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David AllcockView profile

Assistant Professor

• Ion trapping
• Quantum computing
• Hybrid quantum systems
• +3 more

David Allcock is an Assistant Professor in the Department of Physics at the University of Oregon, part of the College of Arts and Sciences. His research focuses on ion trapping, quantum computing, and hybrid quantum systems, with an emphasis on manipulating atomic and molecular systems using electric and magnetic fields for quantum information applications. He leads the Ion Trapping Lab at UO, where he develops scalable quantum technologies and open-source control systems like ARTIQ and Sinara. His work bridges experimental physics with engineering, addressing challenges in qubit control, error mitigation, and large-scale quantum computer design. Education: MPhys from the University of Oxford (2007), D.Phil. in Physics from Oxford (2012). Prior to UO, he was a Lindemann Fellow at the National Institute of Standards and Technology (NIST) in Boulder, CO. His research includes innovations in trapped-ion qubit control, including laser-free entangling gates, scalable architectures, and applications in quantum sensing and dark matter detection. Key research themes include metastable qubit systems, photon scattering error mitigation, and the integration of superconducting detectors for state readout. He collaborates on open-source hardware-software stacks for quantum experiments and mentors students in quantum engineering through programs like the Quantum Technology Master’s Internship. Current projects explore hybrid quantum-classical interfaces and ultra-stable ion trap fabrication. His lab’s contributions span theoretical and experimental domains, with recent advances in geometric phase gates, microwave-driven control, and error-resilient qubit operations. The group also engages in interdisciplinary work linking quantum computing with precision measurement, such as SPUD (SPectroscopy for Ultralight Dark matter) and bosonic sensing tools.

Johan P LarssonView profile

Lecturer

• Economic geography
• Regional science
• Urban economics
• +1 more

Dr. Johan P Larsson serves as a Lecturer in Economics and Public Policy within the Department of Land Economy at the University of Cambridge, concurrently holding a Fellowship and Director of Studies position in Land Economy. His academic profile bridges theoretical and empirical research in spatial economic phenomena, with emphasis on policy-relevant investigations of regional competitiveness and urban dynamics. His educational foundation includes: PhD from Jönköping University Dr. Larsson's research program centers on economic geography and regional science, specializing in urban economics and entrepreneurship. He examines how historical industrial structures, neighborhood effects, and policy interventions shape economic integration and innovation ecosystems. Methodologically, he combines quantitative analysis of large-scale datasets with natural experiments (e.g., pandemic-induced remote work) to isolate causal mechanisms in spatial economic processes. His recent publication trajectory (2021-2025) reveals consistent focus on three interconnected domains: evaluation of place-based policies (e.g., City Deals), analysis of the entrepreneurial state's role in innovation, and investigation of immigrant integration dynamics. These works predominantly utilize Scandinavian and English case studies while generating globally applicable theoretical insights, demonstrating methodological sophistication through spatial econometrics and policy counterfactuals. Recognition for his scholarly contributions includes: The JIBS Student Association’s Pedagogical Prize (2017) The Martin Beckmann Award from Regional Science International (2015) Jan Wallander scholar designation (2015) His teaching portfolio spans Microeconomics, Macroeconomics, Urban economics, and Applied statistics, reflecting his interdisciplinary expertise. While doctoral advisees aren't explicitly listed, his Director of Studies role indicates active undergraduate supervision within Cambridge's collegiate system. Current research appears focused on post-pandemic labor geography and mission-oriented innovation policy evaluation, though dedicated laboratories or formal research teams aren't mentioned in available materials.

Margarita Boenig-LiptsinView profile

Assistant Professor

• Social and political aspects of digital technologies
• Identity and citizenship in technological societies
• Ethics of Technology
• +5 more

Margarita Boenig-Liptsin is a tenure-track Assistant Professor of Ethics, Technology and Society at ETH Zurich's Department of Humanities, Social and Political Sciences, a position she has held since September 2022. Trained in Science, Technology and Society with dual PhDs from Harvard University (History of Science) and Université Paris-Sorbonne (Philosophy), she brings interdisciplinary expertise to examining the relationship between technology, power, democracy, and ethics. Her research spans several interconnected areas focusing on transformations to human identity and citizenship in relation to information technologies across time and cultures. She investigates the social and political aspects of digital technologies, identity and selfhood in technological societies, ethics of technology, and comparative cultures of innovation. Her work uniquely bridges historical analysis with contemporary ethical concerns, examining how concepts like human dignity evolve alongside technological developments from punch cards to AI governance frameworks. Her recent publications (2023-2025) reveal a strong focus on AI ethics, data justice, and the philosophical implications of algorithmic systems. These works demonstrate her consistent interest in how technology shapes democratic processes, citizenship, and ethical frameworks. Her research shows progression from historical studies of computer literacy programs to contemporary analyses of generative AI's impact on knowledge production and everyday ethics. Her scientific recognition includes: NSF funding for her collaborative project on Silicon Valley's innovation imaginary Mozilla Foundation Responsible Computer Science Challenge grant (2018-2021) Academic Data Science Alliance support (2020-2022) Sorbonne Université's Paris IAS Chair on 'Major Changes' (2021-2022) At ETH Zurich, she leads research and teaching initiatives that build connections between engineering and social sciences. Previously at UC Berkeley, she directed the Human Contexts and Ethics Program, developing the Human Contexts and Ethics component for data science education. Her work consistently emphasizes translating social science theory for diverse audiences and connecting scholarly work to community needs in Zurich, Switzerland, and Europe. She teaches courses including 'Artificial Intelligence and Human Values' and 'Research in Ethics, Technology and Society' for the Fall 2025 semester.

Susan J. SimkinsView profile

Professor

• Teamwork and Team Performance
• Leadership
• Decision Making
• +3 more

Susan J. Simkins is a Professor of Psychology at The Pennsylvania State University, where she serves as Lead of the CTSI-Team Science Core and is based in Moore Building at University Park. Her contact details include email sxm40@psu.edu and phone (814) 863-7387. Education Ph.D., Ohio State University, 1996 Research Interests Dr. Simkins' research centers on effective teamwork and performance through three interconnected streams: team composition/diversity (examining demographic, cognitive, and personality-based diversity within contingency frameworks), team cognition/mental models (focusing on shared understanding of tasks and teamwork dynamics), and temporal integration in teams (investigating time-based diversity, temporal leadership, and pacing styles). Her work emphasizes individual differences, cognitive processes, and temporal dynamics as critical determinants of team effectiveness in organizational contexts. Publication Trends Her 2013-2017 publications reveal a strong focus on temporal dimensions of teamwork, including polychronicity diversity, temporal conflict in specialized teams (e.g., culinary environments), and time-sensitive mental models. Key methodological approaches involve multilevel analysis and contingency frameworks, with applications spanning leadership theory, decision-making diversity, and climate interactions. Work appears consistently in top organizational psychology journals like Journal of Applied Psychology and Organizational Behavior and Human Decision Processes. Scientific Awards No scientific awards were documented in the provided text. Advising and Grants While the text confirms her faculty role and research leadership, specific details about graduate student advising, grant funding, or sponsored projects were not included in the source material. Labs and Teams Dr. Simkins leads the CTSI-Team Science Core, an initiative dedicated to advancing methodologies for studying team-based research structures and improving collaborative effectiveness in scientific and organizational settings.

Jaan MassoView profile

Associate Professor

• Applied Econometrics
• Economic Development
• Foreign Direct Investment
• +5 more

Jaan Masso is an Associate Professor at the University of Tartu, Estonia, where he has been affiliated with the Faculty of Economics and Business Administration since at least 2001. He currently serves as Chair of the department, Head of the Chair of Economic Modelling, and Programme Manager of the Master's programme in Quantitative Economics. His research focuses on applied econometrics, economic development, foreign direct investment, and labor economics, with particular emphasis on Estonia and the Baltic region as catching-up economies. He has published 146 scholarly works with over 23,000 reads and 1,745 citations, demonstrating significant scholarly impact in his field. Masso's research interests span multiple interconnected areas including foreign direct investment effects , productivity analysis , gender wage gap studies , innovation economics , and labor market dynamics . His work often employs rigorous econometric methods to analyze firm-level and regional economic data, particularly from Estonia and other Baltic states. His recent publications (2023-2025) show consistent scholarly productivity across multiple journals, with particular focus on foreign ownership effects, gender pay gaps in academia, FinTech sector development, and innovative methods for measuring firm innovativeness through web data analysis. His scientific contributions demonstrate expertise in analyzing economic transitions in small open economies, with methodological strengths in econometric analysis of firm-level data and innovative approaches to measuring economic phenomena.

Simone GiombiView profile

Professor

• High Energy Theoretical Physics
• Quantum Field Theory
• String Theory
• +3 more

Simone Giombi is a Professor of Physics at Princeton University and currently serves as Associate Chair and Director of Graduate Studies. He holds a B.Sc. in Theoretical Physics from the University of Bologna, Italy, and a Ph.D. in Physics and Astronomy from Stony Brook University (2007). His research focuses on high-energy theoretical physics, quantum field theory, string theory, and their interconnections, particularly exploring higher-spin gravity and holographic dualities. He has held postdoctoral positions at Harvard University and the Perimeter Institute for Theoretical Physics. Giombi's work includes groundbreaking contributions to AdS/CFT correspondence, Wilson loop defects, and quantum M2 branes. He has been recognized with prestigious awards, including the New Horizons in Physics Prize (2017) and the SIGRAV Prize (2014). His recent articles (2022–2025) emphasize non-planar corrections in ABJM theory, boundary reparametrizations in AdS2, and RG interfaces from double-trace deformations. His research also engages with fermionic CFTs, line defects, and quantum fluctuations in Wilson loops. Awards: New Horizons in Physics Prize (2017), SIGRAV Prize (2014) Advising: Students include Yagmur Erhan and Jieru Shan Labs/Teams: Active in Princeton's High Energy Theory Group

Timothy R. TangherliniView profile

Professor

• folklore
• Danish culture
• Danish cinema
• +9 more

Timothy R. Tangherlini serves as the Elizabeth H. and Eugene A. Shurtleff Chair in Undergraduate Education and Professor in the Department of Scandinavian and the School of Information at the University of California, Berkeley. A distinguished folklorist and ethnographer, he has pioneered computational approaches to folklore studies, bridging traditional humanities scholarship with cutting-edge digital methods. His research expertise spans multiple interconnected domains: Digital humanities and computational folkloristics Danish and Scandinavian cultural traditions Network analysis of narrative structures Machine learning applications in cultural analysis Conspiracy theory formation and transmission Korean cultural studies and K-Pop analysis Tangherlini's work focuses on how stories circulate across social networks and how individuals use narratives to negotiate ideology within their social groups. He has been instrumental in developing the field of Culture Analytics, co-directing a three-year program at the NSF's Institute for Pure and Applied Mathematics and leading the NEH's Institute for Advanced Topics in Digital Humanities on Network Analysis for the Humanities. His research combines ethnographic depth with computational sophistication, creating novel methodologies for analyzing large cultural corpora. His scholarly contributions have earned him significant recognition: Fellow of the American Folklore Society Fellow of the Royal Gustav Adolf Academy (one of Sweden's Royal Academies) Elizabeth H. and Eugene A. Shurtleff Chair in Undergraduate Education Tangherlini has secured substantial funding from prestigious organizations including the NEH, NSF, NIH, AFOSR, Mellon Foundation, Nordic Council of Ministers, and Google. His work on conspiracy theories, K-Pop choreography analysis, and historical Danish folklore has garnered media attention, demonstrating the public relevance of his research. With extensive international experience including appointments at the University of Copenhagen, University of Iceland, and Harvard University, he maintains a global scholarly perspective while contributing significantly to undergraduate education at Berkeley.

Andrea MartinelliView profile

Lecturer

• Optimal Control
• Reinforcement Learning
• Decentralized Control
• +4 more

Dr. Andrea Martinelli is a Lecturer and Postdoctoral Researcher at the Automatic Control Laboratory (IfA), ETH Zurich. He holds a PhD in Automatic Control from ETH Zurich (2024) under Prof. John Lygeros, an MSc in Control Engineering (2017) from Politecnico di Milano, and a BSc in Management Engineering (2015). His research focuses on optimal control, reinforcement learning, and decentralized control strategies for large-scale systems, emphasizing scalability and applicability to renewable energy systems. He received the ETH Medal for his doctoral thesis on data-driven control methods. Education: BSc in Management Engineering, Politecnico di Milano (2015) MSc in Control Engineering with Honours, Politechnico di Milano (2017) PhD in Automatic Control, ETH Zurich (2024) Research Interests: Optimal control and reinforcement learning Data-driven methods for control systems Decentralized control of interconnected systems Dissipativity theory and passivity-based approaches Applications in renewable energy systems (DC microgrids) Teaching & Outreach: Program Manager for the CAS ETH in Automation Teaching a post-graduate course on automation in 2025 Professional Activities: Worked at Laboratoire d'Automatique (EPFL) during MSc thesis (2017) Research Assistant with Prof. R. Scattolini, Politecnico di Milano (2018)

• Dynamics of Innovation
• Regulatory Sciences
• Economics of Science and Innovation
• +5 more

Dr. Jarno Hoekman is an Associate Professor in Innovation Studies at the Copernicus Institute of Sustainable Development, Utrecht University. His research focuses on the dynamics and governance of science in the context of innovation, regulation, and societal challenges, with particular emphasis on sustainability and health. He is affiliated with both the Copernicus Institute of Sustainable Development and the Utrecht collaborating Centre for Pharmaceutical Policy & Regulation in the Department of Pharmaceutical Sciences. Dr. Hoekman serves as the programme leader of the research master in Innovation Sciences and teaches academic integrity courses to Master students and PhD candidates. Dr. Hoekman's research is organized around three interconnected themes: Science in transition , examining how scientific practices and institutional arrangements are evolving through open science, interdisciplinary research collaborations, and alternative recognition systems; Regulatory science and innovation , investigating innovations in tools and standards for assessing risks and benefits of new technologies, including safety assessment methods and regulatory authorization standards; and Geography of science , exploring the role of location factors in scientific knowledge production and diffusion. Analysis of Dr. Hoekman's recent publications (2022-2024) reveals a strong interdisciplinary focus spanning pharmacology, toxicology, innovation studies, and science policy. Key research trends include examining conditional marketing authorization pathways, post-approval studies for conditionally authorized medicines, animal-free safety testing methodologies, and the societal impact of transdisciplinary research projects. His work frequently employs mixed-methods approaches and involves multi-stakeholder perspectives to address complex regulatory and innovation challenges. Dr. Hoekman actively contributes to policy-relevant research, including major European Commission studies on pharmaceutical legislation. His collaborative work extends across multiple institutions and involves interdisciplinary teams working on pharmaceutical policy, sustainable innovation, and science-society interactions. As a member of the Utrecht Young Academy and the UU Open Science Platform, he engages with broader academic community initiatives related to research integrity and open science practices.

Jonathan M. BakerView profile

Assistant Professor

• Quantum Computing
• Quantum Computer Architecture
• Quantum Error Correction
• +4 more

Jonathan M. Baker is an Assistant Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin, holding the Advanced Micro Devices Chair in Computer Engineering. His research centers on quantum computer architecture with emphasis on practical quantum error correction implementation across the quantum computing stack. His educational background includes a Ph.D. in Computer Science from the University of Chicago (advised by Fred Chong) and dual B.S. degrees in Mathematics and Chemistry and Computer Science from the University of Notre Dame. Baker's research spans quantum compilation, logic synthesis, multi-radix architectures, and error mitigation for both near-term and fault-tolerant quantum systems. His work addresses critical challenges in quantum hardware-software co-design, with particular focus on optimizing quantum circuits for real-world hardware constraints and noise characteristics. Current projects emphasize qudit-based computing, neutral atom architectures, and efficient error correction implementations. His publication record shows strong focus on quantum architecture innovations, with recent work exploring qudit advantages, modular chiplet designs, and dynamic noise adaptation. Key trends include hardware-aware compilation techniques, communication optimization across quantum systems, and practical approaches to fault tolerance. Best Paper Award Runner Up, MICRO 2020 IEEE Micro Top Pick, 2020 (Virtualized Logical Qubits) IEEE Micro Top Pick, 2020 (Extending Frontier with Qutrits) IEEE Micro Top Pick, 2021 (Emerging Technologies) Best Poster Award, MICRO 2018 Baker actively mentors graduate students in quantum computing architecture research and serves on conference review committees including MICRO and ASPLOS. His teaching includes specialized quantum systems courses at UT Austin and online EdX modules covering quantum computation fundamentals and architecture. He collaborates with the Duke Quantum Center and maintains strong industry connections through the AMD Chair position, focusing on bridging academic research with practical quantum computing implementations.

Anders RantzerView profile

Professor

• Control Systems Theory
• Scalable Control
• Adaptive Control
• +7 more

Anders Rantzer is a Professor of Automatic Control at the Department of Control Engineering, Faculty of Engineering, Lund University, Sweden. He has held visiting positions at Caltech (2004–2005) and the University of Minnesota (2015–2016) as the Taylor Family Distinguished Visiting Professor. His academic journey began with a PhD from KTH Stockholm in 1991, followed by a postdoc at the Institute for Mathematics and its Applications (IMA), University of Minnesota. His research interests center on modeling, analysis, and synthesis of control systems , with a strong focus on scalability, adaptation, and applications in energy networks . He is particularly known for foundational work in positive systems and integral quadratic constraints (IQCs) . These theoretical frameworks are critical in analyzing stability and robustness of large-scale interconnected systems. His work bridges mathematical rigor with practical engineering applications, especially in sustainable energy and networked systems. The recent publications and lecture materials reflect a consistent trajectory in scalable and robust control, optimization, and distributed systems. Themes such as large-scale convex optimization , nonlinear and stochastic control , and network dynamics dominate his scholarly output, indicating a sustained commitment to advancing control theory for complex, real-world systems. Scientific honors include: Fellow of IEEE Member of the Royal Swedish Academy of Engineering Sciences (IVA) Chairman of the Swedish Scientific Council for Natural and Engineering Sciences Chairman of the Royal Physiographic Society of Lund Rantzer has supervised numerous students and contributed extensively to academic leadership and education. He has been involved in major national and international research initiatives such as WASP (Wallenberg AI, Autonomous Systems and Software Program) and ELLIIT. His work includes developing educational tools and courses in control, optimization, and machine learning. He leads and contributes to research projects on autonomous systems, cloud control, and smart energy networks. He is affiliated with the Control Lab at LTH and participates in collaborative efforts such as the Nordic University Hub on Industrial Internet of Things (HI2OT). His work integrates theoretical advances with practical implementations in robotics, biomedical systems, and industrial automation.

Rex YingView profile

Assistant Professor

• Graph Neural Networks
• Geometric Representation Learning
• Explainable AI
• +3 more

Rex Ying is an Assistant Professor in the Department of Computer Science at Yale University's School of Engineering & Applied Science. He leads research in graph neural networks, geometric representation learning, and explainable AI, with applications spanning physical simulations, biology, knowledge graphs, and recommender systems. His lab actively recruits PhD students interested in geometric deep learning, graph neural networks, and trustworthy AI. Dr. Ying received his PhD in Computer Science from Stanford University under Jure Leskovec, with a thesis titled "Towards Expressive and Scalable Deep Representation Learning for Graphs." Prior to that, he graduated from Duke University in 2016 with highest distinction, majoring in Computer Science and Mathematics. His research focuses on three interconnected areas: advancing graph neural network architectures for improved expressiveness, scalability, and interpretability; innovating in geometric representation learning for data with diverse characteristics; and developing real-world applications across scientific domains. He has pioneered influential algorithms including GraphSAGE, PinSAGE, and GNNExplainer, and developed the first billion-scale graph embedding services at Pinterest as well as graph-based anomaly detection algorithms at Amazon. His recent publication trends show a strong focus on hyperbolic geometry for foundation models, non-Euclidean representation learning, and multimodal applications in computational biology. The research demonstrates increasing integration of geometric deep learning with large language models and foundation model architectures. KDD 2022 Dissertation Award 2019 Baidu Scholarship in Artificial Intelligence Dr. Ying actively serves the research community as a committee member for major conferences including AAAI, ICML, NeurIPS, ICLR, KDD, and WebConf for over seven years, and as area chair for LoG 2022. He co-leads the open-source PyTorch Geometric project and has organized numerous workshops on graph learning. His industry collaborations include Pinterest, Amazon, Facebook AI Research, DeepMind, Siemens, SLAC National Accelerator Laboratory, and Saudi Aramco. He teaches "Deep Learning for Graph-Structured Data" at Yale and mentors students in developing cutting-edge graph learning algorithms. His research lab collaborates with both academic institutions and industry partners to advance the state-of-the-art in graph representation learning, with particular emphasis on geometric deep learning and its applications to scientific discovery and real-world systems.

Isik AkinView profile

Senior Lecturer

• Behavioral Finance
• FinTech
• Credit Risk Management
• +5 more

Dr Isik Akin is a Senior Lecturer in Accounting and Finance at Bath Spa University and leads the Accounting Pathway. He teaches undergraduate and postgraduate modules including Financial Accounting, Management Accounting, Corporate Financial Management, and Quantitative Research Methods. Education: PhD in Accounting and Finance (Bath Spa University), PhD in Economics and Finance (Istanbul Gelisim University), MSc in Finance (University of the West of England), BSc in Mathematics (Trakya University) Professional Qualifications: Fellowship in Higher Education Academy, Chartered Institute for Securities & Investment (CISI) His research focuses on Behavioral Finance , FinTech , Credit Risk Management , and Sustainable Finance . Recent publications analyze: Enterprise valuation dynamics (FTSE 100) Metaverse asset valuation frameworks Interconnected financial markets (stocks, commodities, crypto) Green investments in real estate He has secured significant international funding including the Connect4Innovation UK-Turkey partnership grant (2021-2022, £50,000) and coordinated EU projects like the Life-Long Learning Programme (2016-2017). Scientific Awards & Roles: Chartered Institute for Securities & Investment (CISI) certified Fellow of the Higher Education Academy Advisory Board Member: Izlek Academic Journal, Metropolitan Business Review Editorial Board Member: International Journal of Economics and Financial Research His career spans multiple institutions including Worcester University and University of Arts London, with expertise in international finance, quantitative methods, and financial globalization.

Fahad Ahmad BisharaView profile

Associate Professor

• Legal History
• Economic History
• Indian Ocean World
• +7 more

Fahad Ahmad Bishara is an Associate Professor at the University of Virginia , specializing in the economic and legal history of the Indian Ocean and Islamic world . His work bridges global capitalism, international law, and historical narratives of mobility. Key Books: A Sea of Debt (Cambridge, 2017) and Monsoon Voyagers (UC Press, forthcoming) Awards: Hurst Prize, Jerry Bentley Prize, Peter Gonville Stein Book Award Research Focus: Explores debt, legal systems, and trade through microhistories of ships and merchant families, with recent interests in narrative scales and conceptualizations of law in global history. Academic Collaborations: Co-authored works with Nandini Chatterjee, Hollian Wint, and others, emphasizing Persianate and Indian Ocean interconnections. Scientific Awards: J. Willard Hurst Prize (Law and Society Association) Jerry Bentley Prize (World History Association) Peter Gonville Stein Book Award (American Society for Legal History)

Lucia DolceView profile

Professor

• Japanese Buddhism
• Medieval Japanese Religious Culture
• Ritual Studies
• +7 more

Lucia Dolce serves as the Numata Professor of Japanese Buddhism within the Department of Religions and Philosophies at SOAS University of London, part of the School of History, Religions and Philosophies. Her academic base is room 342 in the Russell Square: College Buildings campus. Her educational background includes: Laurea MA (University of Venice) PhD (Leiden University) Professor Dolce's research centers on two interconnected projects: first, the discourse on the body in medieval Japanese Buddhist rituals and its connections to continental Tantric practices, emphasizing ritual fluidity and performative theory applications; second, contemporary Buddhism-Shinto syncretism with focus on revival of premodern practices in Kyoto shrines. She also examines Tokyo's urban pilgrimage routes like the Seven Gods of Fortune, analyzing institutional negotiations and religious marketing dynamics. Her journal articles (1992-2023) consistently explore ritual knowledge transfer in Japanese Buddhism, with recent works on scriptural repurposing and tantric exegesis highlighting material culture and practice-centered approaches. Earlier publications establish foundational studies on Nichiren Buddhism's esoteric dimensions, astrological cults, and celestial body worship, revealing enduring thematic threads across three decades of scholarship. Scientific awards: No awards listed in provided text Advising and grants: She currently supervises four PhD candidates: Rachel Williams (Japanese Secularity), Haruka Saito (Repentance Rituals), Sooyeun Yang (Korean Astrological Buddhism), and Yeonju Lee (Korean Nationalism). Previous supervisees include twelve PhD graduates such as Emanuela Sala (2022, Sannō Shintō), Ronit Wang (2022, Thai Hell Parks), and multiple 2011 completions. Dolce led the Newton Fellowship-associated project 'The Lucky Gods of Tokyo' (2014-2016), investigating spatial politics in Buddhist-Shinto pilgrimage networks.