Find Academic Supervisors

• Urban Archaeology
• Cultural Heritage
• Urban Development
• +5 more

Liisa Seppänen serves as Adjunct Professor of Urban Archaeology at the University of Turku, leveraging dual expertise in archaeology and cultural history alongside professional background in business and communications. Her academic foundation includes a PhD in Archaeology (2012) and MA in Cultural History, both from the University of Turku. Her educational qualifications: PhD in Archaeology, University of Turku (2012) MA in Cultural History, University of Turku Seppänen's research centers on medieval urban landscapes, particularly Turku (Finland's oldest city and a major medieval Swedish settlement). She investigates construction activities, townscape evolution, and multidisciplinary urban development frameworks while addressing critical questions about cultural heritage valuation, preservation methodologies, and social complexity in urban transitions. Her fieldwork includes directing Finland's largest urban excavation (1.2+ hectares) in Lahti (2013-2014), which catalyzed studies on stakeholder collaboration in city planning. Her 2014 publication analyzes interdisciplinary data collection and dissemination challenges in urban archaeology, reflecting consistent engagement with practical heritage management issues across Scandinavia and international contexts. No scientific awards were documented in the source material. While no student advising or grant activities were specified, Seppänen actively contributes to the international Archaeology, Architecture and Contemporary City Planning network (established 2013) and has delivered invited lectures at the University of Bergen (2015) and University of Turku (2014) on archaeological information valuation. Her collaborative work with urban planners and heritage specialists constitutes her primary research ecosystem, focusing on integrating archaeological insights into contemporary city development processes.

• Machine Learning
• Energy Harvesting
• Low Latency Systems
• +3 more

Kiwan Maeng is an Assistant Professor in Computer Science and Engineering, focusing on the intersection of machine learning systems, privacy-preserving techniques, and low-latency computing architectures. His research emphasizes algorithm-system co-design for scalable and secure AI implementations. Research Trends : His recent work explores retrieval-augmented generation systems, low-latency diffusion models, privacy-preserving federated learning, and energy-harvesting intermittent computing frameworks. Publications highlight collaborations across machine learning, cryptography, and hardware-software co-design. Key Projects : He leads a 3-year NSF SaTC grant (2024-2027) addressing privacy-preserving data embedding for untrusted ML services, and contributes to serverless video analytics frameworks (SVDE) and VR streaming optimization (PIRATE). Technical Contributions : His scholarship spans 17 conference contributions and 3 journal articles since 2007, with notable work on memory encryption for edge devices, secure MPC-based inference, and sustainable AI systems. Current research focuses on balancing privacy guarantees with model utility while optimizing for environmental efficiency.

Clémence PoirierView profile

Research Fellow

• Space cybersecurity
• Electronic conflict in outer space
• Cyber conflict in outer space
• +3 more

Clémence Poirier is a Senior Researcher in the Cyberdefense Project within the Risk and Resilience Team at the Center for Security Studies (CSS) at ETH Zurich. She previously served as a Research Fellow at the European Space Policy Institute (ESPI) in Vienna and as a Researcher for Flinders University in Adelaide, Australia. She also holds the position of Space Generation Advocacy and Policy Platform's Lead on Responsible Space Behavior at the Space Generation Advisory Council (SGAC). Her educational background includes a Master's degree in International Relations, International Security and Defense and a Bachelor's degree in Foreign Applied Languages (English, Russian, Spanish), both from University Jean Moulin Lyon III, France. Dr. Poirier is multilingual, which supports her international research collaborations. Dr. Poirier's research focuses on the critical intersection of space operations and cybersecurity, with particular emphasis on geopolitical implications of cyber conflict in outer space. Her work examines how terrestrial conflicts like the Ukraine war impact space security architecture and explores policy frameworks for protecting space infrastructure from cyber threats. She has conducted extensive research on space cybersecurity policy across multiple jurisdictions including Australia, Europe, and the United States. Analysis of her publication record reveals a clear progression from foundational space policy research toward increasingly specialized work on space cybersecurity. Her recent publications demonstrate growing attention to practical policy implementation challenges, with several papers addressing specific national and regional approaches to space cybersecurity governance. There's also a notable trend toward multidisciplinary collaboration, particularly with technical experts in space systems engineering. Dr. Poirier has established significant research partnerships with major space institutions including the European Space Agency, with whom she collaborated on climate policy research examining the integration of space-based data in European environmental policies. Her work with SmartSat CRC in Australia demonstrates international research coordination on space infrastructure security. She leads research initiatives focused on responsible space behavior and has contributed to policy development through her work with the European Economic and Social Committee. Her current Cyberdefense Project at ETH Zurich's CSS represents the culmination of her expertise in space security policy development.

• Machine Learning Ethics
• Philosophy of Science
• Interpretability in AI
• +5 more

Thomas Grote is a Research Fellow at the University of Tübingen's Ethics and Philosophy Lab within the Cluster of Excellence 'Machine Learning: New Perspectives for Science'. His research focuses on philosophical and ethical dimensions of artificial intelligence, particularly interpretability, fairness, and reliability in medical and social contexts. He co-supervises the Carl-Zeiss-Stiftung-funded project 'Certification and Foundations of Safe Machine Learning Systems in Healthcare' and co-organizes the 'Philosophy of Science Meets Machine Learning' conference series. Research Focus Grote's interdisciplinary work bridges philosophy of science and applied AI ethics. Key areas include: Methodological foundations of AI ethics and epistemology Clinical reliability and safety of ML systems Fairness metrics in sociotechnical healthcare systems Interpretability requirements for medical AI Computational psychiatry and evolving mental health frameworks His recent publications demonstrate strong emphasis on healthcare applications, with critical analyses of reliability in foundation models, ethical paradigms for LLMs, and rethinking evaluation methodologies at the epistemology-ethics interface.

Tania BurchardtView profile

Associate Professor

• theories of justice
• capability approach
• concepts and measurement of inequality
• +6 more

Tania Burchardt is an Associate Professor of Social Policy at the London School of Economics (LSE) , where she serves as Deputy Director of STICERD and Associate Director of CASE (Centre for Analysis of Social Exclusion). Her work bridges theoretical frameworks like the capability approach with empirical analyses of inequality , disability policy , and applied welfare policy . Key Research Areas : Theories of justice, inequality measurement, time poverty, and social care systems Leadership Roles : Co-led projects on multidimensional inequality, intergenerational exchanges, and child poverty Her recent work explores intra-household resource allocation , social care inequities , and public engagement in policymaking . She has collaborated with organizations like the Nuffield Foundation and Sense about Science to translate research into practice. Scientific Contributions span empirical studies on: Long-term care funding reforms (2015–2020) Disability-related income disparities Time poverty intersections with economic hardship Data-driven policy recommendations for Roma/Gypsy/Traveller communities Multidimensional child poverty frameworks

Philip J. EthingtonView profile

Professor

• Urban History
• Political History
• Social History
• +10 more

Philip J. Ethington is Professor of History, Political Science, and Spatial Sciences at the University of Southern California's Dornsife College of Letters, Arts, and Sciences. As Co-Director of the USC Center for Transformative Scholarship and Fellow of the Los Angeles Institute for the Humanities, he bridges historical scholarship with digital innovation through projects like HyperCities. Ethington's educational background includes: Ph.D. in History from Stanford University (1989) Postdoctoral Fellowship at Harvard University's Charles Warren Center (2007-2008) Getty Scholar at the Getty Research Institute (1996-1997) His research pioneers spatial theory of history through chronographs and digital cartography, examining urban evolution from Pleistocene times to present. Key interests include global metropolis studies , visual culture , and digital humanities , with focus on Los Angeles as a case study for transnational urban dynamics. Recent publications reveal consistent exploration of spatial dimensions in historical analysis, particularly through geographic institutionalism and deep historical regionalism. His work integrates cartographic innovation with theoretical frameworks to map urban change across millennia, emphasizing institutional ecology and transnational connections. Scientific recognition includes: Nomination for USC's Steven B. Sample Teaching Award (2010-2011) USC Interdisciplinary Faculty Fellowship (2004-2005) Award-winning documentary film Visual Acoustics (2009) Ethington mentors undergraduate researchers in urban history while leading major grants including MacArthur Foundation's HyperCities project ($238,000) and NEH's Digital Humanities initiative ($248,492). His funded work develops collaborative platforms for geohistorical research and digital publishing. He co-directs the USC History Lab and Center for Transformative Scholarship, fostering interdisciplinary collaboration through the Population Dynamics Lab and HyperCities consortium for participatory urban mapping.

Yuyin ZhouView profile

Assistant Professor

• Biomedical Artificial Intelligence
• Medical Image Analysis
• Foundation Models for Healthcare
• +9 more

Yuyin Zhou is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, Santa Cruz (UCSC), within the Baskin School of Engineering. She previously held a postdoctoral fellowship at Stanford University, collaborating with Prof. Lei Xing and Prof. Matthew Lungren. She earned her Ph.D. in Computer Science from Johns Hopkins University under the supervision of Bloomberg Distinguished Professor Alan Yuille. Her research is centered on advancing biomedical artificial intelligence to match medical experts in decision-making. Key focuses include developing medical multimodal models, building fair and trustworthy real-time learning systems for clinicians and patients, enabling one-shot/few-shot adaptation of foundation models to diverse medical tasks, and generating synthetic data aligned with clinical knowledge. Dr. Zhou’s recent publications span top-tier venues such as Nature Medicine , Medical Image Analysis , ICLR, CVPR, NeurIPS, MICCAI, and ECCV, reflecting a strong trend in foundation models for medical imaging, trustworthy AI, and efficient deployment. Her work bridges computer vision, deep learning, and clinical applications, with notable projects including TransUNet, BioMedGPT, and MicroSegNet. She has been recognized with the Google Research Scholar Award and the Hellman Fellowship . Dr. Zhou actively contributes to the academic community as an Area Chair for CVPR, ICLR, MICCAI, and CHIL. She organizes workshops and tutorials, including the CVPR 2024 Workshop on Foundation Models for Medical Vision and MICCAI 2024’s FOMMIA tutorial. Google Research Scholar Award Hellman Fellowship Dr. Zhou is actively recruiting self-motivated PhD students and interns to work on machine learning, computer vision, and AI for healthcare. She leads a dynamic research group focused on pushing foundation models into real-world clinical settings. Her team has launched public datasets, such as a micro-ultrasound dataset for prostate segmentation, and open-sourced tools to foster community collaboration.

Adegboyega OjoView profile

Professor

• Digital Government
• Artificial Intelligence Governance
• Public Sector Innovation
• +6 more

Dr. Adegboyega Ojo is a Professor at the School of Public Policy and Administration (SPPA), Carleton University , holding the prestigious Canada Research Chair (Tier 1) in Governance and Artificial Intelligence since 2014. His work bridges digital government , AI governance , and smart city development , with a focus on public sector innovation and policy analytics . Research Interests Smart Cities and Urban Digital Infrastructure Open Government Data and Transparency Blockchain Applications in Public Administration AI Ethics and Algorithmic Governance Electronic Participation and Citizen Engagement Publication Trends : His research emphasizes interdisciplinary approaches to digital governance, often involving data-driven policy analysis , smart city frameworks , and open data platform design . Collaborations span institutions in Ireland, Poland, and the U.S., with citations exceeding 5,200. Scientific Awards : Canada Research Chair in Governance and AI (Tier 1) Labs & Teams : Collaborates with the Insight Centre for Data Analytics (Ireland), Delft University of Technology , and United Nations University on projects like OpenGovIntelligence and BOLD (Big and Open Linked Data).

Jennifer EdmondView profile

Associate Professor

• Digital Humanities
• Research Infrastructures
• Open Science
• +2 more

Jennifer Edmond is Associate Professor of Digital Humanities and co-director of the Trinity Center for Digital Humanities at Trinity College Dublin, where she also directs the MPhil in Digital Humanities and Culture. She holds a PhD in Germanic Languages and Literatures from Yale University and specializes in applying advanced methods and infrastructures for arts and humanities research. Her research focuses on Digital Humanities, Research Infrastructures, Open Science, Cultural Heritage, and Knowledge Technologies. She has developed significant expertise in European research policy, having coordinated the €6.5m CENDARI FP7 project and participated in numerous EU initiatives including PARTHENOS, Europeana Cloud, and the Computational Literary Studies Infrastructure (CLS Infra). Dr. Edmond maintains an active publication record exploring digital scholarly editing, privacy in literary texts, open science practices, and cultural heritage narratives. Her recent work demonstrates a strong focus on the intersection of technology and democracy, digital ethics, and innovative methodologies for humanities research. Awards and Honors: Named one of Ireland's five 'Champions of EU Research' (2012) She served as President of DARIAH-EU's Board of Directors (2018-2022) and represented the organization on the European Commission's Open Science Policy Platform. Dr. Edmond has contributed to strategic developments at national and institutional levels, while actively promoting public outreach through various media formats and art installations.

Dermot J HayesView profile

Professor

• Agricultural Economics
• International Trade Policy
• Commodity Markets
• +5 more

Dermot J Hayes is the Charles F. Curtiss Distinguished Professor in Agriculture and Life Sciences and holds the Pioneer Hi-Bred International Chair in Agribusiness at Iowa State University's Department of Economics and Ivy School of Business. His expertise spans agricultural economics, financial economics, and international trade policy with a focus on commodity markets, farm policy, and China's agricultural impacts. Education: Ph.D. and M.S. in Agricultural Economics from the University of California, Berkeley (1986 and 1982). Research Interests: Includes U.S. farm policy, international trade dynamics, agribusiness strategies, crop insurance, financial derivatives, and China's role in global commodity markets. His work emphasizes policy analysis, market resilience, and emerging challenges like disease outbreaks (e.g., African Swine Fever). Awards: AAEA Fellow (2007), AAEA Enduring Quality Award (2006), and J.H. Ellis Teaching Award (2005). His research on food safety auctions remains influential. Consulting: Since 1995, he has advised the National Pork Producers Association on trade economics. His work informs policy debates on tariffs, trade deals, and market disruptions. Labs & Collaborations: Engaged with Iowa State's interdisciplinary initiatives on agriculture-environmental nexus and bioenergy systems.

• Bayesian Statistics
• Ecological Statistics
• Capture-Recapture Modeling
• +5 more

Prof. Ruth King is the Thomas Bayes’ Professor of Statistics at the University of Edinburgh’s School of Mathematics. Her research focuses on applying Bayesian statistical methods to ecological and public health challenges, including population estimation for hidden groups (e.g., injecting drug users, modern-day slaves) and wildlife conservation. She develops computationally efficient techniques for analyzing large datasets, such as spatial capture-recapture models for animal populations and spatio-temporal abundance models for hidden human populations. Key projects include estimating survival rates of guillemots (30,000 individuals) and improving capture-recapture models to account for animal movement dynamics. Her work bridges statistical methodology with real-world applications, emphasizing rigorous inference and scalable algorithms. King’s academic contributions span Bayesian modeling frameworks, parameter clustering in neuroscientific data, and hierarchical centering in random effects models. She collaborates with biologists and policymakers to address conservation and public health issues. Notable recent projects include incorporating memory effects into spatial capture-recapture models and developing semi-complete data augmentation for state-space models. Her interdisciplinary approach addresses challenges in ecology, epidemiology, and computational statistics, with a focus on methodological innovation for large-scale data. Her scientific contributions are highlighted through over 100 peer-reviewed articles, including work on integrated population models, animal movement dynamics, and hidden Markov models for seabird behavior. King emphasizes the importance of statistics in uncovering hidden information within datasets, advocating for robust methodologies that ‘stand up in court’ when applied to critical real-world problems.

James ZouView profile

Associate Professor

• Machine Learning
• Artificial Intelligence in Healthcare
• Biomedical Data Science
• +3 more

James Zou is an Associate Professor of Biomedical Data Science at Stanford University, with courtesy appointments in Computer Science and Electrical Engineering. His research focuses on advancing machine learning methodologies for healthcare applications, emphasizing reliability, fairness, and statistical rigor. He holds a Ph.D. from Harvard University and has held positions at Microsoft Research, Cambridge University (as a Gates Scholar), and UC Berkeley (Simons Fellow). Zou leads the Stanford Data4Health hub and is a Chan-Zuckerberg Investigator. His work spans AI-driven diagnostics, spatial transcriptomics, and ethical AI frameworks. Key achievements include the EchoNet AI system for echocardiography and foundational contributions to data valuation (e.g., Data Shapley). Awards include the Sloan Fellowship, NSF CAREER Award, and Google/Tencent AI awards. Education: Ph.D., Harvard University (2014); Postdoctoral roles at Microsoft Research, Cambridge, and Berkeley. Research Interests: Machine learning for healthcare, algorithmic fairness, interpretable AI, spatial omics, and translational bioinformatics. His lab develops tools like TextGrad (PyTorch for text agents) and frameworks for evaluating medical AI systems. Recent work addresses LLMs in peer review and clinical decision-making. Grants/Grants: Supported by NSF, Sloan Foundation, Chan-Zuckerberg Initiative, and industry partnerships (Google, Amazon, Adobe). Advises on over 20 doctoral students, many contributing to high-impact papers in Nature , Science , and top conferences (NeurIPS, ICML). Leads collaborations in cardiology, oncology, and veterinary medicine. Labs/Teams: Stanford AI Lab, Stanford Data4Health, and interdisciplinary groups in precision medicine. Active in open-source projects like FrugalML and MetaViz.

Ryan KoView profile

Professor

• Cyber Security
• Data Provenance
• Industrial Control Systems (ICS) Security
• +6 more

Professor Ryan Ko is a leading academic in Cyber Security at the University of Queensland (UQ), serving as Chair and Director of the UQ Cyber Research Centre, Director of Research at the School of Electrical Engineering and Computer Science, and a member of UQ's Academic Board. He holds a BEng (Computer Engineering) and PhD from Nanyang Technological University, Singapore. His research focuses on data provenance, industrial control systems (ICS) security, privacy-preserving technologies, and AI-driven cybersecurity solutions. Ko has pioneered initiatives such as the UQ Cyber Centre, interdisciplinary cybersecurity education programs (MCyber, PGDipCyber), and the Oceania Cybersecurity Challenge. He has attracted over AUD 20 million in competitive grants as lead investigator, including the NZ$12.2M STRATUS project. Ko’s work spans industry and policy, including advisory roles with INTERPOL, governments, and NGOs. He has authored over 100 publications, contributed to ISO standards (e.g., ISO/IEC 21878), and co-founded cybersecurity startups. Awards include Fellowships from the Australian Computer Society and Queensland Academy of Arts and Sciences, and the CSA Ron Knode Service Award. Education: Bachelor of Engineering (Computer Engineering) (Hons.), Nanyang Technological University (2005) PhD in Computer Science, Nanyang Technological University (2011) Awards: Fellow, Australian Computer Society (2016) Fellow, Queensland Academy of Arts and Sciences (2020) Young Professional Award, Singapore Government (2018) Grants & Leadership: AUD 20M+ lead investigator grants; NZ$12.2M STRATUS project (2014–2018) Established UQ Cyber Centre (2019) and NZ’s first cybersecurity graduate program (2012) His research emphasizes returning data control to users, with applications in agriculture, energy, and critical infrastructure. Ko’s contributions include patents, open-source tools (e.g., Kali Linux), and frameworks like TrustCloud for cloud accountability.

Simon MakView profile

Assistant Professor

• Statistical Modeling
• Bayesian Statistics
• Gaussian Process
• +5 more

Simon Mak is an Assistant Professor of Statistical Science at Duke University and a Faculty Network Member of the Duke Institute for Brain Sciences. His educational background includes: Ph.D. in Statistics, Georgia Institute of Technology (2018) M.S. in Statistics, Georgia Institute of Technology (2018) B.S. in Statistics, Simon Fraser University (2013) Dr. Mak's research focuses on advanced statistical methodologies for complex scientific problems. His expertise spans statistical modeling , Bayesian inference , Gaussian process emulation , and uncertainty quantification . He applies these methods to nuclear physics (heavy-ion collisions), engineering (engine control systems), and music information retrieval, emphasizing scalability and interpretability in scientific computing. Analysis of his 2023-2025 publications reveals dominant trends in scalable Gaussian process methods for massive datasets and multi-fidelity simulations, particularly applied to high-energy physics and engineering systems. He has pioneered innovations in Bayesian optimization for expensive simulators and developed novel frameworks for online change-point detection in streaming data, demonstrating exceptional cross-disciplinary impact. Dr. Mak leads multiple significant research initiatives: Collaborative Research: Cost-Efficient and Confident Sampling for Modern Scientific Discovery (2023-2026) Science-Integrated Predictive modeLing (SCINPL) for scalable scientific computing (2022-2025) The X-SCAPE collaboration for statistically advanced nuclear collision modeling (2020-2025) These projects fund his development of statistical frameworks for scientific discovery in complex systems. He actively contributes to the JETSCAPE collaboration, developing multi-stage frameworks for studying jet quenching in heavy-ion collisions, and applies statistical methods through the Duke Institute for Brain Sciences to advance neuroscience research.

Pascale BironView profile

Professor

• Hydro-geomorphology
• River Restoration
• Floodplain Management
• +3 more

Pascale Biron is a Professor in the Department of Geography, Urban Planning and Environment at Concordia University, Montreal. She holds a Ph.D. in Geography from Université de Montréal (1995) and has been with Concordia since 1998. Her research focuses on river dynamics, stream restoration for fish habitat, flood modeling, and climate change impacts. She specializes in hydrogeomorphology, river management in agricultural watersheds, and numerical modeling of fluvial processes. Research Interests: Her work includes river restoration strategies, flood risk assessment using LiDAR technology, and the 'river freedom' concept promoting ecosystem resilience. She collaborates closely with government agencies to translate research into practical river management policies. Professional Affiliations: Canadian Geomorphology Research Group, Canadian Association of Geographers, American Geophysical Union, GRIL (Limnology Research Group), and RIISQ (Quebec Flood Risk Network). Publications & Research: Recent studies address global salmonid biomass patterns, fluvial hazard detection via machine learning, and large-scale flood modeling. She supervises 19 graduate students in Ph.D./M.Sc. programs in Geography and Environmental Studies, focusing on topics like river confluence hydraulics and agricultural stream restoration. Grants & Funding: Active projects include river dynamics in fish habitats, flood modeling for road infrastructure vulnerability, and computational fluid dynamics simulations of river flows. She also leads research on societal dimensions of river restoration and policy frameworks for flood resilience.