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Roland LarssonView profile

Professor

• Tribology
• Lubrication
• Contact Mechanics
• +2 more

Roland Larsson is a Professor and Head of Subject in Machine Elements at Luleå University of Technology, Sweden. His research focuses on Tribology, particularly lubrication regimes (boundary to elastohydrodynamic), contact mechanics, surface roughness effects, and applications in rolling element bearings, clutches, hydraulic systems, tires, and sports equipment. He has supervised over 20 doctoral and licentiate students, contributed to advanced courses, and developed teaching methods like Flipped Classroom and Constructive Alignment . Education: Ph.D. (1996, Luleå University of Technology), Docent (2001), M.Sc. in Mechanical Engineering (1988). Research: Central themes include elastohydrodynamic lubrication, surface roughness in contact interfaces, and sustainable lubricants. His work explores water-based lubricants, ionic liquids, and glycerol mixtures. Publications: Recent articles (2025) investigate water-based lubricants' film formation, ski-snow friction dynamics, and tribochemical properties of green lubricants. Earlier works (2024-2023) cover micropitting, wear models, and multi-scale contact analysis. Awards: Recipient of multiple tribology awards including ASME Best Paper, Nordea's Vetenskapliga Pris, and Venture Cup North. He has held leadership roles at Luleå University, including Dean and Vice-Dean of the Faculty of Engineering Board. Collaboration: Active in international research networks as peer-reviewer, faculty opponent, and external examiner. His post-doctoral work includes affiliations with Leeds University and SKF Engineering Research Centre.

Monty A. EscabiView profile

Associate Professor

• Auditory Neuroscience
• Neural Engineering
• Signal Processing
• +3 more

Monty A. Escabi is an Associate Professor at the University of Connecticut. His research focuses on understanding the neural mechanisms underlying auditory perception and sound recognition, combining large-scale neural recordings with computational modeling and machine learning. He explores how the brain processes sounds in complex environments, aiming to develop advanced sound recognition technologies and treatments for hearing loss. Education: B.S., Electrical Engineering, Florida International University, 1993 M.S., Electrical Engineering: Signal Processing and Stochastic Modeling, Columbia University, 1995 Ph.D., Bioengineering, University of California at Berkeley and San Francisco, 2000 Research Interests: Dr. Escabi investigates the computational principles of natural hearing, focusing on spectrotemporal processing in auditory pathways. His work bridges signal processing and neuroscience to uncover how neural circuits encode sound features like temporal periodicity and acoustic envelopes. The Escabi Lab also develops neurotechnologies for high-resolution auditory cortex recordings. Grants & Collaborations: National Science Foundation ($890,842): Cortical Specializations for Behavioral Discrimination of Temporal Shape and Rhythm of Sound (2014–2018) National Institutes of Health ($1,448,437): CRCNS: Role of Statistical Regularities in Neural Sound Coding (2015–2020) Laboratory: The Escabi Lab (http://escabilab.uconn.edu) specializes in auditory neuroscience, employing multi-disciplinary approaches to study neural coding and its translational applications in hearing technology.

• Biomedical Informatics
• Data Science
• Machine Learning
• +7 more

Lucila Ohno-Machado, MD, PhD, MBA, is the Waldemar von Zedtwitz Professor of Medicine and Biomedical Informatics and Data Science at Yale University. She serves as Deputy Dean for Biomedical Informatics and Chair of the Department of Biomedical Informatics and Data Science at the Yale School of Medicine. Her leadership roles include overseeing informatics infrastructure for Yale’s academic health system and fostering interdisciplinary collaboration across departments such as Medicine and the Halicioğlu Data Science Institute (previously at UCSD). Ohno-Machado holds an MD from the University of São Paulo (Brazil), an MBA from Fundação Getúlio Vargas (Brazil), and a PhD in Medical Information Sciences and Computer Science from Stanford University. She has held faculty positions at Harvard Medical School, MIT’s Health Sciences and Technology Division, and the UCSD Health Department of Biomedical Informatics, where she pioneered federated learning and privacy-preserving AI methodologies. Her research focuses on predictive analytics, federated learning, quantum computing in healthcare, and blockchain applications to enhance data security. She emphasizes addressing algorithmic bias and promoting health equity through data-driven solutions. Recent work includes developing frameworks for medical device safety evaluation and guiding principles to mitigate disparities in algorithmic healthcare applications. Key achievements include the Inaugural Helen M. Ranney Award (2024), election to the National Academy of Medicine (2024), and the William W. Stead Award (2019). She has led NIH-funded informatics centers and contributed to the first large-scale clinical data-sharing initiative across five UC medical systems. Her grants span AHRQ, PCORI, NSF, and blockchain-related initiatives through the IT/NIST Challenge Award. Ohno-Machado advises on translational research strategies and mentors teams in YBIC (Yale Biomedical Informatics & Computing). Her lab collaborates globally, leveraging federated models and AI to advance personalized medicine while prioritizing patient privacy. She also chairs the OHER Awards for Yale Research Excellence, promoting interdisciplinary health equity research.

Philippe MoireauView profile

Professor

• Inverse Problems
• Data Assimilation
• Partial Differential Equations
• +4 more

Philippe Moireau is a Full Professor in the Department of Applied Mathematics at École Polytechnique, where he is also affiliated with the Center for Applied Mathematics (CMAP). He serves as the head of the Inria Project-Team MΞDISIM (Mathematical and Mechanical Modeling with Data Interaction for Simulation in Medicine) and holds the distinguished position of Ingénieur Général of The Corps des Mines. His primary research focuses on inverse problems and data assimilation for partial differential equation models, with particular emphasis on: Observer-based methods from optimal control perspectives Stabilization approaches for evolution equations Numerical analysis of time-dependent control problems Digital twin applications in cardiovascular medicine Professor Moireau's publication portfolio demonstrates consistent focus on mathematical methods for physical systems, with recurring themes in: Data assimilation techniques for PDE-based models Numerical stabilization and discretization methods Cardiovascular biomechanics and hemodynamics Stochastic modeling of biological systems Epidemiological forecasting and control He leads the ANANKΞ project-team at Inria focused on Analysis And Numerics of physical-Knowledge-based Estimation. His educational contributions include lectures on data assimilation theory at CEMRACS and courses on mathematical modeling in cardiac biomechanics at Institut Polytechnique de Paris.

Julijana GjorgjievaView profile

Professor

• Computational Neuroscience
• Theoretical Neuroscience
• Neural Circuit Development
• +4 more

Prof. Julijana Gjorgjieva is a tenured W3 Professor of Computational Neuroscience at the School of Life Sciences Weihenstephan, Technical University of Munich (TUM). She leads an independent research group at the Max Planck Institute for Brain Research and is affiliated with the Bernstein Center for Computational Neuroscience. Her research focuses on the principles governing neural circuit development, balancing learning plasticity with functional stability through computational and theoretical approaches. Key interests include synaptic organization, energy-efficient neural computation, and evolutionary optimality principles. Education & Career: B.Sc. Mathematics, Harvey Mudd College (2006) M.A.St. in Applied Mathematics, University of Cambridge (2007) Ph.D. Applied Mathematics, University of Cambridge (2011) Postdoctoral Fellowships: Harvard University (2011-2014), Brandeis University (2014-2016) Max Planck Research Group Leader (2016-2022) W2/W3 Professor at TUM since 2016 Research Interests: Computational neuroscience, theoretical modeling of neural circuits, synaptic plasticity mechanisms, homeostatic regulation, and the interplay of development and evolution in shaping brain architecture. She employs mathematical frameworks to study how circuits achieve robustness while enabling adaptive learning. Awards: Heinz Maier-Leibnitz Prize (2022) Eric Kandel Young Neuroscientist Prize (2021) ERC Starting Grant (2018) Multiple postdoctoral and early-career fellowships Grants & Funding: Includes DFG Collaborative Research Center on Neural Homeostasis, HFSP grants, and EU Horizon 2020 initiatives. Active in mentoring and promoting computational neuroscience through programs like Neuromatch Academy. Labs & Collaborations: Leads a multidisciplinary lab integrating experimental and theoretical approaches. Collaborates with institutions such as the Max Planck Society and international computational neuroscience networks.

• Developmental Psychology
• Family Psychology
• Child Mental Health
• +6 more

Professor Bonamy Oliver is a Professor of Developmental and Family Psychology at University College London's IOE - Faculty of Education and Society, leading the Mental Health, Wellbeing and Education Network. Her research focuses on children’s mental health, family relationships, and behavioral genetics. She developed the ESO observation tool, enabling remote parent-child interaction assessments, now used globally. She holds a prestigious 2023 ACAMH Impact Award and contributes to NICE guidelines. Academic roles include Associate Professor (2020-2024) and promoted to full Professor in 2024. She chairs IOE’s Mental Health and Wellbeing Network and directs NurtureLab. Education: PhD in Psychology and Behavioural Genetics (King’s College London, 2006), postdoctoral training at King’s College, followed by faculty roles at Sussex and Goldsmiths. Collaborations span UCL’s Institute of Mental Health, ICH GOS Mental Health Strategic Initiative, and the Accessible Genetics Consortium. Research interests include genetic influences on child development, intervention efficacy, and bridging academic-practitioner gaps. Recent work emphasizes mindful parenting, sibling dynamics, and resilience mechanisms. Articles (2024–2025) address parent-child relationships, polygenic scores in psychopathology, and cross-cultural studies of household chaos. Awards: ACAMH Impact Award (2023), NICE Guidelines contributor Leadership: Chair of IOE’s Mental Health Network, Director of NurtureLab Key Projects: ESO tool, CoTEDS children-of-twins study Advising and grants include interdisciplinary collaborations on child mental health interventions. Labs/Teams: NurtureLab at UCL, cross-institutional mental health initiatives.

• Earthquake Site Response
• Ground-Motion Modeling
• Seismic Building Codes
• +3 more

Dr. Paolo Bergamo is a Senior Researcher at the Swiss Seismological Service (SED), ETH Zurich, since April 2016. He specializes in engineering seismology, focusing on earthquake site response models, ground-motion modeling, and seismic risk assessment. His work includes projects such as the Earthquake Risk Model Switzerland (ERM-CH23) and the SERA Horizon2020 initiative. He holds a PhD in Earth Sciences from Politecnico di Torino (2012) and advanced degrees in Environmental Engineering. Key research areas include soil amplification analysis, geophysical surveys, and the integration of empirical and computational methods for seismic hazard mitigation. His contributions span microzonation studies, site characterization using borehole and ambient vibration data, and the development of design-compatible waveforms for Swiss building codes. Education: PhD in Water and Territory Management Engineering, Politecnico di Torino (2012) MSc and BSc in Environmental Engineering, Politecnico di Torino (2008, 2005) Research Interests: Dr. Bergamo’s work emphasizes the collation of empirical ground-motion data with building codes, spatial modeling of soil amplification, and geophysical site characterization. He employs advanced techniques like surface-wave analysis, machine learning, and canonical correlation for seismic hazard assessment. Projects & Grants: ERM-CH23: Site response implementation and national seismic risk modeling SERA Project (Horizon2020): Site characterization indicators Swiss Federal Office for Environment-funded studies on microzonation and geophysical monitoring Labs & Teams: Active contributor to the Engineering Seismology group at SED, leading efforts in alpine valley seismic modeling and offshore site characterization in Lake Lucerne.

Samuel V. ScarpinoView profile

Professor

• Artificial Intelligence
• Public Health
• Epidemiology
• +3 more

Samuel V. Scarpino is a Professor at Northeastern University , leading as Director of AI + Life Sciences in the Institute for Experiential AI . He holds appointments in the Khoury College of Computer Sciences , Bouvé College of Health Sciences , and the Network Science Institute . Scarpino’s career spans roles at The Rockefeller Foundation, Dharma Platform, and co-founding Global.health , a Google-backed pathogen tracking initiative. Education: PhD in Biology (2013) from The University of Texas at Austin; Omidyar Fellow at the Santa Fe Institute (2013–2016). His research focuses on integrating AI , network science , and epidemiology to address global health challenges. Key areas include disease modeling , wastewater surveillance , and health equity . Recent work explores AI applications for H5N1 pandemic preparedness , scRNA-seq analysis , and social determinants of health . Scarpino’s scientific contributions include over 100 publications in Nature , Science , and PNAS , alongside fellowships from the ISI Foundation (2017), Santa Fe Institute (2020), and Vermont Complex Systems Institute (2021). He mentors PhD students like Wan He and leads interdisciplinary teams at Northeastern’s Roux Institute and Network Science Institute . Grants from the McGovern Foundation and Microsoft Research support his work on AI for public health.

• Optimization under Uncertainty
• Stochastic Programming
• Risk Analysis
• +6 more

Giovanni Pantuso is an Associate Professor at the Department of Mathematical Sciences, University of Copenhagen, specializing in stochastic programming and optimization under uncertainty . His work bridges mathematical methods with practical applications in transportation, logistics, and production planning. Education : PhD in Operations Analysis from the Norwegian University of Science and Technology (Feb 2014) Research Focus : Developing mathematical frameworks for decision-making under risk, with applications to maritime fleet renewal, car-sharing systems, and ride-sharing logistics. Teaching : Courses in Advanced Operations Research: Stochastic Programming, Risk Optimization, and Introduction to Numerical Analysis. His methodological contributions include novel algorithms for stochastic programming and decomposition methods, while applied work spans electric car-sharing systems, first-mile transportation challenges, and production planning under uncertainty. Current research explores dynamic fleet management and cost-service tradeoffs in shared mobility.

• Multiphase Flow
• Turbulence
• Experimental Fluid Dynamics
• +3 more

Dr. Yinghe Qi is a Professor in the Department of Experimental Fluid Dynamics at ETH Zürich, Switzerland. His research focuses on multiphase flows, turbulence, and free-surface dynamics, with applications in aerospace, marine engineering, and computational fluid dynamics. He has contributed extensively to understanding bubble dynamics, flow instabilities, and turbulence modulation through experimental and phenomenological studies. Research Interests: Dr. Qi’s work addresses complex phenomena in multiphase flow instabilities free-surface turbulence deformable bubble dynamics supersonic jet interactions vortex-induced fragmentation machine learning in fluid dynamics Recent Publications: His recent studies (2023–2025) explore multiscale bubble deformation, free-surface turbulence structure, and supersonic jet-plume interactions. Key themes include turbulent fragmentation, vortex-bubble coupling, and novel computational methodologies. Laboratory Affiliations: He collaborates with the Coletti Group, Jenny Group, and Supponen Group at ETH Zürich, advancing experimental and computational techniques in fluid dynamics.

Ahmed F AbdelghanyView profile

Professor

• Commercial Airlines
• Airports
• Big Data Cloud Computing
• +7 more

Dr. Ahmed F. Abdelghany is the Associate Dean for Research and Professor of Operations Management at the David O'Maley College of Business, Embry-Riddle Aeronautical University, since January 2006. He specializes in commercial airlines, airports, big data cloud computing, business analytics, and operations research models. Prior to his academic career, Dr. Abdelghany worked in enterprise optimization at United Airlines, Chicago. Education: Ph.D. in Civil Engineering (Transportation Systems) from the University of Texas at Austin (2001) Dr. Abdelghany’s research focuses on airline network planning, flight scheduling, simulation of complex transportation systems, and NextGen air traffic management. He has authored two influential books: Modeling Applications in the Airline Industry (Routledge 2010) and Airline Network Planning and Scheduling (Wiley 2018). His publications analyze airline operations, competitive dynamics, and crowd management in transportation facilities. He teaches courses like Airline Management (BA 315) and Airline Operations & Mgmnt (BA 609), and participates in industry short courses. Dr. Abdelghany contributes to research projects such as NextGen air traffic implementation, integrated airport initiatives, and benefit-cost analysis of arrival management systems. His work bridges academic theory with real-world airline and transportation challenges.

• Computational Mechanics
• Dynamics of Learning
• Evolutionary Dynamics
• +12 more

Jim Crutchfield is a Distinguished Professor of Physics at the University of California, Davis, where he also serves as Director of the Complexity Sciences Center. He holds additional affiliations as President and Scientific Director of the Art & Science Laboratory in Santa Fe, External Faculty at the Santa Fe Institute, General Member of the Telluride Science Research Center, and Visiting Scholar at the Redwood Center for Theoretical Neuroscience. His work bridges physics, computation, and complex systems. Education: B.A. summa cum laude in Physics and Mathematics, University of California, Santa Cruz (1979) Ph.D. in Physics, University of California, Santa Cruz (1983) Crutchfield's research centers on computational mechanics , a framework he pioneered to quantify how natural systems store, process, and transmit information. His interests span nonlinear dynamics, evolutionary dynamics, information engines, quantum computation, and pattern discovery. He explores how structure emerges in complex systems, from cellular automata to biological evolution and neural networks. His recent work focuses on thermodynamic computing, causal inference, and the physics of intelligence. His publications reveal a consistent focus on the interplay between information, energy, and computation in physical systems. Themes include the thermodynamics of information engines, causal architecture in time series, emergent organization, and intrinsic computation in quantum and classical domains. These works span disciplines such as physics, computer science, biology, and cognitive science. Scientific Recognition: Postdoctoral Fellow, Miller Institute for Basic Research in Science IBM Postdoctoral Fellow, Condensed Matter Physics Distinguished Visiting Research Professor, Beckman Institute Bernard Osher Fellow, San Francisco Exploratorium NSF Graduate Fellow UCB Chancellor’s Fellow Crutchfield has advised over two dozen PhD students in physics, computer science, and mathematics, contributing significantly to the next generation of complexity scientists. He has led major interdisciplinary initiatives, including NSF-funded museum exhibits and workshops on network dynamics, collective cognition, and evolutionary dynamics. He has also been active in public discourse through talks, films, and publications on the philosophy of complexity. He leads research groups exploring the dynamics of learning, pattern discovery, and distributed intelligence, often in collaboration with institutions like the Santa Fe Institute and Caltech. His work continues to shape the theoretical foundations of complex systems science.

Jiaxuan LiView profile

Assistant Professor

• Seismology
• Distributed Acoustic Sensing
• Earthquake Rupture Dynamics
• +7 more

Jiaxuan Li is an Assistant Professor of Geophysics in the Department of Earth and Atmospheric Sciences at the University of Houston's College of Natural Sciences and Mathematics. His research focuses on developing fiber-optic sensing technologies for seismic monitoring across diverse geological environments including volcanic, crustal, and glacial settings. Dr. Li's educational background includes a Ph.D. in Geophysics from the University of Houston (2015-2020) and a B.S. in Geophysics from Peking University (2011-2015). He previously held a postdoctoral position at Caltech Seismolab under Prof. Zhongwen Zhan. His research program centers on distributed acoustic sensing (DAS) applications, with major contributions in volcanic eruption forecasting through minute-scale magma migration imaging, earthquake rupture dynamics via high-frequency fault asperity analysis, and subsurface characterization for carbon sequestration and geothermal energy. Recent work demonstrates DAS capabilities as dense geodetic arrays for real-time volcanic monitoring systems deployed in Iceland through collaborations with the Icelandic Met Office and Reykjavik University. Analysis of Dr. Li's publication record reveals a strong emphasis on operationalizing fiber-optic networks for geophysical monitoring, with significant advancements in eruption early warning systems, earthquake source characterization, and subsurface imaging techniques. His work bridges fundamental seismological research with practical hazard mitigation applications. Dr. Li actively mentors graduate students and recently welcomed postdoc Dr. Tianfan Yan to his research team. His lab operates real-time DAS streaming systems for volcanic eruption monitoring in Iceland, developed through international collaborations involving the University of Houston, Caltech, Ljósleiðarann, and Reykjavik University. Current research directions include expanding DAS applications for carbon sequestration verification and deep geothermal reservoir characterization.

• Biogeochemistry
• Ecosystem Ecology
• Remote Sensing
• +3 more

Ulisse Gomarasca is a doctoral researcher at the Max Planck Institute for Biogeochemistry's Department Biogeochemical Integration, affiliated with the International Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC). He works within the Global Diagnostic Modelling group and Ecosystem Function from Earth Observation project team, focusing on understanding ecosystem functioning through eddy covariance fluxes and biodiversity links. Education: Master's in Ecology and Biodiversity from University of Innsbruck Research: Spatiotemporal dynamics of ecosystem functioning, Sun-Induced Chlorophyll Fluorescence, drought legacy effects on productivity Methodologies: Remote sensing integration with eddy covariance networks, biodiversity-ecosystem function analysis His publications address terrestrial ecosystem responses to climate extremes, scaling of plant traits to ecosystem level, and development of remote sensing tools like the Biodiversity Observing System Simulation Experiment (BOSSE). This work combines satellite observations with ground-based flux measurements to understand global biogeochemical patterns. Contact: ugomar@bgc-jena.mpg.de

Mikael WibergView profile

Professor

• Human–Computer Interaction
• Interaction Design
• Materiality of Interaction
• +5 more

Mikael Wiberg is full Professor of Informatics at Umeå University, Sweden, where he leads research groups in Design Informatics and Digital Interaction & Design. He is co Editor-in-Chief of ACM Interactions and has held chaired and guest professorships at Uppsala, Södertörn and Chalmers universities. His work sits at the intersection of human-computer interaction, materiality, architecture and emerging technologies. Education: PhD in Informatics, Umeå University, 2001 Docent (Associate Professor) in Informatics, Umeå University, 2004 Research interests revolve around interactivity, mobility, materiality and architecture . Wiberg coined the notion of “materiality of interaction” to study how digital resources merge with physical materials, spaces and artefacts. Recent strands include more-than-human design, human-building interaction, autonomous systems UX, and social justice in HCI, all interrogating how interactive technologies shape—and are shaped by—human and non-human actors. Across more than two decades he has published in top venues such as ACM TOCHI, Design Issues, Int. Journal of Design, Human-Computer Interaction journal and the magazine ACM Interactions . His 2018 MIT Press monograph The Materiality of Interaction consolidates his theoretical stance and has become a touchstone for architectural and material HCI discourse. Editorial & scientific awards: Co Editor-in-Chief, ACM Interactions (2019-) Member, Royal Skyttean Society (Kungliga Skytteanska Samfundet) Board member, Professors’ Association, Umeå University He currently leads interdisciplinary projects on digital heritage archives, autonomous vehicle experiences for children with intellectual disabilities, and sustainable interaction infrastructures. Although the provided text does not enumerate specific grants or doctoral students, his continuous project leadership and editorial roles evidence sustained funding and supervisory activity. Wiberg directs the Design Informatics research environment and is a core member of Umeå’s Internet of Things group, fostering collaboration between informatics, architecture, design and social sciences. His overarching agenda asks how interactive technologies can support just, sustainable and aesthetically rich futures at architectural and urban scale.