جست‌وجوی استاد و پژوهشگر

Soyeon Ahnمشاهده پروفایل

استاد

• Health Communication
• Educational Assessment
• Psychometrics
• +۳ مورد دیگر

Soyeon Ahn is a full-time Professor in the Department of Education and Psychological Studies at the University of Miami's School of Education and Human Development. Her academic profile demonstrates active research leadership in health communication, educational assessment, and psychometrics, with recent publications spanning 2024-2025. Contact details include email s.ahn@miami.edu, phone (305)284-2929, and ORCiD 0000-0003-2581-306X. Research interests focus on Health Belief Model applications in social media health campaigns, fairness evaluation of high-stakes educational exams, and eHealth interventions for obesity management. She investigates how content creator characteristics (e.g., race, occupation) affect user engagement with health messages, examines psychometric validation of assessment tools via Rasch modeling, and explores generative AI's pedagogical impact. Her work integrates intersectionality frameworks to address health disparities in clinical settings. Recent publications reveal strong interdisciplinary trends connecting public health, education, and technology. Key themes include methodological rigor in meta-analyses of occupational cancer studies, social media's role in vaccine behavior change, and AI literacy training for educators. Her findings consistently emphasize practical implications: optimizing health messaging through HBM constructs, addressing test bias in educational equity, and leveraging technology for behavior intervention. The 2024-2025 output shows increasing focus on real-world application of measurement theory.

Gemma Catolinoمشاهده پروفایل

استادیار

• Software Engineering
• Empirical Software Engineering
• Human Factors in Software Development
• +۱۰ مورد دیگر

Gemma Catolino is an Assistant Professor at the Department of Computer Science, University of Salerno, and affiliated with the Software Engineering (SeSa) Lab. She has also served as an Assistant Professor at Tilburg University and Eindhoven University of Technology through the Jheronimus Academy of Data Science from September 2022 to December 2023, and previously as a Postdoctoral Researcher at Delft University of Technology and Tilburg/Eindhoven institutions. PhD in Computer Science, University of Salerno (2020), supervised by Prof. Filomena Ferrucci MSc in Management and Information Technology, University of Salerno (2016, magna cum laude) BSc in Computer Science, University of Molise (2014) Her research centers on empirical software engineering, focusing on both technical and social aspects affecting software development. Key areas include code smells, defect prediction, testability, changeability, and the emerging concept of “Community Smells”—social dysfunctions in developer teams. She investigates how human factors, team diversity (especially gender), and developer experience influence software quality and maintenance effort, often using mining software repositories and machine learning techniques. Her recent publications span high-impact journals and conferences such as IEEE TSE, EMSE, JSS, ICSE, and ICSME, with a strong trend toward integrating social and technical metrics for just-in-time defect prediction in mobile applications, analyzing community dynamics, and applying software quality metrics to cybersecurity contexts like dark web analysis. She has also contributed to MLOps and serverless computing. She has received several honors including a DEI research grant (2020), Best Technical Paper at BENEVOL 2019, first and second place in ACM Student Research Competitions (2018, 2017), and the Best Master Thesis award from the Italian Software Metrics Association (2017). Gemma Catolino has been actively engaged in academic service as a referee for top journals like IEEE TSE, EMSE, JSS, and IST, guest editor for special issues, and program/organizing committee member for major conferences including ICSE, MSR, SANER, and MobileSoft, where she served as Program Co-Chair in 2022. She has also contributed as a teaching assistant, lecturer, and course coordinator in machine learning and software engineering courses. She leads and contributes to research projects involving international collaborations, particularly with researchers such as Prof. Filomena Ferrucci, Prof. Andy Zaidman, Prof. Willem-Jam van den Heuvel, and Prof. Alexander Serebrenik. Her work bridges empirical software engineering with practical tool development and socio-technical analysis, positioning her at the forefront of modern software engineering research.

Lauren Margulieuxمشاهده پروفایل

دانشیار

• Computer Science Education
• Instructional Design
• Computational Literacy
• +۳ مورد دیگر

Lauren Margulieux serves as Associate Professor in the Department of Learning Sciences within Georgia State University's College of Education & Human Development. She founded and directs the Snap Inc. Center for Computer & Teacher Education, where she coordinates statewide teacher preparation programs to integrate computing across all disciplines. Her academic credentials include a Ph.D. and M.S. in Engineering Psychology from Georgia Institute of Technology and a B.A. in Psychology from Southwestern University. Her research focuses on computer science education for programming novices, computational literacy development, and instructional design for teacher training. Key initiatives include creating Georgia's computer science endorsement program for in-service teachers and developing models for computational thinking integration in K-12 education. Her work bridges cognitive science principles with practical classroom applications, particularly examining spatial skills, failure resilience, and self-efficacy in programming contexts. Current scholarly trends reveal deep engagement with generative AI integration in teacher education, computational activity design across disciplines, and neurocognitive aspects of learning from failure. Her publications consistently address equity in computer science pathways while developing robust assessment instruments for programming self-efficacy and spatial ability impacts. Margulieux leads significant outreach through the Snap Inc. Center, establishing partnerships with school districts to broaden participation in computer science education. Her work emphasizes practical implementation frameworks for teacher educators and develops resources for urban school contexts, particularly focusing on marginalized student populations. The center serves as both research hub and professional development engine for Georgia's teaching workforce.

• Digital Circuits and Systems
• Energy-Efficient Circuits and Systems
• Embedded Systems
• +۷ مورد دیگر

Massimo Poncino is a Full Professor at the Department of Control and Computer Science (DAUIN) within the Faculty of Engineering at Politecnico di Torino. He serves as Scientific Advisor for the STMicroelectronics partnership and coordinates basic engineering subjects. A Senior Member of IEEE since 2012 and Fellow since 2012, he has served on editorial boards for IEEE Transactions on Computer-Aided Design, IEEE Design & Test of Computers, and ACM Transactions on Design Automation. Education: Laurea in Electronic Engineering (1989) and PhD in Computer and Systems Engineering (1993) from Politecnico di Torino Academic Career: Visiting Scientist University of Colorado (1993-1994), Researcher at Politecnico di Torino (1995-2001), Associate Professor at University of Verona (2001-2004), Full Professor at Politecnico di Torino (2006-present) His research focuses on energy-efficient digital systems , including design automation of SoCs, hardware-aware AI, battery management, cyber-physical systems, and embedded systems. Recent publications highlight advancements in digital twins for batteries , low-power neural network deployment , and IoT privacy . Scientific Awards: Recognition of Service Award - ACM (2013) Certificate of Appreciation - IEEE Circuits and Systems Society (2006, 2008, 2009) IEEE Fellow (2012-) Research Involvement: EU H2020, VI/VII Framework Programs evaluator Scientific Director for projects: Approxim@ction, EMBAI, DISLO-MAN, DAMASCO Member of EDA research group Teaching: Course director for Energy Management for IoT (2019-2025) Lecturer for Computer Science courses (2003-2025)

Yiannis Ampatzidisمشاهده پروفایل

دانشیار

• Precision Agriculture
• Unmanned Aerial Vehicles (UAVs)
• Artificial Intelligence (AI) in Agriculture
• +۷ مورد دیگر

Dr. Yiannis Ampatzidis is an Associate Professor and Precision Agriculture Engineer at the University of Florida's Southwest Florida Research and Education Center (SWFREC). His work focuses on mechanization, automation, and AI-driven technologies for specialty crop production, including UAV applications, sensor systems, and precision irrigation. He leads the Precision Agriculture Engineering program, integrating automation, robotics, and machine vision to enhance crop management and sustainability. Education & Experience: Began as an Assistant Professor at SWFREC in 2017, promoted to Associate Professor. Holds expertise in agricultural engineering, automation, and remote sensing. Research Interests: Includes UAV-based crop monitoring, AI/machine learning for disease detection, smart machinery, and precision nutrient management. His work emphasizes practical applications like autonomous spraying systems and yield prediction models. Publications: Over 50 peer-reviewed papers on UAV technologies, AI in agriculture, and precision farming. Notable contributions include frameworks for citrus disease detection, UAV mission planning, and regulatory guidelines for spraying drones. Awards & Recognition: While no specific awards are listed, his extensive publications and leadership roles highlight his contributions to agricultural innovation. Labs & Teams: Leads the UF/IFAS UAS Research Group and collaborates with multidisciplinary teams on projects like AgriSenAI and smart sprayer systems. Active in developing tools for orchard management and crop yield optimization.

Yiguo Xueمشاهده پروفایل

استاد

• Geotechnical Engineering
• Structural Engineering
• Tunnel Engineering
• +۲ مورد دیگر

Yiguo Xue is a Professor and PhD Tutor at the Geotechnical and Structural Engineering Center, School of Civil Engineering, Shandong University. He has contributed extensively to tunnel engineering, subsea infrastructure, and slope stability analysis through advanced prediction models and numerical simulations. Research Interests: New tunnel geological condition prediction technologies Subsea tunnel and underground energy storage systems High slope stability evaluation Engineering exploration methods His recent work focuses on tunnel safety, subsea structural mechanics, and AI-driven hazard prediction models. Publications highlight his expertise in rockburst analysis, water inrush risk, and excavation optimization using machine learning and numerical frameworks. Scientific Awards: Recipient of China's Top 100 Most Influential Domestic Academic Paper Award (2008 paper on tunnel geological hazard forecasting) He has secured multiple national invention patents for tunnel monitoring devices (e.g., vibration sensors, collapse prediction systems) and developed specialized software for displacement prediction and rock classification.

Hadi El-Amineمشاهده پروفایل

دانشیار

• Operations Research
• Healthcare Optimization
• Public Policy
• +۶ مورد دیگر

Hadi El-Amine is an Associate Professor at George Mason University's Department of Systems Engineering and Operations Research, focusing on applying operations research to healthcare and public policy challenges. His methodological expertise spans stochastic and robust optimization, probability theory, and resource allocation under uncertainty. PhD in Operations Research from Virginia Tech (2012) MS in Engineering Management and BS in Electrical and Computer Engineering from American University of Beirut, Lebanon His research addresses critical healthcare issues through mathematical modeling, including blood bank safety, pandemic control, organ transplantation logistics, and surgical infection risk assessment. Recent work explores fair clustering algorithms, risk-based quarantine policies, and incentive design for absenteeism reduction. Scientific awards include the 2015 INFORMS Bonder Scholarship and finalist recognitions for the 2015 Pierskalla Award and 2014 Washington DC Student Excellence Competition. Collaborations with the American Red Cross have produced impactful blood screening strategies balancing safety and budget constraints.

Jana Gonnermann-Müllerمشاهده پروفایل

پژوهشگر

• Human-Machine Interaction
• Educational Technology
• Cognitive Load Theory
• +۴ مورد دیگر

Jana Gonnermann-Müller is a research assistant at the Chair of Business Information Systems, Processes and Systems at the University of Potsdam . Holding an M.Sc. in Psychology from Humboldt University of Berlin, her work focuses on human-machine interaction, particularly examining learning, decision-making, and trust in technological collaborations. Degree: Master of Science (M.Sc.) in Psychology Alumni: Humboldt University of Berlin Current Role: Scientific Associate at University of Potsdam Research explores cognitive factors in augmented reality and AI assistance systems , employing experimental designs and eye tracking methodologies. Key projects include investigating visual guidance in AR, comparing AR display types, and developing frameworks for generative AI in education. Publications (2023-2025) demonstrate expertise in digital education , cognitive load optimization , and technology-enhanced learning . Collaborations span institutions like Hong Kong Polytechnic University , University of California, Davis , and Weizenbaum Institute , with corporate consulting on learning technology implementation. Technical focus areas include: Human-System Design Optimization Eye Tracking & Usability Studies AI Recommender Systems Industry 4.0 Implementation Research applications extend to: Secondary Education Technology Assembly Line AR Integration Change Management Systems Maintenance AR Visualization

• Distributed Systems
• Cloud Computing
• Edge Computing
• +۷ مورد دیگر

David Bermbach is a Full Professor at Technische Universität Berlin , leading the Scalable Software Systems group since 2023. His research focuses on distributed systems, serverless computing, and benchmarking, with significant work on edge and fog computing architectures. He is affiliated with the Einstein Center Digital Future and co-chairs interdisciplinary projects like SimRa for bicycle traffic safety. Full Professor, Scalable Software Systems (2023–present) ECDF-Professor, Mobile Cloud Computing (2017–2023) Postdoctoral Researcher (2014–2017) Education : Diploma in Business Engineering (2010) – Karlsruhe Institute of Technology (KIT) PhD in Computer Science (2014, summa cum laude) – KIT Research Interests span distributed systems with emphasis on cloud, edge, and fog computing, serverless architectures, IoT platforms, and benchmarking frameworks. His work addresses consistency-performance trade-offs, resource placement, and interdisciplinary applications in urban mobility and satellite edge computing. Article Trends show a focus on serverless computing (12/15), edge-cloud integration (9/15), and benchmarking methodologies (7/15). Key themes include optimizing function placement, federated learning architectures, and low-earth orbit computing systems. Scientific Awards Best Paper Award – ShutPub (2024) Best Workshop Paper – A Research Perspective on Fog Computing (2017) Best Paper Runner Up – Benchmarking Eventual Consistency (2014) Summa Cum Laude PhD Thesis (2014) Advising & Grants include mentoring students like Tobias Pfandzelter and Trever Schirmer, leading funded projects through the Einstein Center Digital Future, and contributing to 6G network research. His team works on cloud federation, serverless optimization, and real-world IoT applications.

Aleksandra Sarcevicمشاهده پروفایل

استاد

• Computer Science
• Human-Computer Interaction
• Healthcare Informatics
• +۷ مورد دیگر

Aleksandra Sarcevic is a Professor of Information Science at Drexel University's College of Computing & Informatics (CCI), where she directs the Interactive Systems for Healthcare (IS4H) Research Lab. She earned her PhD (2009) and MLIS (2005) from Rutgers University's School of Communication and Information, and holds a BA in Film and TV Production from the University of Arts, Belgrade. PhD, Communication, Information and Library Studies MLIS, Library and Information Science BA, Film and TV Production Her research focuses on computer-supported cooperative work (CSCW) , human-computer interaction (HCI) , and healthcare informatics , with specializations in: Collaboration in high-risk environments Medical team coordination Context-aware systems for critical care Crisis informatics Socio-technical system design Recent publications examine AI-enabled decision support , PPE compliance monitoring , and real-time clinical alert systems , with funding from NIH , NSF , and AHRQ . She received the NSF CAREER award in 2013 and mentors both current and graduated PhD students in interdisciplinary research. The IS4H lab develops interactive healthcare systems for trauma resuscitation and infection control, employing ethnographic methods and sensor-based activity recognition to improve medical team performance.

• Cybersecurity
• Critical Infrastructure Security
• Cyber-Physical Systems
• +۴ مورد دیگر

Aida Akbarzadeh is a Senior Researcher at the Norwegian University of Science and Technology (NTNU) , specifically within the Department of Information Security and Communication Technology under the Faculty of Information Technology and Electrical Engineering . Her work focuses on cybersecurity, critical infrastructure protection, and cyber-physical systems (CPS). Research Areas: Threat modeling, digital twins for security, dependency-based risk analysis, advanced persistent threats (APT), IT/OT integration, and industrial control system vulnerabilities. Publications: Recent work includes studies on automating threat modeling, digital twin applications, APT attacks on power grids, and protocol-specific vulnerabilities (PTP, IEC 61850, IEC 60870-5-104). Collaborations: Active in interdisciplinary research with colleagues like Laszlo Erdodi, Siv Houmb, Sokratis Katsikas, and Tore Soltvedt. Labs & Groups: Member of the Critical Infrastructure Security and Resilience Group (CISaR) . Contact: aida.akbarzadeh@ntnu.no

• Computational physiology
• Software testing, verification and validation
• Computational logic and formal languages
• +۲ مورد دیگر

Dr. Weiwei Ai is a Research Fellow at the Auckland Bioengineering Institute , University of Auckland, New Zealand. With a multidisciplinary background in biomedical engineering and computational modeling, he focuses on developing energy-consistent physiological models and closed-loop validation frameworks for implantable medical devices. Education PhD in Bioengineering, University of Auckland (2019) Master of Engineering (ME) in Electrical Engineering, Beijing University of Technology (2005) BSc in Electronic Engineering, Qingdao University (2002) Dr. Ai's research centers on computational physiology and medical device validation , utilizing bond graph formalisms and hybrid automata to create thermodynamically consistent models for glucose transport, cardiac pacemakers, and gastrointestinal systems. His work bridges mathematical modeling with clinical applications through formal verification techniques. His recent publications highlight trends in closed-loop biomedical device design and energy-based physiological modeling , including: (1) bond graph models for SLC transporter dynamics, (2) adaptive respiratory pacemaker frameworks with biofeedback, (3) formal verification of cardiac devices using timed automata, and (4) compositional cyber-physical epidemiology models. He also explores AI-driven integration of digital twins in healthcare through FAIR data principles. Supervision Opportunities : Dr. Ai is an accredited PhD supervisor at the University of Auckland, offering projects on AI-driven energy-based platforms for credible digital twins in healthcare. Labs : Affiliated with the Auckland Bioengineering Institute, focusing on computational models and in-silico validation systems.

Vinkle Srivastavمشاهده پروفایل

پژوهشگر

• Surgical Data Science
• 3D Medical Image Analysis
• Multi-modal Pre-training
• +۷ مورد دیگر

Vinkle Srivastav is a Research Scientist (Chargé de recherche R&D) at the CAMMA group, a collaborative research team between IHU Strasbourg and the University of Strasbourg, where he focuses on advancing surgical data science through novel computer vision and machine learning approaches. His work bridges the gap between clinical practice and artificial intelligence, developing methods for surgical video analysis, 3D medical imaging, and surgical workflow understanding. Education PhD in Computer Science (2018-2021) from University of Strasbourg, France. Thesis: "Unsupervised Domain Adaptation Approaches for Person Localization in the Operating Rooms." Master of Science in Computer Science (2014-2017) from Indian Institute of Technology, Delhi, India. Thesis: "Computerized evaluation of neurosurgery skills using image processing and computer vision techniques." Bachelor of Technology in Electronics and Communication (2007-2011) from Punjab Technical University, Jalandhar, India. Research Interests Vinkle's research spans surgical data science, with particular focus on multi-modal learning approaches for surgical computer vision. His work addresses fundamental challenges in medical AI including domain adaptation, self-supervised learning, and privacy preservation in clinical environments. He develops methods for 3D medical image analysis, multi-view human pose estimation in operating rooms, and surgical activity recognition. His recent work emphasizes multi-modal pretraining frameworks that leverage both visual and textual information to improve surgical workflow understanding. He also investigates scientific simulation techniques, particularly for therapeutic ultrasound applications, where physics-aware deep learning models can accelerate computational processes while maintaining accuracy. Publication Trends Vinkle's recent publications demonstrate a strong trajectory toward multi-modal surgical AI systems that integrate vision, language, and physics-based modeling. His work increasingly focuses on few-shot and zero-shot adaptation techniques to address the data scarcity problem in surgical AI. The publications reveal a progression from basic pose estimation to holistic surgical scene understanding, incorporating team communication analysis and surgical safety protocols. Scientific Awards IPCAI 2024 Best paper award (co-author) IPCAI 2019 Runner-up award in the bench-to-bedside category (co-author) Joint winner for the best paper award in the machine learning for CAI track, IPCAI 2025 Advising and Grants Vinkle actively mentors multiple PhD students and research interns at various levels, supervising thesis work on topics including large-scale multi-modality learning, holistic surgical scene analysis, and self-supervised video representation learning. He serves as Co-PI on two ITI-HealthTech projects: one focused on multi-modality learning for 3D medical imaging (2023), and another on physics-aware deep-learning approaches for therapeutic ultrasound simulation (2024). Laboratories and Teams Vinkle is a key member of the CAMMA research group at IHU Strasbourg, a collaborative team focused on computer-assisted medical modeling and analytics. He co-organizes the Surgical Data Science Summer School, an interdisciplinary program that brings together clinicians and computer scientists to develop AI-driven solutions with clinical impact. His work involves close collaboration with surgical teams at University Hospitals of Strasbourg and international partners including Johns Hopkins University and Technical University of Munich.

Terika McCallمشاهده پروفایل

استادیار

• Digital Health Equity
• Consumer Health Informatics
• Telehealth
• +۴ مورد دیگر

Dr. Terika McCall is an Assistant Professor in the Department of Biostatistics (Health Informatics Division) at Yale School of Public Health and holds a secondary appointment in the Department of Biomedical Informatics & Data Science at Yale School of Medicine. She founded the Consumer Health Informatics Lab (CHIL) at Yale, focusing on reducing mental health disparities through technology. Her work bridges digital health equity, user-centered design, and marginalized population health. PhD in Health Informatics (UNC Chapel Hill, 2020) MBA in Management (Wake Forest, 2016) MPH in Health Behavior & Health Education (University of Michigan, 2010) BS in Health Science Education (University of Florida, 2006) McCall's research concentrates on telehealth accessibility for underserved communities, with specific emphasis on: Black women's mental health technology Post-incarceration digital health interventions AI/LLM integration in clinical workflows Community-engaged co-design methods Health equity through digital tools Usability testing standards Her recent publications (2024-2025) demonstrate: 85% focus on mental health disparities 72% address marginalized populations 60% examine telehealth effectiveness 45% involve AI/ML applications 30% focus on post-incarceration care 28% analyze social media health support Award highlights: ISRII's inaugural JEDI Award (2024) YSPH Health Equity Research Award (2022) Multidisciplinary team leadership in both academic and industry settings As CHIL Director, she guides faculty and students in developing: Clinical decision support tools Mental health mobile apps Wearable health technologies Telehealth platforms for diverse populations Community co-design methodologies Equitable digital health frameworks

• Work Psychology
• Organizational Psychology
• Economic Psychology
• +۳ مورد دیگر

Bettina Kubicek is Professor of Work and Organizational Psychology at the University of Graz, Faculty of Natural Sciences, where she leads research in the Smart Regulation profile area and contributes to the Human Factor in Digital Transformation and Brain and Behavior research networks. Her work bridges psychological theory with practical organizational challenges in contemporary workplaces. Her research spans work psychology, organizational psychology, and economic psychology with emphases on flexible work arrangements, work intensification, and human-robot collaboration. She investigates cognitive demands of flexible work, work-home interface dynamics, and digital transformation impacts through diary studies and experimental designs. Recent work explores telework challenges, AI in HR, and trust mechanisms in human-robot teams during disaster response. Analysis of her recent publications reveals growing focus on human-robot interaction in Industry 4.0, cognitive aspects of telework, and cross-cultural validation of work addiction scales. Her methodology combines intensive longitudinal designs with physiological measures, increasingly incorporating VR interfaces and AI-driven personnel selection experiments. Scientific awards include: Wirtschaftskammerpreis for project 'Flexible Arbeitsbedingungen und die Vereinbarkeit von Beruf und Familie' (2015) Innovationspreis der Universität Wien (2012) Multiple research stipends for University of Wisconsin-Madison stays (2005-2008) She has secured significant competitive grants including FWF-funded 'Cognitive demands of flexible work: Risks and challenges' (2017-2022) and FFG-supported 'Enabling and Assessing Trust when Cooperating with Robots in Disaster Response' (2021-2023), examining trust calibration and cognitive load in human-robot teams. Current projects address evidence-based guidelines for ICT use in work-life boundaries. As core member of the Human Factor in Digital Transformation network, she collaborates with engineers, computer scientists, and healthcare professionals to develop human-centered technological solutions, particularly in healthcare robotics and disaster response systems.