaker at ICRA 2025, IROS 2018, and ICAPS 2025 Program Co-Chair for ICRA 2022 and Editor roles for IEEE TRO and RA-L Teaching: Advanced Topics in AI (COMP4620/8620) Advanced Topics in Machine Learning (COMP4680/8650) Algorithms (COMP3600/6466)

Norbert Jungمشاهده پروفایل

استاد

• Cybersecurity
• Embedded Systems
• Biometrics
• +۴ مورد دیگر

Prof. Dr. Norbert Jung is a Professor of Secure Embedded Systems at the Bonn-Rhein-Sieg University of Applied Sciences (Department of Computer Science), where he also served as Founding Director of the Institute for Security Research (2011–2024). He is a core member of the NRW Promotionskolleg for Applied Research and leads the Biometrics Evaluation Center (BEZ) at the university’s Sankt Augustin campus. His expertise spans cybersecurity, embedded systems, and optoelectronic sensor technology, with a focus on biometric security, real-time signal processing, and safety-critical machine systems. Prof. Jung holds a Diplom-Ingenieur in Communications Engineering from RWTH Aachen University, where he also earned his Dr.-Ing. in optoelectronics and signal processing. His career includes R&D roles at Philips Electronics in medical imaging systems. Since 1999, he has led numerous national and industrial projects, including Biolab II (biometric system evaluation), ROSE3D (robust 3D camera systems), and SMOOTH (safety switches for industrial machinery). His work addresses challenges in anti-spoofing biometrics, industrial robot safety, and sensor-based material classification. Key research themes include: Biometric system resilience against presentation attacks Safety-critical embedded systems for manufacturing Near-infrared (NIR) and multispectral imaging for skin detection Optoelectronic sensor innovation for industrial and medical applications He has spearheaded projects such as the BEZ center, which evaluates biometric systems for government and industry. His lab infrastructure includes optoelectronics and laser labs (H008/H010) and collaborates with the German Federal Office for Information Security (BSI). Prof. Jung is also the laser safety officer for his department.

Henny Admoniمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Assistive Robotics
• Nonverbal Communication
• +۵ مورد دیگر

Henny Admoni is an Associate Professor in the Robotics Institute at Carnegie Mellon University (CMU), with a courtesy appointment in the Human-Computer Interaction Institute. She leads the Human And Robot Partners (HARP) Lab, focusing on assistive and collaborative robotics, particularly how robots can interpret human nonverbal cues like eye gaze to improve interactions. Her research spans healthcare, human-robot teamwork, and socially assistive robotics, supported by NSF, ONR, and industry partners. Admoni holds a PhD in Computer Science from Yale University and a BA/MA from Wesleyan University. Education PhD in Computer Science, Yale University BA/MA in Computer Science, Wesleyan University Research Interests Admoni’s work emphasizes human-centered robotics, including assistive systems for mobility-impaired users, driver situational awareness modeling, and fostering social support networks through AI. She investigates how robots can proactively learn from humans, adapt to team dynamics, and communicate transparently to build trust. Key themes include nonverbal communication, shared autonomy, and ethical design. Grants & Awards NSF CAREER Grant (2020) Okawa Research Grant (2021) A. Nico Habermann Career Development Professorship (CMU) Advising & Teaching Admoni advises graduate students on topics like robot learning, assistive systems, and human-robot teaming. She teaches courses on Human-Robot Interaction at both undergraduate and graduate levels, emphasizing interdisciplinary approaches that blend robotics, AI, and cognitive science. Labs & Projects The HARP Lab develops robots for meal preparation assistance, driving support, and socially assistive interventions. Current projects include the HARMONIC dataset for collaborative tasks and COHUMAIN for socio-cognitive architectures in human-machine teams. Admoni is on sabbatical at KTH University through 2025.

Jake Eckersleyمشاهده پروفایل

پژوهشگر ارشد

• dryland ecology
• biogeochemistry
• plant functional ecology
• +۵ مورد دیگر

Jake Eckersley serves as a Postdoctoral Fellow and Multi-Discipline Research Associate at the School of Biological Sciences, The University of Western Australia, where he conducts ecological research on environmental weeds and river systems in northern Australia's tropics while contributing to casual teaching duties. His academic credentials include: Botany, Honours (First Class), The University of Western Australia (2019) Botany/Zoology, Bachelor, The University of Western Australia (2018) Marketing, Bachelor, Curtin University (2014) Dr. Eckersley's research program integrates dryland ecology, biogeochemistry, and remote sensing methodologies to investigate vegetation dynamics in water-limited environments. His work particularly focuses on riparian systems in Australia's semi-arid regions, examining how shifting hydrological patterns affect plant phenology, functional composition, and ecosystem processes through innovative measurement techniques including satellite-based remote sensing and digital canopy photography. His recent publications demonstrate a cohesive research trajectory centered on quantifying vegetation responses to altered water regimes in dryland rivers. By combining field observations with machine learning approaches and remote sensing technologies, his work addresses critical knowledge gaps regarding ecosystem resilience under changing flow conditions, with particular emphasis on methodological advancements for monitoring leaf area dynamics and functional diversity. Scientific recognition includes: Cooperative Research Centre for Transformations in Mining Economies Top Up Scholarship (2021) James memorial travel award (2021) Research support comes primarily through competitive scholarships including the CRC TiME Top Up Scholarship. While actively engaged in teaching, there is no public record of graduate students formally advised. Current collaborative efforts include ongoing work with UWA's environmental research teams examining invasive species ecology and riverine vegetation dynamics in northern Australia.

Afshin Rahimiمشاهده پروفایل

استاد

• Aerospace Engineering
• Control Systems
• Machine Learning
• +۳ مورد دیگر

Dr. Afshin Rahimi is a Professor of Engineering at the University of Windsor's Faculty of Engineering, specializing in aerospace systems, machine learning applications, and fault diagnosis. His research focuses on enhancing reliability in satellite systems, renewable energy infrastructure, and smart manufacturing through advanced control systems and AI-driven solutions. He has won prestigious awards including gold medals at the Seoul International Invention Fair (2022) and the International Competition for Inventors (2021) for his work on helicopter engine diagnostics and satellite fault detection. Dr. Rahimi's research interests include: Machine learning for fault detection/prognosis in aerospace and energy systems Control systems design for satellites, UAVs, and offshore wind turbines Optimization of energy efficiency in cloud data centers and renewable systems Smart manufacturing applications using computer vision and object detection His recent work emphasizes applying AI to solve challenges in: Real-time satellite fault diagnosis using hybrid frameworks PV-integrated robotic systems for sustainable energy management Thermal regulation in smart buildings via LSTM networks Data scarcity mitigation in space systems using GANs Dr. Rahimi collaborates with industry partners and student teams like the WinSAT satellite design group. His research bridges theoretical advancements with practical implementation in critical infrastructure sectors.

João Barrosoمشاهده پروفایل

دانشیار

• Digital Image Processing
• Accessibility
• Human Computer Interaction

João Barroso serves as Associate Professor with Habilitation at the University of Trás-os-Montes and Alto Douro (UTAD) and Senior Researcher at INESC TEC's Human-Centered Computing and Information Science Centre, where he has been Research Coordinator since October 2012. Previously, he held the position of Pro-Rector for Innovation and Information Management at UTAD from July 2010 to July 2013. His academic credentials include: Doctorate in Electrical Engineering from UTAD (2002) Habilitation in Informatics/Accessibility (2008) Barroso's research centers on Digital Image Processing, Accessibility, and Human-Computer Interaction, with significant extensions into biosignal processing for healthcare applications, machine learning for gaming and autonomous systems, and context-aware architectures for Industry 4.0 environments. His work consistently emphasizes real-world implementation, as demonstrated by his leadership in developing the ElderMind mobile application for cognitive stimulation and portable ECG/EMG acquisition systems. He founded two major conference series: Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion (DSAI, 2006) and Technology and Innovation in Sports, Health and Wellbeing (TISHW, 2016). Analysis of his 15 most recent publications (2024-2025) reveals three dominant research thrusts: (1) Machine learning validation for gaming and autonomous driving (PPO vs. SAC algorithms), (2) High-fidelity biosignal acquisition systems with visual electrode monitoring, and (3) Systematic vulnerability analyses in web/mobile security and context-aware Industry 4.0 architectures. His publications demonstrate a consistent pattern of translating theoretical computing advances into practical health and industrial applications, with 2025 outputs showing particular emphasis on hardware-software integration for telemedicine and production management. Barroso has supervised 40 postgraduate students including Dennis Lourenço Paulino (2024, UTAD) who developed crowdsourcing personalization models and Luís Filipe Jesus Correia (2022, UTAD) who researched Brain-Computer Interfaces. His project portfolio spans 35 research and development initiatives, with recent grants supporting his virtual assistant prototype for Industry 4.0 production environments and high-resolution Bluetooth biosignal modules. He leads the Human-Centered Computing and Information Science Centre at INESC TEC, where his laboratory focuses on prototyping accessible technologies through interdisciplinary teams. Current projects integrate computer vision for elderly care, ROS2 middleware for unmanned vehicle coordination, and semantic interoperability frameworks for digital twins, maintaining his dual focus on theoretical innovation and socially impactful applications.

• Artificial Intelligence
• Cybersecurity
• Internet of Things
• +۴ مورد دیگر

Dr. Mabrouka Abuhmida is a Senior Lecturer in Computing and Mathematical Sciences at the University of South Wales. She holds dual leadership roles as Research and Innovation Group Leader and Course Leader for MSc/BSc AI programs. Her research focuses on Artificial Intelligence applications in Digital Healthcare Transformation, Cybersecurity, and Internet of Things (IoT), particularly in medical and infrastructure contexts. She leads initiatives spanning Computer Science, Data Science, and AI, emphasizing collaborations between academia and industry. Her research interests include Deep Learning, Natural Language Processing (NLP), and empowering women in STEM. Notable projects include developing Annie the chatbot, an empathy-focused NLP tool, and frameworks for IoMT security. She has pioneered work on AI-based intrusion detection in Industrial Control Systems (ICS) and cybersecurity dynamics in critical infrastructure. Publications highlight her cross-disciplinary work across AI ethics, structural health monitoring, and forensic data automation. Recognized for advancing women's participation in STEM, she actively bridges academic research with real-world tech adoption through student-business partnerships. Responsibilities include spearheading: IoT and Machine Learning initiatives Deep Learning in healthcare cybersecurity Natural Language Processing for case management Her lab focuses on AI-driven solutions for digital transformation challenges in healthcare and infrastructure sectors.

Gregory Matthewsمشاهده پروفایل

دانشیار

• Statistical Disclosure Control
• Missing Data Methods
• Statistical Genetics
• +۳ مورد دیگر

Gregory Matthews is an Associate Professor in the Department of Mathematics and Statistics at Loyola University Chicago (LUC), serving as Director of the Center for Data Science and Consulting. He holds a Ph.D. in Statistics from the University of Connecticut (2011), with prior industry experience in predictive modeling (2004–2006) and postdoctoral research at the University of Massachusetts-Amherst (2011–2014). His research focuses on statistical disclosure control, missing data methodologies, statistical genetics, and sports analytics, with applications in anthropology, healthcare, and sports performance analysis. Dr. Matthews’ academic background includes a B.S. in Actuarial Science and M.S. in Applied Statistics from Worcester Polytechnic Institute. His work bridges theoretical statistics with practical applications, including developing imputation methods for aging curves in baseball, analyzing sports performance metrics, and addressing privacy challenges in data dissemination. He has contributed to open-source tools like the 'MixMAP' R package for genetic association studies and 'teamcolors' for sports data visualization. His publications span diverse topics such as dental morphology analysis in primates, predictive modeling for medical diagnostics, and methodological advancements in statistical disclosure limitation. He actively engages in interdisciplinary collaborations, particularly in paleontology, healthcare policy, and sports science. Dr. Matthews’ consulting work emphasizes ethical data practices, including privacy-preserving techniques for biomedical and social datasets. He has advised on projects ranging from emergency department protocols to optimizing NFL defensive strategies. His educational contributions include designing curricula for sports analytics and statistical methodologies.

Khaled Salehمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Autonomous Systems
• +۴ مورد دیگر

Dr. Khaled Saleh is a Lecturer in Computing and Information Technology at the University of Newcastle's School of Information and Physical Sciences. He holds a PhD in Computer Science from Deakin University (2019). Prior to his current role, he served as a Postdoc Research Fellow at the University of Technology Sydney (2020–2022) and a Research Fellow at Deakin University (2018–2019). Research Focus: AI, Machine Learning, Autonomous Systems, Computer Vision, and Intelligent Transportation Systems Grants: Secured over $683K in funding, including projects on traffic safety and AI in education Editorial Roles: Topic Editor at MDPI Sensors and reviewer for top journals/conferences (e.g., IEEE T-ITS, ICRA) Research interests span autonomous systems, traffic safety, and AI-driven solutions for transportation and education. He has published over 30 papers in top venues and actively contributes to grants and industry collaborations. Teaching: Coordinates courses like Programming Languages and Business Intelligence.

Caroline Chanelمشاهده پروفایل

استاد

• Autonomous Systems
• Decision-Making Algorithms
• Robotics
• +۳ مورد دیگر

Caroline Chanel is a Professor at ISAE-SUPAERO (DCAS), holding the CASAC Chair since 2022. She has extensive experience in research and teaching, with roles including Associate Professor (2019-2024), Research Engineer (2013-2019), and HDR accreditation (2023). Her research focuses on embedded decision-making for autonomous systems, including proactive architectures, multi-robot cooperation, and human-machine interaction. She leads and participates in high-profile projects like SAMURAI (AID), CHIP-GT (ANR-DFG), and HAICO (CASAC Chair). She has supervised numerous PhD students and post-doctoral researchers, collaborating with institutions like ONERA, INRAe, and international partners. Education: PhD in Control and Embedded Systems (University of Toulouse 2013), Master's in Automatic Systems (Université Paul Sabatier 2008-2009), and Engineer Diploma from PUCRS (2002-2008). Awards include the Amelia Earhart Fellowship (2011) and ISAE-SUPAERO Foundation PhD Fellowship (2013). Research interests span decision-making algorithms, multi-agent systems, and neuroergonomics. Key projects address UAV navigation, blockchain integration for autonomous systems, and physiological computing for human-robot interaction. Teaching responsibilities include modules on autonomous systems, control systems, and neuroergonomics at ISAE-SUPAERO's engineering and master's programs. She co-leads the DECISIO doctoral team (ISAE-ONERA) and is involved in executive roles for conferences like EDSYS'.

• Edge Computing
• Internet of Things
• Vehicular Networks
• +۵ مورد دیگر

Muhammad Bilal is an Associate Professor at Zhejiang University's School of Computer Science, Department of Computer Science and Technology. His research spans multiple cutting-edge domains in computer science and engineering, with a particular focus on edge computing, Internet of Things, and vehicular networks. His research interests include Edge Computing , Internet of Things , Vehicular Networks , Federated Learning , Digital Twins , and Cloud Computing . His work addresses critical challenges in resource allocation, latency optimization, privacy preservation, and intelligent decision-making in distributed computing environments. He has made significant contributions to developing novel frameworks for service caching, computation offloading, and secure data processing in next-generation networks. His recent publications reveal a strong trend toward integrating artificial intelligence with edge and cloud infrastructure, particularly focusing on privacy-preserving techniques and resource-efficient algorithms. His work spans applications from intelligent transportation systems to healthcare monitoring and meteorological services, demonstrating the versatility and real-world impact of his research. Dr. Bilal has established a prolific publication record with numerous high-impact papers in top-tier journals and conferences, reflecting his active engagement in the academic community. His collaborative approach is evident through extensive co-authorship networks, particularly with researchers in China, Pakistan, and internationally.

• Internet of Things (IoT)
• Edge Computing
• eHealth Systems
• +۷ مورد دیگر

Dr. Menychtas Andreas is an Assistant Professor at the Department of Digital Systems, School of Informatics and Communications, University of Piraeus. He holds a PhD from the National Technical University of Athens (2009), specializing in service-oriented architectures. His teaching focuses on distributed computing, programming, and information systems development across multiple institutions including the University of Piraeus and Hellenic Open University. Research interests center on modern computing infrastructures, software development, and IoT applications, with particular emphasis on Edge Computing, smart cities, telemedicine, and machine learning. He has led over 20 European and national projects, publishing >100 articles with 1,900+ citations. Key areas include AR healthcare solutions, bias mitigation in AI, and secure medical IoT systems. Notable contributions include the MedSecurance project (medical IoT security), CrowdHEALTH platform (big data-driven public health policies), and AGILE framework (open-source edge computing). His work bridges theoretical research with practical implementations in wearable tech, telemedicine systems, and urban smart infrastructure. Grants and collaborations highlight extensive industry partnerships, with current focus on digital twins for healthcare robotics (AI4Work), AI-driven pandemic monitoring, and gamification in healthcare platforms. His lab develops innovative solutions at the intersection of AR, edge computing, and healthcare informatics.

Velichkovska Bojanaمشاهده پروفایل

دانشیار

• Machine Learning
• Healthcare Informatics
• Data Science
• +۳ مورد دیگر

Velichkovska Bojana is an Associate Professor at the Faculty of Electrical Engineering and Information Technologies (FEIT) of the Ss. Cyril and Methodius University in Skopje. Her research focuses on machine learning applications in healthcare, IoT security, and algorithmic bias detection. She actively contributes to addressing ethical challenges in clinical AI through studies on demographic bias in medical datasets and vital sign analysis. Her academic work spans over a decade, with notable contributions in: Machine learning for early cancer diagnosis 3D sign language animation systems IoT traffic classification Racial bias detection in healthcare algorithms Her recent publications emphasize critical analysis of AI fairness in clinical contexts, including groundbreaking work on how vital signs data can inadvertently encode racial biases. Methodologically, she combines computer vision techniques like image segmentation with advanced machine learning models to enhance algorithm transparency. Bojana maintains active collaboration with industry partners in developing wearable sensor systems for healthcare applications. Her pedagogical contributions include teaching advanced machine learning courses at FEIT and supervising multiple research teams in applied AI ethics.

• Critical Data Studies
• Digital Methods
• Digital Infrastructure
• +۴ مورد دیگر

Dr. Jonathan W. Y. Gray is Reader in Critical Infrastructure Studies at the Department of Digital Humanities, King's College London. He also serves as Director of the Centre for Digital Culture and maintains research affiliations with the Digital Methods Initiative at the University of Amsterdam and the médialab at Sciences Po, Paris. Gray's research explores how digital data, methods, and infrastructures shape collective life. His work spans critical data studies, digital methods development, environmental data research, and critical technical practice. Key projects include forestscapes (examining forest-society relations through soundscapes), research on East and Southeast Asian communities in the UK, and investigations into data infrastructures for social justice. His recent publications reveal consistent thematic threads: the politics of data infrastructures, environmental data practices, and critical approaches to digital methods. The forthcoming book 'Public Data Cultures' (2025) and his co-edited works on data journalism demonstrate his commitment to making data practices more transparent and accountable. Gray has received recognition for collaborative research through the Public Data Lab, which he co-founded in 2017 as a distributed network for collective inquiry. His work bridges academic research with public engagement through projects like the forestscapes listening lab and collaborations with organizations including Amnesty International. As an educator, Gray focuses on critical and creative engagements with digital data, methods, and infrastructures. His approach emphasizes engaged, research-led teaching that brings together researchers, students, and external organizations as co-inquirers in addressing complex societal challenges.

Sergio Salinas Monroyمشاهده پروفایل

دانشیار

• Cyberphysical Systems
• Network Security
• Additive Manufacturing Security
• +۶ مورد دیگر

Sergio Salinas Monroy is an Associate Professor at Wichita State University's College of Engineering, School of Computing. His research focuses on cyberphysical systems, network security, and privacy enhancement in critical infrastructures like additive manufacturing, power grids, and edge computing networks. He currently leads the Graduate Certificate in Information Assurance and Cybersecurity program and spearheaded the NSA/DHS CAE-CD designation for WSU. Academic Rank: Associate Professor Department: School of Computing University: Wichita State University Email: sergio.salinasmonroy@wichita.edu His research spans secure resource allocation in supply chains, cyberfraud investigation, and federated deep learning systems. Recent publications emphasize adversarial machine learning, intrusion detection, blockchain applications in manufacturing, and privacy-preserving algorithms. His work integrates deep learning, anomaly detection, and cryptographic protocols for industrial cybersecurity. Research trends in his articles include cyberphysical systems security (4 entries), privacy preservation in distributed networks (3 entries), and machine learning optimization for threat detection (5 entries). He also explores blockchain integration, edge computing economics, and energy-based attack detection in IoT-enabled systems. Professor Salinas Monroy actively contributes to academic service as an organizer and technical program committee member for IEEE conferences. His office hours are held in Jabara Hall (239) on Wednesdays from 3:30–5:00 PM.