جستجوی استاد راهنمای دانشگاهی

Michael Bronsteinمشاهده پروفایل

استاد

• Geometric Deep Learning
• Graph Representation Learning
• Computer Vision
• +۴ مورد دیگر

Affiliations and Roles Michael Bronstein is a Professor at the Università della Svizzera italiana (USI) in the Faculty of Informatics and the Institute of Computational Science . He holds the Chair in Machine Learning and Pattern Recognition at Imperial College London and serves as Head of Graph Learning Research at Twitter . Previously, he was affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI) as an Adjunct Professor. Education Ph.D. in Computer Science, Technion–Israel Institute of Technology (2007) Visiting appointments at Stanford University, MIT, Harvard University, and Tel Aviv University Research Interests Bronstein's work focuses on geometric deep learning , graph representation learning , and non-rigid shape analysis . He pioneered methods for extending machine learning to non-Euclidean domains like graphs and manifolds. His research combines theoretical advancements in spectral geometry with practical applications in computer vision, robotics, and medical imaging. Publications Trends His articles emphasize geometric deep learning frameworks, functional maps for shape correspondence, and spectral methods for manifold analysis. Key themes include invariant representations, partial shape matching, and applications in 3D reconstruction and graph neural networks. Awards and Honors Five ERC Grants Royal Society Wolfson Research Merit Award IEEE and IAPR Fellowships World Economic Forum Young Scientist Advising and Entrepreneurship Bronstein is a serial entrepreneur, founding companies like Novafora , Invision (acquired by Intel), and Fabula AI (acquired by Twitter). His academic advising spans PhD and Master’s students in machine learning and geometry processing. Labs and Teams Active in the Institute of Computational Science at USI and leads Twitter’s Graph Learning Research team, focusing on real-world applications of geometric deep learning.

Andrés M. Urcuqui-Bustamanteمشاهده پروفایل

پژوهشگر

• Environmental Policy and Governance
• Urban Planning
• Natural Resource Management
• +۴ مورد دیگر

Andrés M. Urcuqui-Bustamante is a Postdoctoral Research Associate in the Department of Urban Planning and Policy at the University of Illinois Chicago (UIC). His work bridges environmental science, public health, and policy through a focus on human-nature interactions. He holds a PhD in Environmental Science from SUNY College of Environmental Science and Forestry, alongside multiple master's degrees in rural development and biodiversity conservation from institutions in Colombia and Spain. His research investigates how societal perceptions shape responses to environmental challenges such as Lyme disease prevention, urbanization impacts, and biodiversity conservation. Methodologically, he combines qualitative and quantitative approaches with participatory tools like collaborative modeling and role-play simulations to enhance stakeholder collaboration and policy design. Current projects explore green space accessibility in Chicago and Santiago de Cali, and the non-economic values influencing hydrological services programs in Mexico and Colombia. Urcuqui-Bustamante's publications span environmental policy, public health, and participatory governance, with recent work appearing in Environment and Behavior , EcoHealth , and Environmental Science and Policy . He is affiliated with professional organizations including the Association of Collegiate Schools of Planning and the International Association for Society and Natural Resources.

• Geographic Information Systems (GIS)
• Map Generalization
• Spatial Data Mining
• +۳ مورد دیگر

Jan-Henrik Haunert is a Professor at the University of Bonn, affiliated with the Institute of Cartography and Geoinformatics within the Faculty of Civil Engineering and Geodetic Science. His research focuses on map generalization, geographic information systems (GIS), and optimization techniques in cartography. He has contributed to projects funded by the German Research Foundation (DFG), particularly in deriving scale-dependent representations of geographic data. His work emphasizes logical consistency, semantic accuracy, and quality assessment in geospatial data processing. Key research areas include land cover map generalization, spatial data integration (e.g., volunteered geographic information), and rule-based incremental generalization. He has developed methodologies leveraging mixed-integer programming and straight skeleton algorithms for cartographic automation. His publications span peer-reviewed journals like GeoInformatica and Photogrammetrie - Fernerkundung - Geoinformation , as well as conference proceedings such as AGILE and ACM-GIS. Haunert’s contributions address challenges in geospatial data quality, including polygon simplification and river dataset matching. He has also explored applications in vehicle localization and virtual reality systems like the GeoScope for urban planning. His work bridges theoretical GIScience with practical applications in cartography and geoinformatics.

• Geometric Group Theory
• Group Rings
• Algebra
• +۶ مورد دیگر

Dawid Kielak is a Professor of Pure Mathematics at the University of Oxford and a Tutorial Fellow at Hertford College, Oxford. He holds a DPhil from the University of Oxford and has held academic positions in Warsaw, Bonn, and Bielefeld before returning to Oxford. His research focuses on geometric group theory, particularly the interplay between group rings, algebraic structures, and topological spaces. He is a member of the Algebra and Topology research groups at Oxford. His research interests include geometric group theory, cohomology of arithmetic groups, ℓ²-invariants, and the study of automorphism groups of free groups. His work is funded by prestigious grants such as the ERC Starting Grant 'Fibring' (2019) and the ERC Consolidator Grant 'HigherHyper' (2024). He has also received awards like the Whitehead Prize (2022) and the Frontiers of Science Award (2023). Key research contributions include studies on Kazhdan constants for Chevalley groups, profinite rigidity of fibring, and coherence properties of groups. His work often bridges algebraic and topological methods, with applications to 3-manifold groups and random groups. He supervises multiple DPhil students and has mentored postdoctoral researchers in areas like ℓ²-Betti numbers and group rings. Teaching responsibilities include pure mathematics tutorials at Hertford College and advanced courses on geometric group theory, 3-manifolds, and ℓ²-invariants at the University of Oxford and Bielefeld University. His lab focuses on collaborative projects in algebraic topology and geometric group theory, with a particular emphasis on virtual fibring and higher Kazhdan properties.

• Indoor Localization
• Wireless Networks
• Pervasive Computing
• +۱۱ مورد دیگر

Shueng-Han Gary Chan is a faculty member in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), within the College of Engineering. He is actively engaged in research and mentoring, with a strong publication record in mobile computing, indoor localization, and AI for pervasive systems. His research focuses on indoor localization using Wi-Fi, geomagnetic, and inertial signals , sensor fusion , crowd counting with deep learning , domain adaptation , and efficient mobile AI systems . His work bridges theoretical innovation with real-world deployment, as seen in systems for missing person search and indoor navigation. Recent publications (2023–2025) show a consistent trend toward self-supervised and domain-agnostic learning , efficient model design for mobile devices , and robust signal fusion in noisy environments . His team leverages transformer architectures, graph neural networks, and novel optimization techniques to solve real-world challenges in urban and indoor spaces. He has advised numerous graduate students, including Jierun Chen, Zhuoxuan Peng, and Tianlang He, who have contributed as first authors to joint publications. His collaborations span institutions and include work on large-scale system deployments and mobile AI. He leads a research group focused on mobile and pervasive computing , with projects involving IoT-based contact tracing, indoor navigation (e.g., DeepNavi, SiFu), and real-time localization systems. The team emphasizes practical deployment and system robustness.

• Economic Geography
• Political Geography
• Tourism Studies
• +۳ مورد دیگر

Ilaria Greco is an Associate Professor at Università del Sannio within the Department of Law, Economics, Management and Quantitative Methods (DEMM) . Her research focuses on Economic and Political Geography , with particular emphasis on tourism development, smart city models, rural regeneration, and maritime trade dynamics. Research Trends : Analysis of Food Festivals (2024) and their role in Irpinia , digital tourism strategies (2021), future energy-territory relationships (2020), smart city-region transitions (2017), maritime geopolitics (2017), film tourism (2016), climate change resilience (2016), Indian economic policies (2015), rural-urban balance (2014), thermal tourism (2014), network geography (2013), and rural hospitality models (2010). Key Collaborations : Frequently co-authors with Angela Cresta , exploring topics like Tourism 2.0 , Resilient Landscapes , and Smart Specialization Strategies .

Max Kellnerمشاهده پروفایل

پژوهشگر

• Molecular Biology
• Virology
• Evolutionary Biology
• +۴ مورد دیگر

Dr. Max Kellner is a molecular biologist and research group leader at the Helmholtz Centre for Infection Research (HZI) since April 1, 2025. He established the VICO (Virus-Host Coevolution) junior research group, focusing on molecular interactions between viruses and their hosts, particularly evolutionary mechanisms of innate immunity and viral resilience in mammals. His work spans CRISPR-based diagnostics, organoid culture systems, and zoonotic virus research. Bachelor's degree at University of Vienna Master's thesis at Broad Institute of MIT and Harvard Doctoral studies at University of Cambridge and University of Vienna His research integrates evolutionary biology and molecular virology to explore disease resilience in bats, developing organoid models for studying infections like Marburg virus, MERS-CoV, and SARS-CoV-2. Key methodologies include RT-LAMP assays for rapid diagnostics and CRISPR-based amplification techniques. Recent publications highlight advancements in pathogen detection in resource-limited settings and epithelial antiviral responses. Notable collaborations include work with local scientists in Ghana to improve rural virus diagnostics and partnerships with institutions such as the Broad Institute, MRC Laboratory of Molecular Biology, and IMBA.

Kotaro Haraمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Human-Machine Collaborative Systems
• Accessibility Design
• +۸ مورد دیگر

Kotaro Hara is a Full-time Faculty Assistant Professor of Computer Science at Singapore Management University's School of Computing and Information Systems. His research focuses on Human-Computer Interaction, Human-Machine Collaborative Systems, and Accessibility Design, with applications in urban mobility, digital transformation, and aging population support. He holds a PhD from the University of Maryland (2016). Research Areas: Accessibility, Crowdsourcing, Future of Work, Urban Sustainability Recent publications explore Augmented Reality for low-vision runners, conversational agents for dementia care, and novel tactile data visualization methods. His work integrates natural language processing, multimodal interfaces, and AI ethics frameworks across diverse domains. Academic collaborations include advising PhD candidate Sheshadri Smitha. Contact: kotarohara@smu.edu.sg

Rodney C. Austinمشاهده پروفایل

استاد

• Biochemistry
• Environmental Chemistry
• Chemical Education
• +۷ مورد دیگر

Rodney C. Austin is a Professor in the Department of Chemistry and Biochemistry at Geneva College, part of the College of Arts and Sciences. He teaches a range of courses including General Chemistry, Organic Chemistry, and Biochemistry, and has developed innovative interdisciplinary curricula focused on global water issues. His educational background includes a Ph.D. in Chemistry from the University of Cincinnati (2000) and a B.S. from Mount Vernon Nazarene College (1992). Dr. Austin's research spans environmental chemistry, biochemistry, and chemical education. He actively involves students in projects such as water quality analysis, phytochrome protein characterization, and pharmaceutical testing. His work emphasizes hands-on, inquiry-based learning through frameworks like POGIL (Process Oriented Guided Inquiry Learning). The recent publications reflect a strong trend in interdisciplinary and student-centered research, combining analytical chemistry with environmental monitoring and pedagogical innovation. Topics include glyphosate impact on bacteria, metal contamination in river sediments, and methods for teaching global water issues. Dr. Austin is active in professional societies including the Protein Society and the Society of Analytical Chemistry of Pittsburgh. He also holds a leadership role in the POGIL movement as chair of the Video Workshop Group and has presented at national conferences such as the Biennial Conference on Chemical Education and the American Chemical Society meetings. He mentors numerous undergraduate students, supervising research on water quality, environmental contaminants, and biochemical methods. His collaborations include the Beaver Falls Municipal Authority and Notre Dame on analytical projects. He has led initiatives integrating biology, chemistry, and mathematics in education and continues to develop pedagogical tools for active learning. Dr. Austin's current research includes isolating and characterizing a unique phytochrome from Pedobacter heparinus , analyzing TTHMs in drinking water, and examining industrial metal levels in local river sediments. He works closely with students in field and laboratory settings, promoting experiential learning and community engagement.

• Criminal governance
• Sociology of organized crime
• Economic sociology
• +۸ مورد دیگر

Federico Varese is Professor of Sociology at Sciences Po , affiliated with the Centre for European Studies and Comparative Politics (CEE) and the Department of Sociology, University of Oxford , where he also holds the position of Senior Research Fellow at Nuffield College. He previously served as Director of the Department of Sociology at Oxford (2021–2023) and is currently Director of the Extra-legal Institute. Education: University of Bologna University of Cambridge University of Oxford Research Interests: Varese specializes in the sociology of organized crime, criminal governance, economic sociology, and social theory. His research explores the structures and dynamics of mafia groups, particularly the Russian mafia, transnational crime migration, cybercrime markets, and the relationship between criminal organizations and the state. He employs methodologies including social network analysis and ethnography to investigate how informal institutions govern social order in the absence of state authority. Recent Research Trends: His recent publications reflect a strong focus on global cybercrime mapping, Russian political repression, and comparative studies of organized crime. The works demonstrate a shift toward digital criminology, transnational criminal networks, and the use of data-driven methods to analyze illicit markets and governance structures. Scientific Awards: International Association for the Study of Organized Crime 2012 Outstanding Publication Award for Mafias on the Move ED A. Hewett Book Prize (co-recipient) for The Russian Mafia Niccolini Prize first prize for non-fiction for Mafia Life Bernagozzi Prize from the city of Portomaggiore, Italy Advising and Grants: Varese has supervised numerous PhD and postdoctoral researchers and has led major funded research projects. He currently holds an Advanced ERC Grant titled CRIMGOV (2022–2026), hosted at Sciences Po and Oxford University, focusing on criminal governance. He has collaborated with institutions globally and mentored scholars in criminology and sociology. His editorial roles include serving on the board of The British Journal of Criminology and as past Editor of Global Crime . Labs and Research Groups: He is the Director of the Extra-legal Institute , a research hub focused on informal governance and illegal institutions. He is also a key figure in the Centre for European Studies and Comparative Politics (CEE) at Sciences Po and has led thematic research seminars on state transformation, organized crime, and democratic strains.

James R. Greenمشاهده پروفایل

استاد

• Machine Learning
• Biomedical Informatics
• Computational Biology
• +۹ مورد دیگر

James R. Green is a Professor in the Department of Systems and Computer Engineering at Carleton University , where he has been a faculty member since 2005. He holds a PhD from Queen's University and is a licensed Professional Engineer (P.Eng.) and Senior Member of IEEE. His work integrates machine learning, biomedical informatics, and high-performance computing. His educational background includes: B.A.Sc. in Systems Design Engineering, University of Waterloo (1998) M.Sc.(Eng.), Queen's University (2000) PhD, Queen's University (2005) Dr. Green's research focuses on machine learning challenges in biomedical informatics , particularly class imbalance and rare event prediction. Key areas include protein structure, function, and interaction prediction; microRNA detection in unique species; non-contact neonatal monitoring; and accelerating scientific computing via parallel architectures like the Cell BE processor. His lab has developed several widely used bioinformatics tools such as PIPE, ProtDCal, and PCI-SUMO. His recent publications reflect a strong trend in computational biology and machine learning , with applications in proteomics, genomics, and medical diagnostics. He has published over 100 peer-reviewed papers and secured funding from NSERC, CIHR, CFI, ORF, OCE, MITACS, and IBM. Scientific and teaching recognitions include: Three teaching awards NSERC Best Project Award (twice: 2006-2007 and 2007-2008) Multiple student projects resulting in conference papers (e.g., CMBEC) He has supervised numerous undergraduate capstone projects in areas such as assistive technologies, robotic systems, and bioinformatics. His teaching portfolio includes courses in Pattern Classification, Machine Learning, Computer Architecture, and Biomedical Engineering. He leads an active research group that bridges computer engineering and life sciences, fostering interdisciplinary collaboration. Lab and research team initiatives include: Development of open-access web servers for protein analysis Collaborations with biologists and clinicians Integration of hardware and software for medical applications

Joan Font Fàbregasمشاهده پروفایل

استاد

• Public Policy
• Political Science
• Democracy Studies
• +۳ مورد دیگر

Joan Font Fàbregas is a Professor at the Faculty of Political Sciences and Sociology at Universitat Autònoma de Barcelona (UAB). He holds a PhD in Political Science from UAB (1993) and a Master of Arts from the University of Michigan. He has served as Director of IESA (CSIC), Visiting Professor at multiple universities, and Director of Research at CIS. His research focuses on mechanisms to integrate citizen preferences into public policies through referendums, elections, advisory councils, surveys, and citizen juries. He collaborates with organizations like Oxfam-Intermon, Open Society Foundation, and the World Bank. Key projects include studies on participatory democracy in Southern Europe, the impact of economic crises on participatory processes, and the design of effective participatory instruments. He has published extensively on topics like stealth democracy, policy proposal implementation, and expert roles in governance. His work spans academic books, journal articles, and conference presentations. He has advised on participatory policies at local, regional, and national levels, emphasizing methodological innovation in studying democratic innovations. Font Fàbregas has led projects such as 'Assodem-A' mapping advisory councils in Andalusia and 'EUCOMMEET' exploring deliberative participation. His research integrates quantitative and qualitative methods, addressing challenges in large-scale studies of participatory experiences. He has supervised PhD theses on topics like deliberative surveys, charisma in politics, and participatory limits.

Edith W. Clowesمشاهده پروفایل

استاد

• Russian Literature
• Czech Literature
• Literary and Cultural Studies
• +۱۲ مورد دیگر

Edith W. Clowes is the Brown-Forman Professor in the Department of Slavic Languages and Literatures at the University of Virginia, within the College of Arts and Sciences. She holds a PhD in Slavic from Yale University and is a leading scholar in Russian and Czech literature, culture, and intellectual history. Her work spans philosophy, religion, utopian thought, and the concept of imagined geographies in post-Soviet identity. Her research focuses on the intersection of literature and philosophical thought, particularly in revolutionary and fin-de-siècle Russia. She has pioneered interdisciplinary studies on regional identities in Russia and is currently advancing digital humanities through literary cartography, including the project Mapping Imagined Geographies of Revolutionary Russia (1914–1922) . Her scholarship explores how space, place, and identity are constructed in cultural discourse. The most recent publications reflect a sustained engagement with imagined geographies, regional identity, and digital methodologies. Her work bridges literary analysis, cultural theory, and spatial cognition, with a strong emphasis on interdisciplinary and multimodal approaches. She frequently publishes in both English and Russian, contributing to international scholarly dialogue. Her scientific awards include prestigious fellowships from ACLS, NEH, DAAD, Fulbright-Hays, IREX, and others, underscoring the recognition and impact of her research. Professor Clowes has served as a past director of the Center for Russian, East European, and Eurasian Studies at the University of Kansas. She mentors through editorial leadership and collaborative scholarship, though specific advisees are not listed. Her research has been supported by major institutional grants, including Title VI, US Army Research Office, DAAD, Open World Institute, and the Institute of Turkish Studies. She is actively involved in editorial work as Associate Editor of Russian Review and serves on the editorial boards of Losevskie chteniia , Region , and Beiträge zur slavistischen Philologie . She also co-founded 'Music Works' to support music education and has collaborated with university museums on art exhibits and conferences.

• Real Estate Economics
• Housing Economics
• Urban Economics
• +۸ مورد دیگر

Rainer Schulz is a Senior Lecturer at the Business School of the University of Aberdeen, where he conducts research and teaches in real estate economics, housing markets, and financial economics. He is actively accepting PhD students and supervises research in real estate. His affiliations include the Gillmore Centre for Financial Technology at Warwick Business School and the Berlin Center for AI Research in Economics and Management. Research Interests: Dr. Schulz's research focuses on urban real estate markets using econometric and machine learning methods. Key areas include automated valuation modelling (AVM), real estate investment vehicles, fund management, and location choice. He investigates the impact of teleworking on housing demand and the application of real options in real estate development. His work is interdisciplinary, combining urban economics, financial theory, and data science. Publication Trends: His recent publications (2022–2024) emphasize the effects of teleworking on housing markets, machine learning applications in real estate, and local housing market information systems. Earlier works focus on land value mapping, hurdle rates in investment, and the relationship between house prices and macroeconomic variables. His research consistently applies advanced quantitative techniques to real-world property market problems. Scientific Awards: Poster award for Semiparametric Estimation of Land Values, 2015 Aareal Award of Excellence in Real Estate Research, 2012 ARES Foundation Award, 2006 Deutsche Immobilien Akademie Research Prize for doctoral thesis, 2003 Advising and Grants: Dr. Schulz is currently accepting PhD students in Real Estate. He leads the compilation of the Aberdeen Housing Market Report, a knowledge exchange project with the Aberdeen Street Property Company (ASPC). While specific grants are not listed, his research is supported through institutional collaborations and publications in high-impact journals. Labs and Teams: He is affiliated with the Centre for Real Estate Research at the University of Aberdeen Business School. He collaborates with researchers at Humboldt University (Berlin) and participates in international research networks such as the Berlin Center for AI Research. His work involves interdisciplinary teams focusing on urban data, housing policy, and financial technology.

• Cardiac Electrophysiology
• Biomedical Instrumentation
• Mechanoelectric Feedback
• +۷ مورد دیگر

Irene del Canto Serrano is a Researcher in the Department of Electronic Engineering at the School of Engineering, Universitat de València. Her work integrates biomedical engineering with cardiac electrophysiology, focusing on the interaction between mechanical forces and electrical activity in the heart. She is actively involved in two key research groups: GRELCA (Cardiac Electrophysiology group) and i2N (Electronic Instrumentation in Medical and Nuclear Physics), reflecting her dual expertise in physiology and instrumentation. Education: PhD in Biomedical Engineering, Universitat Politècnica de València (2015). Thesis: Estudio de las modificaciones farmacológicas de los efectos electrofisiológicos producidos por el estiramiento local miocárdico a partir de técnicas dinámicas de cartografía eléctrica, en un modelo experimental de corazón aislado de conejo , supervised by Dr. David Moratal Pérez and Dr. Francisco Javier Chorro Gascó. Her research interests center on cardiac electrophysiology , particularly mechanoelectric feedback , myocardial stretch , arrhythmia mechanisms , and pharmacological modulation using experimental models. She also explores cardiac imaging , especially cardiac MRI for strain and deformation analysis, and applies machine learning to improve detection and classification in myocardial infarction. Her recent publications highlight a strong trend toward integrating biomarkers (e.g., ferritin), iron therapy , and cardiac function recovery in heart failure, showing translational relevance. Her 15 most recent publications reflect a consistent focus on experimental cardiology using isolated heart models, pharmacological interventions (ranolazine, GS967, eleclazine), and advanced imaging techniques. She investigates how drugs affect stretch-induced arrhythmias, evaluates MRI-based strain changes post-iron therapy, and develops AI tools for cardiac image analysis. These works span basic science (e.g., CaMKII inhibition) to clinical applications (e.g., Myocardial-IRON trial analysis). Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: While no formal students or grants are listed, her role as a postdoctoral researcher and active publication record suggest involvement in mentoring junior researchers and contributing to funded projects, particularly within the GRELCA and i2N groups. She has co-authored numerous experimental studies, indicating strong collaborative and project-based research activity. Labs and Teams: Irene is affiliated with two prominent research groups at Universitat de València: GRELCA (Cardiac Electrophysiology group) , which studies arrhythmia mechanisms and therapeutic interventions, and i2N (Electronic Instrumentation in Medical and Nuclear Physics) , which develops advanced tools for medical diagnostics. These affiliations underscore her interdisciplinary approach, combining physiology, engineering, and data science.