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Liudas GiraitisView profile

Professor

• Econometrics
• Time Series Analysis
• Quantitative Methods
• +3 more

Liudas Giraitis is a Professor of Econometrics at Queen Mary University of London, affiliated with the School of Economics and Finance. He holds a PhD from Vilnius University and has extensive research experience at Heidelberg University, Boston University, and the London School of Economics. His research focuses on econometrics and quantitative methods, emphasizing long memory processes, ARCH models, semiparametric inference, and time-varying random coefficient models. He has published extensively in leading statistical and econometric journals. His work bridges econometrics, statistics, and probability theory, with a strong emphasis on time series analysis and asymptotic theory. Recent research explores forecasting under ongoing structural change, heteroscedasticity testing, and dynamic stochastic general equilibrium (DSGE) models with financial frictions. Education: PhD in Econometrics from Vilnius University Key Research Themes: Long memory processes, ARCH/GARCH models, time-varying models, nonstationary time series, and asymptotic theory Affiliations: Queen Mary University of London, School of Economics and Finance Research Interests: Dr. Giraitis’s work addresses theoretical and applied challenges in econometric modeling, including robust inference for time series with general heterogeneity, cyclical time series analysis, and the development of asymptotic frameworks for dependent data. His contributions span both foundational theory and practical applications in finance and macroeconomics. Publications: Over 50 peer-reviewed articles in journals such as Journal of Econometrics , Annals of Statistics , and Journal of Time Series Analysis . Key works include the monograph Large Sample Inference for Long Memory Processes (2012) and recent studies on time-varying volatility and structural change. Lab/Team: Active in the School of Economics and Finance’s research group on econometric theory and applied time series analysis.

• Materials Science and Engineering
• Superconductors
• Energy Materials
• +4 more

Dr. Mahboobeh Shahbazi is a Senior Research Fellow in the School of Chemistry & Physics at Queensland University of Technology (QUT) . She holds a PhD in Materials Science and Engineering from the University of Wollongong, specializing in energy materials like superconductors and magnetic materials. Her research focuses on developing cost-effective methods to synthesize materials for applications such as MRI instruments, fusion reactors, hydrogen liquefaction, and green hydrogen systems. Dr. Shahbazi is a recipient of the Advance Queensland Fellowship (2017) and currently serves as a Foundation Fellow in the Future Energy Exports CRC, leading hydrogen-related projects in Programme 2. She collaborates with experts globally on ARC Linkage projects and has been part of ARENA-funded teams investigating battery safety in renewable energy facilities. Research Interests: Superconductors, magnetocaloric materials, energy storage, and sustainable synthesis methods. Key Projects: Hydrogen Export and Value Chains (Future Energy Exports CRC). Nanostructure-engineered superconductors for fusion energy and MRI (ARC Linkage). Her work bridges fundamental material science with practical applications, emphasizing the relationship between material structure, properties, and performance. She actively supervises postgraduate students and collaborates on interdisciplinary research to address global energy challenges.

Marie-Christine ZdoraView profile

Research Fellow

• X-ray Physics
• X-ray Imaging
• Phase Contrast Imaging
• +4 more

Marie-Christine Zdora is a Research Fellow in the School of Physics and Astronomy at Monash University. She holds adjunct roles including Adjunct Scientist at ETH Zürich (2022–2020) and Postdoctoral Researcher at Paul Scherrer Institut (2021–2021). Her academic journey includes a PhD in Physics from University College London (2015–2020), and master’s degrees from TU Munich and the University of Sydney. Her research focuses on advanced X-ray imaging techniques, particularly phase-contrast imaging using near-field speckles, dark-field imaging, and multi-modal approaches. Key areas include medical imaging applications, biological tissue analysis, and synchrotron-based tomography. She leads projects such as Multi-scale, multi-modal X-ray imaging using speckle and collaborates internationally on diagnostic radiology innovations. Zdora has received prestigious awards including the Springer Thesis Award (2020) and the Award of Congressi Stefano Franscini (2016). She serves as an Associate Editor for Optics Express and actively supervises students and mentors interns. Her work contributes to SDGs related to health, innovation, and sustainable development.

• Structural Geology
• Tectonics
• Rift Basin Studies
• +4 more

Haakon Fossen is a Professor at the University of Bergen, affiliated with the Department of Natural History and the University Museum of Bergen. His research focuses on structural geology, tectonics, and the evolution of rift basins, particularly in the North Sea region. He is part of the Geodynamics and Basin Studies research group. His work integrates field observations, seismic data analysis, and microstructural studies to understand orogenic processes, fault mechanics, and basin formation. Key research areas include the Caledonian orogen collapse, Jurassic North Sea rifting, and the interplay between structural inheritance and rift development. Fossen has authored a textbook on Plate Tectonics and collaborates internationally on projects involving deformation band analysis, fault permeability, and seismic interpretation. His contributions span both academic studies and applied geoscience, including work with industry partners like Aker BP ASA and Equinor. Recent research highlights include studies on gravity tectonics in the North Sea, quartz texture analysis for orogenic collapse insights, and structural evolution of Paleozoic basins. Fossen’s methodologies combine advanced techniques like EBSD and machine learning with traditional geologic analysis, emphasizing interdisciplinary approaches to tectonic problems. He has advised numerous collaborative projects and contributed to major international conferences such as the 85th EAGE Annual Conference. His affiliations include roles in both academic and museum settings, reflecting a commitment to both research and public science outreach.

Douglas AllaireView profile

Associate Professor

• Multidisciplinary design optimization
• Bayesian optimization
• Multifidelity methods
• +4 more

Douglas Allaire is an Associate Professor and Sallie and Don Davis '61 Faculty Fellow in the J. Mike Walker ’66 Department of Mechanical Engineering at Texas A&M University, part of the College of Engineering. He leads the Computational Design Laboratory, focusing on computational methods for complex engineered systems. His research spans multidisciplinary design optimization, Bayesian optimization, machine learning, and materials design. Education: Ph.D., Aerospace Engineering, Massachusetts Institute of Technology (2009) M.S., Aerospace Engineering, Massachusetts Institute of Technology (2006) B.S., Aerospace Engineering, Massachusetts Institute of Technology (2004) Research Interests: Bayesian optimization and uncertainty quantification Materials design using machine learning Autonomous experimentation and data fusion Predictive analytics for engineering systems Recent Trends in Publications: His work emphasizes integrating Bayesian methods with materials discovery, autonomous systems, and high-fidelity modeling. Key themes include optimizing multifidelity systems, inverse microstructure design, and real-time decision frameworks. Awards: ASEM Fellow (2024) AIAA Associate Fellow (2023) ASME Young Engineer Award (2018) Advising & Grants: Advised students like Jaylen James (Ph.D. 2022) and Danial Khatamsaz. Active in securing grants for computational design and materials research. Collaborates with institutions like the American Institute of Aeronautics and Astronautics. Labs & Teams: Directs the Computational Design Laboratory, part of the Engineering Systems Design Group. Engages in interdisciplinary projects with Texas A&M’s Multidisciplinary Engineering program.

• Textile Engineering
• Forensic Science
• Material Science
• +3 more

Professor Steve Michielsen is a leading academic in the Department of Fashion & Textiles at RMIT University , based in Brunswick, Australia. His research focuses on advanced textiles, forensic material analysis, and nanotechnology applications in fabrics. He holds a Professor rank and is actively engaged in supervising PhD and Master’s students in projects like Enhanced Mycelium Materials and Stimuli-Responsive Textiles. Key research interests include forensic bloodstain pattern analysis, textile performance under environmental conditions, and the development of smart fabrics with functional properties such as odor control, thermal regulation, and antimicrobial features. His work bridges material science with biomedical and crime scene analysis applications. Professor Michielsen’s recent publications (2020–2025) emphasize interdisciplinary approaches, including studies on bloodstain dynamics, nanodiamond integration in textiles, and wicking mechanisms mimicking human sweating. These contributions highlight innovations in forensic science, sustainable materials, and wearable technology. He oversees supervision of 4 active research projects and collaborates widely in academic and industry networks. While no formal awards are listed, his prolific publication record (over 88 outputs) underscores his scholarly impact. His work frequently appears in journals like Textile Research Journal , Forensic Science International , and Journal of the Textile Institute .

Daniel WangpraseurtView profile

Researcher

• Coral Ecophysiology
• Coral Restoration and Engineering
• Aquatic Benthic Photosynthesis
• +3 more

Dr. Daniel Wangpraseurt is an Associate Researcher at Scripps Institution of Oceanography, University of California, San Diego, where he leads the Coral Reef Ecophysiology and Engineering Lab. He joined Scripps in summer 2024 and co-founded Hybrid Reef Solutions, a startup developing sustainable coral reef protection technologies. Wangpraseurt serves as associate editor for Frontiers in Marine Science: Coral Reefs and sits on the Coral Restoration Consortium advisory board. His educational background includes: PhD from University of Technology Sydney, Australia MSc from Max Planck Institute for Marine Microbiology & Leibniz Center for Tropical Marine Ecology, Germany BSc from James Cook University, Australia Wangpraseurt's research bridges coral reef science, engineering, and biophysics with core interests in coral ecophysiology, restoration engineering, benthic photosynthesis, and blue technology. His work develops innovative tools for reef restoration while investigating fundamental coral physiological processes and optical properties. Analysis of his 2024-2025 publications reveals dominant themes in coral restoration technology development, including biomimetic settlement substrates, acoustic larval enrichment, and engineered biofilms. His optical research focuses on coral microstructure imaging via the Benthic Underwater Microscope (BUMP) and light-harvesting mechanisms across depth gradients. No specific scientific awards are mentioned in the source material. He directs the Coral Reef Ecophysiology and Engineering Lab and leads Hybrid Reef Solutions. His collaborative research includes NSF-BSF projects on Red Sea mesophotic corals and IntBIO grants integrating nanobiotechnologies for coral symbiosis studies. Wangpraseurt maintains active roles in the Coral Restoration Consortium advisory board and Frontiers in Marine Science editorial board, driving both technological innovation and scientific discourse in coral reef conservation.

• Material Science
• Mathematical Modeling
• Fractal Networks
• +5 more

Professor Tony Roberts is the Head of School in the School of Mathematical Sciences at Queensland University of Technology (QUT). He holds a PhD from the Australian National University and is a Fellow of the Australian Mathematics Society. His research focuses on the interplay between material microstructure and macroscopic properties, with emphasis on topology optimization, random structure modeling (e.g., Gaussian fields, percolation models), and material property analysis such as conductivity, diffusion, and fluid flow. He develops computational methods for analyzing experimental techniques like 3D statistical reconstruction and small-angle scattering. His recent work includes optimizing piezoelectric materials for robotics, studying diffusion dynamics in fractal networks, and modeling material failure mechanisms. Key contributions span multi-functional piezoelectric components, anisotropic elastic properties of additively manufactured alloys, and fracture mechanics in perforated materials. Awards include his fellowship in the Australian Mathematics Society. Supervision interests include structural optimization, diffusion in random media, and porous material failure modeling. Education: PhD (Australian National University) Affiliations: Faculty of Science, School of Mathematical Sciences Research Themes: Material science, computational modeling, fracture mechanics, stochastic systems

Gaurav SharmaView profile

Professor

• Data Analytics
• Cyber Physical Systems
• Signal and Image Processing
• +3 more

Gaurav Sharma is a Professor at the University of Rochester, holding joint appointments in the Department of Electrical and Computer Engineering, Computer Science, and Biostatistics and Computational Biology. He is also a Distinguished Researcher at the Goergen Institute for Data Science and Artificial Intelligence. His research focuses on Data Analytics, Cyber Physical Systems, Signal and Image Processing, Computer Vision, Media Security, and Communications. Previously, he served as Director of the Center for Emerging and Innovative Sciences (2008-2010) and held roles at Xerox Research (1996-2003). He earned a PhD in Electrical and Computer Engineering from North Carolina State University (1996), alongside degrees from Indian institutions including the Indian Institute of Science and IIT Roorkee. Education: PhD (NCSU), M.S. Applied Mathematics (NCSU), M.S. Electrical Communication Engineering (IISc), B.Eng (IIT Roorkee) Awards: Fellow of IEEE, SPIE, and IS&T; Elected Sigma Xi member Editorial Roles: Editor-in-Chief of IEEE Transactions on Image Processing (2018-2020) and Journal of Electronic Imaging (2011-2015) Leadership: Chair of IEEE Signal Processing Society committees and SPIE/EI conferences His research spans interdisciplinary areas like medical imaging analytics, cybersecurity in IoT systems, and computational methods for biomedical applications. Recent work includes studies on cardiac mortality patterns, viral protein inhibition, and federated learning for privacy-sensitive healthcare tasks. Dr. Sharma’s contributions to academic governance include roles on IEEE publication committees and strategic planning boards, reflecting his commitment to advancing technical standards and open science practices.

Nicholas BarberisView profile

Professor

• Behavioral Finance
• Behavioral Economics
• Asset Pricing
• +3 more

Nicholas Barberis is the Stephen and Camille Schramm Professor of Management and Professor of Economics at Yale University. He holds a dual appointment in the Yale Department of Economics and the Yale School of Management. His research focuses on behavioral finance, asset pricing, and decision-making under uncertainty, emphasizing psychological factors influencing financial markets. Barberis has published extensively on topics such as prospect theory, investor behavior, market anomalies, and behavioral asset pricing models. His work bridges psychology and economics, addressing questions like how cognitive biases affect investment decisions and market dynamics. Notable contributions include the development of the X-CAPM model (2015), analysis of tail risks (2013), and empirical investigations of realization utility (2012). He has also written on the behavioral aspects of the 2007–2008 financial crisis and the role of mental accounting in investor behavior. Barberis’ research has been cited widely in academic journals and policy discussions. His affiliations include the National Bureau of Economic Research (NBER) and the American Finance Association. He currently serves on editorial boards of leading finance journals.

Jules van BinsbergenView profile

Professor

• Corporate Finance
• Asset Pricing
• Macroeconomics
• +7 more

Jules van Binsbergen is the Anthony L. Davis Director of the Joseph H. Lauder Institute for Management and International Studies and holds the Lauder Chair Professorship at the University of Pennsylvania. He is also the Nippon Life Professor of Finance at The Wharton School and currently a Visiting Professor at MIT Sloan School of Management. His research focuses on asset pricing, financial markets' macroeconomic interactions, and financial intermediaries' performance. He earned a PhD in Finance from Duke University and an MA in Financial Econometrics from Tilburg University, with an undergraduate degree in Jazz Piano from The Hague's Royal Conservatory. Prof. van Binsbergen’s work bridges theoretical and empirical finance. His current research explores the dynamics between financial systems and broader economic trends, including monetary policy impacts, environmental risks, and mutual fund management strategies. He co-hosts the podcast All Else Equal: Making Better Decisions and is affiliated with the NBER and CEPR as a research scholar. His academic trajectory includes teaching roles at Stanford Graduate School of Business and Northwestern’s Kellogg School. Beyond research, he addresses practical finance challenges such as risk-free rate calculation methodologies and the valuation of long-term liabilities. His contributions span asset pricing models, corporate finance, and the evaluation of financial professionals’ skill and incentives. Prof. van Binsbergen’s interdisciplinary approach integrates econometric rigor with real-world financial phenomena, emphasizing both theoretical innovation and policy-relevant insights.

• Computer Science
• Electronics
• Mechanical Engineering
• +7 more

Guillermo Carpintero del Barrio is a Full Professor at Carlos III University of Madrid (UC3M), leading the Optoelectronics and Laser Technology Group (GOTL). His research spans Photonics Terahertz communications Integrated microwave photonics Optical frequency combs with applications in satellite systems, biomedical imaging, and 6G telecommunications. Recent publications focus on InP/Si3N4 hybrid lasers, dielectric slot waveguides, and photonic-enabled wireless transmission systems. His work demonstrates strong interdisciplinary expertise across electronics, optics, and telecommunications. Key contributions include: Hybrid photonic integration techniques Terahertz waveguide probe design Coherent photonic THz transmitters Optical frequency comb generators He has received multiple patents for photonic interconnects and optical devices. Current projects include TERA6G (terahertz systems for 6G networks) and MLPLUS-CM (microsatellite platform development).

• Electrochemical Energy Storage
• Lithium-ion Batteries
• Battery Materials
• +5 more

Ann Mari Svensson is a Professor at the Department of Materials Science and Engineering at NTNU. She leads research on electrochemical energy storage technologies, focusing on lithium-ion batteries and emerging battery systems. Her work emphasizes silicon anodes, cathode stability, and electrolyte development. She manages battery materials research in the national research center Mozees (www.mozees.no). She holds an MSc in Physics (Semiconductor Physics) and PhD in Electrochemistry. Her research integrates laboratory facilities at NTNU's Department of Materials Science and NTNU Nanolab. Key collaborations involve industry and national projects. Recent work includes silicon/graphite composite anodes, high-voltage cathode stability, and sustainable diatom-SiO2 anodes. Public outreach includes articles in NRK on battery advancements. Her publications span 2015–2025, addressing electrolyte optimization, nanostructured materials, and interfacial engineering. She has advised numerous PhD and Master’s students through collaborative projects, though no named advisees are listed in the text. No scientific awards are explicitly mentioned, but her contributions to battery science are highlighted in her research output.

Jennifer Sinclair CurtisView profile

Professor

• Particle Technology
• Granular Flow Dynamics
• Fluidization
• +4 more

Jennifer Sinclair Curtis is the Dean of the UC Davis College of Engineering since 2015. Previously, she served as the Associate Dean for Research and Facilities at the University of Florida’s College of Engineering, Chair of Chemical Engineering, and Head of Freshman Engineering at Purdue University. She holds a B.S. in Chemical Engineering from Purdue University and M.S./Ph.D. from Princeton University. Her research focuses on particle flow behavior, with applications in food processing, pharmaceuticals, aerospace, energy, mining, and natural processes like debris flows. She employs computational methods (DEM, CFD) to study granular flows, fluid-particle interactions, and material dynamics. Her work bridges engineering education and industry, emphasizing diversity and inclusion initiatives. Key awards include Fellowships from AAAS, AIChE, and ASEE. Her articles span particle dynamics, fluidization, and educational strategies, reflecting her dual expertise in technical and pedagogical innovation. She has advised numerous students and contributed to national advisory boards, including co-chairing the National Academies Chemical Science Roundtable.

Davide La VecchiaView profile

Professor

• Time series analysis
• Robust and semiparametric inference
• Financial econometrics
• +3 more

Davide La Vecchia is a Full Professor at the Research Institute for Statistics and Information Science (RISIS) at the University of Geneva, Switzerland. He holds dual PhDs in Statistics from Bocconi University (2007) and Economics from Università della Svizzera italiana (2011). His academic journey includes roles as an Assistant Professor at the University of St. Gallen and Monash University, and he has held visiting positions at Princeton University, the University of Copenhagen, and CREST (Paris). His expertise spans time series analysis, robust and semiparametric inference, financial econometrics, and spatial statistics. Key research contributions include work on saddlepoint approximations, optimal transportation methods, and latent variable models. Davide has led multiple grants, including from the Swiss National Science Foundation and the Australian Research Council. He serves as a referee for top-tier journals in statistics and econometrics. Teaching focuses on advanced statistical methods, including probability theory, time series analysis, and multivariate inference. His recent work emphasizes high-dimensional data modeling, spatio-temporal factor models, and applications to commodities trading networks. He has been honored with editorial roles and speaker invitations at global conferences, reflecting his leadership in statistical methodology.