Yuanzhu Chen is a Professor in the School of Computing at Queen’s University, affiliated with the Faculty of Arts and Science. He previously served as Professor and Department Head at Memorial University of Newfoundland (2005–2021). His research focuses on computer networking, mobile computing, complex networks, and applied machine learning, emphasizing wireless innovation beyond traditional wired systems. He holds a PhD from Simon Fraser University (2004) and a B.Sc. from Peking University (1999). Education: PhD in Computing Science (Simon Fraser University, 2004); B.Sc. in Computer Science (Peking University, 1999). Earlier roles include Post-doctoral Researcher at Simon Fraser University (2004–2005) and leadership positions at Memorial University, including Department Head (2019–2021). Research Interests: Network Coding and Opportunistic Routing Mobile and Wireless Network Protocols Complex Network Analysis Machine Learning Applications Indoor Positioning Systems Social Network Dynamics Selected Awards: Recipient of Queen’s University President's Award for Distinguished Teaching. Lab Affiliation: Director of the Wireless Networking and Mobile Computing Lab (WineMocol). Active in collaborative projects involving smartphone sensors, community-based environmental monitoring, and stock market prediction using web data.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۶۶۱-۶۷۵ از ۴۱٬۹۳۵ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Dr. Cai Ladd is a Lecturer in Geography at Swansea University's School of Biosciences, Geography and Physics. His research focuses on coastal wetlands, integrating biogeomorphology, socio-ecological resilience, and ecosystem service sustainability. He leads the 'Coastal Wetlands and Ecosystem Services' theme at the Climate Action Research Institute. Dr. Ladd teaches modules such as Coastal Processes, GIS Applications, and Sustainable Development Goals, emphasizing practical fieldwork and spatial statistics. Current projects include the Community-Led Enhancement and Restoration of Coastal Ecosystems in the Cumbrian Solway Firth (2022–2025), funded at £175,977. He supervises PhD student Rhian Hedd Meara on cross-border coastal conservation. His research employs spatial statistics, hydrological monitoring, and citizen science to develop management tools for coastal conservation. Notable contributions include studies on saltmarsh carbon stocks, mangrove restoration in tropical deltas, and innovative Mini Buoy sensor technology. Dr. Ladd collaborates globally, with publications in Frontiers in Marine Science , Nature Communications , and Environmental Pollution . His work bridges natural and social sciences, addressing climate adaptation and community-led conservation strategies.
- Macroeconomic modeling of health disorders
- Infectious disease economics
- Computable General Equilibrium (CGE) Modeling
- +۷ مورد دیگر
Dr Marcus Keogh-Brown is an Associate Professor in the Department of Global Health and Development within the Faculty of Public Health and Policy at the London School of Hygiene & Tropical Medicine (LSHTM). His position is split between research focusing on macroeconomic modeling of health and serving as Deputy Programme Director for the school's public health distance learning program. Education: BSc in Mathematics and Statistics, Queen Mary University of London (1995-1998) MSc in Computer Studies, University of Essex (1998-1999) PhD in "A Statistical Model of Internet Traffic," Queen Mary University of London (1999-2004) PGCILT Modules 1 and 2, London School of Hygiene and Tropical Medicine (2008-2012) Dr Keogh-Brown's research focuses on analyzing the macro-economic impact of health disorders and developing macro-economic models in health contexts. His areas of interest include infectious diseases (SARS, influenza, COVID-19, tuberculosis, malaria) and non-communicable diseases (Alzheimer's Disease, Dementia). He specializes in health-related applications of Computable General Equilibrium (CGE) Modeling with GAMS, with current work on health and macroeconomic modeling of COVID-19, tuberculosis, child labor, and health-related food policies. His publication record shows a strong trend toward integrated macroeconomic-epidemiological modeling, particularly for infectious disease outbreaks and public health interventions. Recent work focuses on tuberculosis in India, Covid-19 impacts in Pakistan, and food policy interventions like the UK Soft Drinks Industry Levy. His research consistently applies economic modeling frameworks to evaluate the health and economic impacts of disease and health policies across multiple countries including Ghana, India, Thailand, Myanmar, UK, and China. Grants: Current: "Modelling the health social care and macroeconomic impacts of dementia policies in the UK" (NIHR, 2025-2026) Current: "Co-designing food system fiscal policy for healthy people and planet" (University of Oxford, 2022-2025) Completed: "COVID-19 vaccine scenario analysis for health economic and social impacts" (WHO, 2022) Completed: "Evaluation of the impact of the UK industry levy of sugar-sweetened beverages" (University of Cambridge, 2017-2023) Completed: "Macroeconomic Burden of Alzheimers in China" (Jansen Global Services LLC, 2014-2015) Dr Keogh-Brown is affiliated with several research centers at LSHTM including the Malaria Centre, Global Health Economics Centre, and Centre for Mathematical Modelling of Infectious Diseases. His collaborative work spans multiple countries and addresses critical intersections between health, economics, and policy.
Ally Kruparمشاهده پروفایل
استادیار
Dr. Ally Krupar (she/her) is a faculty member at American University's School of International Service, specializing in education in emergencies, monitoring and evaluation in international development, and lifelong learning in crisis contexts. With over five years of teaching experience, she focuses on applied methodology and international development programming, including teaching PROF-660 Data-Driven Decision Making in Summer 2025. Education: Ph.D. in Lifelong Learning, Adult Education, and Comparative and International Education, Pennsylvania State University M.A. in Interdisciplinary Studies (International Peace and Conflict Resolution, Human Rights Law, Public Anthropology), American University B.A. in Anthropology, Case Western Reserve University Her research centers on the intersection of education, humanitarian response, and wellbeing, particularly in emergency settings. She designs, supports, and evaluates research and development programs aimed at enhancing lifelong learning opportunities and psychosocial wellbeing during crises. Her interdisciplinary approach draws from anthropology, education, and human rights frameworks to inform policy and practice in global development contexts. While no publications are listed in the provided text, her academic and professional focus suggests strong engagement with data-driven decision-making, program evaluation, and educational interventions in fragile environments. Dr. Krupar has not been mentioned as receiving specific scientific awards in the provided content. She advises on research and development programming in international education, with a focus on evidence-based design and impact assessment. Though no formal advisees are listed, her role involves mentoring students through coursework and applied projects in development programming. There is no mention of external grants, but her work implies involvement in research design and evaluation for educational initiatives in humanitarian settings. There is no explicit information about labs, research teams, or collaborative groups she leads or participates in, though her work involves designing and evaluating development programs, suggesting potential affiliation with research centers or initiatives focused on global education and emergency response at American University.
Amanda Jensen-Doss is a Professor and Director of Clinical Training in the Department of Psychology at the University of Miami's College of Arts and Sciences. Her work focuses on improving mental health care for children and adolescents through evidence-based practices, particularly in community settings. She leads the Child Implementation and Effectiveness Lab (CIELO Lab), which emphasizes translating research into clinical practice. Her research interests include measurement-based care (MBC), trauma-informed treatments, and implementation science. She has extensively studied clinician training, consultation strategies, and the role of data in optimizing youth psychotherapy outcomes. Key areas of focus include unaccompanied migrant children, adolescent treatment engagement, and therapist fidelity to evidence-based protocols. Dr. Jensen-Doss collaborates with community agencies to scale up evidence-based practices (EBPs), addressing barriers like funding and clinician self-efficacy. Her work bridges academic research with real-world clinical challenges, emphasizing pragmatic solutions to enhance mental health service delivery. She has contributed to national initiatives on MBC and EBP sustainability, and her lab provides resources for clinicians via platforms like shinyDLRs diagnostic tool. Notable grants and projects include the COMET study (Community Study of Outcome Monitoring for Emotional Disorders in Teens), which evaluates transdiagnostic treatments, and a focus on modular therapy approaches for anxiety, trauma, and conduct problems in schools. She advocates for clinician training models that balance expert consultation with cost-effectiveness. Her lab’s CIELO Lab website highlights ongoing projects on family support protocols for internalizing disorders and podcasts to improve health literacy. She is active in editorial roles, emphasizing methodological rigor and translational research in youth mental health.
Joshua Jackson is a Professor of Psychological & Brain Sciences at Washington University in St. Louis, holding the endowed Saul and Louise Rosenzweig Professorship of Personality Science. His research focuses on personality development and assessment within the Department of Psychological & Brain Sciences, where he maintains an active laboratory in Somers Family Hall. His academic credentials include a PhD from the University of Illinois, Urbana-Champaign and a BS from the University of Wisconsin, Madison. These foundational experiences established his expertise in psychological methodology and longitudinal research design. Professor Jackson's research program investigates the genetic and environmental antecedents of personality change, with particular emphasis on educational experiences as catalysts for development. He examines methodological challenges in personality assessment, comparing self-reports, observer-reports, behavioral observations, and physiological measures across the lifespan. His work bridges theoretical personality psychology with real-world applications in health, relationships, and occupational outcomes. Analysis of his 2012-2014 publications reveals consistent themes: personality's role in predicting life outcomes (divorce, longevity, occupational success), the plasticity of traits in adulthood, and innovative methodological approaches to longitudinal assessment. His research demonstrates how personality traits interact with major life transitions including marriage, retirement, and military service. While no specific awards are documented in the provided materials, his work appears in premier journals including Psychological Science and the Journal of Personality and Social Psychology. Information regarding graduate student mentoring and research funding sources remains unspecified in available records.
Yong-Bin Kangمشاهده پروفایل
پژوهشگر ارشد
Yong-Bin Kang is a Senior Data Science Research Fellow at the ARC Centre of Excellence for Automated Decision Making and Society (ADM+S) at Swinburne University of Technology, affiliated with the School of Social Sciences, Media, Film and Education. He holds a PhD in AI from Monash University and leads numerous transdisciplinary research projects applying artificial intelligence to address complex societal challenges. Education: PhD in Faculty of IT, Monash University, Australia Dr. Kang's research focuses on Responsible AI and Society, with specific interests in developing Societal-AI platforms that integrate social data with ethical principles. His work spans healthcare, humanitech, education, financial planning, environmental health, and justice domains. He investigates how AI can enhance decision-making processes while promoting societal well-being, with particular attention to ethical implementation and human-centered approaches. His expertise encompasses AI, natural language processing, machine learning, and decision-making optimization. Analysis of Dr. Kang's recent publications reveals a strong trajectory toward socially responsible AI applications across diverse domains. His work consistently bridges technical AI capabilities with social implications, particularly focusing on ethical frameworks, community-centered design, and addressing societal inequalities through technology. The publications demonstrate increasing collaboration across disciplines including criminology, environmental science, mental health, and education. Dr. Kang is actively involved in significant research funding initiatives, with multiple ongoing projects that address critical societal challenges through AI. His supervision availability includes Doctorate (PhD) candidates, indicating his commitment to mentoring the next generation of researchers in AI and data science fields. Current Flagship Areas: Digital Capability Innovative Society Manufacturing Futures Sustainable Development Goals: Good Health and Well Being (SDG 3) Industry, Innovation and Infrastructure (SDG 9) Affordable and Clean Energy (SDG 7)
Nikolaos Tziavelisمشاهده پروفایل
استادیار
Nikolaos Tziavelis is an Assistant Professor in the Department of Computer Science and Engineering at Basking Engineering, University of California, Santa Cruz. His research bridges theoretical and practical aspects of database systems, focusing on improving real-world data processing through novel algorithmic solutions. Education: Ph.D. from Northeastern University (advised by Mirek Riedewald and Wolfgang Gatterbauer) Diploma from National Technical University of Athens, Greece Research Interests: Data Management Database Theory Query Processing and Optimization Algorithms for Big Data Integration of Machine Learning with Database Systems Publication Trends: His work emphasizes ranked enumeration, join algorithms, and query optimization, with applications in responsive database systems and machine learning integration. Key themes include theoretical foundations, practical system improvements, and algorithmic efficiency for complex data processing tasks. Scientific Awards: 2022 Google PhD Fellowship PODS 2021 Best of Recognition 2023 VLDB PhD Workshop Best Paper Award 2024 Khoury Research Award from Northeastern University Service: He has served on program committees for major conferences including SIGMOD, VLDB, PODS, EDBT, ICDE, and Northeast Database Day.
Changjian Liمشاهده پروفایل
استادیار
Changjian Li is an Assistant Professor in the School of Informatics at the University of Edinburgh. He leads the GraphViX Group (Graphics, Vision and X) and is a member of the Institute of Perception, Action and Behaviour (IPAB). His research spans computer graphics, computer vision, and human-computer interaction with a focus on 3D generation and analysis. Education: Bachelor's Degree from Shandong University (2014) Ph.D. from the University of Hong Kong (2019) under Prof. Wenping Wang Postdoc at University College London (UCL) with Prof. Niloy Mitra Starting Researcher position at Inria with Dr. Adrien Bousseau Research Interests: Changjian's research focuses on sketch-based 3D modeling, CAD modeling, point cloud processing, and medical imaging applications. He develops systems that bridge intuitive sketching with precise CAD workflows, enhances 3D animation pipelines, and applies neural methods to sparse medical data reconstruction. Scientific Recognition: Best Paper Honorable Mention Award (MICCAI 2021) CADTalk selected as Highlight (CVPR 2024 top 10%) ACM SIGGRAPH Asia 2018 cover image selection ACM SIGGRAPH Asia 2015 technical paper highlight CVPR 2019 poster highlighted in 'Computer Vision News' Advising & Collaborations: He mentors postdocs and PhD students including Duolikun Danier, Haocheng Yuan, Ankan Bhunia, and Lei Zhong. Former advisees include Salvatore Esposito (now at Edinburgh), Guangshun Wei (Shandong University), and Mingjun Yang (University of Melbourne). Collaborates with Oisin Mac Aodha, Hakan Bilen, and Niloy Mitra. Professional Service: Currently serves as Associate Editor for IEEE TVCG and participates in program committees for SIGGRAPH Asia, SIGGRAPH, EuroGraphics, and Geometry Design and Computing (GDC) conferences.
Markus Vinczeمشاهده پروفایل
دانشیار
- Robotics
- Computer Vision
- Human-Robot Interaction
- +۵ مورد دیگر
Markus Vincze is an Associate Professor at the Institute of Automation and Control Engineering (ACIN) at Vienna University of Technology (TU Wien). He founded the Vision for Robotics (V4R) group in 1996 to advance robotic perception, particularly in real-world environments and homes. His work focuses on cognitive computer vision techniques for robotics. Education: Diplom in Mechanical Engineering (1988) and PhD (1993) from TU Wien; M.Sc. (1990) from Rensselaer Polytechnic Institute. V4R coordinates EU projects like ActIPret, robots@home, HOBBIT, and national initiatives like vision@home. Markus has edited a book on Robust Vision with Gregory Hager and authored 62 peer-reviewed journal articles and over 400 reviewed publications. His recent research explores zero-shot 6D pose estimation, sim-to-real transfer, and transparent object detection. Markus has served as program chair for ICRA 2013 and organized HRI 2017 in Vienna. He has advised numerous students and secured grants from the Austrian Academy of Sciences for work at HelpMate Robotics and Yale's Vision Laboratory. The V4R group leads innovations in robotic vision, including frameworks for synthetic data generation (Unrealgensyn), depth completion (CAGT), and educational robotics applications for sustainability. Their work spans household robotics (RH3), agricultural robotics (EdgeSoil), and human-robot collaboration.
Thomas Hermannمشاهده پروفایل
پژوهشگر
Dr. rer. nat. Thomas Hermann is a faculty member at Bielefeld University's Faculty of Engineering, leading the Ambient Intelligence Group and coordinating the Computer Science program. He specializes in sonification, auditory data science, and smart environments. Head of Ambient Intelligence Working Group Computer Science Program Coordinator Member of multiple academic advisory boards His research focuses on interactive sonification for biomedical applications, quantum systems, and smart environments. Key projects include ECG sonification for cardiac diagnosis, real-time auditory feedback in swimming, and sonic interfaces for AR cooperation. Recent publications span 2025 with Python-based sonification tools ( pya AGen ), quantum system sonification, and ST-elevation myocardial infarction monitoring. He contributes to open-access supplementary materials and interdisciplinary workshops. As a researcher , Hermann develops practical sonification frameworks like Panson for facial behavior analysis, CardioScope for portable ECG monitoring, and Base Cube One for smart environments. His work bridges academic research with industry applications.
- Data Integration
- Entity Matching
- Data Cleaning
- +۴ مورد دیگر
AnHai Doan is the Vilas Distinguished Achievement Professor and Gurindar S. Sohi Professor in the Department of Computer Science at the University of Wisconsin-Madison. His research focuses on data integration, entity matching, and data science, with particular emphasis on building end-to-end systems that leverage machine learning, scalable data management, and human-data interaction. He leads the Magellan project, which develops open-source tools for entity matching as part of the Python data ecosystem. Dr. Doan's research interests include: Data cleaning and integration: Building end-to-end data integration systems as parts of the Python ecosystem of open-source data tools Data science: Developing an agenda that integrates research, system building, education, and outreach, with focus on data quality Crowdsourcing: Pioneering work on using crowdsourcing for data management and integration Knowledge bases: Building community-centric knowledge bases His recent work shows a strong trend toward developing practical systems for data integration that combine machine learning with traditional database techniques. The Magellan project represents a comprehensive effort to build an end-to-end entity matching system, with numerous publications spanning entity matching algorithms, debugging tools, and cloud-based matching services. His research increasingly focuses on the intersection of data science and data management, particularly on data quality issues. Selected scientific awards: Gurindar S. Sohi Professorship (2020) Vilas Distinguished Achievement Professorship (2018) SIGMOD Research Highlight Award (2017) Vilas Associate, UW-Madison (2016) Alfred P. Sloan Research Fellowship (2007) NSF CAREER Award (2004) ACM Doctoral Dissertation Award (2003) Dr. Doan has been actively involved in service to the data management community, including serving on the SIGMOD Advisory Board, as associate editor for VLDB, and co-chairing the industrial program for VLDB. He has also played a key role in strategic initiatives at UW-Madison, including helping to establish the School of Computer, Data, and Information Sciences. He has mentored numerous students and researchers through his work on the Magellan project and related research efforts. Additionally, he co-founded GreenBay Technologies to commercialize Magellan, which was later acquired by Informatica. He leads the Database Group at UW-Madison and has been instrumental in developing data science educational programs at both undergraduate and graduate levels. His work bridges research, education, and practical applications in the rapidly evolving field of data management and data science.
Phil Bernstein is a Distinguished Scientist in the Data Systems Group at Microsoft Research Redmond and an Affiliate Professor at the University of Washington where he occasionally teaches CSEP 545 Transaction Processing. With over four decades of pioneering work in database systems, he has made significant contributions across transaction processing, data integration, and distributed systems. His research interests focus on database systems, transaction processing, and data integration, with recent work on approximate nearest neighbor search over vector databases, improving database servers using disaggregated cloud resources, and the Orleans distributed systems programming framework. Bernstein's work on Orleans (2012-2019) resulted in an open-source framework widely used inside and outside Microsoft, with components addressing indexing, geo-distribution, and transactions. Bernstein has received numerous prestigious awards including being named a Fellow of the ACM and AAAS, receiving the SIGMOD Edgar F. Codd Innovations Award, and election to the National Academy of Engineering and Washington State Academy of Sciences. Fellow of the ACM Fellow of the AAAS SIGMOD Edgar F. Codd Innovations Award Member of the National Academy of Engineering Member of the Washington State Academy of Sciences As an active researcher and academic, Bernstein serves on numerous conference program committees including SIGMOD 2024 (keynotes), VLDB 2024 (Industry), and has held editorial positions for Information Systems and Springer Data-Centric Systems and Applications. His influential books, Principles of Transaction Processing (2009) and Concurrency Control and Recovery in Database Systems, remain foundational texts in the field.
Daniel Schnurr holds the Chair of Machine Learning, especially Uncertainty Quantification at the University of Regensburg since August 2022, where he conducts research at the intersection of artificial intelligence, data economics, and digital market regulation. Previously, he headed the Data Policies research group at the University of Passau, building his expertise in the economic and regulatory aspects of digital markets. His educational background includes a doctorate in business informatics from the Karlsruhe Institute of Technology (2016), where he also worked for three years as a research associate at the Institute for Information Systems and Marketing. He completed his undergraduate and master's studies in Information Systems at KIT (2007-2013), with international experience at Concordia University in Canada and Singapore Management University. Professor Schnurr's research focuses on the technical, economic, and social implications of new machine learning methods and data as a decisive competitive factor and driver of innovation in digital markets. His work examines how data functions as both an economic asset and regulatory challenge, particularly in contexts of market power, competition policy, and AI governance. He investigates uncertainty quantification in machine learning systems while considering their broader economic and societal impacts. His publication portfolio demonstrates consistent output in top-tier journals including Management Science, Journal of Information Technology, and Journal of Competition Law & Economics, with recent work increasingly focusing on AI regulation, data access remedies, and uncertainty-aware AI systems. The trajectory shows evolution from telecommunications infrastructure research to contemporary digital market and AI regulation issues. As a Research Fellow at the Centre on Regulation in Europe (CERRE) since 2022, he has authored numerous policy reports addressing regulation of cloud computing services, digital platforms, and data economy frameworks. His policy contributions bridge academic research with practical regulatory implementation, particularly regarding the European AI Act and Digital Services Act. His research program involves experimental approaches to understanding data markets, human-AI interaction dynamics, and regulatory effectiveness. Through his work at CERRE and collaborations with international scholars, he contributes to shaping evidence-based digital policy in the European context while maintaining strong connections to academic research communities in information systems and economics.
Klaus Schmidt is a Professor of Economics at Ludwig Maximilian University of Munich, holding the chair in the Department of Economics within the Faculty of Economics. His research focuses on theoretical and applied aspects of contract theory, game theory, and industrial organization, with significant contributions to understanding venture capital finance, privatization, and fairness in economic behavior. His educational background includes a Ph.D. in Economics from the University of Bonn (1991) with the dissertation "Commitment in Games with Asymmetric Information" and Habilitation (1994) with "Contracts, Competition, and the Theory of Reputation". Early academic support included scholarships from Studienstiftung des Deutschen Volkes (1982-87) and a German Academic Exchange Service grant (1988/89). Professor Schmidt's research centers on contract theory applications across diverse domains. His work on fairness and reciprocity (notably with Ernst Fehr) revolutionized behavioral contract theory, while contributions to venture capital finance and privatization established foundational frameworks for analyzing incomplete contracts in real-world settings. He employs rigorous game-theoretic modeling to address incentive problems in procurement, privatization, and organizational design. His publication record since 1991 reveals consistent focus on contract-theoretic problems, with increasing emphasis on behavioral aspects after 1999. Key thematic clusters include venture capital finance (2002-2003), fairness/reciprocity (1999-2000), and privatization/incomplete contracts (1995-1996), demonstrating evolution from pure theory to policy-relevant applications. Gossen Prize of the German Economic Association (2001) Commerzbank Prize of the Berlin-Brandenburg Academy of Sciences (2001) Teaching Prize of the Bavarian ministry of science (2000) Walter-Adolf-Jörn Prize (1993) German Academic Exchange Service Grant (1988/89) Studienstiftung des Deutschen Volkes Scholarship (1982-87) Professor Schmidt has secured major research funding including German Science Foundation grants for "Incomplete Contracts" (1999-present) and "Venture Capital Finance" (1998-present). His teaching excellence was recognized with Bavaria's highest teaching award (2000), and he maintains active collaboration with leading economists including Ernst Fehr and Monika Schnitzer. While specific student mentorship details aren't documented, his extensive publication record and seminar leadership indicate significant academic supervision.