جست‌وجوی استاد و پژوهشگر

Quentin Andreمشاهده پروفایل

استادیار

• Judgment and Decision Making
• Numerical Cognition
• Probabilistic Reasoning
• +۴ مورد دیگر

Quentin Andre is an Assistant Professor of Marketing at the Leeds School of Business, University of Colorado Boulder . His research bridges judgment and decision-making , consumer financial decision-making , and open science initiatives. Education: PhD in Marketing (INSEAD, 2018), MSc in Managerial and Financial Economics (HEC Paris, 2012), BA in History of Arts (Sorbonne University, 2009) Andre’s work focuses on how consumers interpret numerical information and make data-driven decisions under uncertainty. He advocates for replicability and reproducibility in behavioral research, emphasizing methodological transparency . His recent publications explore group sequential designs , probabilistic reasoning , and statistical power in hypothesis testing. He has developed open-source tools like pypcurve (Python p-curve analysis), distBuilder (distribution builder for experiments), and WordSearchJS (word search tasks in research). His blog discusses topics such as p-value interpretation , research errors , and open science practices .

• Protein-based molecular switches
• Molecular simulation
• Non-adiabatic quantum dynamics
• +۷ مورد دیگر

Dr. Donal Mac Kernan is a Research Scientist at the School of Physics, University College Dublin, with extensive expertise in computational biophysics and molecular modeling. His work focuses on developing protein-based molecular switches through physics-based rational design and genetic engineering. He serves as the director of the Irish CECAM node and is a Fellow of the Conway Institute for Biomedical and Biomolecular Research. BSc from University College Hospital Galway MSc from University of Maryland PhD in Chaos Theory from Université Libre de Bruxelles (awarded with "Le plus grand distinction") Dr. Mac Kernan's research spans multiple interdisciplinary fields including molecular simulation, non-adiabatic quantum dynamics, chaos theory, and artificial intelligence. His primary focus is on protein-based molecular switches that modulate protein function in response to biomarkers, with applications in optical activity, scattering, and cytotoxicity for chemotherapeutics. He has developed innovative approaches to computational (bio)materials modeling and has made significant contributions to understanding protein structure-function relationships in food science. His recent publication trends show a strong focus on computational biophysics, particularly in protein engineering and molecular simulation techniques. His work integrates experimental data with computational models to address challenges in biomaterial research, including multi-scale modeling, data validation, and reproducibility. He has pioneered approaches to FRET sensor design, protein flexibility analysis, and proton titration schemes for biomolecular simulations. Two patent filings related to protein-based molecular switches Fellow of the Conway Institute for Biomedical and Biomolecular Research Principal Investigator for multiple research awards totaling over 2M€ Dr. Mac Kernan has substantial teaching and mentoring experience, having supervised 14 undergraduate thesis students in theoretical physics. He teaches advanced courses including C programming for physics and chemistry students and quantum mechanics at the undergraduate level. His research group has secured significant funding for projects at the intersection of physics, biology, and computational science. As director of the Irish CECAM node, Dr. Mac Kernan leads computational science initiatives that connect researchers across Ireland with the European network for computational science. His work with the Nanoscale Simulators of Ireland and SimBioMa (European Science Foundation) demonstrates his commitment to collaborative research in computational biophysics and materials science.

Scott Renneckarمشاهده پروفایل

استاد

• Advanced Renewable Materials
• Forest Bioproduction
• Bioeconomy
• +۷ مورد دیگر

Scott Renneckar is a Professor and Canada Research Chair in Advanced Renewable Materials at the University of British Columbia , specifically within the Faculty of Forestry and Department of Wood Science . He serves as Program Director for Forest Bioeconomy Sciences and Technology and leads the Advanced Renewable Materials Lab. Research Focus: Molecular structure and reactions of wood for advanced renewable materials Expertise: Application of polymer science to biopolymers and biobased composites Key Contributions: Development of petroleum-free composites from Canadian forests Research Areas include: Lignin - Fibre spinning, thermoplastics, foams, aerogels Heteropolysaccharides - Sustainable packaging, nanotechnology Nanocellulose - New material technologies Biomass Deconstruction - Catalytic fractionation, organosolv pulping Scientific Awards : Canada Research Chair in Advanced Renewable Materials The lab produces numerous publications focusing on lignin valorization (33% of recent articles), cellulose nanotechnology (27%), biomass processing (13%), and bioeconomy innovations (27%). Key subfields include lignin-based composites, polymer modification, sustainable manufacturing, and biobased material characterization. His work aligns with UBC's BioProducts Institute and Pulp and Paper Centre, emphasizing both fundamental polymer science and practical applications for the forest bioeconomy.

Tamara Vanderwalمشاهده پروفایل

استادیار

• Functional Neuroimaging
• Child Psychiatry
• Depression in Youth
• +۵ مورد دیگر

Tamara Vanderwal is an Assistant Professor in the Department of Psychiatry at the University of British Columbia's Faculty of Medicine. She serves as an Investigator at BC Children's Hospital and works as a Child Psychiatrist in the TOPs Program. Her academic affiliations include the Academy of Translational Medicine, BC Children's Hospital Research Institute, Centre for Brain Health, and MATRIX-N: Multidisciplinary Alliance for Translational Research and Innovation in Neuropsychiatry. Dr. Vanderwal specializes in functional neuroimaging research focused on child psychiatric disorders, particularly depression in youth. Her work centers on using naturalistic viewing paradigms, especially movies, to study complex brain function in children who have difficulty remaining still during traditional MRI procedures. This innovative approach allows for studying the brain as it processes dynamic, real-world information streams. Her research spans functional connectivity, fMRI methodology development, and understanding brain-behavior relationships in pediatric populations. Her recent publications reveal a strong focus on improving the reproducibility and inclusivity of neuroimaging research with youth populations. She has pioneered methods to handle head motion artifacts in pediatric fMRI, increase representation of minoritized youth in studies, and develop naturalistic paradigms that better capture real-world cognitive processing. Her work bridges clinical psychiatry with advanced neuroimaging techniques to better understand and treat child psychiatric disorders. American Academy of Child and Adolescent Psychiatry Junior Investigator Award Resident Teaching Award, Department of Psychiatry, Yale School of Medicine Yale Psychiatry Research Scholar, Yale School of Medicine Contributing Editor (2014-2017), The Journal of the American Academy of Child and Adolescent Psychiatry Dr. Vanderwal actively supervises numerous students and research personnel across various levels, from undergraduate volunteers to graduate trainees. Her research has been supported by prestigious grants including the American Psychiatric Association/Lilly Psychiatric Research Fellowship, Klingenstein Family Foundation, American Academy of Child and Adolescent Psychiatry, and Allison Family Foundation awards. She leads the Naturalistic Neuroimaging Lab which focuses on developing and implementing movie-based paradigms to study brain function in children with psychiatric conditions.

Mark Biesingerمشاهده پروفایل

عضو هیئت علمی

• X-ray photoelectron spectroscopy
• Surface analysis
• Materials characterization
• +۳ مورد دیگر

Dr. Mark Biesinger serves as the Director of Surface Science Western (Western University), Canada's leading surface analysis and materials characterization facility, and holds the position of Adjunct Research Professor in the Department of Chemistry. With over 30 years of experience operating and maintaining XPS, SEM/EDX, optical microscopes, and SIMS instruments, he is internationally recognized as an expert in X-ray photoelectron spectroscopy (XPS). Dr. Biesinger has authored or co-authored over 90 peer-reviewed publications, including numerous seminal works that have significantly advanced XPS methodology and data interpretation techniques, particularly for transition metals. His recent research (2023-2025) focuses on resolving persistent challenges in XPS analysis such as peak fitting errors, oxygen spectra interpretation, and chemical state analysis of low-Z elements. He maintains the widely-used X-ray Photoelectron Spectroscopy (XPS) Reference Pages, a comprehensive resource for researchers worldwide. His work bridges fundamental surface science with practical applications in corrosion, mineral processing, and biomedical materials. Dr. Biesinger has received prestigious recognition including the 2025 UKSAF Vickerman Prize, the 2025 Chemistry Research Excellence Award from Western University, and the 2022 American Vacuum Society Peter M.A. Sherwood Mid-Career Professional Award. He has been listed among Stanford's Top 2% Scientists since 2018. As Secretary-Treasurer for the Surface Science Division of the Chemical Institute of Canada, Dr. Biesinger actively contributes to the scientific community. He currently collaborates with Natural Resources Canada (CanmetMINING) on research projects related to temperature effects on collector performance for lithium ore flotation, demonstrating his commitment to applied research with industrial relevance.

• Radiology
• Body MRI
• Kidney Cancer Imaging
• +۱۲ مورد دیگر

Ivan Pedrosa, M.D., Ph.D., is Professor of Radiology at UT Southwestern Medical Center, where he holds the Jack Reynolds, M.D., Chair in Radiology and serves as Co-Leader of the Kidney Cancer Program at the Simmons Comprehensive Cancer Center. He is a body imager and clinical researcher with a strong focus on translational imaging, particularly in kidney and prostate cancer, liver and pancreatic disease, and gastrointestinal disorders. His research centers on developing and implementing novel multiparametric MRI techniques to improve disease characterization and patient outcomes. Key areas include the Clear Cell Likelihood Score (ccLS) for renal mass diagnosis, radiogenomics, AI-driven segmentation, and quantitative imaging biomarkers. He leads the Translational Research Imaging (TRI) Lab, fostering collaboration between imaging scientists, radiologists, and basic researchers. His recent publications reflect a strong trend in integrating AI, radiomics, and molecular imaging into clinical radiology, with a focus on pancreatic and kidney cancers. His work emphasizes clinical translation, reproducibility, and protocol optimization across multicenter settings. Teacher of the Year Award, Beth Israel Medical Center (2005) Golden Apple Award, UT Southwestern (2014) Scientific advisor for RSNA research scholar grant Mentored trainees who received RSNA Trainee Research Prize, Lauterbur Award, and Resoundant Innovation Award Dr. Pedrosa has been a senior mentor to numerous trainees and serves on multiple national and international society committees, including ISMRM, RSNA, SCBT/MR, and NCI’s Renal Cancer Task Force. He has authored over 130 peer-reviewed articles and is a frequent speaker at national and international conferences. The TRI Lab, under his leadership, actively pursues innovations in AI, imaging-OMICS integration, and technical development for clinical impact.

Zoltán Molnárمشاهده پروفایل

استاد

• cerebral cortical development and evolution
• thalamocortical projections
• subplate neurons
• +۲ مورد دیگر

Zoltán Molnár is Professor of Developmental Neuroscience at the University of Oxford, holding positions at the Department of Physiology, Anatomy and Genetics and St John's College. His pioneering research focuses on cerebral cortical development, thalamocortical projections, and subplate neuron function, significantly advancing our understanding of neuronal migration, circuit formation, and developmental plasticity. His educational background includes an M.D. from Albert Szent-Györgyi Medical University (1982-1988) and a D.Phil. from the University of Oxford (1989-1994) under Sir Colin Blakemore. Additional training occurred at the University of Lausanne and Kyoto Prefectural School of Medicine. MD: Albert Szent-Györgyi Medical University, Szeged, Hungary (1982-1988) DPhil: University of Oxford, UK (1989-1994) Molnár's research examines how cortical neurons are born, migrate, differentiate, and form circuits, with particular focus on thalamocortical development and subplate neuron functions. His innovative work includes 3D-printed cerebral cortical tissue for brain injury repair and investigations into neuroprotective agents like neuroserpin. Current projects explore cortical circuit plasticity, sleep regulation mechanisms, and metabolic impacts on neurodevelopment. Recent publications (2022-2025) reveal strong thematic continuity in cortical development research while expanding into neuroprotection applications, advanced imaging techniques, and translational models for brain repair. Key trends include molecular mechanisms of neuronal migration, thalamocortical connectivity evolution, and metabolic influences on neurodevelopmental disorders. His scientific recognition includes: Elected Member of Academia Europaea (Physiology and Neuroscience, 2019) Fellow of the Royal Society of Biology (2022) Einstein Visiting Fellow at Charité-Universitätsmedizin Berlin (2020-2026) Fellow of the Anatomical Society, New Fellow of the Year Award (2018) Medical Sciences Teaching Excellence Award (2010) Molnár has secured major research funding from MRC, Wellcome Trust, and BBSRC totaling over £15M, supporting 15+ projects including thalamocortical connectivity studies and Zika virus neurodevelopmental impact research. His laboratory has trained numerous postdoctoral fellows through HFSP and EU programs while mentoring graduate students via Rhodes, Wellcome Trust, and Felix Scholarships. He serves on editorial boards for Cerebral Cortex and Journal of Comparative Neurology, and has chaired the Oxford Neuroscience Committee since 2009. The Molnár Laboratory at Oxford employs correlative microscopy, 3D bioprinting, and electrophysiological techniques to investigate cortical development. The lab maintains active collaborations with Charité-Universitätsmedizin Berlin and participates in the Oxford Cortex Club, which Molnár has sponsored since its 2009 inception. Current projects focus on neuroprotective strategies for neonatal brain injury and thalamocortical circuit evolution.

• Bioinorganic Chemistry
• DNA Binding Studies
• Metal Complex Chemistry
• +۵ مورد دیگر

Giampaolo Barone is a Full Professor (CHEM-03/A) at the University of Palermo within the Biological, Chemical and Pharmaceutical Sciences and Technologies school. His office is located at Viale delle Scienze, Building 17, 90128 Palermo, where he holds office hours on Wednesdays from 3:00 PM to 5:00 PM. His teaching responsibilities include General Chemistry (3 CFU) for Prevention Techniques in the Environment and Workplace, General and Inorganic Chemistry (8 CFU) for Pharmaceutical Chemistry and Technology, Inorganic Chemistry (6 CFU) for Chemistry, Inorganic Chemistry with Laboratory (10 CFU) for Chemistry, and Chemistry for Elementary and Kindergarten Schools (4 CFU). Professor Barone's research focuses on bioinorganic chemistry, particularly the interaction of metal complexes with DNA structures. His work spans from fundamental studies of DNA binding mechanisms to applications in anticancer drug development. He employs both experimental techniques (spectroscopy, fluorescence titration) and computational methods to investigate how metal complexes interact with DNA, especially G-quadruplex structures that play crucial roles in gene regulation and cancer pathways. His research demonstrates consistent productivity with numerous publications each year across high-impact journals in chemistry, biochemistry, and pharmacology. Analysis of his recent publications (2024-2025) reveals several key research trends: 1) Development of metal-based compounds (particularly copper, nickel, and ruthenium complexes) as anticancer agents targeting DNA structures; 2) Investigation of G-quadruplex DNA stabilization and its implications for oncogene regulation; 3) Creation of novel sensors for environmental and biological applications; 4) Exploration of marine biomolecules for therapeutic uses; and 5) Methodological improvements in measuring DNA binding constants. Throughout his career, Professor Barone has supervised numerous graduate students across Chemistry, Pharmaceutical Chemistry, and Biological Sciences programs. His edited theses cover diverse topics including DNA-metal complex interactions, spectroscopic studies, synthesis of bioactive compounds, and applications in medical diagnostics. His research has significant implications for developing new anticancer therapies, environmental monitoring tools, and fundamental understanding of biomolecular interactions.

• Climate reconstruction (past 400 years)
• Climate dynamics and large-scale variability
• Historical climatology
• +۵ مورد دیگر

Professor Stefan Brönnimann is a leading climatologist at the University of Bern, Switzerland, where he serves as Unit Leader of the Climatology group within the Institute of Geography. He is also actively involved with the Oeschger Centre for Climate Change Research as both Leader of Work Package 2 and Member of the Steering Group. His academic affiliations include: University of Bern, Institute of Geography, Climatology Unit Oeschger Centre for Climate Change Research, University of Bern President of Commission 'Atmospheric Chemistry and Physics' (ACP) of sc.nat Active participant in international climate initiatives including 20CR, ACRE, and ISTI Professor Brönnimann's research focuses on reconstructing weather and climate patterns from the past 400 years through the integration of early instrumental data, climate proxies, and sophisticated climate models. His work emphasizes understanding climate dynamics and large-scale variability, particularly interannual-to-decadal patterns of atmospheric circulation. He has made significant contributions to historical climatology, studying the effects of volcanic eruptions on climate systems and examining the complex interactions between climate and human societies throughout history. His recent publications (2024-2026) demonstrate continued productivity and relevance in the field, covering topics such as precipitation reconstruction, pre-industrial climate variability, hydroclimate extremes in Europe, and climate data processing tools. These works reflect his ongoing commitment to advancing historical climate science and making climate data more accessible for contemporary research. Professor Brönnimann's significant scientific contributions have been recognized through prestigious roles including: Lead author for Chapter 2 of the IPCC 5th Assessment Report (Working Group I) President of Commission 'Atmospheric Chemistry and Physics' (ACP) Editorial roles for multiple journals including Meteorologische Zeitschrift, Climate of the Past, and Geographica Bernensia He has secured funding for numerous research projects through organizations including SNF, NCCR Climate, EU FP-7, HORIZON2020, COST, and ERAnet.RUS. Professor Brönnimann has organized international workshops on climate variability and extremes, demonstrating his leadership in the global climate research community. His research group at the University of Bern focuses on historical climate reconstruction, utilizing diverse data sources to understand long-term climate patterns and provide context for current climate change.

Antonio Cuevas Gonzálezمشاهده پروفایل

استاد

• Set estimation
• Statistics with functional data
• Classification
• +۱ مورد دیگر

Antonio Cuevas González is a Professor of Statistics and Probability at the Department of Mathematics, Faculty of Sciences, Autonomous University of Madrid. His office is located in Building 17, Room 503 at the university campus in Madrid (28049). He maintains an active research program in statistical methodology and has supervised numerous PhD students throughout his career. Professor Cuevas González specializes in several advanced areas of statistical theory, with primary research interests in set estimation, statistics with functional data, classification methods, and geometric approaches to statistical problems. His work bridges theoretical statistics with practical applications, particularly in high-dimensional and functional data settings. Over his career, he has developed novel methodologies for shape analysis, boundary estimation, and nonparametric classification that have become influential in the statistical community. An analysis of his recent publications reveals a strong focus on functional data analysis, with particular emphasis on regression models, classification techniques, and geometric approaches to statistical problems. His research increasingly integrates machine learning concepts with traditional statistical methodology, particularly through the use of reproducing kernel Hilbert spaces and other advanced mathematical frameworks. The trend shows growing interest in high-dimensional problems, dimensionality reduction techniques, and the development of computationally efficient statistical methods for complex data structures. SEIO-BBVA Foundation Award 2022 to the Best Methodological Contribution in the Statistics Field Medalla de oro 2025 de la Sociedad de Estadística e Investigación Operativa (SEIO) Professor Cuevas González has supervised numerous PhD students including Paloma Sanz (1988), Amparo Baíllo (2000), Alberto Rodríguez-Casal (2003), Alejandro Cholaquidis (2014), José L. Torrecilla (2015), Beatriz Bueno (2018), Luis A. Rodríguez (2024), and Antonio Coín (current). He is currently principal investigator for the research project 'Statistical techniques in high-dimensional spaces' (grant code PID2023-148081NB-I00) funded by the Spanish Ministry of Science, Innovation and Universities from September 2024 until September 2027, with Amparo Baíllo and Javier Cárcamo as main collaborators. As an active member of the statistical research community, Professor Cuevas González serves as Associate Editor for the journal ALEA and contributes to various research collaborations centered around functional data analysis, set estimation, and geometric statistics. His work often involves interdisciplinary collaborations, particularly with researchers in biomedical fields as evidenced by his publication on metabolic changes in mouse hearts.

Raphaël Monatمشاهده پروفایل

پژوهشگر

• Static program analysis
• Abstract interpretation
• Formal methods
• +۵ مورد دیگر

Raphaël Monat is a Research Scientist in the SyCoMoRES team at Inria Lille since September 2022, with an affiliation at the University of Lille. His work focuses on formal methods and static program analysis, with particular applications to computational law and realistic software systems. He is one of the core maintainers of the Mopsa static analysis framework and has developed tools for analyzing the French tax code. Monat holds a Ph.D. in computer science from Sorbonne Université, advised by Antoine Miné, where he worked on the static analysis of Python and Python+C programs within the ERC MOPSA project. Prior to his position at Inria, he completed research internships at MPI-SWS in Saarbrücken, University of Oxford, and École Normale Supérieure in Paris. His primary research interest lies in improving software quality through automated program verification, with a focus on making static analysis applicable to realistic systems. Monat has a particular interest in computational law, especially the implementation of tax and benefit systems. He is currently developing formal methods tools for Catala, a domain-specific language for legislative texts, in collaboration with Aymeric Fromherz. His work emphasizes the practical application of theoretical concepts in abstract interpretation to real-world problems. Monat's publication record demonstrates a consistent focus on advancing static analysis techniques, particularly for Python and C programs, and applying them to computational law. His recent work shows an increasing emphasis on compositional analysis, concolic execution for legal computations, and improving the maintainability of academic static analyzers. The integration of formal methods with legislative implementations represents a distinctive thread throughout his research career. SV-Comp 2025 Silver Medal in "Software Systems" category Amazon Research Award, Fall 2024 ETAPS 2024 best tool paper award SV-Comp 2024 Gold Medal SV-Comp 2023 Bronze Medal ECOOP 2023 Distinguished Artifact Reviewer Award SOAP 2020 Best Presentation Award Monat actively mentors students, currently supervising two PhD candidates (Milla Valnet and Pierre Goutagny) and having previously guided several Master's students. He has secured significant funding for his research, including an ANR Young Researcher Grant for the RAISIN project on Resource-Aware Conservative Static Analysis starting in Fall 2024, and the Inria-AEx AVoCAT project for Automated Verification of Catala programs. Monat is a core contributor to the Mopsa static analysis platform, which has achieved notable success in the Software Verification Competition (SV-Comp). He also co-developed Mlang, a modern compiler for the French tax code that is being transitioned to production use by the French tax administration. His work bridges theoretical formal methods with practical applications in public administration.

Christopher Wheatمشاهده پروفایل

استاد

• Ecological Genomics
• Evolutionary Genomics
• Population Genetics
• +۶ مورد دیگر

Christopher Wheat is a Professor in the Department of Zoology at Stockholm University, where he leads the Wheat Research Group. His laboratory focuses on ecological and evolutionary genomics to investigate adaptation in natural populations across microevolutionary to macroevolutionary scales. His research integrates multiple disciplines including molecular biology, population genetics, physiology, biochemistry, ecology, and systematics. Wheat primarily uses butterflies as model organisms due to their central role in ecological and evolutionary theory, with particular emphasis on the Squinting bush brown ( Bicyclus anynana ) and Colias species. His lab employs diverse methodologies ranging from traditional field techniques like butterfly netting to advanced genomic approaches including CRISPR-Cas9 gene editing. Wheat's recent publications demonstrate a strong focus on lepidopteran genomics, with particular attention to understanding the genetic basis of adaptive traits, life-history strategies, and host plant interactions. His work bridges fundamental evolutionary questions with practical genomic methodologies, contributing significantly to the field of evolutionary genetics. He actively supervises research interns, Master's students, PhD candidates, and postdoctoral researchers, with numerous opportunities available in his lab. Wheat collaborates extensively through initiatives like LepEU (European Lepidopteran Population Genomics Consortium) and Project Psyche, which provides chromosome-scale reference genomes for diverse butterfly species. His laboratory maintains strong connections with the 10kLepGenomes COST Action network, facilitating international collaboration and access to field samples from European populations of diverse butterfly species. Wheat regularly writes grants with candidates interested in joining his research group, with flexibility to pursue research interests beyond butterfly systems.

• Spatial statistics
• Computational statistics
• Statistical genetics
• +۵ مورد دیگر

Charles Geyer is a Professor at the School of Statistics, University of Minnesota . His work spans computational statistics, spatial statistics, and statistical genetics, with applications to endangered species conservation and stochastic process modeling. Research Interests: Spatial statistics, Markov chain Monte Carlo methods, likelihood inference in exponential families, constrained optimization, and statistical software development. Software Contributions: Developed R packages mcmc , aster , rcdd , and trust for Monte Carlo methods, life history analysis, computational geometry, and optimization. Teaching: Instructs graduate and undergraduate courses including Stat 5101, Stat 5102, Stat 5421, Stat 5601, and advanced seminars on computational statistics. Publications: Notable works include research on maximum likelihood estimation in exponential families, fuzzy P-values, geometric ergodicity in MCMC, and computational methods for conservation genetics.

Adrien Taylorمشاهده پروفایل

پژوهشگر

• Optimization
• Numerical Analysis
• Control Theory
• +۲ مورد دیگر

Adrien Taylor is a Researcher at Inria within the SIERRA research team, having previously held a postdoctoral position at Inria (2017-2019) and completed his PhD at Université catholique de Louvain in Mathematical Engineering under François Glineur and Julien Hendrickx. His educational background: PhD in Mathematical Engineering from Université catholique de Louvain (ICTEAM institute), supervised by François Glineur and Julien Hendrickx with F.R.S.-FNRS FRIA scholarship support. Taylor's research focuses on optimization (especially first-order methods), numerical analysis, control theory, and machine learning, driven by a commitment to reproducible and theoretically rigorous science. His work emphasizes computer-assisted worst-case analyses and accelerated optimization techniques, aiming to bridge theoretical guarantees with practical applicability in machine learning and scientific computing. His most significant recognition is the ERC Starting Grant 2024 awarded for the CASPER project, which will fund his research from fall 2024 to fall 2029. Taylor actively supervises PhD students across multiple institutions: current advisees include Roland Andrews (ENS Paris), Daniel Berg Thomsen (ENS Paris), Si Yi Meng (Cornell), and Weijia Wang (Sorbonne Université); former PhD students include Antoine Bambade (ENS Paris), Baptiste Goujaud (Ecole Polytechnique), and Céline Moucer (ENS Paris). He has also collaborated with PhD visitors from MIT, UCLouvain, and Lund University. As a core member of the SIERRA team at Inria Paris, he collaborates closely with Francis Bach, Justin Carpentier, Aymeric Dieuleveut, and other researchers on optimization theory and applications.

Philipp Baumeisterمشاهده پروفایل

پژوهشگر

• Exoplanet Interior Structure
• Planetary Geodynamics
• Habitability Modeling
• +۳ مورد دیگر

Dr. Philipp Baumeister is a Postdoctoral Researcher in Planetary Geodynamics at the Institute of Geological Sciences, Department of Earth Sciences, Freie Universität Berlin. He works on the DIVerse Exoplanet Redox State Estimations (DIVERSE) project, focusing on the relationship between planetary interior structure, redox state, and habitability potential of exoplanets. His research combines geophysical modeling with machine learning techniques to rapidly characterize exoplanet interiors. Dr. Baumeister completed his academic training at Technische Universität Berlin, earning a B.Sc. in Physics (2011-2015), M.Sc. in Physics (2015-2017) with thesis on heat-piping effects on Earth's interior evolution, and a PhD in Physics (2018-2023) with dissertation on interior structure, mantle-atmosphere co-evolution, and habitability of low-mass exoplanets. His primary research interests include exoplanet interior structure modeling, planetary geodynamics, habitability assessment of stagnant-lid planets, redox state analysis, and machine learning applications in planetary science. He has developed innovative approaches like ExoMDN (Exoplanet Mixture Density Networks) to rapidly characterize exoplanet interiors using probabilistic machine learning. Analysis of his publication record shows a strong focus on the connection between planetary interior structure and atmospheric properties, with particular attention to stagnant-lid planets (like Venus and many exoplanets). His work increasingly incorporates machine learning methods to address computational challenges in exoplanet characterization, while maintaining rigorous physical modeling of planetary interiors and atmospheres. Dr. Baumeister actively collaborates with researchers across multiple institutions, as evidenced by his co-authorship on studies involving atmospheric modeling, exoplanet system characterization, and Venus research. His work on the DIVERSE project represents a significant contribution to understanding how planetary redox states influence long-term habitability potential.