W. Brent Lindquist is a Professor in the Department of Mathematics and Statistics at Texas Tech University, affiliated with the TTU Mathematical Finance Program. His contact details include office location in the Mathematics & Statistics building (Room 104), phone (+1 806 834 2348), and email brent.lindquist@ttu.edu. His research spans computational financial mathematics, porous media flow, neuroscience applications, and quantum electrodynamics. Key contributions include dynamic asset pricing with market microstructure integration, pore-scale flow modeling using 3D micro-tomography, automated neuron morphology identification, and QED computations for electron magnetic moments. Recent work emphasizes ESG factor incorporation into financial models. Analysis of 2023–2025 publications reveals a dominant focus on sustainable finance, particularly ESG-integrated option pricing and portfolio optimization. Methodologies include random forests for market microstructure analysis, skew random walks for volatility modeling, and Lévy processes for Bitcoin dynamics. Cross-cutting themes involve hedonic real estate models with ESG factors and unified asset pricing frameworks bridging classical finance theories.
Evelyn Lake is an Associate Professor in the Department of Radiology and Biomedical Imaging at Yale University, with affiliations to the Wu Tsai Institute and Yale Biomedical Imaging Institute. Her research focuses on functional neuroimaging, particularly using rodent models to study brain connectivity, neurovascular coupling, and disorders like Alzheimer’s disease and autism spectrum disorder. PhD in Medical Biophysics, University of Toronto (2016) Postdoctoral Associate, Yale University (2019) BSc (Honors) in Biophysics, University of Guelph (2010) Her work spans multimodal imaging techniques (e.g., simultaneous Ca2+ and fMRI), examining how genetic mutations (e.g., PTEN, KATNAL2) affect cerebrospinal fluid dynamics and neuronal connectivity. She investigates longitudinal changes in Alzheimer’s models and methodological aspects of animal neuroimaging, such as sample size optimization and awake imaging protocols. Recent publications highlight her contributions to understanding autism-related white matter abnormalities, transdiagnostic connectome predictive modeling, and the impact of neurovascular uncoupling in awake mice. Collaborations include Todd Constable, Francesca Mandino, Xilin Shen, and Xenophon Papademetris.
Gajanan S. Bhat is a Professor and Department Head at the University of Georgia within the College of Family and Consumer Sciences . He earned his PhD in Textile and Polymer Engineering from Georgia Tech in 1990. Education : PhD (Georgia Tech, 1990) Professional Journey : Joining the University of Tennessee, Knoxville (UTK) in 1990, became Director of UTNRL , researching nanofibers, sustainable materials, and high-performance fibers. Recently transitioned to UGA as department head. Dr. Bhat's research focuses on nonwovens (meltblown, spunmelt), sustainable materials (cotton-based composites, biodegradable polymers), and high-performance fibers (carbon fibers, ballistic materials). His work bridges nanotechnology and industrial applications , addressing challenges in filtration , protective fabrics , and recycling . Recent publications highlight advancements in thermal conductivity modeling , flexible sensors , and ecological composites . His research has expanded into flushable nonwovens , PLA-based filters , and stretchable cotton textiles . Scientific Recognition : Outstanding Young Engineering Alumni, Georgia Tech (1996) Distinguished Achievement Award, The Fiber Society (1999) Technical Achievement Award, TAPPI (2014) He serves on editorial boards of journals like International Journal of Textile Engineering and Processes and Journal of Nanomaterials and Molecular Nanotechnology . Active in professional societies including The Fiber Society , INDA , and Textile Institute .
Lawrence Staib is Professor of Radiology and Biomedical Imaging, Biomedical Engineering, and Electrical Engineering at Yale University. He serves as Director of Undergraduate Studies in Biomedical Engineering and is a member of Yale's Bioimaging Sciences division, Image Processing & Analysis Group, Yale Biomedical Imaging Institute, and Yale-BI Biomedical Data Science Fellowship program. Dr. Staib earned his A.B. in Physics from Cornell University (1982), followed by a Ph.D. in Engineering and Applied Science from Yale University (1990), and completed a postdoctoral fellowship at Yale School of Medicine (1991). His research focuses on developing advanced medical image analysis methods using machine learning and model-based approaches. Key research areas include neuroimaging applications for autism spectrum disorder classification, cardiac imaging analysis for strain and motion assessment, prostate cancer diagnosis and risk mapping, and innovative techniques for medical image segmentation with limited labeled data. Dr. Staib's work emphasizes uncertainty estimation in deep learning models, multi-modal image registration, and domain adaptation techniques to improve clinical decision support systems. His recent publications demonstrate a strong trend toward developing interpretable AI models for clinical applications, with particular emphasis on fMRI analysis for neurological conditions, cardiac motion analysis, and prostate cancer diagnosis. His work frequently addresses the challenge of limited labeled data in medical imaging through innovative self-supervised, semi-supervised, and few-shot learning approaches. Fellow of the American Institute for Medical and Biological Engineering (AIMBE) (2015) Distinguished Investigator Award from the Academy for Radiology & Biomedical Imaging Research (2017) MICCAI Fellow (2022) Medical Image Analysis Second Best MICCAI Paper Award (2005) ASNR Cum Laude Scientific Exhibit Award (2003) Dr. Staib serves on the editorial board of Medical Image Analysis and as Associate Editor of IEEE Transactions on Biomedical Engineering. His research is supported by NIH grants including the Autism Center of Excellence program. He leads the Image Processing & Analysis Group within Yale's Bioimaging Sciences division, collaborating extensively with James Duncan, John Onofrey, Xenophon Papademetris, and other Yale researchers on applications spanning neuroimaging, cardiology, and oncology. Current projects focus on developing robust AI models for clinical decision support with emphasis on uncertainty quantification and interpretability.
Prof. Jürgen Rühe is a Full Professor of Chemistry and Physics of Interfaces at the Institute of Microsystems Technology, Albert Ludwigs University of Freiburg, within the Faculty of Engineering. He serves as Deputy Coordinator of Research Area C and Principal Investigator for Research Areas A, B, C, and D. His expertise spans polymers at interfaces, metamaterials, biomedical surfaces, and self-healing materials. He leads the Cluster of Excellence liv MatS, focusing on adaptive and energy-autonomous materials systems. Education: Not explicitly stated in text. His research emphasizes programmable materials, 4D printing, and bioinspired design, with projects funded by the German Research Foundation (DFG). Notable contributions include anti-fog coatings, magnetic microactuators for cell stimulation, and hygromorphic materials for adaptive architecture. He supervises doctoral and postdoctoral researchers, advancing fields like tribology and surface functionalization. Key scientific achievements include developing C,H-insertion cross-linking (CHic) for durable polymer networks and exploring smart materials for biomedical and environmental applications. His work bridges fundamental polymer chemistry with practical applications in energy, healthcare, and sustainable architecture. He advises over ten doctoral students and collaborates with industry partners. His lab, part of the Institute of Microsystems Technology, focuses on micro- and nanostructuring, with projects funded by the Cluster of Excellence.
Professor Fernando Calamante is a Professor of Biomedical Engineering at The University of Sydney and Director of Sydney Imaging Core Research Facility. He leads the National Imaging Facility node and focuses on advanced MRI methodologies, particularly Diffusion and Perfusion MRI, to study brain connectivity and neurological disorders. His work includes developing the MRtrix software, widely used in diffusion MRI analysis. He holds extensive funding (~$50M) and has been recognized with awards like ISMRM Fellowship and NHMRC grants. His research spans super-resolution imaging, brain connectomics, and clinical applications in stroke and tumors. Education: BSc (Physics, Argentina), PhD (Magnetic Resonance Imaging, University College London). Career highlights include leadership roles at The Florey Institute and ISMRM presidency (2021-2022). Research interests include: Novel MRI methods for brain connectivity and super-resolution imaging Applications of Diffusion and Perfusion MRI in neurology Integration of structural and functional connectomics Key achievements: Over 200 publications, software innovations, and leadership in global MRI societies.
Essa Yacoub is a Professor in the Department of Radiology at the University of Minnesota, affiliated with the PhD Program in Medical Physics and the Center for Magnetic Resonance Research. His work focuses on advancing MRI and fMRI technologies, particularly at ultrahigh magnetic fields (e.g., 10.5 T), to achieve unprecedented spatial and temporal resolution in brain imaging. He leads projects in RF coil design, noise reduction algorithms, and developmental neuroimaging. Roles: Professor, Medical Physics Program Faculty Affiliations: Center for Magnetic Resonance Research, Department of Radiology Research emphasizes high-resolution fMRI applications, including layer-specific brain mapping, pediatric neurodevelopment studies (e.g., Baby Connectome Project), and translational tools like BIBSNet for infant brain segmentation. His innovations bridge hardware engineering (RF coils) and software (denoising pipelines) to tackle challenges in mesoscopic-scale imaging. Key contributions include optimizing imaging protocols at 7T/10.5T, developing NORDIC denoising for submillimeter data, and advancing understanding of brain networks in aging and neurological disorders. His work is foundational for large-scale initiatives like the Human Connectome Project and non-human primate neuroimaging collaborations. Grants and collaborations focus on translational imaging technologies, while educational contributions include training through the Medical Physics PhD Program. Ongoing efforts aim to refine ultra-high field MRI applications for clinical and basic neuroscience research.
Suresh K. Sitaraman is a Regents' Professor and Morris M. Bryan, Jr. Professor in Mechanical Engineering at the Georgia Institute of Technology's George W. Woodruff School of Mechanical Engineering. His primary research focuses on Computer-Aided Engineering (CAE) and Design, manufacturing processes, micro/nano engineering, and mechanics of materials. He leads the Computer-Aided Simulation of Packaging Reliability (CASPaR) Lab and is involved in flexible hybrid electronics research through the Flexible Electronics Center . Dr. Sitaraman holds a Ph.D. from The Ohio State University (1989), M.A.Sc. from the University of Ottawa (1985), and B.E. from the University of Madras (1982). His research includes developing novel techniques like fixtureless magnetic actuation for interfacial fracture testing, compliant micro-scale interconnects for stress mitigation, and synchrotron X-ray diffraction analysis for through-silicon vias (TSVs). He has pioneered studies on carbon nanotube forests' mechanical properties and reliability challenges in 3D microsystems. His awards include the NSF CAREER Award (1997-2002), ASME Fellow designation (2004), and Sigma Xi Sustained Research Award (2008). He has authored over 150 publications and holds multiple patents on compliant interconnect technologies and packaging reliability solutions. Key Research Themes: Micro/nano-scale material characterization, physics-based predictive modeling, flexible electronics, 3D integration, and thermal management. Labs/Initiatives: CASPaR Lab ( caspar.gatech.edu ), Flexible Hybrid Electronics Center. Industry Impact: Contributions to semiconductor packaging, wearable electronics, and advanced manufacturing techniques.
Roy Johnsen is a Professor in the Department of Mechanical and Industrial Engineering at the Norwegian University of Science and Technology (NTNU), specializing in corrosion and surface technology. With a Dr.ing. degree from NTH (1984), he has extensive industry experience from Statoil Research Centre (1985-1991) and CorrOcean (1991-2004), where he expanded the company globally. His current research focuses on hydrogen embrittlement, corrosion protection, and integrity management in offshore systems, with collaborations across Europe, Asia, and the Americas.
Teng-Fong Wong is a Research Professor in the Department of Geosciences at Stony Brook University, where he has been a faculty member since 1982. His research focuses on the intersection of rock mechanics, earthquake processes, and environmental applications, making significant contributions to understanding deformation mechanisms in geological materials. Education: Sc.B., Brown University, 1973 M.S., Harvard University, 1976 Ph.D., Massachusetts Institute of Technology, 1981 Research Interests: Professor Wong's research centers on rock mechanics with emphasis on earthquake mechanics, energy resources, and environmental applications. He investigates both phenomenological and micromechanical aspects of rock deformation and fluid flow using an integrated approach combining high-pressure deformation experiments, quantitative microstructure characterization, and theoretical analysis. His work spans brittle-ductile transitions in porous rocks, permeability evolution, strength properties of fault zone materials from SAFOD and TCDP drilling projects, and submarine groundwater discharge systems. Publication Trends: Wong's recent publications (2006-2008) demonstrate a consistent focus on strain localization mechanisms in porous rocks, particularly examining compaction bands and deformation bands in sandstones. His work integrates advanced imaging techniques (X-ray radiography, CT scanning) with mechanical testing to understand the micromechanics of rock failure. A significant thread connects his research on fault zone properties from major drilling projects (SAFOD, TCDP) with fundamental rock deformation processes. Scientific Recognition: U.S. Patent 6,874,371 for Ultrasonic Seepage Meter (2005) U.S. Patent 7,107,859 for Ultrasonic Seepage Meter (2006) Co-author of "Experimental Rock Deformation - The Brittle Field" (2nd Edition, Springer-Verlag, 2005) Professional Activities: Professor Wong maintains an active international research profile with numerous visiting appointments including at Australian National University, MIT, ETH Zurich, and institutions in China and France. His work involves extensive collaboration with USGS and international research teams on major fault zone drilling projects. He has developed specialized equipment like the ultrasonic seepage meter for measuring submarine groundwater discharge. Research Infrastructure: Wong's laboratory utilizes advanced capabilities including high-pressure deformation equipment, 3D visualization through laser scanning confocal microscopy and synchrotron microCT, and integrates these with analytic modeling and numerical simulation techniques (finite element and discrete element methods) to investigate micromechanics of dilatant and compactant failure in geological materials.
Dr. Daan van Rooij serves as an Assistant Professor in the Department of Experimental Psychology at Utrecht University's Faculty of Social and Behavioural Sciences. His academic work is centered within the Helmholtz Institute Experimental Psychology research program under Chair Kenemans. His research expertise spans Cognitive Neuroscience, Functional Magnetic Resonance Imaging, Psychology, Disruptive Behaviour Disorders (specifically ADHD, ODD, CD), Cognitive Development, and Artificial Intelligence. Van Rooij employs fMRI and EEG imaging metrics to study brain development during childhood and adolescence, with particular focus on understanding how biological and environmental factors shape the development of impulsive behavior in youth. His scholarly publications demonstrate strong contributions to autism research, ADHD symptomology, and the genetic architecture of brain structures, with work appearing in high-impact journals including Molecular Autism, NeuroImage: Clinical, and Nature Genetics. Dr. van Rooij teaches various courses within the bachelor and master programs of Applied Cognitive Psychology, as well as AI bachelor and master tracks at Utrecht University, including courses such as 'Artificial Intelligence for an Open Society' and 'Experimentele methoden en statistiek' (Experimental Methods and Statistics).
Marc De Graef is the John and Claire Bertucci Distinguished Professor of Materials Science and Engineering at Carnegie Mellon University (CMU). He leads the J. Earle and Mary Roberts Materials Characterization Laboratory and is affiliated with the Materials Science and Engineering Department within the College of Engineering. De Graef holds dual roles as a faculty director and researcher, specializing in advanced materials characterization techniques, particularly electron microscopy and microstructural analysis. Education: Ph.D. in Physics, Catholic University of Leuven (1989) M.S. and B.S. in Physics, University of Antwerp (1983) Research Interests: De Graef's work focuses on 3D microstructure analysis, materials informatics, magnetic materials, and advanced characterization methods like Lorentz microscopy. His research emphasizes quantitative electron microscopy techniques, including electron backscatter diffraction (EBSD), and their application to study complex materials systems. He has pioneered software tools for materials characterization, such as orientation mapping algorithms and dictionary-based indexing methods. Key Achievements: Recipient of the 2025 Microscopy Society of America Distinguished Scientist Award Author/co-author of over 350 publications and two textbooks: Introduction to Conventional Transmission Electron Microscopy and Structure of Materials Principal investigator on grants including a $7.5M Air Force-funded Center of Excellence in data-driven materials research Lab & Collaborations: Directs the Materials Characterization Facility at CMU, advancing capabilities in X-ray and electron microscopy. His team collaborates on projects involving additive manufacturing, magnetic domain analysis, and topological magnetic structures. Recent work includes studies on skyrmions in thin films and phase stability in novel alloys.
Professor Denis Doorly is a Professor of Fluid Mechanics in the Department of Aeronautics at Imperial College London's Faculty of Engineering. His research focuses on biomedical fluid mechanics, particularly respiratory and cardiovascular systems, with expertise in computational fluid dynamics (CFD) and aerosol transport. He has published extensively on nasal airflow modeling, cardiovascular MRI simulations, and aerosol dynamics in medical contexts. Key contributions include CFD cohort studies on nasal decongestion effects, benchmarking models for SARS-CoV-2 transmission, and ventilator strategies during the pandemic. Research interests span biological fluid mechanics, biomedical flows, and medical device design. His work integrates computational modeling with clinical applications, addressing issues like tracheal compression, myocardial perfusion, and aerosol extraction during surgeries. Collaborations include studies on isolated heart models and particle deposition in respiratory systems. Affiliations include the Biological Fluid Mechanics and Biomedical Flows groups at Imperial. His publications (139+ articles) highlight interdisciplinary applications of fluid mechanics to healthcare challenges.
Olivier Tougait is a Professor at the Chemistry, materials and processes for sustainable nuclear power (CIMEND) department within the Unité de Catalyse et Chimie du Solide (UCCS) at Université Lille . He specializes in solid-state chemistry, nuclear materials, and actinide-based compounds, with a focus on understanding fuel cycle processes for nuclear energy. Academic Background: PhD in Chemistry (1998, Université de Rennes1), Postdoctoral Fellow at Northwestern University (1998-2000). Career: Lecturer at Rennes1 (2000-2014), now Professor at UCCS since 2014. Collaborations include the French Alternative Energies and Atomic Energy Commission (CEA) , Orano , and Framatome . Research Interests: Actinide-based intermetallic compounds Phase diagrams of nuclear materials Magnetocaloric properties Fuel cycle process optimization Synthesis and thermodynamic behavior of uranium alloys Collaborative industrial nuclear R&D Publications since 2012 focus on: Uranium-molybdenum fuel characterization Germanium/Aluminum substitution in actinide systems Thermal stability of uranyl peroxide nanoclusters Crystallographic analysis of heavy-fermion materials Labs: Directs the joint research laboratories LR4CU and LRC PUMA, which collaborate with Orano and Framatome on nuclear fuel cycle innovations.
Mitra Taheri is a Professor in the Department of Materials Science and Engineering at Johns Hopkins University, serving as Director of the Materials Characterization and Processing (MCP) facility and a member of the Hopkins Extreme Materials Institute. She holds affiliations with the Pacific Northwest National Laboratory and the Ralph O’Connor Sustainable Energy Institute. Her research focuses on electron microscopy, particularly in-situ and operando techniques, combined with artificial intelligence to study materials under extreme conditions (e.g., high temperatures, radiation, and oxidation). She aims to accelerate materials discovery by integrating AI with microscopy for real-time analysis. Dr. Taheri earned her BS, MSE, and PhD in Materials Science and Engineering from Carnegie Mellon University. Her work spans corrosion-resistant alloys, additive manufacturing, quantum materials, and biomaterials. Research sponsors include PNNL, JHU, NSF, ARPA-E, and ONR. She leads the Dynamic Characterization Group (DCG), which develops autonomous platforms for materials analysis and explores applications in energy, aerospace, and medical systems. Key research areas include: Design of corrosion-resistant multi-principal element alloys AI-driven microscopy for real-time material behavior insights Additive manufacturing of soft magnetic composites for electric vehicles Biomedical hydrogels for tissue engineering Her team develops novel materials and tools to probe structural, functional, and biological systems across scales, with an emphasis on sustainability and extreme environment applications.
