جست‌وجوی استاد و پژوهشگر

• Applied Statistics
• Optimization
• Data Visualization
• +۷ مورد دیگر

Zhongyuan (Annie) Yu is a Teaching Associate Professor in the Department of Systems and Enterprises at Stevens Institute of Technology. She holds a PhD in Systems Engineering (2014), and two MS degrees in Operations Research (2012) and Industrial Engineering (2010), both from Georgia Institute of Technology. Her research bridges applied statistics, optimization, data visualization, and socio-economic systems analysis. Key focus areas include healthcare systems engineering, defense acquisitions, and interactive decision support systems. She leads software engineering education initiatives, including serving as Program Director for the Software Engineering Program (2022-2024). Yu has secured major grants from DoD DASD(SE) and NIH, focusing on mega-project management, digital engineering integration, and healthcare policy simulations. Her 2023-2024 research explores HIPAA compliance challenges in software engineering and patient trust in electronic health records. Her publications span health informatics, portfolio optimization networks, and systems engineering methodology. Notable works include developing policy flight simulators for healthcare interventions and semantic integration frameworks for digital engineering interoperability. Teaching responsibilities include courses like Agile Methods for Software Development, Data Analysis & Visualization, and Engineering Economics. She advises capstone projects and maintains active roles in curriculum development for systems and software engineering programs.

Lane Harrisonمشاهده پروفایل

دانشیار

• Information Visualization
• Visual Analytics
• Human-Computer Interaction
• +۳ مورد دیگر

Lane Harrison is an Associate Professor in the Department of Computer Science at Worcester Polytechnic Institute (WPI), where he directs the Visualization and Information Equity lab (VIEW). His research leverages cognitive and perceptual principles to improve information visualization and visual analytics systems, with critical applications in cybersecurity and health-risk communication for high-stakes decision-making. His educational background includes a BS (2009) and PhD (2013) in Computer Science from the University of North Carolina, Charlotte. Prior to WPI, he was a Postdoctoral Researcher at Tufts University's Visual Analytics Lab. Harrison's research focuses on empirical evaluation of visualization techniques , investigating how cognitive principles can optimize user performance with visual representations. He develops design guidelines for effective visualizations in domains like cybersecurity and healthcare, while creating adaptive systems that integrate models of user abilities. His work bridges theoretical foundations with practical applications to address real-world challenges in data interpretation. Analysis of his 2016-2021 publications reveals consistent emphasis on user-centered evaluation methodologies , including crowdsourcing and controlled experiments. Key trends include quantifying exploration behaviors in web visualizations, addressing cognitive biases in data reproduction, and developing healthcare-focused analytics for drug interactions and risk communication. His research demonstrates strong interdisciplinary connections between visualization, cognitive science, and domain-specific applications. His scientific recognition includes: Best Paper Award at ACM CHI 2016 for adaptive interface research Harrison secures significant research funding including an NSF Grant (2022) for visualization studies and participates in an 11-school AI collaboration for intelligence professionals (2025). He teaches data visualization and web programming courses, mentoring students through the VIEW lab on projects applying visualization techniques to social issues and scientific domains. He directs the VIEW lab at WPI, which develops computational methods to understand how people engage with data visualizations while emphasizing equitable information access. Current projects integrate user modeling with visualization systems to optimize design for diverse cognitive abilities and application contexts.

Thais Webberمشاهده پروفایل

مدرس

• Healthcare Systems
• Cybersecurity
• User Authentication
• +۳ مورد دیگر

Thais Webber is a Lecturer in Software Engineering and Cybersecurity at Aston University's School of Computer Science and Digital Technologies. Her research focuses on developing secure, user-centered healthcare systems through participatory approaches and longitudinal studies. Recent work explores personalized authentication paradigms, non-invasive diagnostic technologies for conditions like endometriosis, and simulations of healthcare resource allocation during disruptions. Her publications demonstrate strong interdisciplinary collaboration, bridging computer science with clinical healthcare challenges. Methodologies include statistical modeling, system verification, and stakeholder engagement frameworks to address vulnerabilities in medical data systems and improve care delivery efficiency.

Rui Daiمشاهده پروفایل

دانشیار

• Wireless Sensor Networks
• Multimedia Communications
• Video Analytics
• +۲ مورد دیگر

Dr. Rui Dai is an Associate Professor in the Department of Computer Science at the University of Cincinnati's College of Engineering and Applied Science. Her research focuses on wireless sensor networks, multimedia communications, and video analytics for healthcare and surveillance applications. She directs multiple NSF and NIST-funded projects on perceptual-quality-aware video systems. Research interests include quality-of-experience optimization for video analytics, compressed domain feature extraction, and edge computing frameworks for intelligent surveillance. Recent work develops deep feature compression techniques, multi-camera fall detection systems, and quality-aware video distribution strategies for 5G networks. Publications demonstrate consistent innovation in video processing for resource-constrained environments, with applications spanning healthcare monitoring, public safety networks, and embedded vision systems. Current projects investigate metaverse communication challenges for 6G networks and PHP vulnerability detection through hybrid static-fuzzing analysis.

Mikael Eklundمشاهده پروفایل

استاد

• Autonomous Systems
• Nonlinear System Identification and Control
• Health Informatics
• +۳ مورد دیگر

Dr. Mikael Eklund is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, within the Faculty of Engineering and Applied Science. He holds a PhD (2003), MSc (1996), and BSc (1989) in Electrical and Computer Engineering from Queen’s University. His research focuses on Autonomous Systems , Nonlinear System Identification and Control , Health Informatics , and Pervasive and Mobile Computing . He has expertise in medical image processing, robotic vehicles, and smart sensors for assisted living. Education and Work Experience : - PhD (Electrical and Computer Engineering), Queen’s University (2003) - MSc and BSc from Queen’s University (1996, 1989) - Visiting Postdoctoral Scholar at UC Berkeley (2003–2006) - Adjunct Assistant Professor at Queen’s University (2003) - Former Teaching Fellow at Queen’s University (1996–2001) - Industrial experience in flight control system engineering (CAE Inc., 1989–1996) Research Contributions : - Developed SensorNet, a wireless infrastructure for assisted living. - Advanced methods for nonlinear system identification in chemical processes and aerospace systems. - Pioneered real-time UAV safety protocols and model predictive control algorithms for aerial pursuit-evasion games. - Explored EMG signal processing for hand force estimation and MEG signal source localization in neuroscience. Teaching and Outreach : - Teaches courses like Medical Image Processing and Electric Circuits. - Active in interdisciplinary projects like the ITALH initiative for elder tech integration. - Presented at conferences such as IEEE EMBC, ACC, and CDC, emphasizing healthcare IT and autonomous systems.

Timothy Verstynenمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Cognitive Science
• Computational Neuroscience
• +۱ مورد دیگر

Timothy Verstynen is a Professor of Psychology and Neuroscience Institute at Carnegie Mellon University, affiliated with the Dietrich College of Humanities and Social Sciences. His research focuses on cognitive neuroscience, cognitive science, computational modeling, and learning science. He investigates how neural pathways regulate action planning, skill learning dynamics, and structure-function relationships in the brain. His work integrates psychophysics, computational models, and neuroimaging techniques (fMRI, TMS, diffusion imaging). Key research themes include: 1) Action selection and stopping mechanisms under sensory input; 2) Neurobiological bases of skill acquisition timelines; 3) White matter architecture's role in cognitive functions. Recent studies explore links between brain structure, cardiovascular health, and decision-making processes using multimodal imaging and machine learning. Notable publications address cortico-basal ganglia-thalamic circuits' role in decision policies, stress-brain connectivity, and reward-based learning. His CoAx Lab develops tools like CBGTPy for modeling decision-making systems. Research spans neuroimaging methodological advancements (e.g., local connectome fingerprinting) and translational health neuroscience projects.

Milica Miočevićمشاهده پروفایل

دانشیار

• Quantitative Psychology
• Statistical Mediation Analysis
• Bayesian Methods
• +۳ مورد دیگر

Milica Miočević is an Associate Professor in the Department of Psychology at McGill University. She previously held an Assistant Professor position at Utrecht University's Department of Methods and Statistics. Her research focuses on statistical mediation analysis and Bayesian methods applied to social, health, and behavioral sciences, with three main research lines: optimal methods for Bayesian mediation priors, synthesizing mediated effect findings across studies, and mediation analysis in Single Case Experimental Designs (SCEDs). Dr. Miočević earned her Ph.D. from Arizona State University under advisors Dave MacKinnon and Roy Levy. Her work emphasizes methodological innovation in small sample contexts and evidence synthesis. The Miocevic Lab at McGill explores quantitative psychology and modeling techniques. Her recent publications span Bayesian vs frequentist estimation comparisons, prior distribution development, and mediation analysis methodologies. She has contributed to edited volumes on small sample solutions and published extensively in Structural Equation Modeling journals. Dr. Miočević's research bridges statistical theory and applied practice, advancing tools for researchers working with complex data structures and limited sample sizes.

Mark Wealمشاهده پروفایل

استاد

• Digital Health
• Behavioral Interventions
• Semantic Web
• +۲ مورد دیگر

Professor Mark Weal is a faculty member in the Department of Electronics and Computer Science at the University of Southampton. He holds roles as Co-Director of the Web Science Institute, Director of the Centre for Doctoral Training in Web Science Innovation, and Web Science Trust Fellow. His research focuses on digital health interventions, behavioral change technologies, and semantic web applications. Notably, he co-leads the LifeGuide project, a £45M initiative developing online health interventions for conditions like diabetes, cancer, and respiratory illnesses. Research interests include social media analytics for disaster management, semantic web infrastructures, and information systems design. He has supervised multiple PhD students in web science and digital health domains. Professor Weal has received significant grant funding from bodies like MRC, EPSRC, and the European Commission. Key achievements include over 45 million pounds in research funding and leadership in interdisciplinary projects. His work spans technical innovation and societal impact, addressing challenges in healthcare accessibility and digital infrastructure governance.

Yeqing Kongمشاهده پروفایل

استادیار

• Technical Communication
• Risk/Crisis Communication
• Cross-cultural Communication
• +۵ مورد دیگر

Yeqing Kong is an Assistant Professor of Technical Communication at Georgia Institute of Technology’s School of Literature, Media, and Communication (Ivan Allen College of Liberal Arts). Her research focuses on transnational risk communication, AI-assisted technologies, and social justice in communication. She holds a Ph.D. in Communication, Rhetoric, and Digital Media from North Carolina State University (2017-2021), an M.A. in Language and Linguistics from Lancaster University (2014-2015), and a B.A. in English from Hunan University (2010-2014). Education: Ph.D. North Carolina State University | M.A. Lancaster University | B.A. Hunan University Her research interests include corpus-assisted discourse analysis, cross-cultural communication strategies for vulnerable communities, and AI ethics in recruitment technologies. Recent work explores global health communication during the pandemic and environmental justice in crises like the Flint Water Crisis. Publications span journals like IEEE Transactions on Professional Communication and ACM conferences, focusing on technical communication, crisis management, and digital rhetoric. Her work emphasizes participatory approaches to promote equitable communication practices. Awards : Over $40,000 in grants (2017-2024), including IAC SODA Award, ACM SIGDOC grants, and HASTAC Scholar recognition. Grants and projects include AI-assisted recruiting tools and pedagogical initiatives like the Information Literacy Faculty Fellowship. She advises on technical writing pedagogy and health communication strategies, with ongoing collaborations in global media studies.

Javier Irizarryمشاهده پروفایل

استاد

• Unmanned Aerial Systems (Drones) in Construction
• Construction 4.0
• Reality Capture Technology
• +۳ مورد دیگر

Javier Irizarry is a Professor and Interim Chair in the School of Building Construction at Georgia Tech's College of Design. He also serves as Associate Dean for Academic Affairs and Outreach , overseeing academic programs, diversity initiatives, and recruitment efforts. As Director of the CONECTech Lab, he pioneers research in Construction 4.0 and UAV applications for infrastructure challenges. Education : Ph.D. (Civil Engineering), Purdue University Masters in Engineering Management, Polytechnic University of Puerto Rico B.S. (Civil Engineering), University of Puerto Rico, Mayagüez Research Focus : Irizarry’s work integrates cutting-edge technologies into construction, including Unmanned Aerial Systems (UAS), Reality Capture, Virtual/Augmented Reality, and Human Factors in Robotics. His lab develops frameworks for Construction 4.0 , emphasizing technology-driven solutions for safety and efficiency. Lab & Impact : The CONECTech Lab focuses on Construction 4.0 , advancing drone-based inspection systems, digital twins, and safety analytics. His research has led to over 100 publications, with applications in infrastructure monitoring, safety management, and educational tools. Leadership : As Associate Dean, Irizarry drives academic innovation and outreach, including pre-college programs and diversity strategies. He is a licensed Professional Engineer (PE) and FAA-licensed drone pilot, bridging academia and industry.

Inga Prokopenkoمشاهده پروفایل

استاد

• Genetic Epidemiology
• Multi-Omics Analysis
• Type 2 Diabetes
• +۵ مورد دیگر

Professor Inga Prokopenko is a faculty member at the University of Surrey's School of Biosciences (Faculty of Health and Medical Sciences), specializing in e-One Health and leading the Statistical Multi-Omics group. Her research focuses on genetic epidemiology, multi-omics approaches, and the comorbidity between metabolic disorders like type 2 diabetes and conditions such as cardiovascular disease, cancer, and mental health disorders. She leads studies on genetic determinants of blood glucose regulation, obesity-related risks, and shared pathophysiological pathways between diseases. Key research areas include: Genetic links between type 2 diabetes and cancers (breast, pancreatic, etc.) Mechanisms of GLP-1 receptor signaling in diabetes treatment Causal relationships between depression and diabetes using Mendelian randomization Role of abdominal obesity in cancer susceptibility She supervises PhD/MSc students in biosciences and medicine programs and develops computational tools like comorbidPRS for polygenic risk score analysis. Her work integrates large-scale genomic data from cohorts like the UK Biobank and EPIC studies to uncover shared genetic mechanisms across diseases. Recent work highlights include: Systematic reviews on flavan-3-ols and cardiovascular health Meta-analyses of trans-ethnic diabetes GWAS data Epigenetic studies linking blood metabolites to cancer risk Her research bridges statistical genetics with clinical applications, emphasizing precision medicine strategies for complex diseases.

Carlos Cámara-Menoyoمشاهده پروفایل

مدرس

• Urban Studies
• Open Science
• Urban Commons
• +۳ مورد دیگر

Carlos Cámara-Menoyo is a Senior Research Software Engineer at the University of Warwick's Centre for Interdisciplinary Methodologies, where he bridges technical expertise with urban research. He holds a PhD in Information and Knowledge Society from the Universitat Oberta de Catalunya (2018), awarded the IND+I Science Prize. His academic roles include Lecturer at Universidad San Jorge and Associate Lecturer at Oxford Brookes University and Universitat Oberta de Catalunya. Education : PhD in Information and Knowledge Society (2018), Universitat Oberta de Catalunya MSc in Information and Knowledge Society (2012), Universitat Oberta de Catalunya MSc Architecture (2004), Universitat Politècnica de Catalunya Research Interests : Urban Studies, Open Science, Spatial Justice, Data Visualization, and Urban Commons. His work explores commodifications between cities, technology, and society, focusing on equitable urban development and participatory methods. Articles : His recent work addresses the Food-Water-Energy Nexus, participatory urban governance, and inclusive GIS applications. Key themes include sustainability transformations and co-design processes. Awards : IND+I Science Prize (2018), Cum Laude PhD distinction. Advising & Grants : Supervised Master’s theses on urban commons and co-production. Active in collaborative projects like Zaragoza Accesible and the Creating Interfaces initiative. Labs & Teams : Leads research software engineering efforts at CIM, promoting open science and reproducible workflows.

Danyu Linمشاهده پروفایل

استاد

• Statistical Genetics
• Genetic Epidemiology
• Bioinformatics
• +۴ مورد دیگر

Danyu Lin is the Dennis Gillings Distinguished Professor of Biostatistics at the University of North Carolina at Chapel Hill. He is affiliated with the Lineberger Comprehensive Cancer Center and the Center for AIDS Research. His research focuses on statistical methods for biomedical studies, including survival analysis, statistical genetics, and genetic epidemiology. Dr. Lin has published over 200 peer-reviewed articles in leading journals and developed methods incorporated into commercial software. Education: PhD, Biostatistics, University of Michigan, 1989 MS, Biostatistics, University of Michigan, 1986 Research Interests: Dr. Lin’s work spans statistical genetics (GWAS, sequencing studies), survival analysis methodologies, longitudinal data analysis, and design optimization for medical studies. He emphasizes applications in cancer, AIDS, cardiovascular diseases, and psychiatric research. Awards: COPSS George W. Snedecor Award (2019) ICSA Distinguished Achievement Award (2015) Mortimer Spiegelman Award (1999) Fellowships: ASA (2000), IMS (1999) Service & Leadership: Dr. Lin has held editorial roles at Biometrika , JASA , and Statistica Sinica . He served on NIH study sections, DSMB committees, and advisory boards for institutions like the Fred Hutchinson Cancer Research Center. He chairs multiple search and promotion committees within the Gillings School. Labs/Teams: Leads statistical methodology development for large-scale biomedical studies, particularly in genetic epidemiology and vaccine efficacy analysis (e.g., SARS-CoV-2 research).

Damian Smedleyمشاهده پروفایل

استاد

• Computational Genomics
• Genotype-Phenotype Analysis
• Rare Disease Genetics
• +۳ مورد دیگر

Professor Damian Smedley is a Professor of Computational Genomics at Queen Mary University of London, affiliated with the William Harvey Research Institute's Clinical Pharmacology and Precision Medicine department. His research focuses on integrating clinical and model organism phenotype data to elucidate human disease mechanisms, particularly through initiatives like the International Mouse Phenotyping Consortium (IMPC) and the MorPhic project. He leads the development of the Exomiser software, a critical tool for prioritizing genetic variants in rare disease diagnostics, widely used in global projects such as the UK's 100,000 Genomes Project and NHS Genomic Medicine Service. His work bridges computational biology, genetics, and clinical translation, with collaborations spanning academia and industry. Key research areas include genotype-phenotype associations, precision medicine, and federated machine learning applied to multiomics data. Funded by NIH, MRC, Horizon Europe, and Barts Charity, his team collaborates with institutions like the Berlin Institute of Health and the University of Colorado. Notable contributions include advancing diagnostic pipelines for rare diseases and understanding the role of missense variants in genetic disorders. His group's work has been featured in high-impact studies, such as identifying novel disease genes through cross-species phenotype comparisons and optimizing variant prioritization algorithms. External collaborations include Prof. Peter Robinson (Berlin) and Dr. Chris Mungall (Lawrence Berkeley Lab), reflecting his global impact in computational genomics.

Kerstin Noëlle Vokingerمشاهده پروفایل

استاد

• Regulatory Sciences
• Health Policy
• Biomedical Ethics and Law
• +۳ مورد دیگر

Prof. Kerstin Noëlle Vokinger is a double professor at the University of Zurich and ETH Zurich, holding positions in Law and Medicine. She leads the Chair for Regulation in Law, Medicine, and Technology, focusing on interdisciplinary research at the intersection of law, medicine, and technology. Her roles include advising governments and international organizations like the WHO on drug pricing, AI in healthcare, and regulatory frameworks. Education: - MD and JD from University of Zurich - PhD in Biomedical Ethics and Law (University of Zurich) - Habilitation in Medicine (University of Zurich) - LL.M. from Harvard Law School Research Interests: Vokinger's work addresses drug pricing policies, regulatory sciences, AI in healthcare, and global health equity. She has published extensively on topics such as cancer drug economics, AI medical device regulation, and WHO essential medicines policies. Her research bridges legal, medical, and technological challenges to improve access to healthcare technologies. Awards: - 2022 Swiss Science Prize Latsis (most prestigious national award for under-40 researchers) - 2021 Eccellenza Grant from Swiss National Science Foundation Grants & Advising: - Advises UN agencies, WHO, and Swiss government on pharmaceutical policy. - Funded projects include studies on gene therapy pricing, drug shortages, and AI lifecycle regulation. Labs & Teams: Her team at ETH and UZH combines law, medicine, and data science to tackle regulatory challenges in healthcare innovation.