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Pia FrickerView profile

Associate Professor

• Computational Methodologies
• Urban Design
• Landscape Architecture
• +8 more

Prof. Pia Fricker is an Associate Professor and Vice Head of the Department of Architecture at Aalto University's School of Arts, Design and Architecture in Finland. She holds the Professorship of Computational Methodologies in Landscape Architecture and Urbanism, directing the Urban Studies and Planning Programme. Her research integrates urban design, landscape architecture, and digital design culture, focusing on data-driven methods, immersive environments, and adaptive urban development. Collaborations include ETH Zurich, Singapore University of Technology and Design, and Hafencity University Hamburg. Key projects include the Metaversity and Future Smart Cities initiatives. Fricker has led over 80 publications and exhibitions globally, including at the Venice Biennale and National Design Centre Singapore. She is an editorial board member for the Journal of Digital Landscape Architecture and peer reviewer for multiple journals. Awards include the Digital Landscape Architecture Award (2018) and DLA Scientific Merit Award (2021). Her teaching emphasizes computational pedagogy and digital innovation in design education. Education: PhD in Architecture (ETH Zurich, 2021) Postgraduate in Didactics (ETH Zurich, 2011) MAS in Computer Aided Architectural Design (ETH Zurich, 2003) MSc Arch in Urban Design & Landscape Architecture (Technical University of Karlsruhe, 2001) Research Interests: Computational design, parametric modeling, mixed reality, climate-adaptive ecosystems, generative AI, and sustainable urban development. Her work bridges emerging technologies with ecological and urban challenges, emphasizing interdisciplinary collaboration. Grants & Projects: Metaversity (2023–2025, Principal Investigator) Future Smart Cities Sasakawa (2023–2024, Principal Investigator) ABRA (2020–2023, Project Member) Awards: DLA Awards (2018, 2021) DLA Review Committee Awards (2020–2022) Exhibition Recognitions (Venice Biennale, National Design Centre Singapore) Labs/Teams: Leads the Urban Studies and Planning Programme and collaborates with interdisciplinary teams on projects like the RAILCORRIDOR Singapore initiative. Active in digital twin development and AI-driven design tools.

Marc PollefeysView profile

Professor

• 3D Computer Vision
• Robotics
• Machine Learning
• +5 more

Marc Pollefeys is a Full Professor of Computer Science at ETH Zurich and Director of the Microsoft Mixed Reality and AI Zurich Lab. He has held roles such as Visiting Professor at Stanford University (2007) and Assistant/Associate Professor at UNC-Chapel Hill (2002–2009). His research focuses on 3D computer vision, robotics, machine learning, and augmented reality. Education: PhD in Computer Science from KU Leuven (1999), followed by postdoctoral research there until 2002. He transitioned to academic roles at UNC-Chapel Hill before joining ETH Zurich in 2007. Research interests include 3D reconstruction, visual localization, SLAM, and applications in archaeology, urban modeling, and robotics. Notable projects include real-time 3D scanning, city-scale reconstruction, and autonomous vision-based drones. Key awards include ACM Fellow (2022), IEEE Fellow (2012), and ERC Starting Grant (2008). He advises numerous PhD students and collaborates with institutions like Google and Microsoft. Labs and teams: Leads the Computer Vision and Geometry (CVG) lab at ETH Zurich and directs the Microsoft Mixed Reality and AI Lab. His work bridges academia and industry, focusing on perception for mixed reality and autonomous systems.

• Cybersecurity
• Data Security and Privacy
• GRC (Governance, Risk, Compliance)
• +6 more

Dr. Gowri Sankar Ramachandran is a Senior Lecturer in the School of Information Systems at Queensland University of Technology (QUT), specializing in cybersecurity and distributed systems. She holds a PhD from KU Leuven (Belgium) and a postdoctoral position at the University of Southern California (USC). Her research focuses on open-source software security, runtime threat detection, blockchain applications, and IoT vulnerabilities. Notable contributions include the FUSE tool for detecting malicious packages and the discovery of hyperlink hijacking vulnerabilities affecting millions of domains. Research interests span software supply chain security, metadata-based risk analysis, and generative AI for cyber risk modeling. Awards include Best Paper Awards at ACM CBSE (2016), Mobiquitous (2017), and BigMM (2019). Collaborations include projects with CSIRO, the City of Los Angeles, and the University of São Paulo. She teaches courses on cybersecurity, database management, and network security, and actively supervises PhD students in cybersecurity and blockchain domains. Recent publications address blockchain-based data governance, quantum-resilient IoT protocols, and decentralized identity systems. Her work bridges academic research with real-world impact, addressing critical challenges in digital systems security and privacy.

Hugues AschardView profile

Researcher

• Statistical Genetics
• Genome-Wide Association Studies (GWAS)
• Microbiome Research
• +7 more

Hugues Aschard is a Principal Investigator and Structure Manager at the Pasteur Institute in Paris, where he leads research in statistical genetics, microbiome analysis, and computational genomics. He is the principal investigator of the MicMat project, the EpiGenCOV Consortium, and several bioinformatics software initiatives including JASS, RAISS, and MGMM. Research Interests: Statistical and computational methods in genetics Genome-wide association studies (GWAS) Gene-environment interactions Microbiome and host genetics in inflammatory bowel disease Genetic epidemiology of infectious diseases like COVID-19 Development of open-source tools for multi-trait and summary-statistic analysis Recent Research Trends: His recent publications and projects emphasize integrative genetic modeling, multi-trait analysis across diverse populations, and the development of novel computational methods to handle missing data and improve SNP discovery. His work bridges statistical innovation with biological and clinical applications in complex diseases. Scientific Contributions: Development of JASS, RAISS, and MGMM software tools Leadership in large-scale consortia like EpiGenCOV Advancing methods for cross-ancestry genetic studies Advising and Collaboration: He supervises multiple PhD students and postdoctoral fellows, including Christophe Boetto, Antoine Auvergne, and Lucas Chataigner. He collaborates with major institutions such as APHP and CNRGH. His team includes research engineers and administrative staff, indicating an active and well-supported research group. Laboratories and Teams: He is a key member of the Biomaterials and Microfluidics team at the Pasteur Institute, where he contributes to interdisciplinary research involving Bayesian decision processes and genetic modeling.

• Singular Stochastic Optimal Control
• Optimal Stopping and Free-Boundary Problems
• Stochastic Games
• +6 more

Giorgio Ferrari is a Full Professor for Mathematical Finance at the Institute for Mathematical Economics (IMW), Faculty of Economics, Bielefeld University. His research bridges stochastic control theory with applications in economics, finance, actuarial science, and epidemiology. Education: B.Sc. and M.Sc. in Physics and Mathematical Physics from the University of Rome La Sapienza, Ph.D. in Mathematics for Economic-Financial Applications (2012). Academic Appointments: Post-Doctoral Researcher (2012–2015), Substitute Full Professor (2015), Junior Professor (W1) (2016–2017), Associate Professor (2017–2023), and Full Professor (2023–present) at Bielefeld University. Research Interests focus on Singular Stochastic Control , Optimal Stopping , and Stochastic Games , with applications to economic policy, financial markets, and epidemic modeling. His work extends to Mean-Field Games for large-scale strategic interactions and Free-Boundary Problems for investment decision-making under uncertainty. Scientific Contributions include groundbreaking publications in Stochastic Processes and their Applications , Mathematical Finance , and SIAM Journal on Control and Optimization . His research projects, such as the DFG SFB 1283 subproject C4 and the Research Training Group 2865 , address uncertainty in dynamic economies through game-theoretic and stochastic frameworks. Notable Awards: AMASES Best Young Researcher Paper (2014), YITP Research Prize (2017), and multiple research fellowships from the University of Padova. Leadership: Director of the Bielefeld Graduate School in Theoretical Sciences (2023–present) and Principal Investigator in major DFG-funded initiatives.

Serge A. ShapiroView profile

Professor

• Seismology
• Geophysics
• Rock Physics
• +5 more

Prof. Serge A. Shapiro is a Full Professor of Geophysics at Freie Universität Berlin since 1999 and Director of the PHASE consortium since 2004. He holds a Diploma in Applied Geophysics from Lomonosov Moscow State University (1982), a PhD from the Moscow Research Institute of Geosystems (1987), and a Habilitation from Karlsruhe University (1995). His research focuses on seismogenic processes, induced seismicity, rock physics, and subduction zone dynamics, with applications to geothermal energy, CO2 storage, and hydraulic fracturing. Education: Diploma in Applied Geophysics, Lomonosov Moscow State University (1982) PhD in Geophysics, Moscow Research Institute of Geosystems (1987) Habilitation, Karlsruhe University (1995) Research Interests: Induced seismicity from fluid operations CO2 storage and hydraulic fracturing risks Seismic hazard assessment Rock physics under stress Key Contributions: Developed the Seismogenic Index Model for induced earthquakes Pioneered DAS-based seismic monitoring techniques Advanced understanding of fault stability and pressure diffusion effects Awards: Virgil Kauffman Gold Medal (2013) for work in microseismic monitoring and rock physics Grants & Projects: PHASE consortium leader (2004–present) Utah FORGE EGS project advisor Labs/Teams: Seismology Group, Freie Universität Berlin PHASE university consortium

• Materials Science and Engineering
• Additive Manufacturing
• Materials Informatics
• +7 more

S. Mohadeseh Taheri-Mousavi is an Assistant Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU), part of the College of Engineering. She joined CMU in September 2022 after postdoctoral appointments at MIT and Brown University. Her research is supported by major grants from NASA STRI, DARPA, the Army Research Laboratory, and the Naval Nuclear Laboratory, and she is affiliated with the NextManufacturing Center and the Wilton E. Scott Institute for Energy Innovation. Her educational background includes a Ph.D. from EPFL, Switzerland, and M.Sc. and B.Sc. degrees from Sharif University of Technology, Iran. She was awarded both early and advanced Swiss National Science Foundation fellowships during her postdoctoral studies. Taheri-Mousavi’s research focuses on the intersection of materials science, mechanical engineering, and computer science. She develops multi-scale computational models and AI-driven frameworks—such as AlloyGPT and generative AI agents—to design next-generation structural alloys, particularly for additive manufacturing and extreme environments. Her work emphasizes materials sustainability, industrial decarbonization, and uncertainty quantification in alloy design. The integration of machine learning with Integrated Computational Materials Engineering (ICME) and CALPHAD methods enables rapid exploration of high-dimensional composition and processing spaces. Her recent publications (2023–2025) show a strong trend toward AI/ML applications in alloy discovery, hydrogen embrittlement modeling, and high-temperature aluminum and tungsten alloys. These works reflect a deep commitment to accelerating materials innovation through human-AI collaboration and smart experimental validation. Her scientific honors include prestigious Swiss National Science Foundation fellowships. She has also received seed funding from the Scott Institute for Energy Innovation to study hydrogen embrittlement. She advises a dynamic team of doctoral students and a postdoctoral researcher, working on topics including hydrogen embrittlement, generative AI for welding, and gradient alloys. Her research is funded by high-impact grants from NASA, DARPA, the Army, and the Naval Nuclear Laboratory, supporting transformative projects in structural alloy design. She leads the Taheri-Mousavi Group, which operates within CMU’s Materials Characterization Facility and the NextManufacturing Center. The group focuses on developing novel AI-integrated computational frameworks to guide efficient and intelligent experimentation in alloy development.

Jan CarmelietView profile

Professor

• Multiscale behaviour of porous and granular materials
• Heat-air-moisture flow in urban environments
• Energy systems at building and urban scale
• +4 more

Jan Carmeliet is a Full Professor at the Department of Mechanical and Process Engineering at ETH Zürich , holding the Chair of Building Physics since 2008. He previously held academic positions at Katholieke Universiteit Leuven and Eindhoven University of Technology . His research focuses on multiscale modeling of porous and granular materials , urban heat-air-moisture flows , and energy-efficient urban systems . His work integrates advanced computational techniques (e.g., lattice Boltzmann methods , CFD , FEM ) with experimental approaches ( X-ray tomography , wind tunnel PIV ). He leads major projects such as the RePoDH and Urban Multiscale Energy Modelling initiatives, aiming to decarbonize urban energy systems and understand local heat islands. Current projects emphasize renewable-powered district heating networks and urban climate modeling . Key collaborations include institutions like Empa , University of Illinois , and Los Alamos National Laboratory . He has secured significant grants from the Swiss National Science Foundation (SNSF) and ETH Domain , focusing on urban energy resilience and material science. His leadership roles include directing the Energy Science Center ETH Zürich and coordinating the SCCER-efficiency program.

• Health Economics
• Health Services Research
• Applied Econometrics
• +9 more

Dr Elisabeth Huynh is a Senior Research Fellow at the Australian National University's Centre of Epidemiology for Policy and Practice. She specializes in health economics, focusing on understanding health-related preferences, choice behavior, and economic evaluations in public policy and medical interventions. Education: PhD in Economics (Econometrics) and B.Com from the University of Sydney. Affiliations: Research Affiliate at the University of Sydney (2021-2026). Research Interests: Her work spans health economics, applied econometrics, and public policy, with specific contributions to discrete choice experiments, best-worst scaling, health workforce dynamics, healthy aging, nutrition interventions, and quality-of-life valuation. She investigates decision-making patterns in health care, including patient preferences, end-of-life care, and health service provider behavior. Publications: Her recent articles focus on pediatric quality-of-life metrics, pandemic preparedness modeling, dietary supplement choices during pregnancy, and workforce dynamics in health care. These studies employ advanced econometric methods and systematic reviews to inform policy decisions. Supervision: Elisabeth supervises PhD candidates exploring topics like child health valuation, chronic disease management, and maternal nutrition programs.

• Transportation Network Modeling
• Data Analytics
• Intelligent Transportation Systems
• +5 more

Sean Z. Qian is a Professor at Carnegie Mellon University with joint appointments in the Department of Civil and Environmental Engineering (College of Engineering), Heinz College of Information Systems and Public Policy, and the Department of Electrical and Computer Engineering. He directs the Mobility Data Analytics Center (MAC) and founded the spinoff firm TraffiQure Technologies in 2020 to commercialize AI/ML technologies in infrastructure and mobility services. His academic credentials include: 2012: MS in Statistics, Stanford University 2011: Ph.D. in Civil Engineering, University of California, Davis 2006: MS in Civil Engineering, Tsinghua University 2004: BS in Civil Engineering, Tsinghua University Qian's research centers on large-scale dynamic network modeling and data analytics for multi-modal transportation systems, applying AI, network flow theory, and economics to address aging infrastructure challenges. His work spans Infrastructure Resilience under climate stress, Urban Systems Interdependency , and Intelligent Transportation Systems , with emphasis on sustainable network optimization and cyber-physical-social system integration. Key methodologies include remote sensing, transportation economics, and digital twin technologies for infrastructure management. His notable scientific awards include: NSF CAREER Award (2018) Greenshields Prize, Transportation Research Board (2017) Research funding has been secured from diverse sources: Federal Agencies: National Science Foundation (NSF), U.S. Department of Energy (DOE), U.S. Department of Transportation (DOT) State Agencies: Pennsylvania Department of Transportation (PennDOT), Maryland Department of Transportation (MDOT), Pennsylvania Department of Community and Economic Development (DCED) Industry Partners: IBM, Honda Research Institute, Fujitsu Inc. Foundations: Benedum Foundation, Hillman Foundation As Director of the Mobility Data Analytics Center (MAC), Qian leads collaborations with Fujitsu on digital twin technologies for infrastructure management in southwestern Pennsylvania, while actively mentoring graduate students and recruiting Ph.D. candidates with strong quantitative backgrounds for Fall 2025.

Susan D. HovorkaView profile

Research Professor

• Geological Sequestration of Greenhouse Gases
• Sedimentology
• Reservoir Characterization
• +3 more

Dr. Susan D. Hovorka is a Research Professor at the Bureau of Economic Geology, The University of Texas at Austin, specializing in geological techniques for environmental applications. She focuses on subsurface permeability dynamics in both tight and highly transmissive systems, with a primary emphasis on geological carbon sequestration and CO₂ storage security. Ph.D. in Geology (1990), The University of Texas at Austin M.A. in Geology (1981), The University of Texas at Austin B.A. in Geology (1974), Earlham College Her research addresses critical challenges in carbon geological storage, including: Characterizing salt formations as containment materials Analyzing carbonate fabrics for karst aquifer flow understanding Field CO₂ injection experiments for sequestration assessment Developing composite confining systems for secure CO₂ retention The articles she has contributed to since 2002 demonstrate a consistent focus on: Carbon capture and storage (CCS) technologies Reservoir pressure dynamics and fault permeability Permit-ready site workflows and risk mitigation Geological analogs from petroleum systems Dr. Hovorka actively collaborates with institutions like the Gulf Coast Carbon Center (GCCC) and participates in international CCS initiatives. Her work integrates sedimentology, geophysics, and environmental policy to advance subsurface carbon management solutions.

Arman KhoshghalbView profile

Senior Lecturer

• Numerical Modelling
• Multi-phase Porous Media
• Unsaturated Soils
• +3 more

Dr. Arman Khoshghalb is a Senior Lecturer in Geotechnical Engineering at the School of Civil and Environmental Engineering, UNSW Sydney, where he has been a faculty member since 2012. His academic credentials include a PhD in Geotechnical Engineering from UNSW (2012), an MSc from Sharif University of Technology (2005), and a BSc in Civil Engineering from the same institution (2003). His research focuses on numerical modeling of multi-phase porous media , with emphasis on unsaturated soils, large deformation analysis, and dynamic soil behavior. Key areas include meshfree computational methods, soil-structure interaction, bio-cementation, and thermo-hydro-mechanical processes in geotechnical systems. His work bridges theoretical advancements with practical applications in slope stability, foundation engineering, and sustainable ground improvement. Dr. Khoshghalb's publications predominantly explore geomechanical modeling, experimental soil mechanics, and computational techniques. Recent trends highlight innovations in bio-cemented soils, thermal properties of unsaturated soils, and adaptive numerical methods for complex geotechnical simulations. Awards & Honors: IACMAG Excellent Paper Award (2017) UNSW Research Excellence Award (2012) Advising & Grants: He has supervised 7+ PhD students on topics ranging from weak rock mechanics to computational geomechanics. Funded projects include: ARC Discovery Project (2019–2021): "Non-isothermal dynamic strain localisation in unsaturated porous media" ($298,257) ARC Linkage Infrastructure Grant (2015): "Earthquake shaking table for soil-structure interactions" ($320,000) ARC Linkage Project (2014–2017): "Constitutive modelling of weak rocks" ($314,280) He leads research within UNSW's geotechnical engineering group, collaborating on large-scale experimental testing and computational frameworks for infrastructure resilience.

• Sustainability
• Environmental Policy
• Corporate Social Responsibility
• +4 more

Diana Mangalagiu is an Associate Professor at NEOMA Business School , with expertise in Sustainability, Environmental Policy, Corporate Social Responsibility (CSR), Low Carbon Transition, Modeling, and Social Experimentation . Her research bridges natural and social sciences, focusing on systemic risks, foresight, and equitable climate policy. Education : PhD in Artificial Intelligence (École Polytechnique), MSc in Physics, MSc in Sociology, MSc in Management Leadership Roles : Co-founder of the Initiative for Science, Society and Policy Dialogue; scientific board member of the Global Climate Forum, Integrated Risk Governance Project, and Global System Dynamics and Policy; Co-Chair of UNEP’s Global Environmental Outlook. Research Interests : Dr. Mangalagiu’s work explores the intersection of environmental and economic policies through modeling , social experimentation , and foresight . Recent studies focus on coal and carbon-intensive regions, stakeholder engagement, and systemic tipping points in sustainability transitions. Recent Publications : Her 15 most recent articles (2025–2020) span journals like Global Environmental Change and Climatic Change , addressing topics such as social-ecological tipping scales , socio-technical transitions , and green gentrification . These works emphasize equity , cross-regional comparisons , and policy innovation . Projects and Collaborations : She has led or participated in advisory and research projects with the World Bank , OECD , UNEP , and UNDP , focusing on climate policy, energy efficiency, and sustainable urban development. Fluent in seven languages, her international perspective enriches her work in global contexts.

Hongbo ZhangView profile

Professor

• Functional Materials
• Drug Delivery
• Biomedical Engineering
• +4 more

Professor Hongbo Zhang is a leading academic at Åbo Akademi University , affiliated with the Faculty of Natural Sciences and Engineering and the InFLAMES (Innovation Ecosystem based on the Immune System) flagship program. With over 227 publications and 21 active/completed projects since 2006, his research spans Functional Materials , Drug Delivery , and Clinical Translation . Research Interests: His work focuses on Engineering nanostructures for blood-brain barrier penetration Microfluidics-enabled biomedical devices Antimicrobial resistance solutions Cellulose-based sustainable materials Mitochondrial delivery systems Theranostic hydrogels Scientific Awards: Fellow of the Royal Society of Chemistry (2024) MDPI Pharmaceutics Young Investigator (2020) Chinese Orthopedic Association 1st Prize (2019) Best Oral Drug Formulation (Control Release Society, 2014) 10 Leading Chinese Talents in Europe (2023) Collaborative Network: Actively hosts international researchers and contributes to EU/Nordic-funded projects like NAP4DIVE and Printed Intelligence Infrastructure . His recent publications demonstrate expertise in nanomedicine, biocomposites, and lignin valorization.

Irina RishView profile

Professor

• Machine Learning
• Neural Scaling Laws
• Emergent Behaviors in AI
• +13 more

Irina Rish is a Full Professor at the Université de Montréal and a core academic member of Mila – Quebec Artificial Intelligence Institute, where she leads the Autonomous AI Lab. She holds a Canada Excellence Research Chair (CERC) and a CIFAR AI Chair, reflecting her leadership in foundational AI research. Her work is supported by major initiatives, including the U.S. Department of Energy’s INCITE project on Summit and Frontier supercomputers. PhD in AI, University of California, Irvine MSc in AI, University of California, Irvine MSc in Applied Mathematics, Moscow Gubkin Institute Her research focuses on machine learning, neural scaling laws, emergent behaviors in foundation models, continual learning, robustness, and neuroscience-inspired AI . She explores how AI systems can become more general, flexible, and aligned with human cognition. Her recent work investigates training dynamics in large language models, efficient pruning techniques, and the development of time-series foundation models. The analysis of her recent publications reveals a strong focus on scaling behaviors, continual adaptation, and robustness in AI systems . Her work spans theoretical understanding of training dynamics (e.g., zero-sum learning), practical optimization methods, and applications in climate modeling and mental health. She emphasizes open science, leading open-source projects and co-founding Nolano.ai to build efficient, compressed foundation models. Canada Excellence Research Chair (CERC) CIFAR AI Chair IBM Eminence & Excellence Award (2018) IBM Outstanding Innovation Award (2018) IBM Outstanding Technical Achievement Award (2017) IBM Research Accomplishment Award (2009) Irina Rish advises a large group of PhD and Master’s students across Université de Montréal, McGill, and Concordia. She leads major research grants and collaborates internationally on HPC-based AI research. She is also the co-founder and CSO of Nolano.ai, driving innovation in efficient AI systems. She leads the Autonomous AI Lab, which focuses on building large-scale foundation models, understanding neural scaling laws, and developing bio-inspired learning systems. She actively organizes reading groups on scaling, continual learning, and out-of-distribution generalization, fostering a collaborative research environment.