Find Academic Supervisors

• Performance Measurement
• Management Accounting
• Management Audit
• +7 more

Josep Bisbe Viñas is a Professor at Ramon Llull University's Esade Business School, affiliated with the Department of Economics, Finance and Accounting. He is part of the Group of Research in Economics and Finance (GREF) and has been involved in multiple research projects focused on performance measurement, management control systems, and innovation ambidexterity. His work contributes to UN Sustainable Development Goals related to responsible consumption and production, and climate action through corporate sustainability research. Key research interests include: Performance measurement systems and their impact on organizational outcomes Top management team dynamics and cognitive conflict Management audit practices in virtual and distributed teams Sustainability reporting and internal decision-making processes Recent research trends show a focus on integrating sustainability into corporate decision-making frameworks and exploring how performance measurement systems influence innovation and knowledge absorption. His work bridges theoretical conceptualization with practical applications in management accounting and control systems. Notable projects include: IOIAP (2022–2026): Examining corporate sustainability from internal and external accounting perspectives GREF (2022–2025): Cross-disciplinary research in economics and finance Decision Making Project (2024): Investigating environmental internal reporting's impact on organizational outcomes He collaborates with institutions like the Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR) and has led research groups such as the Centre Català de Metodologia Estadística Aplicada i d'Enquestes.

Emily KangView profile

Professor

• Spatial Statistics
• Environmental Statistics
• Data Assimilation
• +2 more

Emily Kang is a Professor in the Department of Mathematical Sciences at the University of Cincinnati, where she leads the Group on Data Analytics and Decision Sciences (GDADS). Her research develops statistical methodologies for spatial and spatio-temporal data, with applications in environmental science, climate modeling, and remote sensing. Kang specializes in hierarchical Bayesian models, data assimilation techniques, and scalable algorithms for large environmental datasets. Her work includes developing the EcoPro framework for ecological projections using Earth system models and remote sensing data, creating statistical downscaling methods for climate variables, and designing visualization tools for global environmental data on multi-resolution grids. Kang received the American Statistical Association's ENVR Early Investigator Award for contributions to environmental statistics. Current projects focus on neighborhood-scale extreme heat projections, coral reef habitability under climate change, and recursive co-kriging models for multi-fidelity spatial data. Her research advances uncertainty quantification in remote sensing products and climate impact assessments.

Björn SchemberaView profile

Researcher

• Research Data Management
• Metadata
• Semantics
• +4 more

Björn Schembera is a Researcher at the Institute of Applied Analysis and Numerical Simulation (IANS) at the University of Stuttgart, focusing on Research Data Management (RDM), metadata standards, and ontologies. He holds a Dr.-Ing. (Engineering Doctorate) and a Diplom-Informatik (Computer Science) degree, with interdisciplinary training in philosophy. His current work centers on FAIR principles, knowledge graphs, and dark data in computational and mathematical sciences, particularly within the MaRDI (Mathematical Research Data Initiative) project under NFDI funding. Education and Professional Background: After completing his doctoral studies on dark data in simulations at HLRS (2011–2022), he joined IANS in 2022. His research bridges technical RDM challenges with societal implications of information technology. Research Interests: Schembera’s work emphasizes metadata models (e.g., EngMeta), ontology development for mathematics and engineering, and ethical aspects of data stewardship. He contributes to projects like bwDataArchive and NFDI4Cat, addressing interoperability and standardization in research data infrastructures. Teaching: He leads the course 'Schlüsselqualifikation Forschungsdatenmanagement' since 2023/24, promoting open science and RDM practices. Key Achievements: His 2023 Best Paper Award (MTSR Conference) recognizes contributions to metadata and semantic research. Over 50 publications span journals like Energies, IEEE Transactions, and conference proceedings on metadata, ontologies, and simulation workflows. Projects: He collaborates on MaRDI (mathematical data infrastructure), NFDI4Cat (catalysis sciences), and bwDataArchive (long-term storage).

• Healthcare workforce
• Opioid use disorder and policy implications
• Medicare and long-term care
• +7 more

Ulrike Muench is an Associate Professor with tenure in the Department of Social and Behavioral Sciences at the UCSF School of Nursing, with affiliations at the Philip R. Lee Institute for Health Policy Studies and Healthforce Center. She specializes in nursing workforce dynamics, opioid policy, Medicare systems, and disparities in healthcare. Her research leverages large datasets like Medicare claims and the Medical Expenditure Panel Survey. Education & Training: MSN (2005) and PhD (2012) in Nursing from Yale University Postdoctoral Fellowship (2014) at Vanderbilt University School of Nursing Research Interests: Focuses on nurse practitioner roles, prescribing patterns in primary care/nursing homes, dementia care trajectories, and gender-based pay disparities in healthcare. Her work bridges health policy analysis with real-world clinical outcomes, aiming to inform equitable healthcare delivery systems. Awards: 2016 Academy Health New Investigator Award 2018 American Academy of Nursing Fellow 2019 UCSF School of Nursing Mentoring Award Grants & Advising: Leads studies funded by NIH and foundations, mentoring early-career researchers in health services research. Collaborates on projects addressing workforce distribution, rural-urban care disparities, and policy reform. Labs/Teams: Active in UCSF's Healthforce Center, focusing on healthcare workforce analytics and interdisciplinary policy development.

Daniel T. BaldassarreView profile

Associate Professor

• Ornithology
• Behavioral Ecology
• Speciation
• +2 more

Daniel T. Baldassarre is an Associate Professor in the Department of Biological Sciences at SUNY Oswego. He holds a Ph.D. in Neurobiology and Behavior from Cornell University and a B.S. in Biology from Syracuse University. His research integrates field studies and genomic analyses to investigate avian diversity, urbanization impacts on bird behavior, speciation dynamics, and sexual selection. Research focuses include: Behavioral syndromes in Northern Cardinals under urban-rural gradients Plumage reflectance and sexual dichromatism in waterbirds Genomic underpinnings of itinerant breeding in desert birds His publications consistently explore adaptations to environmental stressors, with recent work emphasizing climate change impacts on avian physiology and mating systems. He mentors undergraduate researchers at the Rice Creek Bird Observatory and collaborates internationally on avian morphology databases. No major scientific awards are documented.

Elisa BaniassadView profile

Teaching Professor

• Software Engineering
• Educational Technology
• Aspect-Oriented Programming
• +3 more

Elisa Baniassad is a Teaching Professor in the Department of Computer Science at the University of British Columbia (UBC), within the Faculty of Science. She specializes in software engineering education and has received numerous teaching accolades including the UBC Killam Teaching Prize and CS-Can/INFO-CAN Excellence in Teaching Award. Her courses focus on software construction, engineering principles, and advanced software design. Dr. Baniassad has taught CPSC 310 (Introduction to Software Engineering), CPSC 210 (Software Construction), and CPSC 410 (Advanced Software Engineering) across multiple terms since 2000. Her research interests span educational methodologies in software engineering, aspect-oriented programming, and the design of effective learning tools. Notable contributions include studies on team dynamics in software development, automated assessment techniques, and pedagogical frameworks for large-scale programming courses. She has authored over 50 peer-reviewed articles on topics ranging from mutation analysis in student tests to the efficacy of online learning environments. Awards include recognition for teaching excellence at UBC and contributions to computer science education. Her work emphasizes practical applications of software engineering principles in academic settings, with a focus on fostering student mastery through innovative assessment strategies and feedback mechanisms.

• Computational Neuroscience
• Neural Networks
• Synaptic Plasticity
• +3 more

Prof. Tatjana Tchumatchenko is Professor and TRA Steering Committee member at the University of Bonn, leading a computational neuroscience group at the Institute of Experimental Epileptology and Cognition Research. Her research focuses on computational analysis of recurrent neural networks and molecular dynamics of synapses. Research examines how molecular dynamics in dendrites organize synaptic plasticity outcomes, and how synaptic learning rules help neural networks solve computational tasks. The group develops quantitative methods to understand neural data and predictive models of neural network function across molecular, synaptic, and network levels. Honors include the Boehringer Ingelheim FENS Research Award (2022), ERC Starting Grant (2020), Heinz Maier-Leibnitz-Prize (2016), and election to the Young Academy of Europe. Current projects investigate dendritic protein distribution, energy constraints in neurons, and astrocyte contributions to learning.

Hangfeng HeView profile

Assistant Professor

• Machine Learning
• Natural Language Processing
• Reasoning
• +4 more

Hangfeng He is an Assistant Professor of Computer Science and Data Science at the University of Rochester , affiliated with the Hajim School of Engineering & Applied Sciences. He holds a PhD from the University of Pennsylvania and focuses on machine learning and natural language processing. His research emphasizes incidental supervision for natural language understanding, interpretability of deep neural networks, and reasoning in natural language. Education : PhD in Computer Science from University of Pennsylvania Research Interests : Machine Learning (especially deep learning theory, generalization, and optimization) Natural Language Processing (incidental supervision, language understanding, and multimodal reasoning) Reasoning (inductive biases, temporal data analysis, and model interpretability) Research Trends : His work spans foundational AI research and applied NLP, with recent focus on large language models, multimodal systems, and constraint-aware methods. He explores how models generalize from limited supervision and mitigate biases in real-world data. Key themes include improving model robustness, understanding inductive mechanisms, and applying AI to financial and social text analysis. Labs/Teams : While specific lab affiliations aren’t listed, his work aligns with the Department of Computer Science’s research clusters in AI, machine learning, and data science.

Jennifer MortonView profile

Professor

• Ethics
• Philosophy of Education
• Political Philosophy
• +3 more

Jennifer Morton is the Presidential Penn Compact Professor of Philosophy and Graduate Chair at the University of Pennsylvania, with a secondary appointment at the Graduate School of Education. She is also a senior fellow at the University of Wisconsin-Madison’s Center for Ethics and Education and a 2023-2024 Guggenheim Fellow. Her research focuses on how poverty and social class shape agency, particularly the ethical costs of upward mobility for first-generation and low-income students. Her book *Moving Up Without Losing Your Way* won the Grawemeyer Award in Education and the Frederic W. Ness Book Award. Education: Ph.D. in Philosophy from Stanford University; A.B. in Philosophy from Princeton University. Awards & Fellowships: Grawemeyer Award (2023), APA Scheffler Prize, Australasian Association of Philosophy Best Paper Award (2017), and a Guggenheim Fellowship (2023-2024). She has held positions at UNC Chapel Hill, City College of New York, and Swarthmore College. Research Interests: Ethics of education, moral psychology of poverty, and structural inequalities in agency. Her work bridges philosophy with social science, emphasizing the hidden costs of upward mobility and strategies for equitable educational practices. Labs/Teams: Collaborates with the Center for Ethics and Education (UW-Madison) and has advised students on topics intersecting philosophy, education, and social justice.

Melanie FeinbergView profile

Professor

• Data Modeling
• Critical Data Studies
• History of Information Science
• +3 more

Melanie Feinberg is a Professor at the School of Information and Library Science (SILS), University of North Carolina at Chapel Hill. She specializes in data modeling, critical data studies, and the history of information science. Her research examines the human dimensions of data, blending information science, design, and humanities perspectives. She holds a BA in Humanities from Stanford University, an MIMS from UC Berkeley, and a PhD in Information Science from the University of Washington. Feinberg’s work focuses on classification systems, metadata architectures, and the design of expressive information collections. Her book Everyday Adventures with Unruly Data (MIT Press, 2022) explores how data interacts with human practices. She teaches courses like Foundations of Information Science (INLS 201), Organizing Information (INLS 520), and Metadata Architectures (INLS 720). Her research has been recognized with awards including the Marie Skłowdoska-Curie Fellowship (2019-2021) and IAH Faculty Fellowship (2018-2019). Her articles span HCI, library science, and design, addressing topics like database interactions, rhetorical design, and ethical classification systems. She has advised numerous projects on digital curation, metadata standards, and data-driven storytelling. Feinberg’s interdisciplinary approach bridges technical systems and humanistic inquiry. She actively contributes to academic discourse through her work on classification ethics, data criticism, and the role of design in shaping information systems.

Maria Grazia TurriView profile

Senior Lecturer

• Creative Arts and Mental Health
• Theatre Studies
• Psychoanalysis
• +3 more

Dr. Maria Grazia Turri is a Senior Lecturer in Creative Arts and Mental Health at Queen Mary University of London, co-directing the MSc program collaborating between the Centre for Psychiatry and the Department of Drama. Affiliated with the Wolfson Institute of Population Health, she holds dual expertise as a psychiatrist, psychoanalytic psychotherapist, and theatre scholar. Her roles include teaching, research, and clinical practice. Educated in Padova (Italy) for medicine, she earned a DPhil in Psychiatry from Oxford and a PhD in Drama from Exeter. She trained in medical psychotherapy and practised for 15 years in the NHS, including as a Consultant Psychiatrist in Medical Psychotherapy. Her research bridges psychoanalytic theory with theatre studies, focusing on processes like identification in performance and the role of laughter in Commedia dell’Arte. She also explores creative arts in mental health interventions, including social prescribing and arts-based therapies. Her teaching spans critical mental health, psychoanalysis, and theatre practice, with supervision of MSc and PhD students. Public engagement includes the annual 'Mad Hearts' conference and collaborations with arts organizations to enhance mental health through the arts. She co-founded the MadHeartists collective and advocates for integrating artistic practices into mental health care systems.

Gharad BryanView profile

Associate Professor

• Development Economics
• Behavioral Economics
• Experimental Economics
• +5 more

Gharad Bryan is an Associate Professor of Economics at the London School of Economics and Political Science (LSE) , affiliated with the STICERD Economic Organisation and Public Policy Programme. He holds a PhD from Yale University and specializes in Development Economics, Behavioral Economics, and Experimental Economics. His research explores topics such as migration, climate adaptation, urbanization, and mental health interventions in low-income settings. Education: PhD in Economics, Yale University (2011) MPhil and MA, Yale University (2010 and 2007) LLB and BCom with Honors, University of Melbourne (2004 and 2003) Research Interests: Bryan’s work focuses on applying experimental methods to real-world challenges, including seasonal migration in Bangladesh, cognitive behavioral therapy’s impact on poverty reduction in Ghana, and the distributional effects of urban infrastructure in Tanzania. He also studies land market design in Uganda and Kenya to improve resource allocation. Key Projects: Lead on the IGC Cities Research Programme, addressing urban growth in climate-vulnerable areas. Co-designed interventions to boost seasonal migration in Bangladesh and evaluate slum redevelopment in Addis Ababa. Explores climate migration adaptation strategies in Bangladesh and sustainable shrimp farming in climate-sensitive regions. Awards & Honors: British Academy Mid-Career Fellowship (2015–2016) Kauffman Dissertation Fellowship (2008–2011) Raymond Powell Teaching Prize (2007–2008) Grants & Collaborations: Bryan has secured funding from DFID, J-PAL, IPA, World Bank, and others for projects totaling over $2 million. He collaborates with institutions like Innovations for Poverty Action and the Jameel Poverty Action Lab (J-PAL). Labs & Teams: Active in LSE’s Department of Economics and the STICERD initiative, leading interdisciplinary teams on urban development, climate policy, and behavioral interventions.

Alex VoorhoeveView profile

Professor

• Distributive Justice
• Rational Choice Theory
• Political Philosophy
• +4 more

Alex Voorhoeve is a Professor in the Department of Philosophy, Logic and Scientific Method and the LSE School of Public Policy at the London School of Economics and Political Science. He holds visiting positions at Harvard, Princeton, National Institutes of Health, Erasmus University Rotterdam, and Nuffield College, Oxford. He studied economics and philosophy at Erasmus University, Cambridge University, and UCL. Research interests focus on distributive and procedural justice in health, rational choice theory, moral psychology, and Epicureanism. Key areas include: Theory and practice of fair decision-making in health financing Moral psychology of ethical judgments and biases Philosophical foundations of economic policy His publications analyze ethical frameworks for health policy, pandemic response strategies, and moral decision-making under uncertainty. Recent work emphasizes procedural fairness in universal health coverage implementations. Professional engagements include advisory roles for the World Health Organization, World Bank, Norwegian Institute of Public Health, and the Bank of England's Academic Advisory Group for the digital pound. He will become Vice-President for Faculty Development at LSE in 2025. Research outputs demonstrate consistent focus on integrating ethical principles with economic policy design, particularly in health financing systems.

• Medical Physics
• Radiation Oncology
• Proton Therapy
• +3 more

Sara Margareta Cecilia Pilskog serves as an Associate Professor in the Department of Physics and Technology at the University of Bergen, Norway, with dual affiliation at Haukeland University Hospital's Department of Cancer Treatment and Medical Physics. Her research bridges theoretical medical physics and clinical oncology applications, focusing on precision radiotherapy techniques and biological optimization. Her primary research interests center on proton therapy innovation, where she investigates biological optimization strategies using linear energy transfer (LET) and relative biological effectiveness (RBE) modeling. She develops adaptive radiotherapy frameworks to address inter-fractional motion in pelvic cancers, particularly prostate and rectal malignancies. Her work also pioneers neutron-based in-vivo range verification systems and statistical deformation models for dose accumulation. Current projects emphasize reducing treatment margins through anatomical robustness and optimizing biological dose distributions for organ sparing. Analysis of her 15 most recent publications reveals a dominant focus on improving proton therapy precision for pelvic cancers through biological modeling and motion management. Approximately 70% of her work addresses prostate cancer applications, with significant contributions to adaptive strategies for inter-fractional changes and biological optimization techniques. Her research consistently employs Monte Carlo simulations (particularly FLUKA) and clinical data analysis to translate theoretical models into clinically viable solutions. No scientific awards were documented in the provided materials. While specific advising details remain unreported, her collaborative patterns indicate active mentorship within the University of Bergen's medical physics research ecosystem. Her publications consistently involve junior co-authors from clinical physics teams at Haukeland University Hospital, suggesting hands-on supervision of technical staff and research fellows in radiotherapy innovation projects. Grant funding appears primarily channeled through institutional hospital-university partnerships focused on clinical translation of advanced radiotherapy techniques. Dr. Pilskog operates within the University of Bergen's medical physics research cluster that maintains close operational ties to Haukeland University Hospital's radiotherapy department. This integrated academic-clinical environment enables direct implementation of her research on adaptive proton therapy and biological optimization into clinical workflows, with particular emphasis on pelvic cancer treatment protocols. The team utilizes advanced Monte Carlo simulation platforms and clinical treatment planning systems to develop and validate next-generation radiotherapy approaches.

Brian FisherView profile

Professor

• Cognitive Science
• Visual Analytics
• Human-Computer Interaction
• +2 more

Brian Fisher is a Professor at Simon Fraser University's School of Interactive Arts and Technology, where he leads the Interaction Science Research Group. He holds affiliate positions at the University of British Columbia and serves as Associate Director for the Media And Graphics Interdisciplinary Centre (MAGIC). His research investigates human reasoning in responsive environments through cognitive science approaches, developing visualization systems that support individual and distributed cognition. Fisher's work spans personalized health, aircraft safety analysis, space object classification, and emergency management. His teaching integrates perceptual, cognitive, and social science knowledge into design education. He actively participates in science policy through organizations including NSERC, Defence R&D Canada, EUREKA Eurostars, and IEEE committees. Fisher has been recognized as a Fellow of the Psychonomics Society and chaired major conferences including IEEE VIS 2019. His research is characterized by strong interdisciplinary collaboration and real-world applications in high-stakes decision domains.