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جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۱-۱۵ از ۱۹۷ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Tommaso Gabrieliمشاهده پروفایل

دانشیار

University College LondonUnited Kingdom

Dr. Tommaso Gabrieli is an Associate Professor in Real Estate at the Bartlett School of Planning, University College London (UCL), where he has been employed since September 2015. His academic career spans multiple institutions including the University of Reading, City University London, University of Warwick, and the Catholic University of Milan. His educational background includes: PhD in Economics from the University of Warwick (2009) MSc in Economics from the London School of Economics and Political Science (2003) Fellowship of the Higher Education Academy from the University of Reading (2013) As a theoretical economist trained in the ambrosian tradition of social welfare, Gabrieli's research focuses on the economic analysis of urban policy issues. His expertise encompasses economic modeling of real estate markets, financial viability of urban projects, multi-dimensional value measurements, and value-capture mechanisms. He has developed novel interdisciplinary methods bridging urban planning and design with economics, making him one of few economists actively collaborating with urban planning scholars in the UK. His work addresses Sustainable Development Goals including No Poverty, Good Health, Decent Work, Reduced Inequalities, Sustainable Cities, and Climate Action. His recent publications demonstrate a strong focus on urban design governance, value capture mechanisms, and the interface between economic theory and urban planning practice. The research spans theoretical explorations of post-growth planning and practical applications in land value recovery, particularly examining implications for housing affordability, wealth distribution, and community wellbeing in both urban and rural contexts. His work often integrates behavioral economics with spatial planning considerations. Professional recognition includes: Fellow of the Higher Education Academy Gabrieli has extensive experience supervising PhD and MSc dissertations across multiple institutions. His teaching portfolio includes Real Estate Appraisal and Valuation at UCL, where he leads relevant modules for both undergraduate and graduate programs. He has contributed to significant research projects including 'Street Appeal' commissioned by Transport for London and the Horizon 2020-funded 'UrbanMaestro' project worth 1 million Euros. His research impact has been formally recognized by Transport for London. Currently, he leads the 'Future Urban Growth Lab' project, funded by UCL Knowledge Exchange and Innovation Funding, in partnership with the Royal Town Planning Institute and Politecnico of Turin. This project aims to operationalize an urban growth model prototype for use by local authorities in planning future city development, bridging academic research with practical planning applications.

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Dongwook Yoonمشاهده پروفایل

دانشیار

University of British ColumbiaCanada

Dongwook Yoon is an Associate Professor at the Department of Computer Science , University of British Columbia , and serves as Director of the SOCIUS Lab . He actively contributes to research in Human-Computer Interaction, Human-AI Interaction, and Virtual/Augmented Reality as a member of the Designing for People (DFP) and CAIDA research clusters. Education : PhD in Computer Science from Cornell University (2017), MS (2009) and BS (2007) in Computer Science from Seoul National University Research Focus : Designing socio-technical systems that bridge the gap between technology and human social processes, with innovations in AR/VR, multimodal interaction, and inclusive design Article Trends show his work spans: Temporal and bichronous learning environments AI self-clones and ethical implications Income inequality in virtual platforms Enhanced multimodal collaboration in VR Eyes-reduced interfaces for situational impairments Speculative participatory design for gig economy challenges Scientific Awards include: Google Academic Research Award (2024) Best Paper Award at CHI 2024 High Impact Award in Educational Technology (2024) CHCCS/SCDHM Graphics Interface Early Career Award (2023) Multiple Honorable Mentions at CHI, DIS, and CSCW Students & Collaborators range from active PhD candidates (Anika Sayara, Yuri Kim) to notable alumni (Thitaree Tanprasert, Ashish Chopra) across his SOCIUS Lab projects. His research receives funding from NSERC , KIST , Adobe , Microsoft , and Google grants.

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Yu Xiaمشاهده پروفایل

پژوهشگر

Stockholm UniversitySweden

Yu Xia is a Post Doc at the Department of Chemistry, Stockholm University, Sweden. He is affiliated with the Tom Willhammar Research Group, focusing on advanced electron microscopy and diffraction techniques for structural characterization of materials. PhD (2019–2023) from a joint program between the University of Birmingham (UK) and the Southern University of Science and Technology (China). Research emphasizes fabrication of metallic nanoparticles with non-equilibrium structures and shapes using gas-phase condensation and thermal shock methods. Specializes in scanning transmission electron microscopy (STEM), in-situ heating experiments, and electron energy loss spectroscopy (EELS) for nanoparticle analysis. Current work prioritizes 4DSTEM imaging for electron beam-sensitive materials and Python-based post-processing of electron microscopy datasets. Yu Xia's research spans Materials Science , Nanotechnology , and Electrocatalysis , with applications in photocatalytic hydrogen evolution , graphene composites , and advanced electron microscopy techniques . His work often integrates computational image processing with structural characterization to optimize material properties. Publications highlight innovations in heterostructure engineering , metallic alloy catalysts , and electron beam-sensitive material imaging . No scientific awards are explicitly mentioned in the provided text. Yu Xia's technical expertise includes Python scripting for image analysis, in-situ electron microscopy , and multifunctional graphene-based materials .

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Hui Luanمشاهده پروفایل

استادیار

University of Texas Southwestern Medical CenterUnited States

Hui Luan is an Assistant Professor in the Department of Public Health at the Peter O’Donnell Jr. School of Public Health, UT Southwestern Medical Center. He joined UT Southwestern in 2024 after serving as an Associate Professor (tenured) at the University of Oregon (2018–2024). His research focuses on spatial epidemiology, Bayesian spatiotemporal statistics, and GIS applications to address health disparities and environmental determinants of disease. Education: Ph.D. in Planning, University of Waterloo, 2017 M.S. in Cartography and GIS, Wuhan University, 2011 B.S. in GIS, Wuhan University, 2009 Research Interests: Dr. Luan investigates spatial and temporal variations in health outcomes, particularly HIV incidence, and the role of social, physical, and built environments. He develops Bayesian models and spatial analytics to inform geographically tailored interventions. Current projects include optimizing PrEP accessibility, analyzing food environment equity, and leveraging spatial data science for public health policy. Key Achievements: Lead investigator of an NIH-funded R01 project on reducing HIV incidence via spatial data science Editorial board member of Spatial and Spatiotemporal Epidemiology Recipient of the Vu Fellowship (2021–22) Teaching: Teaches courses on GIS in Public Health, Spatial Analysis, and Big Data applications in geography. Recent courses include GIS and Public Health and Spatial and Spatiotemporal Analysis at the University of Oregon. Labs/Teams: Leads the Spatial Data Science Lab focused on advancing Bayesian methods for health data analysis and promoting GIS applications in public health practice.

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Barak Arielمشاهده پروفایل

استاد

University of CambridgeUnited Kingdom

Barak Ariel is a Professor of Experimental Criminology at the Institute of Criminology, University of Cambridge. He holds a PhD in Criminology from Hebrew University of Jerusalem, an LLM (Hebrew University), LLB (Academic Centre of Law & Business), MA in Criminology (Hebrew University), and BA in Psychology (University of New York). Since 2008, he has been affiliated with the Jerry Lee Centre of Experimental Criminology and teaches on the MSt in Applied Criminology and Police Management. Academic Rank: Professor of Experimental Criminology Key Affiliations: University of Cambridge, Jerry Lee Centre of Experimental Criminology Education: PhD, LLM, MA, LLB, BA Dr. Ariel specializes in experimental criminology, evidence-based policing, and the role of technology in crime prevention. His research focuses on evaluating policing strategies through randomized controlled trials (RCTs), particularly in areas such as body-worn cameras, domestic abuse hotspots, and interventions to reduce violence against women. He has advised police departments and governments across the UK, USA, Latin America, and Europe. His recent publications highlight trends in global crime dynamics, the impact of police interventions on offender behavior, and the use of machine learning for crime forecasting. These works span subfields including hot spots policing, procedural justice, victim-offender overlaps, and network analysis of organized crime. Scientific Awards : Academy of Experimental Criminology Young Experimental Scholar Award European Society of Criminology Young Criminologist Award Fellow of the Division of Experimental Criminology As Chair of the Division of Experimental Criminology (2019–2021), Dr. Ariel has contributed to advancing methodological rigor in criminological research. He has conducted extensive evaluations of police-led interventions, including trials on body-worn cameras, victim communication strategies, and data-driven approaches to domestic homicide prevention. His work bridges academic research with practical policing reforms, emphasizing the importance of empirical evidence in criminal justice policy.

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Sanjay Srinivasanمشاهده پروفایل

استاد

Pennsylvania State UniversityUnited States

Sanjay Srinivasan is a Professor of Petroleum and Natural Gas Engineering and the John and Willie Leone Family Chair in the Department of Energy and Mineral Engineering at Penn State University. He serves as Director of the EMS Energy Institute and leads the Penn State Initiative for Geostatistics and GeoModeling Applications. His research focuses on petroleum reservoir characterization, CO2 sequestration, and integration of seismic data in reservoir models through advanced geostatistical and machine learning methods. Ph.D., Petroleum Engineering, Stanford University M.S., Petroleum Engineering, University of Southern California B. Tech, Petroleum Engineering, Indian School of Mines Srinivasan’s work addresses reservoir recovery processes, unconventional reservoirs, and subsurface energy security. His methodologies include probabilistic modeling, data assimilation, and AI-driven workflows for fracture network mapping and porous media generation. Key applications span Gulf of Mexico deepwater plays and geological carbon storage. Recent publications highlight trends in: Reinforcement learning for geostatistical workflows and well optimization Physics-informed GANs for 3D porous media modeling Probabilistic integration of geomechanical and geostatistical inferences Machine learning approaches for seismic fracture identification CO2 sequestration in heterogeneous reservoirs Scientific awards include Distinguished Member (SPE, 2022), SPE Faculty Pipeline Award (2012), Cox Visiting Fellowship (Stanford, 2010), and SPE Southwest Region Reservoir Description Award (2009).

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Felipe Thomazمشاهده پروفایل

دانشیار

University of OxfordUnited Kingdom

Felipe Thomaz is an Associate Professor of Marketing at Saïd Business School, University of Oxford, and Deputy Director of the Oxford Future of Marketing Initiative. He holds a PhD in Marketing from the University of Pittsburgh and previously taught at the University of South Carolina. His research focuses on marketing strategy, AI ethics, illicit markets, and ESG integration, with notable contributions to frameworks like Ad Net Zero for net-zero advertising emissions. He collaborates with UN agencies, NGOs, and tech companies to address global sustainability goals and wildlife trafficking networks. Education: PhD in Marketing (University of Pittsburgh), MSc in Marketing & Finance (University of Pittsburgh), BSc in Animal Sciences (University of Florida). Research interests include digital marketing channels, brand performance via social networks, AI-driven marketing strategies, and conservation science linked to wildlife trade. His work bridges academia and industry, resulting in spinouts and IP transfers from Saïd Business School. Key projects include: Ad Net Zero: Global standard for reducing advertising emissions UN collaboration on wildlife trafficking through dark web analysis UNESCO partnerships on eliminating stereotypes in advertising His interdisciplinary approach spans marketing, mathematics, and conservation science, with publications in top journals like Journal of Marketing and Conservation Science and Practice .

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Clinton Fookesمشاهده پروفایل

استاد

Queensland University of TechnologyAustralia

Professor Clinton Fookes is a faculty member at the Queensland University of Technology (QUT) within the School of Electrical Engineering & Robotics . His research focuses on leveraging computer vision and artificial intelligence to develop automated systems that understand, anticipate, and interact with human behaviors, with applications in medical diagnostics, autonomous vehicles, defense, and industrial efficiency . Research areas include AI adaptability, multimodal biosignal analysis, and human-machine interaction Collaborates with CSIRO Data61, Defence Science and Technology Group, Orica, Airbus, and Sentient Vision Systems Develops systems for human action detection, infrastructure monitoring, and stress response prediction His work addresses critical challenges in AI deployment, such as environmental adaptability and reducing diagnostic errors in medical and autonomous systems. Recent publications highlight trends in self-supervised learning, zero-shot knowledge transfer, multimodal integration , and 3D reconstruction for healthcare , while exploring ethical AI use in sectors like mining and defense . Professor Fookes emphasizes interdisciplinary collaboration, bridging engineering, medicine, and social sciences to advance AI systems capable of real-world impact. His research agenda includes improving AI memory capabilities and explainability for safer, more reliable automation.

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Michael Everettمشاهده پروفایل

استادیار

Northeastern UniversityUnited States

Michael Everett is an Assistant Professor at Northeastern University with a joint appointment in the Department of Electrical & Computer Engineering and the Khoury College of Computer Sciences. He directs the Autonomy & Intelligence Laboratory, focusing on certifiable learning machines at the intersection of robotics, deep learning, and control theory. His research emphasizes safety, reliability, and efficiency in robotics applications like off-road navigation and social environments. Education: PhD in Mechanical Engineering, Massachusetts Institute of Technology (2020) SM in Mechanical Engineering, MIT (2017) SB in Mechanical Engineering, MIT (2015) Research Interests: Robotics and motion planning Control theory and neural network verification Reinforcement learning applications Certifiable safety guarantees for autonomous systems Navigation in dynamic/human environments Awards: Runner-Up: Best Paper Award (ICML 2022) Winner: Best Student Paper (IROS 2017/2023) Editors’ Top 5 Published Articles (IEEE Access 2021) Lab & Contributions: The Autonomy & Intelligence Lab develops algorithms for high-speed off-road autonomy, socially aware navigation, and neural feedback verification. His work includes the RAMP planning pipeline and Evora traversability learning framework. He collaborates with Google’s PAIR team on trustworthy AI.

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Toby Daviesمشاهده پروفایل

دانشیار

University of LeedsUnited Kingdom

Toby Davies is an Associate Professor in Criminal Justice Data Analytics at the University of Leeds, School of Law. His work focuses on quantitative criminology, spatial analysis, and computational methods to inform crime prevention. He holds a Mathematics degree from the University of Oxford (2008) and a PhD from University College London (UCL), followed by postdoctoral research on the EPSRC-funded Crime, Policing and Citizenship project. Before joining Leeds in 2023, he was at UCL’s Department of Security & Crime Science. His research spans interdisciplinary topics including urban form and crime, crime modeling, social networks, and cybercrime. He has collaborated with police agencies (West Yorkshire, Thames Valley, West Midlands Police) and governmental bodies (UK Home Office, London Mayor’s Office). A strong advocate for Open Science, he co-founded JDI Open to promote open practices in crime science. His recent work emphasizes policy interventions like phasing out pointed kitchen knives to reduce knife crime, leveraging data-driven approaches. He publishes widely in criminology, physics, network science, and general science journals, and has guest-edited special issues. His applied research aims to bridge theory and practice, developing tools deployed operationally in policing. Current interests include financial crime dynamics, social contagion of crime, and street network configurations’ impact on crime patterns.

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Ruben Snellingsمشاهده پروفایل

استاد

KU LeuvenBelgium

Ruben Snellings is a Professor at the KU Leuven , affiliated with the Institute for Sustainable Metals and Minerals and the Division of Geology . His research focuses on sustainable cementitious materials, mineral carbonation, and valorization of industrial by-products in construction. He actively contributes to RILEM technical committees, including TC 309-MCP and TC 267-TRM, establishing terminology and testing protocols for carbonation-based construction products. Research Highlights Advancing low-carbon binders through co-calcination of waste materials Investigating hydration kinetics and reactivity of supplementary cementitious materials (SCMs) Developing CO2 mineralization techniques for sustainable construction Technical Contributions Co-developing standardized R3 reactivity tests for SCMs Leading interlaboratory validation studies for binder performance Environmental Focus Reducing environmental leaching via carbonation of metallurgical slags Optimizing circular economy approaches for concrete recycling

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W. Eric Wongمشاهده پروفایل

استاد

University of Texas at DallasUnited States

W. Eric Wong is a Professor of Computer Science at The University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds a Ph.D. in Computer Science from Purdue University (1993), following earlier degrees from Purdue and Eastern Michigan University. His research focuses on reducing software production costs while enhancing reliability, safety, and quality through program-based and architecture/design-based testing methodologies. Key areas include automated test generation, fault localization, debugging, and software safety analysis. Professional Background: Tenured Professor at UTD since 2002 Prior roles include Senior Scientist at Telcordia Technologies (1995–2002) and Consultant at Texas Instruments (2004–2005) Active in industry partnerships, such as projects with Motorola, Avaya Labs, and Raytheon Research Interests: Software Testing & Debugging Dependable Software Development Security Requirements Engineering Fault Localization Techniques Model-Based Testing Software Reliability Modeling Awards & Recognition: 2007 IEEE COMPSAC Best Paper Award 1997 NASA Quality Assurance Special Achievement Award Recipient of a $404,772 NSF grant for software safety and reliability research (2021) Professional Activities: Editorial roles for journals like Journal of Systems and Software and International Journal of Software Engineering Program Chair for ISSRE 2012, COMPSAC 2010, and multiple ACM SAC conferences Member of IEEE Reliability Society Administrative Committee (2008–2013) IBM System z Curriculum Advisory Panel member Labs & Teams: Leads the Software Engineering Group at UTD, collaborating on projects like eXVanatge (dependable software solutions) and Fault-Prone Module Identification in telecommunications systems. Engages in cross-disciplinary efforts with industry and international institutions.

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Sarah Collins Rossettiمشاهده پروفایل

دانشیار

Columbia UniversityUnited States

Sarah Collins Rossetti is an Associate Professor of Biomedical Informatics and Nursing at Columbia University’s Vagelos College of Physicians and Surgeons. She focuses on leveraging computational tools to reduce documentation burden in EHR systems and improve patient safety through predictive analytics. PhD in Nursing from Columbia University School of Nursing Post-Doctoral Research Fellowship at Columbia’s Department of Biomedical Informatics Her research emphasizes AI-driven patient deterioration prediction , user-centered design , and interprofessional collaboration to enhance clinical workflows. She co-leads the CONCERN Early Warning System study, which reduced mortality risk by 35% and sepsis risk by 7.5%. Recent publications highlight trends in generative AI limitations in EHRs, equity in predictive systems , and healthcare process modeling . She chairs AMIA’s 25×5 Task Force to reduce documentation burden by 75% by 2025. 2019 PECASE recipient 2024 Donald A.B. Lindberg Award for Informatics Innovation 2019 FAMIA recognition Rossetti collaborates with health analytics centers and trains future researchers through NIH- and AHRQ-funded projects, blending machine learning with clinical expertise in critical care settings.

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Shweta Singhمشاهده پروفایل

استادیار

University of WarwickUnited Kingdom

Dr. Shweta Singh serves as an Assistant Professor of Information Systems and Management at Warwick Business School, University of Warwick. She concurrently holds prestigious appointments as a Fellow at the Warwick Institute for Global Sustainability Development (IGSD) and a Behavioral Data Science researcher at The Alan Turing Institute in London. Her academic journey includes a Ph.D. in Information and Decision Sciences from the Carlson School of Management at the University of Minnesota, complemented by dual Master's degrees in Computer Science and Applied Economics from the same institution. Ph.D. in Information and Decision Sciences, University of Minnesota Master's in Computer Science, University of Minnesota Master's in Applied Economics, University of Minnesota Dr. Singh's research centers on developing ethical and responsible artificial intelligence systems that address societal challenges. Her work specifically targets mitigating AI bias, creating explainable AI frameworks, and leveraging technology to combat societal injustice. She investigates how digital platforms, sharing economy models, and IT outsourcing create business value while ensuring these technologies promote sustainability and reduce inequalities. Her innovative approach combines technical AI expertise with deep social awareness, particularly focusing on gender equality and child protection in digital spaces. Her publication record demonstrates consistent high-impact contributions to Information Systems Research, International Conference on Information Systems, and related venues. The trajectory of her work shows increasing focus on practical applications of responsible AI, with recent projects addressing online child safety and human trafficking prevention. Her research increasingly intersects with policy development, as evidenced by her contributions to UK Parliamentary Office of Science and Technology briefs. Doctoral Dissertation Fellowship, University of Minnesota McNamara Fellowship, University of Minnesota Social Impact Project of the Year shortlist (2023) Asian Women of Achievement Award finalist (2023) British Indian Awards finalist (2019) Top 5 Women in Tech for Good Award shortlist (2022) Inspiring 50 UK recognition (2025) Dr. Singh actively mentors students and has been recognized with the Staff Social Inclusion Award (2024) for her teaching excellence. Her advisory roles extend beyond academia to include the UN Women UK delegation for the Commission on the Status of Women and the Advisory Board of AI retail company 'Love the Sales'. She serves as an external collaborator for Boston Consulting Group's Henderson Institute, bridging academic research with industry applications. Through her leadership in the ISM-Analytics (ISMA) Group at Warwick, Dr. Singh fosters interdisciplinary collaboration focused on creating socially responsible technological solutions. Her work with the IGSD specifically targets UN sustainability goals related to reducing inequalities and promoting inclusive societies through responsible AI implementation.

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Glenn Myersمشاهده پروفایل

پژوهشگر ارشد

Australian National University (ANU)Australia

Dr. Glenn Myers is a Research Fellow in the Department of Materials Physics at Australian National University (ANU), where he works within the X-ray tomography and applications research group. His work focuses on advanced imaging techniques, particularly in the field of X-ray tomography and computed tomography. He collaborates extensively with researchers across multiple institutions and has made significant contributions to the development of imaging methodologies for both scientific and industrial applications. Dr. Myers' research interests span X-ray tomography, computed tomography, micro-CT imaging, image reconstruction algorithms, and beam hardening correction techniques. His work addresses fundamental challenges in imaging physics, including photon statistics, spectral information extraction, and dose reduction in imaging procedures. He has developed novel approaches for motion correction, alignment, and high-fidelity imaging of complex materials, particularly additively manufactured metal components. His research bridges theoretical physics with practical applications in materials science and non-destructive testing. Analysis of Dr. Myers' publication record reveals a strong focus on advancing X-ray imaging technologies, with particular emphasis on ghost imaging techniques, neutron imaging applications, and methods for improving image quality and reducing radiation dose. His work demonstrates consistent innovation in imaging methodology over the past decade, with applications spanning medical imaging, materials characterization, and environmental science. The interdisciplinary nature of his research connects physics, engineering, and materials science to solve complex imaging challenges. Key Collaborators: Andrew Kingston, Wilfred Fullagar, Shane Latham, Glenn Sheppard Research Group: X-ray tomography and applications group Primary Applications: Materials characterization, non-destructive testing, medical imaging

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