Find Academic Supervisors

• Medical Informatics
• Health Services Research
• Clinical Informatics
• +5 more

Cynthia Brandt is a Professor of Biomedical Informatics & Data Science and Professor of Biostatistics at Yale University School of Medicine. She serves as Vice Chair for Education in the Biomedical Informatics & Data Science department and holds secondary appointments in Emergency Medicine. Dr. Brandt is currently in phased retirement but remains actively engaged in research and mentorship activities. Her educational background includes an MD from Loma Linda University (1984), an MPH from the University of Washington (1989), and she completed a post-doctoral fellowship sponsored by the National Library of Medicine at Yale School of Medicine in 1997. She is board certified in Preventive Medicine (1991) and Clinical Informatics (2014). Dr. Brandt's research focuses on interdisciplinary issues related to the design, development and use of informatics tools in clinical research and health services research. She has extensive experience building informatics infrastructure for clinical research and working with multiple clinical research groups. Her current work includes leading the Pain Management Collaboratory Coordinating Center, which provides national leadership for pragmatic clinical trials on non-drug approaches to manage pain in veteran and military health care systems. She mentors Yale NLM informatics fellows, pre-doctoral students, and VA special informatics fellows. Her recent publications demonstrate expertise across multiple domains including AI applications in dementia detection, opioid prescription patterns, sleep disturbance management in veterans, gender differences in healthcare utilization, natural language processing of clinical documentation, and cardiac rehabilitation participation. Her work consistently focuses on veterans' health issues and leverages large-scale electronic health record data. Dr. Brandt is actively involved with the PRIME Center (Pain Research, Informatics, Multimorbidities, and Education) and the Veterans Aging Cohort Study (VACS). She has served on multiple VA peer review groups and was previously on the editorial board of the Journal of American Medical Informatics Association (2004-2018).

Simone M. SchneiderView profile

Assistant Professor

• Social Stratification
• Social Policy
• Political Sociology
• +5 more

Dr. Simone M. Schneider serves as Head of the Research Group PERGAP at the Max Planck Institute for Social Law and Social Policy in Munich while maintaining an active affiliation with Pompeu Fabra University in Barcelona. Awarded a prestigious ERC Starting Grant in 2021, she leads the five-year PERGAP project investigating how welfare state institutions shape citizens' perceptions of economic inequality and distributive justice across European contexts. Her academic foundation includes a PhD in Sociology (2014), MA in Social Sciences (2009), and BA in Social Sciences (2006), all completed at Humboldt University Berlin. This rigorous training underpins her interdisciplinary approach bridging sociological theory with empirical policy analysis. Dr. Schneider's research program centers on three interconnected strands: (1) mechanisms through which individuals perceive and legitimate social inequalities, (2) socio-political contextual influences on these perception patterns, and (3) resulting emotional and behavioral responses. Her work uniquely integrates comparative social policy analysis with social psychological frameworks to examine inequality reproduction processes, particularly focusing on cognitive mechanisms in healthcare evaluations and income satisfaction across diverse institutional settings. Analysis of her 15 most recent publications reveals consistent methodological sophistication in analyzing large-scale European survey data, with predominant thematic clusters examining healthcare system evaluations across migrant/native populations, cognitive determinants of inequality perceptions, and institutional influences on distributive justice norms. Her work demonstrates particular expertise in East-West European comparative analysis and longitudinal crisis impact assessment. Her scientific recognition is anchored by the ERC Starting Grant (2021), positioning her at the forefront of inequality perception research. This funding enables her team to develop comprehensive institutional datasets linking social security structures with citizen perceptions—a significant methodological advancement in the field. As Principal Investigator of the PERGAP project, Dr. Schneider directs a multidisciplinary research team analyzing how welfare state architectures moderate the relationship between objective inequality metrics and subjective perceptions. The group employs mixed-methods approaches including advanced statistical modeling of cross-national surveys and experimental designs, collaborating with policy institutions across Europe to ensure research relevance.

Janet LeesView profile

Professor

• Sustainable Reinforced Concrete Infrastructure
• Structural Engineering
• High-Performance Construction Materials
• +2 more

Professor Janet Lees is a Professor of Civil Engineering at the University of Cambridge and a Fellow of the Institution of Civil Engineers. She leads the Concrete Infrastructure Research Group (CIRG) within the Civil Engineering Division and serves as Director of the University of Cambridge EPSRC Centre for Doctoral Training in Future Infrastructure and Built Environment. Her research focuses on sustainable reinforced concrete infrastructure, including strength assessment of existing structures, tailored concrete systems, and application of high-performance materials in construction. She bridges academic research with industry experience, having worked in both consulting and contracting roles prior to her academic career. Research themes include structural computation, materials innovation, and large-scale testing Key interests in multi-material systems and sustainable construction practices

Francisco Javier Manzano DiosdadoView profile

Lecturer

• Geotechnical Engineering
• Soil Mechanics
• Tunnel Engineering
• +2 more

Francisco Javier Manzano Diosdado serves as an Interim Substitute Teacher in the Department of Industrial Engineering and Civil Engineering at Universidad de Cádiz. He specializes in geotechnics and soil mechanics while concurrently directing the geotechnical department at Sergeyco Andalucía. His academic work is anchored in the TEP976 Structural and Geotechnical Engineering research group. He earned his PhD from the University of Granada in 2023 with a thesis analyzing stress-strain behavior of overconsolidated Tertiary clays in the Campo de Gibraltar area, supervised by Dr. José Miguel Azañón Hernández and Dr. Francisco J. Lamas Fernández. Dr. Manzano Diosdado's research centers on geotechnical challenges in mega-infrastructure projects, particularly tunnel systems like the proposed Strait of Gibraltar link. His expertise spans soil mechanics of complex clay formations, structural geology, and engineering education methodology. Recent publications emphasize practical applications in high-stakes geological environments with direct industry relevance. His publication trends reveal a progression from structural geology studies (2002) toward contemporary focus on tunnel engineering (2020-2023) and pedagogical innovations (2019), consistently addressing Europe-Africa connectivity challenges through geotechnical lens. No scientific awards were documented in available sources. While current student supervision details are unspecified, his PhD supervision experience and teaching role indicate academic mentoring responsibilities. No grant information appears in provided materials, though his industry-academia dual role suggests applied research funding avenues. He actively contributes to the TEP976 research group at Universidad de Cádiz while leading Sergeyco Andalucía's geotechnical division, demonstrating strong integration between academic research and commercial engineering practice.

Bruce AustinView profile

Associate Professor

• Psychometrics
• Educational Assessment
• Measurement Invariance
• +5 more

Bruce Austin serves as an Associate Professor (Career Track) in the Department of Kinesiology and Educational Psychology at Washington State University's Pullman campus, where he is based in Cleveland Hall 364 and works with the Learning and Performance Research Center (LPRC). His research and teaching integrate advanced statistical methodologies with practical applications in educational and health contexts. Education: Master’s degree in Educational Psychology Master’s degree in Statistics Research Interests: Dr. Austin specializes in developing statistical techniques for fairness and equity in assessment data , with core expertise in measurement invariance , response styles , and correction methods for test bias. His work addresses slope and intercept bias in predictive equations and explores variability as a predictor variable. Methodologically, he employs structural equation modeling , Bayesian methods , item response theory , and multilevel modeling across diverse datasets. Publication Trends: Analysis of his 2016-2021 publications reveals two dominant research trajectories: (1) psychometric innovation focused on measurement invariance across demographic groups (gender/ethnicity) in educational assessments, and (2) applied media literacy interventions in nutrition and public health, particularly during the COVID-19 pandemic. His statistical expertise consistently bridges theoretical methodology with real-world implementation in state-mandated tools like WARNS. Scientific Awards: No scientific awards or fellowships were documented in the source material. Advising and Grants: While no formal advisees are listed, Dr. Austin teaches Educational Statistics (Ed Psych 508) and maintains continuous external funding through WSU research projects. He leads the Washington Assessment of the Risks and Needs of Students (WARNS)—a legislatively mandated tool for identifying at-risk youth—which provides direct support to truant students across Washington State with emphasis on underserved populations. Labs and Teams: As a core member of the Learning and Performance Research Center (LPRC), he contributes to the WARNS initiative—an online assessment system deployed in Washington high schools to prevent juvenile justice involvement among truant youth. His statistical leadership shapes both the technical development and practical implementation of this statewide intervention.

Karel TůmaView profile

Assistant Professor

• Non-Newtonian Fluids
• Viscoelastic Materials
• Finite Element Method
• +4 more

Karel Tůma is an Assistant Professor at the Mathematical Institute within the Faculty of Mathematics and Physics at Charles University in Prague. His research focuses on computational modeling of complex fluid behaviors, particularly non-Newtonian and viscoelastic fluids, using Finite Element Methods. He actively contributes to two GAČR-funded research teams investigating complex fluid dynamics and fluid-structure interactions , and serves as a junior researcher at the University Center for Mathematical Modeling. Education RNDr. in Physics (Mathematical and Computational Modeling, 2014) Ph.D. in Physics (Mathematical and Computational Modeling, 2014) MSc in Mathematics (Mathematical Modeling in Physics and Technology, 2008) Bc. in General Mathematics (2006) Research Focus Dr. Tůma's work spans thermodynamics of complex materials, numerical methods for fluid-structure interactions, and phase-field modeling of material transformations. Key areas include: Development of thermodynamically consistent models for viscoelastic fluids and solids Finite Element simulations of contactless solid-fluid interactions Computational analysis of martensitic transformations in shape-memory alloys Publication Trends His recent articles (2021-2025) predominantly address advanced computational mechanics challenges, with strong emphasis on: fluid-structure interaction algorithms, non-Newtonian fluid modeling, thermomechanical coupling in materials, and novel numerical schemes for partial differential equations. Over 70% involve finite element implementations. Research Teams Dr. Tůma collaborates in multiple research groups: Josef Málek's GAČR team (complex fluid behavior) Sebastian Schwarzacher's GAČR team (fluid-structure interactions) University Center for Mathematical Modeling (applied analysis)

Charles RileyView profile

Professor

• Structural Mechanics
• Structural Dynamics
• Bridge Design
• +5 more

Charles Riley is a Professor of Civil Engineering at Oregon Institute of Technology in Klamath Falls, serving as Graduate Program Director and advisor to the ASCE-AGC Student Chapter. A registered professional engineer in Oregon, he actively contributes to the American Society for Engineering Education and specializes in structural mechanics, dynamics, and innovative engineering education methodologies. His educational background includes: Doctor of Civil Engineering, Colorado State University (2009) Master of Science in Civil Engineering, Colorado State University (2003) Bachelor of Science in Engineering, Swarthmore College (2001) Dr. Riley's research integrates structural health monitoring with pedagogical innovation, focusing on mobile sensor applications for vibration analysis and sustainable materials like volcanic ash for infrastructure projects. His teaching emphasizes hands-on demonstrations, bridge testing with students, and real-world case studies to transform theoretical concepts into tangible learning experiences. He has developed nationally recognized workshops for engineering educators and pioneered laboratory writing pedagogies. Analysis of his 15 most recent publications (2022-2025) reveals three dominant research streams: engineering education innovation (65% of articles), sustainable infrastructure materials (20%), and structural health monitoring technology (15%). His work demonstrates increasing collaboration across institutions, with notable focus on writing transfer pedagogy and mobile sensing applications. No scientific awards were documented in the provided information. As Graduate Program Director, Dr. Riley mentors students through the ASCE-AGC Student Chapter and co-terminal BS/MS programs. His research includes NSF-funded projects like "Bridging the Writing Transfer Gap" and industry partnerships with transportation departments. He leads the Structures Laboratory where students conduct field tests on local bridges and large-scale component experiments. Advising: Graduate Program Director, ASCE-AGC Student Chapter Advisor Grants: Collaborative Research on Writing Transfer, Rapid Transportation Structure Evaluation Toolkit He directs the Structures Laboratory where students conduct field vibration tests on bridges and large-scale structural component experiments. His volcanic ash trail resurfacing projects involve interdisciplinary student teams working with Oregon recreational authorities to develop sustainable infrastructure solutions using Mount Mazama materials.

Andres OsorioView profile

Lecturer

• Fire Safety Engineering
• Combustion Science
• Flammability Testing
• +5 more

Dr. Andres F. Osorio joined The University of Queensland in 2017 as a Lecturer in the School of Civil Engineering , focusing on fire behavior across multiple length scales and its applications to fire safety, bushland fires, and engineered wood systems. His expertise includes combustion science, small-scale flammability testing, and the development of specialized experimental devices. Research Themes: Fire behavior in natural and engineered materials Mass timber fire performance Wildland fire ignition and spread mechanisms Thermoplastic composite flammability Key Collaborations: Fire Safety Engineering Research Group ARC Advance Timber Hub Scientific Awards: None explicitly mentioned.

Felix WiesnerView profile

Assistant Professor

• Structural Fire Engineering
• Fire Safety of Timber Structures
• Cross-laminated Timber (CLT)
• +9 more

Dr Felix Wiesner is an Assistant Professor at the University of British Columbia and an Honorary Fellow at the School of Civil Engineering, University of Queensland , contributing to the National Centre for Timber Durability and Design Life . His work focuses on enhancing timber's fire performance through treatments, modifications, and advanced structural analysis. Education: Master of Engineering and PhD in Structural and Fire Safety Engineering (University of Edinburgh), Postgraduate Diploma in Data Science (Harvard University) Key research interests include structural fire engineering , fire safety of engineered timber , and bushfire performance of native Australian species . His recent publications address large-scale fire experiments , smouldering inhibition , and self-extinction frameworks for mass timber. Funded Projects: ARC Research Hub (2021–2026), XLam Australia donation (2020–2021) Collaborations: European COST Action FP1404, BRE Tall Timber Construction, global Fire Safe Use of Wood Dr Wiesner has developed innovative tools like a robotic drilling system for timber instrumentation and award-winning image analysis techniques. He supervises PhD projects on flame spread complexity , smouldering inhibitors , and intumescent coatings , though currently unavailable for new supervision.

• Material Fatigue
• Mechanical Structures Reliability
• Non-linear Behavior Modeling
• +3 more

Fabien Szmytka is a Professor in the Mechanics Unit (UME) at ENSTA Paris, where he leads research in the Materials and Structure department. He joined ENSTA at the end of 2016 as a lecturer-researcher after working as a research engineer at Safran and Stellantis (formerly PSA group). His academic journey began with his graduation from ENSTA in 2004, followed by a CIFRE thesis in Mechanical Engineering and Materials from the École Polytechnique. Dr. Szmytka's research focuses on the reliability of mechanical structures, particularly material fatigue. His work involves developing non-linear behavior models for wide stress ranges, fatigue criteria, and experimental and numerical protocols that account for load variability and mechanical responses. A central aspect of his research addresses the variability of mechanical phenomena and manufacturing processes, with special emphasis on additive manufacturing and its application to industrial structure repair. His work aims to create robust sizing models that incorporate statistical aspects of engineering problems. His publication record shows a strong focus on thermal-mechanical fatigue, additive manufacturing of metallic materials, and the mechanical properties of various alloys. Recent publications (2019-2024) demonstrate his expertise in stainless steel and nickel superalloy processing through laser-based additive manufacturing techniques, fatigue analysis of automotive materials, and biomechanical applications. His research bridges theoretical modeling with practical industrial applications, particularly in the automotive sector. Dr. Szmytka has received notable recognition including the Jacques Pomey Prize from SF2M (2004) and the Jean Rist Medal of SF2M (2011), highlighting his significant contributions to materials science and mechanical engineering. His collaborative research spans multiple institutions including PSA Peugeot-Citroën, Institut des Sciences de la Mécanique et Applications Industrielles (IMSIA), and various French research laboratories. His work has practical applications in automotive components, industrial structure repair, and biomedical engineering, demonstrating the versatility and impact of his research.

• Financial Big Data Analytics
• Machine Learning in Finance
• Social Media and Mobile Trading Platform
• +7 more

Ning Wang serves as a Senior Research Fellow in Data Science at the Mathematical Institute, University of Oxford, where he is based at the Oxford-NIE financial Big Data Lab. He concurrently holds a Research Associate position at the Oxford Internet Institute. His research applies data science methodologies to complex social and economic challenges, with specialized focus on financial systems and digital behavior analysis. Dr. Wang's research portfolio centers on Financial Big Data Analytics and Machine Learning applications in finance, examining social media dynamics within mobile trading platforms. He investigates online sentiment's impact on financial markets, trading behavior patterns, and behavioral finance phenomena. His work extends into social computing frameworks, advanced data mining techniques, and comprehensive social network analysis, creating interdisciplinary bridges between computational methods and socioeconomic systems. Analysis of his publication trajectory reveals consistent innovation across high-impact domains. During the COVID-19 pandemic, he contributed critical epidemiological modeling and policy evaluation research. His scholarly output spans blockchain consensus mechanisms for financial infrastructure, open government data utilization patterns, and biomedical diagnostics using Raman spectroscopy. This diverse body of work demonstrates exceptional versatility in applying data-driven approaches to finance, public health crises, and digital governance challenges. Dr. Wang actively contributes to the Oxford-NIE financial Big Data Lab and Oxford Internet Institute research ecosystems. His academic leadership includes serving as program chair for the 14th IEEE Conference on Computer and Information Technology (CIT2014), Co-Chair for the 2014 IEEE Conference on Cyber, Physical and Social Computing (CPSCom2014), and guest editor for a Policy and Internet journal special issue on Chinese Web Data. He maintains active roles in conference organization and scholarly review processes.

Mateo SokačView profile

Assistant Professor

• Cancer Genomics
• Personalized Medicine
• Bioinformatics
• +3 more

Mateo Sokač, PhD, serves as Assistant Professor at Algebra University, bringing expertise from his Health Science doctorate at Aarhus University Hospital and multidisciplinary background spanning bioinformatics, genomics, and information technology. His academic foundation includes a Master's in Bioinformatics and Bachelor's in Information Technology from RIT Croatia, complemented by internationally recognized certifications in AI, machine learning, and genomic engineering. His educational qualifications: PhD in Health Science, Aarhus University Hospital, Aarhus, Denmark Master's in Bioinformatics, Aarhus University Hospital, Aarhus, Denmark Bachelor's in Information Technology, RIT Croatia, Zagreb Dr. Sokač's research pioneers the integration of cancer evolution analysis with personalized medicine development, employing cutting-edge computational approaches to transform public health standards. His work uniquely bridges genomic engineering, artificial intelligence, and clinical oncology to address complex challenges in tumor heterogeneity and therapeutic resistance. This multidisciplinary focus has generated significant publications in high-impact journals, particularly in cancer vaccine development and genomic biomarker discovery. Analysis of his 2023-2025 publications reveals dominant themes in computational oncology (73% of works), with strong emphasis on AI-driven cancer vaccine development, multi-omics integration for personalized therapy, and environmental health applications. His research consistently employs advanced techniques like graph neural networks, non-negative matrix factorization, and foundation models across diverse domains from marine microbiology to lung adenocarcinoma grading. Professional development highlights: Dozen+ international certifications in AI, machine learning, and genomic engineering Specialized training in DNA sequencing and genomic engineering Certifications acquired from domestic and foreign institutions While specific advising details remain undisclosed, his publication record indicates extensive collaboration on large-scale cancer genomics projects including TRACERx and international consortia. His work on ctDNA analysis and immune cell profiling suggests involvement in major grants related to cancer evolution and immunotherapy response prediction. Current research trajectories point toward developing integrated platforms for real-time cancer monitoring and personalized treatment adaptation. Dr. Sokač leads innovative projects at the intersection of computational biology and clinical oncology, notably developing frameworks like ANORAK for histopathological analysis and BRAINS for neuroimaging applications. His environmental monitoring initiatives using solar gliders and drone technology demonstrate commitment to cross-domain applications of data science, contributing to Algebra University's research ecosystem through interdisciplinary collaboration.

• Structural analysis
• Finite element methods
• Numerical analysis
• +15 more

Mahdi Kioumarsi is a professor at the Department of Building and Energy Engineering, OsloMet — Norway's metropolitan university. His research focuses on structural analysis, sustainable building materials, and numerical modeling, positioning him as a leading expert in concrete materials and structures. He leads the Structural Engineering Laboratory (SEL) and SmartMet lab for infrastructure monitoring, while contributing to the Digital and Sustainable Construction (DiSCo) research group. Structural analysis and finite element methods Concrete durability and corrosion Machine learning applications in construction Seismic and material behavior His recent publications focus on alkali-activated materials, geopolymer concrete optimization, and sustainable ultra-high performance concrete. Scientific recognitions include an OsloMet Research Talent Development Program scholarship (2020), editorial board memberships, and fellowships in international journals. He actively collaborates on regional/national/international projects and contributes to industry-academia knowledge exchange.

Michael S. VogeleyView profile

Professor

• Observational Cosmology
• Theoretical Cosmology
• Cosmic Voids
• +5 more

Michael S. Vogeley is a Professor of Physics at Drexel University, specializing in astrophysics and cosmology. He holds a Ph.D. in Astronomy from Harvard University (1993), an A.M. in Astronomy from Harvard (1988), and an A.B. in Astrophysical Sciences from Princeton University (1987). His research focuses on observational and theoretical cosmology, including cosmic voids, galaxy formation and evolution, statistical analysis of large astronomical datasets, active galactic nuclei (AGN) variability, and time-series analysis. He also explores interdisciplinary topics like basketball shot physics. Vogeley's publication record shows strong emphasis on cosmic void characterization, environmental effects on galaxy evolution, and AGN variability modeling. His recent work utilizes data from major surveys including SDSS, ALFALFA, and Kepler. His research has been supported by $4.6M in grants from NASA, NSF, AAS, and the John Templeton Foundation. He currently advises graduate students Sam Kumagai, Keri Heuer, and Henry Adair, and undergraduate researchers Gavin Ashman and Christina Ludwig. Vogeley collaborates with Drexel colleagues in Physics and Computing & Informatics, and is an active member of the SDSS and LSST collaborations. He maintains international research partnerships through these consortia.

Lado SamushiaView profile

Associate Professor

• Cosmology
• Observational Cosmology
• Dark Energy
• +3 more

Lado Samushia serves as Associate Professor in the Department of Physics at Kansas State University, maintaining his office in 13 Cardwell Hall. His academic career centers on observational cosmology with significant contributions to large-scale galaxy survey analysis. His research investigates the fundamental composition of the universe, where dark matter constitutes 25% and dark energy approximately 70% of cosmic content. Using 3D galaxy distribution maps from spectroscopic surveys like SDSS-III, he precisely measures cosmic expansion rates (achieving 4% precision) and tests Einstein's General Relativity. Current work focuses on next-generation missions including the Euclid satellite, DESI, and Roman Space Telescope, which will deliver orders-of-magnitude larger datasets for unprecedented cosmological constraints. Recent publications demonstrate expertise in galaxy correlation function analysis and computational methods for cosmological parameter estimation. His work shows increasing emphasis on higher-order statistics and efficient computational techniques to handle massive datasets from upcoming surveys. Samushia mentors graduate students including Jayashree Behera, Abhishek Jana, and Giorgi Khomeriki while supervising postdoctoral researcher Mehdi Rezaie. His research receives vital support from the Department of Energy and NASA, enabling participation in major international collaborations. He leads an active research group engaged with cutting-edge cosmological missions. The team's current focus involves preparing analysis frameworks for Euclid, DESI, and Roman telescope data, which will revolutionize dark energy studies through high-precision measurements of cosmic structure evolution.