جست‌وجوی استاد و پژوهشگر

Qi Alfred Chenمشاهده پروفایل

استادیار

• Network security
• Systems security
• IoT security
• +۶ مورد دیگر

Qi Alfred Chen is an Assistant Professor in the Department of Computer Science at the University of California, Irvine (UCI), within the Donald Bren School of Information and Computer Sciences. He also holds affiliations with the Department of Electrical Engineering and Computer Science (EECS), the Institute of Transportation Studies at UC Irvine (ITS-Irvine), the Center for Embedded and Cyber-physical Systems (CECS), the Institute for Software Research (ISR), and the UC Irvine Cybersecurity Policy & Research Institute (CPRI). His research focuses on network and systems security, with particular emphasis on autonomous vehicle and IoT security. Dr. Chen received his Ph.D. from the University of Michigan in 2018. His educational background has prepared him for his current research in security of critical computer systems. His work bridges theoretical security principles with practical implementations in real-world systems. Chen's research interests center on network and systems security , with a major focus on smart systems and IoT security , particularly in transportation and autonomous vehicle systems . His work addresses security challenges through systematic problem analysis and mitigation, discovering and mitigating security problems in next-generation transportation systems, smartphone OSes, network protocols, DNS, GUI systems, and access control systems. His research has high impact in both academic and industry contexts, with over 10 top-tier conference papers, a DHS US-CERT alert, multiple CVEs, and coverage in major news media like Fortune and BBC News. His publication record shows a clear evolution from foundational work on network protocols and smartphone security toward increasingly sophisticated security analyses of autonomous vehicle systems and AI-powered transportation technologies. The research trajectory demonstrates growing technical sophistication and real-world impact, with recent work focusing on physical-world adversarial attacks against autonomous driving perception systems, LiDAR spoofing, and security of multi-sensor fusion in autonomous vehicles. NSF CAREER Award (2022) on securing the AI stack in emerging autonomous and connected CPSs Chancellor's Award for Excellence in Undergraduate Research Mentorship, UC Irvine (2021) 5th place nation-wide at National CCDC competition (2021, as faculty advisor) 1st place (Gold Medal) at CCDC Western Regional competition (2021) ProQuest Distinguished Dissertation Award, University of Michigan (2019) Dr. Chen has mentored numerous successful students, including PhD candidates and undergraduates who have gone on to positions at major tech companies like Meta, Uber, Amazon, and Intel. His research group has secured significant funding, including an NSF CAREER award, and has made substantial contributions to the field through high-impact publications and vulnerability disclosures. He is also the co-founder of the ISOC VehicleSec Symposium and has organized the AutoDriving CTF contest at DEF CON. Chen leads the AV & IoAT Security Research Group at UCI, focusing on security challenges in autonomous vehicles and the broader Internet of Autonomous Things. His team has developed numerous attack demonstrations and security analyses that have received significant media attention and influenced industry practices. The group maintains an active YouTube channel showcasing their security research.

Ryan Carneyمشاهده پروفایل

دانشیار

• Paleontology
• Epidemiology
• Functional Morphology
• +۵ مورد دیگر

Dr. Ryan Carney is an Associate Professor of Digital Science at the University of South Florida's Department of Integrative Biology (College of Arts and Sciences). His research bridges paleontology and epidemiology, using cutting-edge technologies like 3D imaging, AI, and VR/AR. He studies dinosaur biomechanics (e.g., Archaeopteryx flight mechanics) and mosquito-borne diseases (e.g., malaria, Zika) through NSF/NIH-funded collaborations with agencies like NASA and the CDC. His work integrates citizen science platforms (iNaturalist, Mosquito Alert) for disease surveillance and develops AI tools for mosquito classification. Education: PhD (Brown), MPH/MBA (Yale), B.A.'s in Biology & Art (UC Berkeley) Lab: SCA 107 (focuses on digital paleontology and disease modeling) Research interests span dinosaur functional morphology, epidemiological modeling using GIS/remote sensing, and translating science through immersive technologies. He received awards like the National Geographic Emerging Explorer and multiple USF teaching/research accolades. Awards: CAS Liberal Arts Teaching Award, Outstanding Research Achievement, etc. Grants include NSF funding for AI-driven mosquito surveillance and NIH support for disease control. His lab's innovations include the Global Mosquito Observations Dashboard (GMOD) and VR reconstructions of prehistoric species.

İsmail ÖZTELمشاهده پروفایل

استادیار

• Artificial Intelligence
• Deep Learning
• Image Processing
• +۳ مورد دیگر

Dr. İsmail ÖZTEL serves as an Assistant Professor in the Department of Computer Engineering at Sakarya University's Faculty of Computer and Information Sciences. He has been a faculty member since 2019, following his tenure as a Research Assistant from 2012-2019 at the same institution. His educational background includes: Doctorate in Computer and Information Engineering (2014-2018) from Sakarya University with thesis on "Facial expression detection on partial and full face images using machine learning methods" Master's Degree in Computer and Information Engineering (2012-2014) from Sakarya University with thesis on "Driver simulator for educational purposes" Bachelor's Degree in Computer Engineering (2007-2011) from Sakarya University Dr. ÖZTEL's research focuses on artificial intelligence, deep learning, and computer vision with significant applications in healthcare, mobile technology, and public safety. His work has evolved from foundational facial expression recognition to sophisticated medical applications including skin disease classification using smartphones, monkeypox detection from skin lesions, and pandemic response systems for face mask detection. His research demonstrates strong interdisciplinary connections between computer science and healthcare. An analysis of his publication trends reveals a clear progression toward increasingly complex deep learning architectures applied to real-world problems, with recent work emphasizing medical applications using mobile technology and public health safety systems. His 2023-2025 publications show particular focus on skin disease classification, intelligent vehicle systems, and hybrid feature extraction methods for pandemic response. Dr. ÖZTEL has served as a reviewer for numerous prestigious journals including Expert Systems With Applications (multiple years), World Wide Web, Multimedia Tools and Applications, and Journal of King Saud University - Computer and Information Sciences, demonstrating his recognition in the academic community across multiple domains. His research projects include work on facial expression detection in open scientific databases (2020), performance evaluation of transfer learning approaches (2019), and current projects on brain tumor classification systems and earthquake safety education for individuals with developmental disabilities. His international research experience includes collaboration with Filiz Bunyak in 2017, indicating global engagement in his field.

• Autonomous Driving
• Digital Twin
• Human-Machine Interaction
• +۳ مورد دیگر

Ziran Wang is an Assistant Professor in the Department of Civil Engineering at Purdue University's College of Engineering, appointed as new faculty in 2022. His research bridges digital twin technologies, autonomous driving systems, and human-machine interaction to advance intelligent transportation solutions. Ph.D. in Mechanical Engineering, University of California, Riverside Prior role: Principal Researcher at Toyota North America His work focuses on creating personalized autonomous driving experiences through machine learning, emphasizing safety and efficiency in real-world applications. Key areas include multimodal large language model integration, federated learning for privacy-preserving data sharing, and cooperative perception frameworks. He develops novel approaches for digital twin-based traffic simulation, medical emergency detection in vehicles, and human behavior modeling in complex urban environments. Analysis of his 2024-2025 publications reveals a dominant trend toward generative AI applications in autonomous driving, particularly for perception-prediction-planning integration and real-world validation. His research increasingly incorporates digital twins for safety-critical testing and explores medical applications through in-vehicle health monitoring systems. Dr. Wang advises graduate students including Wenhui Huang and leads the Purdue Digital Twin Lab, which develops advanced simulation and testing platforms for autonomous systems. His lab maintains strong industry partnerships with Toyota for real-world deployment and validation of research成果.

Michael Wiklundمشاهده پروفایل

استاد

• Human Factors Engineering
• Medical Device Design
• Usability Testing
• +۳ مورد دیگر

Michael Wiklund is a current Professor of the Practice in the Department of Mechanical Engineering at Tufts University School of Engineering . He has been in this role since 2014, previously serving as a Lecturer from 1987 to 2013. His work focuses on Human Factors Engineering , Medical Device Design , and Usability Testing in healthcare contexts. His research spans decades, emphasizing ergonomics , software user interfaces , and safety in medical systems . He has authored key publications including books and articles on usability engineering , root cause analysis , and design principles for medical technology. Wiklund teaches courses such as Medical Technology Development and Human Factors in Medical Technology , with a focus on Biomedical Engineering and Mechanical Engineering . His recent publications highlight trends in medical device innovation , user-centered design , and health IT integration. He also serves as General Manager - Human Factors Research & Design at UL since 2012.

Ragib Hasanمشاهده پروفایل

استاد

• Cybersecurity
• Cloud Security
• Internet of Things (IoT) Security
• +۸ مورد دیگر

Ragib Hasan is a Professor in the Department of Computer Science at the University of Alabama at Birmingham (UAB), affiliated with the College of Arts and Sciences. His research focuses on cybersecurity, with specialties in cloud security, IoT systems, digital forensics, and biomedical device security. He leads the Secure and Trustworthy Computing Lab (SECRETLab) and contributes to the UAB Center for Cyber Security and NIST Cloud Forensics Working Group. Education: M.S. and Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign, followed by a postdoctoral fellowship at Johns Hopkins University. Affiliations: NIST Cloud Forensics Working Group, UAB Center for Cyber Security. His research addresses threats in smart cities, autonomous vehicles, and healthcare technologies. Key interests include securing IoT networks, mitigating cyberattacks on critical infrastructure, and advancing forensic methodologies in cloud environments. Recent work emphasizes threat modeling for connected vehicles, medical devices, and AI-driven systems. Dr. Hasan’s funding comes from the Department of Homeland Security, NSF, ONR, and industry partners like Facebook, Google, and Amazon. His awards include the NSF CAREER Award (2014), Google RISE Award (2013), and Deutsche-Welle Best of Blogs (2014) for his BanglaBraille initiative. Grants & Projects: Supported by DHS, NSF, and corporate collaborations. Outreach: Founded Wikimedia Bangladesh, Shikkhok.com (STEM education platform), and contributed to Bangla and English Wikipedia. His lab develops frameworks like StreetBit for pedestrian safety and InSight for emergency alert systems, integrating Bluetooth beacon technology to enhance urban security and sustainability.

Shoshana R. Sheltonمشاهده پروفایل

استاد

• Program Evaluation
• Performance Measurement
• Public Health
• +۱۲ مورد دیگر

Shoshana R. Shelton is a Professor at the RAND School of Public Policy and a Policy Researcher at the RAND Corporation. Her work centers on program evaluation, public health systems, emergency preparedness, and national health security, with significant contributions to pandemic response, violence prevention, and crisis decision-making. She has led major projects for federal agencies including the CDC, DHS, FEMA, and the U.S. Secret Service. Education: M.P.H., The Ohio State University B.A. in English, Denison University Her research focuses on strengthening public health infrastructure through performance measurement, logic modeling, and stakeholder engagement. She has developed tools such as tabletop exercises for continuity of operations in public health laboratories and led after-action reviews of the public health response to COVID-19. Her work emphasizes building resilience against biological threats, natural disasters, and targeted violence. Shelton's recent publications highlight trends in emergency alert systems, disaster resilience, criminal justice reform during pandemics, and equitable health security research investment. She advocates for evidence-based policies that balance bioterrorism preparedness with responses to natural disasters and climate-related emergencies. Scientific Awards: No awards listed in the provided text. She has advised or collaborated with numerous federal and state agencies, contributing to national health security through rigorous evaluation and policy analysis. Her grants and projects reflect sustained funding from DHS, CDC, and other federal bodies focused on improving public safety and health system readiness. She has also led initiatives on behavioral threat assessment in schools and wearable technology for law enforcement wellness. Labs and Teams: Previously led a four-year project on mass attacks and targeted violence for the U.S. Secret Service. Collaborated with the Association of Public Health Laboratories (APHL) on continuity of operations planning. Contributed to the Priority Criminal Justice Needs Initiative, fostering innovation across law enforcement, courts, and corrections.

Richard Allenمشاهده پروفایل

استاد

• Seismology
• Earthquake Early Warning Systems
• Structural Health Monitoring
• +۹ مورد دیگر

Richard Allen is a Professor and the Class of 1954 Endowed Chair at the University of California, Berkeley, serving as Director of the Berkeley Seismological Laboratory. His work focuses on seismology, earthquake early warning systems, and seismic hazard mitigation. Research interests include earthquake rupture mechanisms, regional seismic structure and dynamics, mantle upwelling processes, fault interaction analysis, stress modeling in seismology, and machine learning applications in seismic data analysis. He pioneered smartphone-based seismic networks like MyShake and advanced technologies such as distributed acoustic sensing (DAS) for offshore monitoring. His recent publications highlight trends in earthquake early warning algorithms (EPIC, bEPIC), real-time ground-motion modeling, ShakeAlert system performance, and integration of multimodal data (e.g., social media, LLMs, DAS) for hazard mitigation. Collaborative efforts include global smartphone networks and cloud computing for seismic datasets. Allen leads the Berkeley Seismological Laboratory, driving innovations in seismic monitoring, structural health assessment, and public alerting systems to enhance disaster resilience.

• Artificial Intelligence
• Healthcare Informatics
• Data Science
• +۵ مورد دیگر

Luís B. Elvas is an Assistant Professor at ISCTE-University Institute of Lisbon's Department of Social and Business Sciences (SINTRA) and a Research Assistant at ISTAR-Iscte Research Center. He holds qualifications including a Technical Specialization in TensorFlow for AI (Coursera, 2021) and certifications in IoT/Blockchain from ISCTE and cybersecurity from Palo Alto Networks. His research spans artificial intelligence, healthcare informatics, smart cities, and blockchain, with applied work in medical imaging, data sharing, and urban analytics. Research interests include: Healthcare AI : Developing deep learning models for cardiac diagnostics, medical imaging analysis, and blockchain-based health data systems Smart Cities : Implementing IoT solutions for urban mobility optimization, disaster management, and sustainable transportation Data Science : Creating predictive analytics frameworks for clinical decision support and urban planning His publications demonstrate a strong focus on AI-driven healthcare solutions (67% of recent works) and smart city technologies (33%), with emerging interests in blockchain and NLP. Research consistently targets real-world applications in clinical settings and urban environments. Awards: Award for best internship, Order of Engineers (2022) Distinction for best internship, Order of Engineers (2021) He leads/contributes to multiple EU research consortia including AMR-EDUCare (antimicrobial resistance education), NEEM (e-health in Nepal), and Blockchain.PT. Coordinates the IEEE Computational Intelligence Society Student Branch Chapter at ISCTE and developed the ManagiDiTH master's program in digital health transformation.

Thierry Badardمشاهده پروفایل

دانشیار

• Geospatial Big Data
• GeoAI
• GeoNLP
• +۹ مورد دیگر

Thierry Badard is an Associate Professor at the Department of Geomatics Sciences , Université Laval, where he also serves as Director of the Center for Research in Geospatial Data and Intelligence (CRDIG) . With over 28 years of experience in geospatial science, he leads research initiatives at the intersection of GeoAI , LiDAR processing , and smart city technologies . Director, CRDIG (2016-2022) Steering Committee Member, Big Data Research Centre (CRDM) Researcher, Institute for Intelligence and Data (IID) Research Expertise spans geospatial big data, GeoNLP, and IoT applications for digital twins. His work addresses flood risk modeling , 3D urban analytics , and environmental monitoring through AI-driven solutions. Recent publications focus on contrastive learning for LiDAR segmentation and geospatial ontologies for early warning systems. Grant Leadership includes collaborative projects on smart insurance analytics (2018-2025), Arctic bioaerosol research (2019-2025), and Quebec-Morocco digital twin partnerships (2022-2023). He has advised 15+ graduate students in geomatics and related fields.

Pradeep Lallمشاهده پروفایل

استاد

• Flexible Hybrid Electronics
• Harsh Environment Electronics
• Semiconductor Packaging
• +۷ مورد دیگر

Pradeep Lall is the MacFarlane Endowed Distinguished Professor and Alumni Professor in the Department of Mechanical Engineering at Auburn University’s Samuel Ginn College of Engineering. He serves as Director of the Auburn University Electronics Packaging Research Institute (EPRI) and holds a joint courtesy appointment in the Department of Electrical and Computer Engineering. A leader in flexible hybrid electronics and harsh environment systems, Dr. Lall has built a world-renowned research program focused on additive manufacturing, electronics reliability, and sustainable materials. Ph.D. in Mechanical Engineering, University of Maryland M.B.A. in Finance and Strategy, Northwestern University M.S. in Mechanical Engineering, University of Maryland B.E. in Mechanical Engineering, Delhi College of Engineering Dr. Lall’s research centers on Flexible Hybrid Electronics (FHE) , Harsh Environment Electronics , Semiconductor Packaging , and Prognostics Health Management . His work leverages additive manufacturing techniques such as Aerosol-Jet, InkJet, and screen printing to develop conformal, robust, and sustainable electronic systems. His innovations include the Flexible Biometric Band for monitoring workers in hazardous environments and additively printed antennas for aerospace applications. His recent focus includes eliminating PFAS from electronics and developing water-based inks for eco-friendly manufacturing. The 15 most recent publications reflect a strong trend toward sustainability , additive manufacturing , and real-world applications in defense, aerospace, automotive, and healthcare. His work bridges fundamental research with industrial realization, particularly through partnerships with NextFlex and federal agencies. Themes include reliability under shock and vibration, sensor development for extreme environments, and workforce training in advanced manufacturing. Dr. Lall has received numerous scientific honors, including: SMTA Founder’s Award (2024) SEMI FlexTech R&D Achievements Award (2023) ASME Avram Bar-Cohen Memorial Medal (2022) IEEE Biedenbach Outstanding Engineering Educator Award (2020) IEEE Sustained Technical Contributions Award (2018) NSF Alex Schwarzkopf Prize (2016) Fellow of ASME, IEEE, NextFlex, and Alabama Academy of Science Dr. Lall has secured over $2 million in annual research funding from SRC, NSF, and NextFlex, leading large-scale projects on sustainable electronics and workforce development. He mentors numerous graduate and undergraduate students and leads the NSF-CAVE3 Center. As founding faculty advisor of the SMTA student chapter, he promotes student engagement in electronics manufacturing. His lab, EPRI, features a full prototyping line for additive electronics and collaborates with industry and government to advance domestic manufacturing capabilities. EPRI, under Dr. Lall’s leadership, partners with the Auburn University Research and Technology Park, the Office of Economic Development, and multiple colleges to drive technology commercialization and workforce education in electronic packaging. The institute is at the forefront of the national effort to reestablish U.S. leadership in semiconductor packaging and advanced electronics manufacturing.

John E. Taylorمشاهده پروفایل

استاد

• Smart City Digital Twins
• Urban Infrastructure Resilience
• Network Dynamics
• +۵ مورد دیگر

John E. Taylor is the Frederick Law Olmsted Professor and Associate Chair for Faculty Development and Research Innovation at the Georgia Institute of Technology's School of Civil and Environmental Engineering within the College of Engineering. His research focuses on the intersection of human and engineered networks, with particular emphasis on creating resilient infrastructure systems that serve society's needs while creating more livable communities. Taylor's research interests span multiple domains including Smart City Digital Twins , Urban Infrastructure Resilience , Network Dynamics , and Building-Occupant Interaction . His work examines how human behavior, infrastructure systems, and environmental factors interact during normal operations and extreme events. He has developed innovative approaches to understanding urban systems through the lens of network theory and computational modeling. His publication record demonstrates consistent contributions to the fields of urban analytics and infrastructure resilience, with a recent focus on digital twin technologies for urban systems. Taylor's work shows a clear trajectory toward increasingly sophisticated integration of AI, network science, and civil infrastructure engineering to address complex urban challenges. His research has particular relevance for cities facing climate change impacts and seeking to build more equitable and resilient communities. Taylor leads the Network Dynamics Lab at Georgia Tech, where he mentors PhD students and postdoctoral researchers. His lab has produced significant work on human-infrastructure interaction, particularly during disasters and extreme events. The lab's research combines computational modeling, data analytics, and field studies to understand and improve urban systems. His work has been applied to real-world challenges including river emergency response systems, urban heat exposure forecasting, and disaster response optimization. Taylor has collaborated with city officials and agencies to implement systems that have demonstrable community benefits, such as the AI-enabled camera system for drowning prevention on the Chattahoochee River and crime reduction systems using mobile cameras guided by AI algorithms.

• Data Science
• Artificial Intelligence
• Machine Learning
• +۱۰ مورد دیگر

Professor Zoheir Sabeur is Professor of Data Science and Artificial Intelligence at Bournemouth University (2019–present) and Head of the Processes and Behaviour Understanding (PRO_BU) Research Group. He concurrently serves as Visiting Professor of Data Science at Colorado School of Mines (2017–present) and held the position of Science Director at the IT Innovation Centre, University of Southampton (2009–2019). Over three decades he has led more than 30 large-scale projects as Principal Investigator, securing over £12 million of funding from the European Commission, UKRI, DSTL, NERC, EPSRC and industry. Education PhD in Theoretical Physics, University of Glasgow (1990) MSc in Theoretical Physics, University of Glasgow (1986) BSc First-Class Honours in Physics and Applied Mathematics, Université d'Oran (1984) Advanced Leadership Programme, Ashridge Business School (2011) Research Interests Professor Sabeur’s research focuses on the fundamental theory and application of data science and artificial intelligence to understand complex human, natural and industrial processes and behaviours. His work spans multi-modal sensing, big-data analytics and machine-learning algorithms that extract actionable knowledge from large heterogeneous datasets. Application domains include: Healthcare: AI-driven diagnostics and prognostics for chronic diseases such as COPD, asthma and cancers through omics and phenotypic data integration. Environmental & Climate: Earth-observation analytics for wildlife migration and climate-change impact assessment using satellite data and global grid systems. Maritime & Cyber-Physical Security: Real-time risk assessment for shipping in extreme environments, smart-city safety and critical-infrastructure protection using computer vision and sensor fusion. Recent research has produced novel AI classifiers that analyse lung-auscultation audio signals to grade COPD severity, as well as digital-twin frameworks for detecting malicious behaviour in urban spaces. Scientific Awards & Recognition Fellow of the British Computer Society (FBCS) Fellow of the Institute of Marine Engineering, Science & Technology (FIMarEST) Chartered Engineer (CEng) and Chartered Physicist (CPhys) Multiple ORS Awards (1987, 1988, 1989) Grants & Doctoral Supervision Professor Sabeur has secured and led more than 40 funded projects since 1996, including recent grants such as INSIGHT (NIHR, 2024) and S4AllCities (H2020, 2020). He currently supervises three ongoing PhD students at Bournemouth University and has successfully graduated three others, covering topics from computational hydrodynamics to AI-based respiratory-disease analytics. He welcomes enquiries from prospective postgraduate researchers interested in data science, AI and interdisciplinary applications under schemes such as UKRI and Horizon Europe.

Amany Faragمشاهده پروفایل

دانشیار

• Patient Safety
• Medication Safety
• Nurse Fatigue
• +۴ مورد دیگر

Amany Farag is a tenured Associate Professor at the University of Iowa College of Nursing and Co-Director of the VA Quality Scholars Program (Iowa City site). Her work bridges nursing science, human factors engineering, and data science to address critical patient safety challenges, with a specific focus on medication administration practices across healthcare settings. Education: Postdoctoral Scholar, Case Western Reserve University, Frances Payne Bolton School of Nursing PhD, Case Western Reserve University, Frances Payne Bolton School of Nursing MSN, University of Alexandria, Alexandria Egypt BSN, University of Alexandria, Alexandria Egypt Dr. Farag's research centers on reactive and proactive approaches to patient safety , with dual emphasis on medication error reporting systems and nurse fatigue prevention. Her work integrates human factors engineering and machine learning to develop novel interventions. Key themes include understanding how social and system factors influence nurses' error reporting behaviors, examining fatigue as a precursor to errors, and developing self-management strategies for nurse wellness. Recent projects explore intershift recovery, sleep hygiene using consumer technology, and the impact of shift work on cognitive performance. Publication trends reveal a strong focus on interdisciplinary safety science , with consistent output in nursing, human factors, and healthcare quality journals. Her work increasingly incorporates AI methodologies while maintaining clinical relevance to frontline nursing practice. Scientific Recognition: Mary Hanna Memorial Journalism Award (Journal of Peri-Anesthesia Nursing, 2016) Author of the Year (Journal of Emergency Medicine, 2018) Junior Investigator Award (Midwest Nursing Research Society, 2018) Rogers Endowed Lectureship Award (Mississippi Medical Center, 2018) Dr. Farag secures significant funding from national agencies including the National Council of State Boards of Nursing (NCSBN), NIOSH-funded Healthier Workforce Center of the Midwest, CDC-funded Injury Prevention Research Center, and University of Iowa Institute for Clinical and Translational Science. Her collaborative approach spans nursing, data science, ergonomics, and public health teams. As Co-Director of the VA Quality Scholars Program, she mentors future healthcare quality leaders while advancing her research on medication safety systems and nurse fatigue mitigation strategies through interdisciplinary partnerships.

Erik Prytzمشاهده پروفایل

عضو هیئت علمی

• Human Factors
• Emergency Response Systems
• Stress Management
• +۳ مورد دیگر

Erik Prytz is a Senior Associate Professor in Cognitive Science at the Department of Computer and Information Science (IDA) at Linköping University. His research focuses on applying human factors principles to improve safety-critical systems, particularly in emergency response domains such as first aid, disaster medicine, and prehospital care. He holds a PhD in Human Factors Psychology and has served in roles including Director of the Forum Securitatis graduate school and Program Chair for the Cognitive Science BSc program. Education: PhD in Human Factors Psychology (Old Dominion University, 2014), MSc in Cognitive Science (LiU, 2010). Research Interests: Simulation-based training, stress and mental workload, emergency responder teamwork, and human-system interaction in crisis scenarios. His work emphasizes interdisciplinary collaboration, combining cognitive science, computer science, and medicine to enhance emergency response systems. Recent projects explore driver behavior toward emergency vehicles, ad-hoc responder group dynamics, and optimal placement of bleeding control kits in public spaces. He contributes to initiatives like the Center for Advanced Research in Emergency Response (CARER) and the Forum Securitatis graduate school. Erik’s teaching includes courses on human factors, distributed cognition, and emergency response systems. He actively participates in curriculum development and quality assurance committees within the Faculty of Arts and Sciences.