جست‌وجوی استاد و پژوهشگر

• Internet of Things (IoT)
• Context-aware computing
• Edge and cloud computing
• +۷ مورد دیگر

Prem Prakash Jayaraman is a Professor in the Department of Computer Science and Software Engineering within the Faculty of Science, Engineering and Technology at Swinburne University of Technology. His research focuses on the intersection of Internet of Things, context-aware computing, and distributed systems, with particular emphasis on practical applications in smart cities, digital manufacturing, and healthcare. Dr. Jayaraman's research interests span a wide range of topics within the IoT ecosystem, including context-aware computing, edge and cloud computing integration, digital twins for industrial applications, sensor network optimization, and performance evaluation of IoT middleware platforms. His work often addresses the challenges of real-world deployment, focusing on practical solutions for context management, data quality assurance, and resource optimization in distributed environments. He has made significant contributions to frameworks for context query generation, adaptive context monitoring, and caching strategies that enhance the efficiency of IoT applications. His recent publications demonstrate a strong trend toward applied research with practical implementations in smart city infrastructure, digital manufacturing, and healthcare applications. His work often combines theoretical frameworks with real-world validation, particularly evident in his studies on 5G-enabled smart cities, AI-driven roadside infrastructure monitoring, and digital twin implementations for manufacturing quality control. The research spans multiple sub-disciplines including context-aware systems, performance evaluation methodologies, and resource optimization techniques for distributed IoT environments. Dr. Jayaraman maintains an extensive collaborative network with researchers across Australia and internationally, particularly with Dimitrios Georgakopoulos, Rajiv Ranjan, Arkady Zaslavsky, and Abdur Forkan. His work appears in top-tier journals and conferences including IEEE Transactions on Industrial Informatics, Future Generation Computer Systems, IEEE Internet of Things Journal, and major conferences like MDM, HICSS, and IEEE Cloud.

• HIV/AIDS Research
• Infectious Diseases
• Global Health
• +۵ مورد دیگر

Diane Havlir, MD, is a Professor of Medicine and Chief of the HIV, Infectious Diseases, and Global Medicine Division at Zuckerberg San Francisco General Hospital (ZSFG), part of UCSF. She serves as the Associate Chair of Clinical Research in the Department of Medicine and directs the UCSF AIDS Research Institute. She holds the Robert L. Weiss Memorial Chair for HIV/AIDS Research and was elected to the National Academy of Medicine in 2019. Her work focuses on HIV/AIDS, tuberculosis (TB), and global health, with an emphasis on community-based interventions and policy. Havlir co-founded San Francisco Getting to Zero (GTZ), a citywide initiative to eliminate HIV transmission and deaths. She leads the Sustainable East Africa Research in Community Health (SEARCH) Collaboration, a large-scale trial demonstrating how universal HIV testing and treatment reduces transmission and improves population health. Her research integrates telehealth, long-acting antiretrovirals, and AI-driven precision health to address healthcare equity. Education: MD from UCSF, residency in internal medicine at UCSF during the early AIDS crisis. She has over 400 publications in high-impact journals like NEJM and JAMA. Awards include the National Academy of Medicine membership and leadership roles in the WHO HIV-TB working group and UN AIDS Scientific Advisory Committee. Research interests span HIV prevention, TB co-infection, and global pandemic responses. Key projects include the SEARCH-Sapphire study (AI-driven community health strategies) and the Unidos en Salud partnership (Latinx community HIV/COVID-19 care). She has pioneered interventions like dynamic choice HIV prevention models and telemedicine for marginalized populations. Grants/Awards: NIH-funded investigator, SEARCH Collaboration, Robert L. Weiss Chair, National Academy of Medicine. Labs/Teams: AIDS Research Institute, SEARCH Consortium, GTZ partnership.

• Artificial Intelligence
• Bioinformatics
• Natural Language Processing
• +۳ مورد دیگر

Dr. Ahmad Aghaebrahimian is a researcher at the ZHAW School of Life Sciences and Facility Management, affiliated with the Institute of Computational Life Sciences. He specializes in computational methods applied to healthcare, natural language processing (NLP), and bioinformatics. His work integrates deep learning, ontology-based systems, and signal processing to address challenges in healthcare informatics, biomedical research, and security systems. Research Projects: Project Leader: Advancing Information Accessibility in Hospitals (LLMs) Project Leader: Multi-document Patient Records Summarization Project Leader: Plant Cell Cultures with Deep Learning Deputy Leader: Automatic Supply Chain Monitoring Research Interests: His research focuses on AI-driven solutions for healthcare, including ontology-aware relation extraction, medical text mining, and robust signal processing systems. He also explores NLP applications in question answering, entity disambiguation, and parallel corpus creation. Recent work includes drone detection using CNNs in low SNR environments and computational methods for natural products discovery. Publications Trends: Over the past decade, his publications emphasize interdisciplinary approaches combining machine learning with bioinformatics and medical informatics. Key themes include deep learning model optimization, biomedical knowledge graph construction, and practical applications of NLP in healthcare systems. Grants & Collaboration: Leads research initiatives on AI in colorectal cancer classification and supply chain monitoring, demonstrating expertise in securing project leadership roles within academic-industry collaborations.

Grammati Pantziouمشاهده پروفایل

استاد

• Algorithmic Techniques
• Parallel and Distributed Computing
• Mobile Ad-Hoc and Sensor Networks
• +۵ مورد دیگر

Grammati Pantziou is a Professor at the Department of Informatics and Computer Engineering, University of West Attica (since 2018). She previously held roles as Vice Rector for Administrative Affairs (2019–2023), member of the Governing Committee, and president of the Research Committee at the same institution. Earlier positions include Assistant Professorships at Dartmouth College (1992–1994) and University of Central Florida (1994–1995), and Professor at the Technological Educational Institute of Athens (1998–2018). She served on the Greek Data Protection Authority (2003–2013). Education: Ph.D. in Computer Science, University of Patras, Greece (1991) Research Interests: Focuses on algorithmic optimization, parallel/distributed computing, mobile networks, and cybersecurity. Specializes in sensor networks, pervasive computing security, and smart city applications. Her work bridges theoretical algorithms with real-world systems like tourism route planning, vehicular networks, and IoT. Publications & Impact: Authored/co-authored 11 books, 165+ papers, and edited 5 books. Her research has 5,600+ citations (h-index:34, i10-index:80). Leads 29 funded projects on cybersecurity, transportation optimization, and smart systems. Editorial Roles: Editor-in-Chief of Algorithms Journal's 'Parallel and Distributed Algorithms' section, and editor for journals like Cybersecurity & Privacy (MDPI) and Security and Communication Networks (Wiley). Contributions: Developed frameworks like eCOMPASS for tourist route planning and ETHACA for cybersecurity training. Pioneered algorithms for vehicle relocation in sharing systems and energy-efficient data aggregation in sensor networks.

• Physics Education Research
• STEM Education
• Student Retention in STEM
• +۳ مورد دیگر

John Stewart is a Professor in the Department of Physics and Astronomy at West Virginia University (WVU), specializing in Physics Education Research (PER). He holds leadership roles as the PI of the WVUteach Robert Noyce Scholarship program and the CPHYS Computational Physics Scholarship program, aimed at supporting STEM education and rural students. Stewart is also the site leader of the American Physical Society's Physics Teacher Education Coalition (PhysTEC) at WVU. Dr. Stewart earned his PhD in Condensed Matter Theory from the University of Illinois, Urbana-Champaign in 1994. His career has focused on transforming physics education, notably leading the University of Arkansas' physics departmental transformation, which increased physics graduates tenfold. He transitioned to WVU in 2014, where he founded the Center for Excellence in STEM Education. His research interests include understanding classroom dynamics, student retention in STEM, and equitable physics education. Key areas of study are the structure of student knowledge, gender and ethnic biases in assessments, and improving physics teacher preparation. Stewart has authored numerous articles in journals like Physical Review Physics Education Research and American Journal of Physics . Received APS Fellow (2016) and AAPT Fellow (2018) for contributions to teacher preparation and departmental transformation. Principal Investigator of NSF-funded grants, including the STEM-R and Pulsar Search Collaboratory projects. Former editor of the National Science Digital Library's physics teacher preparation portal. Stewart advises on student scholarships and collaborates on initiatives like the PhysTEC, emphasizing teacher training and rural student support. His work extends to analyzing pandemic impacts on physics learning and developing active learning strategies for STEM retention. He directs the CPHYS scholarship, supporting rural students in computational physics, and oversees the WVUteach program to transition STEM majors into teaching. His efforts have been recognized through fellowships and leadership roles in national physics education organizations.

Kerstin Sophie Haringمشاهده پروفایل

استادیار

• Human-Robot Interaction (HRI)
• Social Robotics
• Ethical AI
• +۴ مورد دیگر

Kerstin Sophie Haring is an Assistant Professor in Computer Science at the Ritchie School of Engineering and Computer Science at the University of Denver. She directs the Human Robot Technology Lab , focusing on human-robot interaction (HRI), ethical AI, and socially contextual robot design. Her work integrates augmented reality, cultural perception studies, and healthcare robotics to advance user-centric robotics solutions. Dr. Haring’s research emphasizes Robot acceptance and trust mechanisms Ethical frameworks for companion robots Cross-cultural HRI studies Empathetic AI design AR/VR interfaces for autonomous systems Her interdisciplinary approach addresses challenges in long-term human-robot teaming , robot lifecycle management , and equity in neuroimaging research . She actively contributes to professional organizations like IEEE and collaborates with industry to bridge academic research with commercial applications. Her lab develops innovative systems like the Brush-E Bot (toothbrushing companion) and explores ethical AI training using virtual environments. Current projects investigate empathy neural mechanisms and abolitionist robotics principles to counteract systemic biases in technology.

Jose Martinez Lorenzoمشاهده پروفایل

استاد

• Antenna Design and Optimization
• Radar Systems
• Explosives Detection
• +۵ مورد دیگر

Jose Martinez Lorenzo is a Professor in both Mechanical and Industrial Engineering and Electrical and Computer Engineering at Northeastern University's College of Engineering. His research focuses on advanced sensing and imaging systems, including radar design, antenna optimization, subsurface scattering analysis, and biomedical applications like breast cancer detection. He holds a PhD in Electrical Engineering from the University of Vigo (Spain). Notable achievements include the 2012 IEEE Homeland Security 'Best Paper Award' and multiple patents in security and sensing technologies. Research interests span compressive sensing, computational electromagnetics, and multimodal imaging. He leads the Sensing, Imaging, Control, and Actuation Laboratory, developing systems for security, sustainability, and healthcare applications. Key projects include NSF-funded 4D mm-wave imaging and DHS-funded explosives detection initiatives. Professional affiliations include IEEE Antennas and Propagation Society, and he teaches courses on electromagnetic fields, antennas, and mathematical methods for engineers. Awards include the 2012 National Security Innovation Competition First Prize and multiple patents for innovative radar and sensing technologies. His work combines theoretical advancements with practical applications, such as non-destructive testing and satellite-based environmental monitoring. Current efforts emphasize high-speed imaging systems and AI-driven sensor fusion for real-time decision-making in dynamic environments.

Kristian Amadoriمشاهده پروفایل

دانشیار مدعو

• Aeronautical Engineering
• Systems Engineering
• Multidisciplinary Optimization
• +۳ مورد دیگر

Kristian Amadori is an Adjunct Associate Professor and Docent at Linköping University's Department of Management and Engineering (IEI), affiliated with the Fluid and Mechatronic Systems (FLUMES) division. His research focuses on aeronautical systems engineering, multidisciplinary optimization, and conceptual aircraft design, with a particular emphasis on sustainable aviation and system-of-systems approaches. He collaborates extensively on projects involving unmanned aircraft systems, radar signature optimization, and technology portfolio analysis. His work bridges theoretical frameworks with practical applications in aerospace engineering, leveraging advanced modeling techniques such as multi-fidelity integration and ontology-based reasoning. Key research interests include systems integration challenges, stealth technology for UAVs, and automated design methodologies. His publications span topics from economic viability of regional aircraft to agent-based simulation for complex systems. Amadori's contributions emphasize holistic engineering approaches that address both technical and operational aspects of aeronautical product development. Recent articles highlight advancements in multidisciplinary optimization, technology prioritization frameworks, and parametric modeling for conceptual design. His work often involves collaboration across academia and industry to address challenges in aircraft design, surveillance systems, and sustainable aviation technologies. While no specific awards or grants are listed, his active publication record reflects sustained engagement with cutting-edge aerospace research.

Caroline Shenton-Taylorمشاهده پروفایل

مدرس ارشد

• Nuclear Physics
• Artificial Intelligence
• Data Analytics
• +۴ مورد دیگر

Dr. Caroline Shenton-Taylor is a Senior Lecturer in Applied Nuclear Physics at the University of Surrey, affiliated with the School of Mathematics and Physics. She holds a PhD from the University of Warwick (2007) and has extensive industry experience with the UK Ministry of Defence and Home Office. Her research focuses on AI-driven solutions for nuclear security, radiation detection, and health monitoring, alongside innovative outreach through platforms like YouTube and podcasts. Key roles include MPhys Placement Lead, Physics Undergraduate Admissions Tutor, and IOP Mentor. Education: PhD in Magnetic Compton Scattering, University of Warwick (2007) MPhys (First Class Honours), University of Warwick (2004) Research Interests: AI optimization for cancer screening and radiation detection Data analytics in nuclear decommissioning and environmental protection Development of novel radiation detection technologies Scientific outreach and public engagement Collaborations: Partnerships with National Physical Laboratory, Royal Surrey NHS Foundation Trust, and institutions like Imperial College London and University of Manchester. Awards: Lynne Millward Academic Staff Member of the Year 2023 Famelab UK National Winner (2014) MoD Chief Scientific Advisers Commendation (2011) Advising & Grants: Supervised 9 PhD students, led projects on AI-driven radiation detection (NuSec SIGMA), and developed algorithms for shielded isotope identification. Active in funding initiatives like TRANSCEND and NTRnet. Labs/Teams: Founded the Nuclear Applications and AI team at Surrey, focusing on interdisciplinary AI-nuclear applications.

Fei Yuمشاهده پروفایل

استادیار

• Health Informatics
• Health Sciences Librarianship
• Bibliometrics
• +۳ مورد دیگر

Dr. Fei Yu is an Assistant Professor at the University of North Carolina's School of Information and Library Science (SILS), where she also serves as a faculty member in the Carolina Health Informatics Program. She holds a PhD in Library and Information Science from the University of Pittsburgh, and advanced degrees in Biomedical and Health Informatics, Information Management, and Library Science from UNC Chapel Hill and Wuhan University. Her research focuses on digital health technology, bibliometrics, research impact evaluation, and user-centered design, with particular emphasis on systematic reviews, AI applications in healthcare, and translational science support. Previously serving as a Health Informatics Librarian at UNC Health Sciences Library for seven years, Dr. Yu has supported researchers across disciplines in research impact assessment, citation analysis, and digital health technology evaluation. She currently leads grant-funded projects such as the iPICS program (US Department of Defense) and contributes to the Lancet Commission on Evidence-based Implementation in Global Health. Her work bridges library science with translational healthcare, emphasizing evidence-based practices and interdisciplinary collaboration. Dr. Yu teaches courses including User Interface Design (INLS718), Systematic Literature Search (INLS490), and Perspectives on Technology in Information (INLS777). Her awards include the 2023 UNC Libraries Peer-to-Peer Award and recognition from Endeavors for her contributions to global health research through librarian partnerships.

Gidon Ernstمشاهده پروفایل

استادیار

• Formal Methods
• Software Verification
• Software Testing
• +۵ مورد دیگر

Gidon Ernst is a Junior Professor (Assistant Professor) for Software Verification at the Department of Computer Science, LMU Munich, where he leads research in the Software and Computational Systems Lab. His work focuses on formal methods for software engineering, with particular emphasis on verification, testing, and security analysis of complex systems. His research interests span formal methods for software engineering, software testing, interactive and automated proofs, hybrid systems, and falsification. Ernst's work addresses challenges in relational proofs for substitution principle, software testing with Legion (a tool combining concolic execution and fuzzing), concurrent information flow security with SecCSL and SecC, and falsification of temporal logic requirements for hybrid systems. His approach often combines theoretical foundations with practical tool development. Ernst's publication record shows a strong focus on verification of security properties, particularly information flow security in concurrent systems, and falsification of hybrid systems. His recent work has advanced techniques for adaptive probabilistic search in falsification, compositional vulnerability detection, and contract-based software specification. He actively contributes to the verification community through competitions like VerifyThis and ARCH. Best Master Lecture 2022 in Computer Science (awarded by Gruppe Aktiver Fachschaftika) Ernst has supervised PhD student Dongge Liu on software fuzzing with machine learning (2018-2022), co-supervised with Toby Murray and Ben Rubinstein from the University of Melbourne. His teaching includes courses on formal specification and verification, methods in software engineering, and various seminars on software quality assurance and deductive verification. He has also served on numerous program committees and organized major verification events including SPIN 2025 and the VerifyThis challenge series. Ernst maintains active collaborations with researchers worldwide, particularly in the areas of hybrid systems verification (with Ichiro Hasuo, Sean Sedwards, and Zhenya Zhang) and information flow security (with Toby Murray). His work bridges theoretical computer science with practical software engineering challenges, developing tools that have seen adoption in both academic and industrial settings.

Nima Maftoonمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Auditory Mechanics
• Medical Devices
• +۹ مورد دیگر

Nima Maftoon is an Associate Professor and Director of the Biomedical Engineering graduate program at the University of Waterloo. He leads the Hearing Lab, which focuses on developing medical devices and methods for hearing loss treatment, and the Computational Metastasis Lab, which creates predictive tools for personalized cancer treatments. His research integrates biomechanics, acoustics, computational modeling, and clinical data analysis. Education: Postdoctoral Fellowship in Hearing Science (2017), Harvard Medical School PhD in Biomedical Engineering (2014), McGill University MSc in Mechanical Engineering (2000), Isfahan University of Technology BSc in Mechanical Engineering (1997), University of Tehran His research interests span auditory mechanics, medical device design, cancer metastasis modeling, and computational fluid/solid mechanics. His work combines experimental measurements with advanced computational techniques to address clinical challenges in hearing and oncology. Recent publications focus on finite-element modeling of biomedical systems, cancer cell mechanics, and acoustic analysis of the middle ear. His labs collaborate across disciplines to bridge engineering and clinical applications. Nima supervises graduate students through his Sole-Supervisory Privilege Status (SSPS) and teaches courses in linear systems and biomedical signal processing.

Donghoon Kimمشاهده پروفایل

دانشیار

• Cloud Computing Security
• High-Performance Computing
• Software Engineering
• +۵ مورد دیگر

Dr. Donghoon Kim is an Associate Professor in the Department of Computer Science at Arkansas State University, part of the College of Engineering & Computer Science. He holds a PhD from North Carolina State University and a Master of Science from Auburn University, following a software engineering role at Samsung Electronics in Korea. His research focuses on cloud computing security, high-performance computing, software engineering, parallel computing, and wireless network security. His work bridges theoretical advancements with practical applications in cybersecurity and machine learning. Dr. Kim’s research interests include analyzing machine learning approaches for detecting Android and IoT malware, enhancing deep hashing models for image retrieval, and improving authentication systems for digital content. He has contributed to optimizing multimedia data processing and evaluating Tor network vulnerabilities through real-time fingerprinting techniques. His teaching expertise spans software engineering and computer architecture. While his Google Scholar publications highlight cutting-edge work in cybersecurity and machine learning, no formal grants or awards are listed. His academic contributions emphasize both foundational research and applied solutions to modern computing challenges.

Paul Greenمشاهده پروفایل

مدرس

• Bayesian Data Analysis
• Categorical Data Analysis
• Transportation Engineering
• +۳ مورد دیگر

Paul Green is a Lecturer II in the Department of Statistics at the University of Michigan, affiliated with the College of Literature, Science, and the Arts. He earned his Ph.D. in Biostatistics from the same university in 1995. His research focuses on Bayesian data analysis, categorical data analysis, and applications in transportation systems. Key areas include driver behavior analysis, human factors in automotive interfaces, and emotion recognition via EEG signals. Education: Ph.D. in Biostatistics, University of Michigan, 1995 Research Interests: Bayesian statistical methodologies Driver cognitive load and fatigue Autonomous vehicle decision-making EEG-based emotion recognition Human factors in transportation safety Recent publications emphasize driver-brain interactions in high-speed rail environments, autonomous vehicle lane-change strategies using deep reinforcement learning, and tactile intervention systems for fatigue mitigation. His work bridges biostatistics with engineering, particularly in automotive human factors and simulation technologies. No scientific awards or grants are explicitly listed. No advisee students are recorded in the provided materials. His research extends to interdisciplinary topics like lifestyle mobilities of aging populations and standardization of driver evaluation protocols.

• Infrastructure Resilience
• Network Theory
• Operations Research
• +۵ مورد دیگر

Nils Goldbeck is an Honorary Research Fellow in the Department of Civil and Environmental Engineering at Imperial College London, part of the Faculty of Engineering. He is affiliated with the Centre for Transport Studies (CTS), Transport Systems and Logistics Laboratory (TSL), Centre for Systems Engineering and Innovation (CSEI), and Climate-KIC. His research focuses on infrastructure resilience, combining reliability engineering, network theory, and operations research to model interdependencies in urban systems. Goldbeck holds an MPhil in Engineering for Sustainable Development from the University of Cambridge and a BSc in Industrial Engineering from Karlsruhe Institute of Technology (KIT), with a minor in Applied Studies of Culture and Society. He was a visiting student at Istanbul Technical University. His work explores cascading failures, supply chain resilience, and disaster response strategies. Recent publications address autonomous vehicle control, scenario-based simulators, and holistic infrastructure risk assessment. Funded by the EPSRC Centre for Doctoral Training and Climate-KIC, his research informs policy and planning for resilient urban systems.