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Francesca BorgoView profile

Lecturer

• Early Modern Art
• Renaissance Visual Culture
• Material Culture
• +2 more

Francesca Borgo is Lecturer in Art History at the University of St Andrews, specializing in early modern visual culture with particular expertise in Renaissance art and material studies. She holds a Ph.D. from Harvard University and has held fellowships at leading research institutes including Villa I Tatti and the Getty Research Institute. Borgo's research examines intersections between art, science, and material culture in fifteenth and sixteenth-century Europe. Her current projects investigate representations of war in Renaissance art and historical perceptions of fragile or decaying artworks. Recent publications analyze zoomorphic armor ornamentation, soundscapes in Leonardo's battle paintings, and waste reuse in artistic workshops. Her scholarly work demonstrates consistent engagement with Leonardo da Vinci's legacy, Vitruvian principles of scale, and material transformations in artistic production. Recent articles explore sensory dimensions of Renaissance art and theoretical challenges in representing human proportions. Borgo co-directs research projects on Renaissance embodiment theories and coordinates collaborative initiatives on material reuse in early modern practices. She contributes to digital art history through open-access publications and database development.

Tiago A. MarquesView profile

Research Fellow

• Ecological Statistics
• Marine Mammal Ecology
• Population Density Estimation
• +3 more

Dr. Tiago A. Marques is a Senior Research Fellow at the School of Mathematics and Statistics, University of St Andrews, UK, and an invited professor at DEIO (Universidade de Lisboa, Portugal). He specializes in Ecological Statistics , focusing on population density estimation using passive acoustic data and distance sampling methods. His work spans marine mammals (cetaceans, polar bears), fish, birds, and other wildlife. Key projects include DECAF (cetacean abundance via passive acoustics) and LATTE (cetacean behavior and human noise impact analysis). Education: Biologist by training, with an MSc and PhD in Statistics. Research Interests: Ecological statistics, acoustic monitoring, conservation biology, and statistical methodology dissemination. Key Contributions: Developed distance sampling software tools, pioneered methods for integrating acoustic data into ecological surveys, and led polar bear population studies in the Arctic. Collaborates globally on wildlife conservation and statistical ecology. Labs/Teams: CREEM (Centre for Research into Ecological & Environmental Modelling) at St Andrews. Active in open-source tool development, including R packages and GitHub repositories like DeepDiverCueRates .

Annette VeeView profile

Associate Professor

• Computation and Writing
• Digital Humanities
• Coding Literacy
• +6 more

Annette Vee is an Associate Professor of English and Director of the Composition Program at the University of Pittsburgh, housed in the Kenneth P. Dietrich School of Arts & Sciences. She specializes in the intersection of computation and writing, with affiliations to the DSAM Certificate, Forbes Corridor Digital Initiative, Humanities Engage, Pitt Cyber, and STEM Coding Lab. Her research explores coding literacy, blockchain, AI-based text generation, and automated writing systems, with a focus on their implications for education, law, and rhetoric. Key publications include Coding Literacy: How Computer Programming is Changing Writing (MIT Press, 2017) and co-edited TextGenEd: Teaching with Text Generation Technologies (2023). Current projects include a monograph on the historical pursuit of automating writing and a co-curated digital exhibit on the 1966 Dartmouth Seminar. She teaches courses like Digital Humanity and Computational Media , emphasizing digital composition and critical engagement with technology. Vee’s work bridges disciplines, examining how computational systems reshape literacy, pedagogy, and societal trust. She has led a Mellon-funded Sawyer Seminar on information ecosystems and collaborates across computer science and humanities departments to design interdisciplinary programs like the Digital Narrative and Interactive Design major. Her research also addresses ethical concerns in AI, automated writing’s impact on political discourse, and the legal frameworks governing code. Vee advocates for open-access publishing and has published widely in journals like Computational Culture , Interfaces , and Literacy in Composition Studies .

Liudas GiraitisView profile

Professor

• Econometrics
• Time Series Analysis
• Quantitative Methods
• +3 more

Liudas Giraitis is a Professor of Econometrics at Queen Mary University of London, affiliated with the School of Economics and Finance. He holds a PhD from Vilnius University and has extensive research experience at Heidelberg University, Boston University, and the London School of Economics. His research focuses on econometrics and quantitative methods, emphasizing long memory processes, ARCH models, semiparametric inference, and time-varying random coefficient models. He has published extensively in leading statistical and econometric journals. His work bridges econometrics, statistics, and probability theory, with a strong emphasis on time series analysis and asymptotic theory. Recent research explores forecasting under ongoing structural change, heteroscedasticity testing, and dynamic stochastic general equilibrium (DSGE) models with financial frictions. Education: PhD in Econometrics from Vilnius University Key Research Themes: Long memory processes, ARCH/GARCH models, time-varying models, nonstationary time series, and asymptotic theory Affiliations: Queen Mary University of London, School of Economics and Finance Research Interests: Dr. Giraitis’s work addresses theoretical and applied challenges in econometric modeling, including robust inference for time series with general heterogeneity, cyclical time series analysis, and the development of asymptotic frameworks for dependent data. His contributions span both foundational theory and practical applications in finance and macroeconomics. Publications: Over 50 peer-reviewed articles in journals such as Journal of Econometrics , Annals of Statistics , and Journal of Time Series Analysis . Key works include the monograph Large Sample Inference for Long Memory Processes (2012) and recent studies on time-varying volatility and structural change. Lab/Team: Active in the School of Economics and Finance’s research group on econometric theory and applied time series analysis.

Clemente MarconiView profile

Professor

• Ancient Greek and Roman Art
• Archaic and Classical Greek Architecture
• Mediterranean Archaeology
• +4 more

Clemente Marconi is the James R. McCredie Professor in the History of Greek Art and Archaeology and University Professor at New York University's Institute of Fine Arts, as well as a Full Professor of Classical Archaeology at the University of Milan. His research focuses on ancient Greek and Roman art, with an emphasis on Archaic and Classical Greek architecture, Sicilian archaeology, and cultural property repatriation. He directs excavations at Selinunte, Sicily, and chairs the Seminar on Ancient Art and Archaeology. Marconi holds prestigious academic affiliations including membership in the Accademia Nazionale dei Lincei and the Academia Europaea. Education: B.A. (1990) from University of Rome La Sapienza; Ph.D. (1997) from Scuola Normale Superiore, Pisa. His interdisciplinary methodology integrates semiotics, anthropology, and hermeneutics to contextualize ancient art within broader cultural frameworks. Recent projects include the Selinunte excavations (since 2006) and a forthcoming exhibition on Picasso's engagement with classical antiquity. Research interests span Greek temple decoration, colonial archaeology, and the social function of monuments. Key publications include Temple Decoration and Cultural Identity in the Archaic Greek World (2007) and The Oxford Handbook of Greek and Roman Art and Architecture (2015). His excavations at Selinunte have revealed critical insights into Punic-Greek interactions and temple biography. Professional contributions include mentoring graduate students involved in international networks, such as the American School of Classical Studies in Athens. Awards and honors reflect his disciplinary leadership, including his role as corresponding member of the German Archaeological Institute.

Emma TowlsonView profile

Assistant Professor

• Network Neuroscience
• Brain Networks
• Mental Health
• +3 more

Dr. Emma Towlson is an Assistant Professor in the Department of Computer Science at the University of Calgary's Faculty of Science, serving as Assistant Head of Undergraduate Curriculum. She holds a Full Member position at the Hotchkiss Brain Institute and is a Child Health & Wellness Researcher at the Alberta Children's Hospital Research Institute. Her research focuses on network neuroscience, exploring how brain networks' structure-function relationships underpin health and disease. Key areas include network control theory, mental illness vulnerability, and brain connectivity analysis across species. Dr. Towlson's work bridges computer science, physics, neuroscience, and biology. She investigates structural brain networks' topological features (e.g., rich clubs, modules) and their spatial constraints, applying these insights to disorders like schizophrenia, depression, and Alzheimer's. Her lab uses network control principles to identify therapeutic targets for brain stimulation therapies and personalized medicine approaches. Recent grants include a $250,000 New Frontiers in Research Fund (NFRF) Explorations grant (2022) to study preterm birth's impact on brain networks and mental illness risk. She teaches courses on social network analysis (CPSC 572/672) and data visualization (DATA 601). Collaborative efforts include partnerships with Harvard Medical School and Monash University's Turner Institute. Her team’s interdisciplinary projects include analyzing mouse brain connectomes, simulating connectome perturbations, and developing open-source network neuroscience tools. Ongoing work emphasizes translating network science insights into clinical applications for mental health interventions.

Peter KedronView profile

Associate Professor

• Spatial Analysis
• Economic Geography
• GIScience
• +3 more

Peter Kedron is an Associate Professor in the Department of Geography at the University of California, Santa Barbara (UCSB), and a member of the Center for Spatial Data Science. Previously, he held faculty positions at Arizona State University (2018–2023), Oklahoma State University (2016–2018), and Ryerson University (2012–2016). He earned his Ph.D. in Geography from SUNY Buffalo, an MA in Economics from the University of Michigan, and BAs in Economics and Psychology from SUNY Buffalo. His research focuses on spatial analytical methods, particularly replication in geographic research, and improving evidence accumulation through statistical approaches. Key areas include computational reproducibility, spatial causal inference, and the integration of replication into GIScience education. He has published over 55 peer-reviewed articles and been consistently funded by the National Science Foundation (NSF). Dr. Kedron emphasizes bridging spatial data science with policy relevance, addressing challenges in urban inequality, environmental conservation, and healthcare accessibility. His work often employs cutting-edge techniques like digital twins, machine learning, and multi-source remote sensing to address complex spatial problems. He has supervised over 20 graduate students and post-doctoral scholars, fostering a collaborative environment. Notable contributions include frameworks for reproducible geospatial research and studies on urban-rural disparities, wildfire risk, and renewable energy sector dynamics. Labs/Teams: Active in UCSB’s Center for Spatial Data Science and collaborates with interdisciplinary teams on projects funded by NSF and industry partnerships.

Jin ZhuView profile

Researcher

• Reinforcement Learning
• Machine Learning
• Statistical Software Development
• +3 more

Jin Zhu is a Researcher in the Department of Statistics at the London School of Economics and Political Science (LSE), working with Prof. Chengchun Shi on reinforcement learning and machine learning. His research focuses on developing algorithms with statistical and computational guarantees, alongside statistical software design to enhance algorithmic applications. Prior to LSE, he earned his PhD in Statistics at Sun Yat-Sen University under Dr. Xueqin Wang and Dr. Na You. Key expertise includes reinforcement learning, machine learning, and computational statistics. His work addresses challenges in off-policy evaluation, robustness in RL, and sparsity-constrained optimization. He has contributed to open-source tools like skscope and abess for efficient statistical computation. Research interests also span causal inference, high-dimensional data analysis, and algorithmic design for complex systems. Notable contributions include methodologies for genetic factor identification, spatial experimental design, and nonparametric statistical inference. Jin’s research bridges theoretical advancements with practical software implementations to address real-world computational and statistical challenges.

Xavier OchoaView profile

Assistant Professor

• Learning Analytics
• Multimodal Learning Analytics
• Artificial Intelligence in Education
• +3 more

Xavier Ochoa is an Assistant Professor of Learning Analytics and Doctoral Program Coordinator at the Steinhardt School of Culture, Education, and Human Development, New York University. He holds a Ph.D. in Engineering (Computer Sciences) from the University of Leuven, Belgium (2008), an M.Sc. in Applied Computer Sciences from Vrije Universiteit Brussels (2002), and a B.S. in Computer Science from ESPOL, Ecuador (2000). His research focuses on Multimodal Learning Analytics, blending AI, sensors, and educational practices to enhance learning environments. He leads the Augment-Ed research group and has held roles such as Vice-President of SoLAR and Editor-in-Chief of the Journal of Learning Analytics. His academic career includes over a decade at ESPOL, where he directed the Information Technology Center and TEA research group. Awards include Best Researcher (2012, 2018), Best Professor (2013), and IEEE’s Best Researcher in Computer Science (2014). His work emphasizes tools for self-reflection, decision-making, and 21st-century skill development in education. Education: Ph.D. (2008, KU Leuven), M.Sc. (2002, VUB), B.S. (2000, ESPOL) Labs/Teams: Augment-Ed Research Group, Former Lead of TEA Group Key Contributions: RAP system for oral presentation feedback, OpenOPAF open-source tool, CrossMMLA initiatives Xavier’s research bridges education and technology, with publications in journals like the Journal of Learning Analytics and conferences such as LAK. His work addresses challenges in collaborative learning, feedback systems, and scalability of learning analytics tools.

• Hydrogeology
• Engineering Geology
• Quaternary Geology
• +6 more

Bjørn Syvert Frengstad is a Professor of Engineering Geology at NTNU's Department of Geosciences within the Faculty of Engineering. He currently serves as Head of the Department of Engineering Geology and Rock Mechanics and leads the Natural Hazards Group under NTNU's Civil Safety and Emergency Preparedness strategic focus area. His academic career includes 19 years at the Geological Survey of Norway (NGU), including five years as Head of the Groundwater Division, and prior research roles at NTH and NTNU from 1990–2001. Research focuses on hydrogeology of loose materials, geothermal energy, Quaternary geology, environmental geochemistry, and groundwater utilization. He leads major projects like EnerGizerS (CO2-enhanced geothermal systems) and Bømoen Plusbygd (integrated groundwater use). Teaching includes courses on engineering geology, hydrogeology, and geothermal energy systems. Over 150 scientific publications span applied geology topics such as groundwater chemistry, geothermal systems, slope stability, and environmental geochemistry. Advised 5 PhD students as main/co-supervisor and actively involved in master's and specialization projects. Recognized for expertise in geohazards, energy storage solutions, and sustainable groundwater management.

Joseph BlankinshipView profile

Associate Professor

• Soil biogeochemistry
• Microbial ecology
• Soil carbon sequestration
• +4 more

Dr. Joseph 'Joey' Blankinship is an Associate Professor in the Department of Environmental Science at the University of Arizona's College of Agricultural, Environmental, and Life Sciences (CALES). He leads the Desert Agriculture Soil Health Initiative (DASHI), focusing on soil microbial roles in ecosystem services like carbon sequestration and greenhouse gas regulation. His research spans biogeochemistry, arid agriculture, and climate change impacts. Education: B.A. Environmental Sciences, University of Virginia (2002) Ph.D. Biology, Northern Arizona University (2009) Postdoctoral studies at UC Merced and UC Santa Barbara Research Interests: Blankinship's work integrates biology, chemistry, and engineering to address desert soil challenges. Key areas include soil aggregate stability, microbial-driven nutrient cycling, and biochar applications. Recent studies explore irrigation impacts on soil carbon in arid croplands and post-wildfire reforestation using biochar and nurse shrubs. Article Trends: Publications emphasize soil carbon dynamics, biochar optimization, and desert agroecosystem resilience. Key themes include threshold effects of biochar rates, synergies between organic amendments and microclimate, and practical soil health metrics for arid regions. Awards: First Place Graduate Poster SWESx (2018) Second Place Undergraduate Poster SWESx (2018) Grants/Advising: Leads projects funded by USDA, NSF, and industry partners. Advised numerous graduate students in soil ecology and biogeochemistry. Labs/Teams: The Blankinship Soil Health Group collaborates with USDA NRCS, Arizona Dust Coalition, and international soil databases like ISRaD.

Brian YoungView profile

Associate Professor

• Scholarly Communication
• Library Collections
• Data Literacy
• +7 more

Brian Young is the Head and Associate Professor of Scholar Support and Data Services at the University of Mississippi's J. D. Williams Library. He serves as the School of Engineering liaison and plays a key role in collection development, research support, and information literacy instruction. His responsibilities include leading data services, teaching first-year writing courses, and providing virtual reference support. His research focuses on scholarly communication , library collections , and the tensions between access and sustainability in academic libraries. Key areas include data literacy education , open educational resources (OER) , user behavior analysis , and innovative instructional methods such as gamification. He has developed numerous research guides across engineering, sciences, and humanities disciplines. Brian’s recent publications reflect a strong trend in user-centered library services , assessment methodologies , and pedagogical innovation . His work explores how students and faculty interact with library resources, evaluates new collection models like PDA/DDA, and experiments with creative outreach such as Dungeons & Dragons-themed library instruction modules. He actively contributes to library science through peer-reviewed research but no formal scientific awards are listed in the available materials. In his advisory and service roles, Brian supports faculty through OER assessment, provides research consultations, and leads instructional initiatives. He teaches information literacy in first-year writing and engineering programs, and supports graduate students across disciplines. Though not explicitly stated, his leadership in Scholar Support and Data Services implies oversight of related programs and staff. He does not appear to advise formal thesis or dissertation students, based on available data. Brian is involved in the Methods & Analysis Lab and supports data services across campus. His work integrates with the Research and Instruction Services department, where he contributes to instruction and reference. While no independent lab or research team is named, his role suggests leadership in shaping institutional data literacy and research support infrastructure.

• Cognitive-Computational Neuroscience
• Threat Forecasting
• Threat Avoidance
• +12 more

Prof. Dr. Dr. Dominik R. Bach is a full Professor and Principal Investigator at the Hertz Chair for Artificial Intelligence and Neuroscience (CAIAN) at the University of Bonn , and also leads the Threat Avoidance group at the Wellcome Centre for Human Neuroimaging, University College London . He is based in Bonn, Germany, and his research is part of the Transdisciplinary Research Area 'Life and Health' at the University of Bonn. His research focuses on cognitive-computational neuroscience , particularly the computing architecture of the human mind and brain in the context of threat forecasting and avoidance . He employs serious games, virtual reality (VR) , and tightly controlled associative learning setups to study how humans avoid real threats, and how this system malfunctions in conditions like anxiety disorders and PTSD . His theoretical models are inspired by those used in artificial agents . His recent publications, in journals like Nature Communications and Biological Psychiatry , show a strong trend in using neuroimaging (fMRI, MEG) and intervention techniques (e.g., transcranial stimulation) to understand and modulate aversive memory and decision-making under threat. His work bridges computational theory, experimental psychology, and clinical applications. Email: d.bach@uni-bonn.de ORCID: 0000-0003-3717-2036 Lab Website: bachlab.org Twitter: @bachlab_cog He is actively recruiting PhD students and postdocs, indicating a vibrant and expanding research team. He has developed open-source tools like the CogLearn Toolkit for Unity for VR-based avoidance learning, demonstrating a commitment to open science.

Anya Helene BaggeView profile

Associate Professor

• Programming Language Design and Implementation
• Software Language Engineering
• Semantics of Programming Languages
• +8 more

Anya Helene Bagge is an Associate Professor in the Department of Informatics at the University of Bergen, where she is a researcher at the Bergen Language Design Laboratory. Her work focuses on programming languages and software language engineering, with strong ties to education and tool development. Research Interests: Programming language design and implementation Software language engineering Semantics of programming languages Domain-specific languages and language extensions Program transformation using Rascal, MPL, and Stratego/XT Aspect-oriented programming, especially Domain-Specific Aspect Languages Her recent publications reflect a consistent focus on software language engineering, refactoring, microservice security, and programming education. Themes across her work include language design, program analysis, and the development of educational tools and methodologies. Scientific Awards: The Realist Committee's Teaching Award 2016/17 Lecturer of the Year in Computer Science (Spring 2015) Anya Bagge actively supervises students, including PhD and Master’s candidates such as Tero Hasu, Kristoffer Haugsbakk, and Nina Andersen. She has been involved in numerous academic activities, including organizing the OOPSLE workshop and serving on program committees for conferences like SLE, HILT, and WCRE. She has also taught core courses including INF101, INF225, and INF328, demonstrating a strong commitment to both research and teaching. Labs and Teams: She is affiliated with the Bergen Language Design Laboratory , collaborating with researchers such as Magne Haveraaen, Eva Burrows, and Tero Hasu.

• Climate Change and Health
• Biometeorology
• Heat Stress
• +3 more

Dr. Claudia Di Napoli is a researcher at the University of Reading specializing in climate-health interactions, with a focus on biometeorology and heat stress impacts. She serves as a key contributor to the Lancet Countdown on Health and Climate Change , an international research collaboration tracking climate-health indicators across 44 organizations. Her work bridges meteorological science and public health through operational climate services development. Her research centers on thermal comfort indices , heat stress epidemiology , and climate reanalysis applications for health protection. Notable contributions include developing the ERA5-HEAT global dataset and Thermofeel open-source library for thermal stress assessment. She investigates regional vulnerabilities from Caribbean heatwaves to European mortality patterns, emphasizing urban environments and occupational exposure risks while advancing methodologies for climate service integration into health systems. Analysis of her 15 most recent publications reveals three dominant trends: (1) operationalization of climate data for health decision-making through tools like Thermofeel; (2) rigorous validation of reanalysis models against health outcomes; and (3) exploration of compound hazards (e.g., heatwaves concurrent with wildfires or pandemics). Her work consistently addresses equity dimensions of climate vulnerability, with increasing focus on transboundary risks and Global South impacts. Dr. Di Napoli actively collaborates with the World Health Organization, European Centre for Medium-Range Weather Forecasts (ECMWF), and Global Heat Health Information Network. Her advisory role in the Lancet Countdown involves mentoring early-career researchers across 20+ countries and securing multi-institutional grants for climate-health monitoring systems. Recent projects include heatwave forecasting during the COVID-19 pandemic and Caribbean climate vulnerability assessments funded by UK Research and Innovation. She co-leads the University of Reading's climate-health analytics team within the European Climate Assessment & Dataset (ECA&D) initiative, developing real-time thermal stress monitoring frameworks adopted by public health agencies in 12 countries. Her group maintains partnerships with the International Society of Biometeorology and WHO's Global Heat Health Information Network for operational tool deployment.