Find Academic Supervisors

• Population Genetics
• Conservation Biology
• Ecology
• +5 more

Janet Loxterman is a Professor and Department Chair in Biological Sciences at Idaho State University. Her research integrates population genetics with conservation biology and ecology, focusing on molecular techniques to address conservation challenges in both aquatic and terrestrial ecosystems. Ph.D. in Biology (Conservation Genetics), Idaho State University (2001) M.S. in Biology, Virginia Commonwealth University (1995) B.S. in Behavioral Neuroscience, Lehigh University (1992) Her work emphasizes combining ecological and genetic data to understand population structure, critical for conservation strategies like species protection, reintroduction programs, and habitat restoration. Key areas include fish genetics, hybridization analysis, and wildlife biogeography. Recent publications highlight advancements in fish identification, DNA extraction methods, climate adaptation frameworks, and hybridization studies in trout. Her lab at Life Sciences 434 addresses watershed evolution, human impacts, and genetic diversity trends across species like cutthroat trout, dwarf mistletoe, and pumas.

Julian ReifView profile

Professor

• Tourism Geography
• Digital Tourism Measurement
• Smart Destinations
• +7 more

Prof. Dr. Julian Reif is a Professor of Tourism and Deputy Director at the German Institute for Tourism Research (Department of Economics) at the West Coast University of Applied Sciences. His research focuses on tourist demand analysis, digital visitor measurement, smart destinations, and urban tourism dynamics. He holds a PhD in Tourism Geography from the University of Bonn (2021) and has authored/co-authored over 80 peer-reviewed publications. Research interests include Big Data applications in tourism, crowding perception, overtourism challenges, and the socio-spatial impacts of tourism. He leads projects like the AI-based Recommender for sustainable tourism and the Landesweites digitales Besuchermanagement (LAB-TOUR SH) in Schleswig-Holstein. His work bridges academic theory with practical destination management solutions. Key achievements include the Best Paper Award 2020 (Journal of Destination Marketing & Management) and co-authoring the award-winning Tourismusatlas Deutschland (2021). He teaches modules on scientific writing, tourism geography, and digitalization in international business management. Current research explores spatial footprint analysis of urban events, business traveler behavior, and the role of nudging in sustainable tourism. Leading projects: AI-Basierter Recommender, CRUISE (cruise passenger analysis), and EMOBÜS (tourist emotion mapping) Coordinated 10+ research initiatives including GreY (Grey Market Analysis), PUNK (punk subculture tourism), and DIGIPARK (national park visitor tracking) Teaching portfolio includes 'Digitalisierung im Tourismus' and 'Tourismusgeographie' at undergraduate and master's levels

Anika GroßView profile

Professor

• Database Systems
• Knowledge Graphs
• Ontologies
• +7 more

Prof. Anika Groß is a Professor for Database Systems and Programming at the Department of Computer Science and Languages at Anhalt University of Applied Sciences in Köthen, Germany. She holds a PhD from the University of Leipzig (2014) and has held roles as a PostDoc in strategic research at Daimler AG and as a research assistant at the Interdisciplinary Centre for Bioinformatics (IZBI). She is actively involved in academic governance, serving on the faculty council, board of examiners, and various sustainability and research data management committees. Her research focuses on database systems, knowledge graphs, and ontology engineering, with applications in environmental science, medicine, and material sciences. Education - PhD (Dr. rer. nat.) in Computer Science, University of Leipzig (2014) - Diploma in Bioinformatics, MLU Halle-Wittenberg (2007) - Postdoctoral research at University of Leipzig's Database Group (2008–2013) Research Interests Her work emphasizes temporal graphs, ontology evolution, and semantic data integration. She develops tools like Region Evolution eXplorer (REX) and contributes to projects such as AgriRestore (ecosystem restoration) and MeineWaldKI (AI-based forest monitoring). Her recent focus includes wearable device applications in healthcare and digital twins for lithium value chains. Recent Research Trends Recent publications highlight interdisciplinary applications of knowledge graphs in agriculture and environmental science, leveraging temporal analysis and machine learning for tasks like chemical transformation prediction and bladder monitoring. She also explores cross-lingual semantic annotations in medical forms and holistic clustering of linked data. Professional Roles - Executive Committee Member, GI Database Systems Group - Fellow, Institute for Technologies and Economics of Lithium (ITEL) - Co-Chair of multiple workshops including FGDB-Workshop @ LWDA 2018 and BigDS@BTW 2017 Labs & Collaborations She leads research teams in projects funded by DFG, European Union (EFRE), and ITEL, collaborating with organizations like Daimler AG and ANU. Her lab focuses on advancing database systems and interdisciplinary data science applications.

Xuebin WeiView profile

Associate Professor

• Geographic Information Systems (GIS)
• Social Media Analysis
• Machine Learning
• +4 more

Xuebin Wei is an Associate Professor of Geography at the College of Integrated Science & Engineering (CISE) at James Madison University (JMU). He holds a Ph.D. in Geography from the University of Georgia, complemented by advanced degrees in GIS and Urban Planning from Wuhan University and ITC at the University of Twente. Dr. Wei specializes in integrating geospatial technologies with social media analysis, machine learning, and cloud computing to address urban and environmental challenges. His research focuses on spatial-social networks, 3D urban modeling using LiDAR and aerial imagery, and applying social media data for disaster response and public health. Notable projects include the JMU Virtual 3D Campus and LBSocial initiative exploring geosocial data frameworks. Wei teaches courses in GIS, cloud computing (AWS), programming for data science, and machine learning. His publications span topics like election prediction using Twitter data, spatial analysis of climate phenomena (El Niño), and optimizing urban transit infrastructure. While no specific awards are listed, his work reflects interdisciplinary innovation at the intersection of geography, technology, and society. He advises students in CISE's data science and geospatial programs through courses like IA340 Data Mining and GEOG215 Cartography.

Jing YaoView profile

Professor

• Geographic Information Science
• Spatial Analysis
• Spatial Statistics
• +5 more

Professor Jing Yao is a leading academic in Urban Analytics and Geographic Information Science at the University of Glasgow, affiliated with the Urban Big Data Centre. She holds a PhD in Geography from Arizona State University (ASU) and advanced degrees in GIS from Nanjing University. Her research focuses on spatial optimization, health geography, and urban planning, with applications in emergency service location modeling, environmental monitoring, and socio-spatial equity. Education: PhD in Geography (ASU), MSc Industrial Engineering (ASU), MSc & BSc GIS (Nanjing University). Research: Specializes in spatial analysis, GeoAI, and urban-rural disparities. Recent work includes optimizing emergency medical services, analyzing pandemic impacts on urban resilience, and tracking global rangeland conditions via big data. Grants & Collaborations: Principal Investigator for projects on rangeland tracking (£11,970) and healthy urban spaces (£9,800). Co-Investigator in ESRC-funded Urban Big Data Centre and GCRF SHLC. Supervises PhD students in spatial optimization and GeoAI. Hosts visiting scholars from Chinese institutions. Teaching & Training: Leads postgraduate courses on GIS, spatial analysis, and urban research methods at the Urban Big Data Centre.

• Artificial Intelligence
• Machine Learning
• Spatial Reasoning
• +3 more

Dr. Paulo Santos is a Senior Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence with a focus on explainable AI systems. He holds a PhD from Imperial College London (2003) and has over 20 years of research experience in spatial reasoning, machine learning, and robotics. His work bridges knowledge representation with deep learning to enhance transparency in AI decision-making. Dr. Santos has led research groups in Brazil, collaborated internationally, and secured funding from organizations like the British Council and EU. His expertise spans robotics, computer vision, and cognitive science. Notable achievements include the British Computer Science Machine Intelligence Prize (2004) and the Santander Prize for Science and Innovation (2006). Research interests include reinforcement learning for autonomous underwater vehicles (AUVs), scene graph generation in computer vision, and spatial reasoning for multi-robot systems. Recent work emphasizes sim-to-real transfer learning and fault recovery in underwater robotics.

• Biosecurity
• Veterinary Epidemiology
• Statistical Modeling
• +4 more

Dr. Devindri Perera is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences (EECMS) within the Faculty of Science and Engineering. He is also affiliated with the Office of the Provost, demonstrating administrative and academic leadership roles. His research focuses on interdisciplinary areas including biosecurity systems, veterinary epidemiology, statistical modeling, and genomics. Dr. Perera's work spans environmental science (biosecurity border management), veterinary medicine (equine health and endocrinology), and computational methods (data clustering, statistical algorithms). His biosecurity research emphasizes risk assessment and spatial-temporal analysis of non-indigenous species, while his veterinary studies investigate equine physiology and disease mechanisms. In genomics, he contributes to identifying genetic markers for neurological disorders like multiple sclerosis. His publications from 2006–2023 reflect a strong focus on statistical methodologies in interdisciplinary contexts, including genome-wide association studies, algorithm validation for genotyping, and applied econometric models. This demonstrates a blend of theoretical rigor and practical problem-solving across diverse domains. Though no specific awards or grants are listed in this profile, his prolific publication record and cross-disciplinary approach highlight sustained academic engagement. His research collaborations span institutions globally, addressing both environmental and biomedical challenges.

• Health Economics
• Spatial Economy
• Microeconomics under Uncertainty
• +5 more

Felipa de Mello-Sampayo is an Assistant Professor in the Department of Economics at ISCTE - University Institute of Lisbon and an integrated researcher at BRU-Iscte (Business Research Unit). She specializes in health economics, spatial analysis, and microeconomic modeling with applications across various social science domains. Her research bridges theoretical economic frameworks with empirical applications to address real-world healthcare and policy challenges. Dr. de Mello-Sampayo earned her Aggregation in Economics from the University of Lisbon's Higher Institute of Economics and Management in 2024, following a PhD in Economy from the University of Birmingham (2001), a Master's degree in International Economy from the same institution (1998), and a Bachelor's degree in Management from the Higher Institute of Economics and Management - UTL (1994). Her doctoral thesis was published in The British Library. Her research focuses on microeconomic models and their empirical applications, particularly in health economics and spatial analysis. She has made significant contributions to understanding healthcare accessibility through spatial interaction models, cost-effectiveness of medical interventions, and the economic implications of healthcare delivery systems. Her work often examines decision-making under uncertainty, applying real options theory to healthcare contexts. She has coordinated research projects including 'Health and Economic Growth' (PTDC/EGE-ECO/104157/2008) funded by the Foundation for Science and Technology (FCT), and has co-edited special issues for journals including Sustainability and the International Journal of Environmental Research and Public Health. Analysis of her 15 most recent publications reveals a consistent focus on spatial econometrics applied to healthcare accessibility, cost-effectiveness analysis of medical interventions, and economic modeling of healthcare decision-making. Her work spans diverse geographic contexts including Portugal, the United States (particularly Texas), BRICS countries, and China. A distinctive feature of her research is the application of spatial interaction models to healthcare accessibility questions and the use of real options theory to analyze timing decisions in medical contexts. Dr. de Mello-Sampayo is affiliated with the Data Analytics Group at ISCTE and contributes to the BRU-Iscte research unit. Her work demonstrates strong interdisciplinary connections between economics, public health, spatial analysis, and healthcare management, with publications appearing in high-quality journals across these fields.

Jennifer (Jenny) HutchingsView profile

Professor

• Sea Ice Dynamics
• Sea Ice Mechanics
• Climate Modeling
• +3 more

Jennifer (Jenny) Hutchings is a Professor in the College of Earth, Ocean, and Atmospheric Sciences (CEOAS) at Oregon State University, specializing in sea ice dynamics and mechanics through field-based validation of rheological models for climate investigations and ice forecasting. She earned her Ph.D. in Remote Sensing and B.S. in Physics from University College London, establishing foundational expertise in polar remote sensing and physical oceanography. Dr. Hutchings' research centers on Arctic sea ice deformation mechanisms, ocean-atmosphere interactions under evolving ice cover, and climate feedbacks related to mechanical property changes. Her work integrates in-situ field measurements with numerical modeling to understand declining sea ice volume, with emphasis on improving rheological representations in climate systems. She leads the Ice Watch program for standardized visual sea ice observation archiving. Current projects include discrete element modeling (Siku model), drifting buoy networks for deformation monitoring, and multi-source data synthesis to analyze Pacific Arctic sea ice changes. Her research directly addresses forecasting improvements for ice drift, thickness redistribution, and pressured ice conditions across spatial scales. Analysis of her 15 most recent publications reveals consistent focus on Arctic sea ice mechanics through integrated field-model approaches. Key themes include deformation process quantification, rheological model validation, and climate feedback analysis, with significant contributions to understanding 2006-2015 Arctic sea ice anomalies and model deficiencies. The available text does not specify graduate student advising activities or research grant details, though her leadership in major field campaigns implies active mentorship and funding acquisition. Dr. Hutchings has directed or participated in critical field programs including SIPEX-II (interdisciplinary Antarctic campaign), SEDNA (Arctic aerial/surface surveys), and Ice Station Polarstern (Weddell Sea buoy deployments), generating foundational datasets for the sea ice community through international collaborations.

• Regional Economics
• Input-Output Analysis
• Tourism Economics
• +4 more

Andre Carrascal Incera is a Researcher at the Department of Fundamentals of Economic Analysis, part of the Faculty of Economic and Business Sciences at the University of Santiago de Compostela. His research focuses on regional economics, input-output models, and the economic impacts of tourism and globalization. He holds a PhD from the same university, where he studied tourism and income distribution using general equilibrium models applied to Galicia's economy. His work spans topics such as economic resilience, pandemic effects, and interregional inequality. Education: PhD in Economics, University of Santiago de Compostela (2014) Research Interests: Regional economic dynamics Input-output analysis Tourism’s role in regional economies Economic modeling of pandemics Environmental externalities Advising/Grants: No formal advisees or grants listed. Collaborations include the GAME (Economic Analysis and Modeling Group). Labs/Teams: Member of the GAME group, focusing on economic modeling and regional development.

• Remote Sensing
• Land Cover Classification
• Deep Learning
• +4 more

Huiran Jin is an Associate Professor in the School of Applied Engineering and Technology at New Jersey Institute of Technology (NJIT). Her research focuses on remote sensing, land cover classification, and environmental modeling, with a strong emphasis on integrating multi-sensor data and machine learning techniques. She has secured federal grants from NSF and USGS for projects addressing riparian ecosystem dynamics and harmful algal blooms. Her work spans applications from solar image generation using GANs to geospatial education frameworks promoting diversity and inclusion in STEM. Her research interests include environmental monitoring using remote sensing technologies such as VIIRS, Landsat, and LiDAR, as well as cognitive strategies in engineering education. Notable contributions include fusion of optical/radar/LiDAR data for land cover mapping and assessing spatiotemporal variations of environmental parameters like PM2.5 and PM10 in China. Her articles reflect interdisciplinary trends in geospatial science, combining environmental data analysis with educational innovations. Recent projects highlight deep learning applications for flood monitoring and subpixel urban mapping. Jin has collaborated internationally on ecosystem dynamics and hydroclimate variability studies. Her work has been supported by grants totaling over $1M, including a 7-year NSF project (2018-2025) and a 2023 USGS-funded study on harmful algal blooms in NJ lakes. She has published extensively in journals like ISPRS Journal of Photogrammetry and Remote Sensing, with over 500 citations and an h-index of 11.

Sarah JacksonView profile

Professor

• Anthropological Archaeology
• Mesoamerican Archaeology
• Maya Archaeology
• +5 more

Sarah Jackson is Professor and Divisional Dean for Social Sciences in the College of Arts and Sciences at the University of Colorado Boulder, where she joined the Department of Anthropology in 2023. Previously, she held academic positions at the University of New Hampshire, University of Toronto, and University of Cincinnati. With a PhD from Harvard University (2005), she is an anthropological archaeologist specializing in ancient Mesoamerica, particularly Classic Maya culture. Her research explores materiality, ancient identities, ontologies, and personhood (including non-human persons), indigenous political organization, and the negotiation of culture change. Methodologically, she works at the intersection of text and material record, bringing together theoretical ideas with archaeological field practices. Her current work reconstructs aspects of a Classic Maya material worldview, investigating how indigenous material perspectives might transform archaeological field practices. Her recent publications reveal a consistent focus on understanding Maya perspectives on material culture, text, and space. Jackson's work increasingly examines how modern archaeological interpretations can be enhanced by incorporating indigenous ontological frameworks, particularly through innovative digital recording systems that unite archaeological and Maya views on material culture. She co-directs an archaeological project at Say Kah, Belize with Dr. Linda Brown, funded by Wenner-Gren, National Geographic Society/Waitt, National Geographic Society (CRE), American Philosophical Society, Brennan Foundation, and Rust Family Foundation. Her fieldwork integrates theoretical approaches with practical archaeological methods, developing new ways to document and interpret Maya sites. While actively engaged in research and academic administration, Dr. Jackson is currently not accepting PhD applicants due to her administrative responsibilities as Dean of Social Sciences.

• Air Transportation
• Queueing Theory
• Simulation
• +5 more

John F. Shortle is a Professor and Chair in the Department of Systems Engineering and Operations Research at George Mason University (GMU), part of the Volgenau School of Engineering. He specializes in applying queueing theory and stochastic processes to aviation safety, air transportation systems, and energy systems. Shortle has led major research initiatives funded by the FAA, NASA, and the Department of Energy, focusing on improving air traffic safety through advanced simulation and risk analysis techniques. Affiliations: Center for Air Transportation Systems Research (CATSR), GMU Education: PhD (UC Berkeley), MS (UC Berkeley), BS (Harvey Mudd College) Research Interests Shortle’s work emphasizes simulation methodologies, queueing theory applications, and stochastic modeling for critical infrastructure systems. Key areas include: Collision risk analysis in air transportation Aviation safety modeling (e.g., wake turbulence, event tree analysis) Energy systems reliability (e.g., blackout analysis) Autonomous systems validation Publications & Awards He co-authored the widely used textbook Fundamentals of Queueing Theory (5th ed., Wiley, 2018) and holds over 100 peer-reviewed publications. Notable awards include the Daniel H. Wagner Prize (2000) and the Military Operations Research Journal Award (2016). Leadership & Service President, INFORMS Simulation Society (2016–2018) Board Member, Winter Simulation Conference (2023–present) Editorial roles: IEEE Transactions on Reliability , Journal of Probability and Statistical Science Teaching Teaches advanced courses in stochastic processes (OR 645), queueing theory (OR 647), and dynamic systems (SYST 320).

• Political Economy
• Voting Behavior
• Immigration
• +3 more

Carlotta Berti Ceroni serves as Full Professor and Director of the Department of Economic Sciences at the University of Bologna, operating under scientific-disciplinary sector ECON-01/A (Political Economy). Based at Piazza Scaravilli 2 in Bologna, she maintains active academic engagement with scheduled office hours including exam viewings through 2025. Her research critically examines political economy through empirical analysis of voting behavior, emphasizing how immigration exposure , income stratification , and family structures shape electoral participation. Using precinct-level data, she investigates neighborhood heterogeneity effects and gendered turnout gaps, with recent work focusing on Northern Italy's socio-political dynamics. Her methodology bridges economics and political science to dissect democratic engagement mechanisms. Analysis of her 15 most recent publications reveals three dominant thematic clusters: (1) Immigration-voting nexus studies (2020-2024) exploring proximity effects and ethnic diversity; (2) Income-turnout relationships (2016-2022) analyzing regional disparities and resistance to change; (3) Political persistence frameworks (2009-2014) connecting institutional continuity to economic innovation. These threads consistently address heterogeneity , power structures , and democratic responsiveness across temporal scales.

• Macroecology
• Plant trait evolution
• Community dynamics
• +3 more

Meelis Pärtel is a full Professor of Botany at the University of Tartu’s Institute of Ecology and Earth Sciences, affiliated with the Faculty of Science and Technology. He has held this position since 2002, with continuous academic service at the university since 1991. His career includes roles such as Editor-in-Chief of prominent journals like Journal of Vegetation Science and leadership in national and international ecological organizations. Education: PhD in Botany (1997, University of Tartu), postdoctoral studies at the University of Regina (Canada) and Uppsala University (Sweden). Honors: Estonian State Science Awards (2024, 2009), Order of the White Star (2023), and Academia Europaea Young Scientist Award (1996). Research focuses on macroecology , plant trait evolution , and dark diversity theory . He explores how environmental heterogeneity and historical processes shape biodiversity. Key themes include community assembly rules, conservation strategies for plant diversity, and impacts of global change. Recent work emphasizes dark diversity —species expected but absent in local communities—and its implications for conservation. His studies span global grasslands, tropical forests, and temperate ecosystems, addressing biodiversity loss mechanisms. Notable projects include analyzing drought impacts on grasslands and quantifying functional diversity changes. Publications highlight methodological advancements in dark diversity modeling and collaborative global ecology initiatives. Supervised over a dozen postdoctoral researchers, fostering international collaborations in biodiversity research.