Dr. Charles Dalang is a Visiting Researcher at Queen Mary University of London's School of Physical and Chemical Sciences, Department of Physics and Astronomy. His work focuses on gravitational wave physics, cosmology, and alternative theories of gravity. He holds a PhD from the University of Geneva (2022), an MSc from ETH Zürich, and a BSc from EPFL, all in Physics. A member of LISA's cosmology working group since 2018, his research bridges cosmological models and gravitational wave observations, addressing topics like dark energy, modified gravity, and large-scale structure. Research interests include observer-dependent cosmology, cosmic microwave background physics, and applications of gravitational wave astronomy to test gravity. His recent work explores peculiar velocity effects on cosmological parameters, standard sirens, and LISA mission science. Publications span 15+ peer-reviewed articles since 2020, tackling issues such as kinematic dipole tensions, screening mechanisms in black hole binaries, and polarization distortions in lensed gravitational waves. Collaborations emphasize interdisciplinary approaches to cosmological puzzles.
Gregory Green is an independent research group leader at the Max Planck Institute for Astronomy (MPIA) in Heidelberg, Germany, specializing in galactic evolution and interstellar dust mapping. His work combines observational data from the Gaia mission, photometric surveys, and computational models to reconstruct three-dimensional structures of the Milky Way. Key research areas include dust extinction curves, stellar dynamics, and data-driven astrophysical inference. Institution: Max Planck Institute for Astronomy Department: Galaxies and Cosmology Position: Sofia Kovalevskaja Group Leader Contact: +49 6221 528-460 | Königstuhl 17, 69117 Heidelberg Green's research focuses on computational astrophysics and galactic structure analysis. He develops novel methods for mapping dust extinction in 3D, studies the dynamics of the Milky Way's gravitational potential, and applies machine learning to stellar population analysis. His work bridges observational astronomy with theoretical modeling, particularly in understanding the interstellar medium's role in galaxy evolution. The 15 most recent publications highlight his emphasis on Gaia data exploitation, dust mapping algorithms (including normalizing flows), and galactic dynamics. Articles span topics from binary star census to radiative properties of the interstellar medium, with methodological innovations in astrometric inference and spectral analysis. Scientific Awards: Sofia Kovalevskaja Award recipient for establishing independent research group Green leads the Galaxy Evolution group at MPIA, contributing to cosmological applications of galactic dust mapping. His work informs models of galaxy formation and provides foundational data for studies of stellar populations and dark matter constraints via satellite galaxies.
Katerina Chatziioannou is an Assistant Professor of Physics at the California Institute of Technology and a William H. Hurt Scholar. She holds a faculty position in the Division of Physics, Mathematics and Astronomy, specifically within the Physics department, and is actively involved in multiple major gravitational wave collaborations including the LIGO Scientific Collaboration, LIGO Laboratory, LISA Consortium, NANOGrav Collaboration, Simulating Extreme Spacetimes Collaboration, and Simons Collaboration on Extreme Electrodynamics of Compact Sources. Dr. Chatziioannou's research revolves around General Relativity and using Gravitational Waves to study the Universe. Her work spans theoretical and observational aspects of gravitational wave astronomy, with particular focus on black hole physics, neutron star physics, and data analysis techniques. She develops methods to extract physical information from gravitational wave signals, studies the properties of compact objects, and investigates fundamental physics through gravitational wave observations. Her research bridges theoretical physics, computational methods, and observational astronomy, with applications to current and future gravitational wave detectors including LIGO, Virgo, and the planned LISA mission. Analysis of her recent publications reveals significant contributions across multiple frontiers of gravitational wave science. Her work addresses critical challenges in parameter estimation for binary black hole systems, neutron star equation of state constraints, glitch mitigation techniques, and waveform modeling. She has made important contributions to both ground-based (LIGO/Virgo) and space-based (LISA) gravitational wave astronomy, as well as pulsar timing array science through her work with NANOGrav. Her research demonstrates a strong interdisciplinary approach connecting nuclear physics, general relativity, and observational astronomy. Dr. Chatziioannou has received recognition as a William H. Hurt Scholar, highlighting her contributions to physics research. This prestigious award underscores her standing in the field of gravitational wave astrophysics and theoretical physics. She leads a vibrant research group at Caltech comprising graduate students, postdoctoral researchers, and staff scientists. Her current research group includes graduate students Sophie Hourihane (2020-present), Isaac Legred (2020-present), Simona Miller (2021-present), and Taylor Knapp (2023-present), along with numerous postdoctoral scholars including Patrick Meyers, Aaron Johnson, Javier Roulet, Eliot Finch, Lucy Thomas, Marco Crisostomi, Lisa Drummond, and Sophie Bini. She also mentors undergraduate researchers through programs like the LIGO SURF program, having supervised multiple summer research fellows over the years. Dr. Chatziioannou teaches several advanced physics courses at Caltech including Physics 106a (Topics in Classical Physics), Physics 129b (Mathematical Methods of Physics, Complex Analysis and Differential Equations), and Physics 236a (General Relativity I), contributing significantly to the education of future physicists and astronomers. Her teaching responsibilities span both undergraduate and graduate levels, reflecting her expertise in theoretical physics and gravitational wave science.
Livieris Ioannis is an Assistant Professor in the Department of Statistics and Insurance Science at the University of Piraeus. He holds academic positions including Adjunct Professorships at the University of the Peloponnese and Technological Educational Institute of Western Greece. His research focuses on optimization methods for neural networks, machine learning, ensemble techniques, and their applications in healthcare, finance, education, and environmental science. Education: Ph.D. in Mathematics (2012), University of Patras M.Sc. in Computational Mathematics & Informatics in Education (2008), University of Patras B.Sc. in Mathematics (2006), University of Patras Research Interests: Dr. Livieris specializes in developing optimization algorithms for neural networks, semi-supervised learning, and ensemble methods. His work emphasizes practical applications such as time series forecasting (financial, environmental), medical image analysis (cancer detection, X-ray classification), and educational data mining (student performance prediction). He also explores explainable AI frameworks to enhance transparency in deep learning models. Key Contributions: He has contributed to over 50 peer-reviewed articles, including work on weight-constrained neural networks, gradient-based optimization, and CNN-LSTM models for cryptocurrency forecasting. His research has been recognized with inclusion in Stanford’s top 2% scientists (2020–2023) and a best paper award at HERCMA ’09. Awards & Roles: Associate Editor, Evolving Systems (Springer) Reviewer for 50+ journals including Neurocomputing and IEEE Transactions on Neural Networks Grants & Projects: Principal investigator in EU-funded projects like NEUROCLIMA (climate resilience via AI), ORBIS (democratic participation via AI), and PVAdapt (sustainable energy systems). He also leads initiatives in explainable AI for medical imaging and causal effect estimation in social science. Labs & Teams: Active in interdisciplinary teams at the University of Piraeus, focusing on AI-driven solutions in education, healthcare, and environmental monitoring. Collaborates with institutions like the IEEE and the Hellenic Association of ICT in Education.
Chen Yu is a Professor of Psychology at the University of Texas at Austin, affiliated with the College of Liberal Arts. He holds a Ph.D. from the University of Rochester. His research focuses on Development and Learning , Language Acquisition , Perception and Action , Visual Attention , Social Interaction , Computer Vision , and Machine Learning . He leads the Developmental Intelligence Lab , exploring interdisciplinary connections between cognitive science and computational methods. Recent teaching includes courses like Introduction to Machine Learning and Computational Behavioral Science . His work intersects with cutting-edge gravitational wave astronomy, contributing to cosmological studies using standard siren measurements and multimessenger observations. Key areas include improving Hubble constant estimation, analyzing binary neutron star mergers, and mitigating biases in cosmological parameter inference. Cosmological research highlights include optimizing gravitational wave detector networks (e.g., Cosmic Explorer), studying lensing effects, and advancing techniques to identify merger host galaxies. His publications span high-impact journals, reflecting expertise in both theoretical and observational astrophysics.
Dr. Omar Ghattas is a Professor and the Ernest & Virginia Cockrell Chair in Engineering at The University of Texas at Austin, leading the Center for Computational Geosciences within ICES. He holds courtesy appointments in Computer Science, Biomedical Engineering, the Institute for Geophysics, and the Texas Advanced Computing Center. His research focuses on computational geosciences, inverse problems, and large-scale simulation of geophysical and biological systems. Prior to UT Austin, he was a professor at Carnegie Mellon University for 16 years, earning degrees from Duke University (BS, MS, PhD, 1984–1988). Education: BS, MS, PhD in Engineering from Duke University (1984–1988). Affiliations: Director of the KAUST-UT Austin Alliance, member of multiple editorial boards, and recipient of prestigious awards including the Gordon Bell Prize. His research interests span computational geosciences, inverse problems, uncertainty quantification, and high-performance computing. Key areas include mantle convection modeling, seismic wave propagation, ice sheet dynamics, and subsurface flows. He has pioneered methods for large-scale inverse problems on supercomputers, addressing challenges in computational efficiency and statistical rigor. Recent work emphasizes real-time Bayesian inference for disaster prediction (e.g., tsunamis) and advanced neural operator techniques for high-dimensional Bayesian inverse problems. His publications explore topics like derivative-informed neural operators, multifidelity sampling, and scalable computational frameworks for geophysical applications. Awards: Allen Newell Medal, Gordon Bell Prize, SIAM Fellowship, and multiple HPC awards. Grants & Leadership: Directorships of ICES research centers and international alliances, funded by NSF and DOE. Labs/Teams: The Center for Computational Geosciences in ICES, collaborations with KAUST, and leadership in interdisciplinary computational science initiatives.
Prof. Roberto Trotta is a Professor of Theoretical Physics at SISSA (Trieste, Italy) and Visiting Professor of Astrostatistics at Imperial College London. He leads the Theoretical and Scientific Data Science group at SISSA and directs its Interdisciplinary Lab. His research focuses on cosmology, dark matter/energy, and applying machine learning/AI to astrophysical data. He holds a PhD from the University of Geneva and an MSc from ETH Zurich. He has been a faculty member at Imperial College London (2008–2023) and a Visiting Professor at Gresham College (2019–2022). Education: PhD in Theoretical Physics, University of Geneva, Switzerland (2004) MSc (Hons) in Physics, ETH Zurich, Switzerland (2011) Research: Analyzes cosmological observations to study dark matter/energy, early universe physics, and particle-physics connections. Develops Bayesian methods, machine learning, and AI for data analysis. Leads projects like STAR NRE and StratLearn-z for improved astrophysical modeling. Collaborates on experiments like LISA, DARWIN, and EDGES. Public Engagement: Award-winning science communicator; authored The Edge of the Sky (2014) and STARBORN (2023). Public lectures at Gresham College and international festivals. Recognized with the Annie Maunder Medal (2020) and Foreign Policy's Global Thinkers (2014). Awards: Annie Maunder Medal (Royal Astronomical Society, 2020) Chair Georges Lemaître (2018) Foreign Policy 100 Global Thinkers (2014) Michelson Prize (2008) Leadership: Directed Imperial’s Centre for Languages, Culture, and Communication (2015–2020). Founded Data Fusion Consultants (2012–2020) for statistical consultancy. Collaborates with museums and artists on science communication. Labs/Teams: Leads the SISSA Data Science group and collaborates with the Theoretical and Scientific Data Science team at SISSA. Active in interdisciplinary projects like the AstroML group and DARWIN observatory collaborations.
Michael Pürrer serves as an Adjunct Assistant Professor in the Department of Physics and Computational Scientist at the Center for Research Computing, University of Rhode Island. A member of the NSF-funded LIGO Scientific Collaboration since 2013, he contributes to gravitational-wave astronomy through advanced data analysis and source modeling. Education: Ph.D. in Theoretical Physics, University of Vienna, Austria, 2007 Diploma in Theoretical Physics, University of Vienna, Austria, 2003 Dr. Pürrer specializes in gravitational-wave signal modeling for binary black hole and neutron star mergers, employing Bayesian inference and deep learning techniques for simulation-based conditional density estimation. His work integrates high-performance computing with statistical learning to enhance gravitational-wave detection and parameter estimation accuracy, directly supporting LIGO-Virgo-KAGRA observational campaigns. Current research emphasizes neural network applications for rapid inference in next-generation detector networks. His publication record reveals a decisive shift toward machine learning integration in gravitational-wave astronomy since 2020, with deep learning methods now central to waveform modeling and inference pipelines. Key focus areas include noise adaptation, surrogate modeling for precessing binaries, and accuracy requirements for future detectors like Cosmic Explorer and Einstein Telescope. Scientific Awards: 2016 Special Breakthrough Prize in Fundamental Physics (LSC) 2016 Gruber Cosmology Prize (LSC) Premio Princesa de Asturias de Investigación 2017 (LSC) 2017 RAS Group Achievement Award ‘A’ (LSC) As a lead contributor to the GWTC-1 catalog paper and developer of critical waveform models, Dr. Pürrer’s work underpins major gravitational-wave discoveries. His research is sustained through LIGO Scientific Collaboration funding, with significant publications in Physical Review Letters and Astrophysical Journal. Though student advising details are unspecified, his leadership in LVK working groups demonstrates mentorship within the collaboration framework. Dr. Pürrer actively participates in the LIGO Scientific Collaboration’s Compact Binary Coalescence group and contributes to the Science Book for future gravitational-wave observatories, positioning him at the forefront of next-generation detector development and multi-messenger astronomy initiatives.
Carl-Johan Haster is an Assistant Professor of Astrophysics in the Department of Physics & Astronomy and the Nevada Center for Astrophysics (NCfA) at University of Nevada, Las Vegas. His academic journey includes a Postdoctoral Associate position at the LIGO Laboratory and the Kavli Institute for Astrophysics and Space Research at MIT, a CITA Postdoctoral Fellowship at the Canadian Institute for Theoretical Astrophysics, a PhD from the University of Birmingham, and an MPhys from the University of Manchester. Dr. Haster's research focuses on gravitational wave astronomy and the extreme physics of our universe. His work primarily involves analyzing data from gravitational wave detectors like LIGO to study compact objects such as black holes and neutron stars. He has made significant contributions to understanding the formation and evolution of these objects, exploring matter under extreme conditions as found in neutron star binaries, and developing advanced inference methods for gravitational wave signal analysis. His research also extends to precision tests of General Relativity using gravitational wave observations, ensuring that potential deviations from Einstein's theory are not confused with analysis inaccuracies. Analysis of Dr. Haster's recent publications reveals a strong emphasis on gravitational wave catalog development (GWTC series), waveform modeling accuracy, population studies of compact binaries, and multi-messenger astronomy approaches. His work increasingly addresses systematic uncertainties in gravitational wave measurements, cosmological applications of gravitational wave data, and the development of more robust analysis frameworks for current and future detectors like Cosmic Explorer. As an active member of the LIGO Scientific Collaboration and Virgo Collaboration, Dr. Haster contributes to major gravitational wave discovery efforts. His GitHub profile shows active participation in gravitational wave data analysis software development, including contributions to projects like lalsuite, gwin, and gwpopulation, which are critical tools for the gravitational wave community.
Dr. Marc van der Sluys van der Sluijs is a researcher at Utrecht University's Department of Gravitational and Subatomic Physics (GRASP) and the Dutch National Institute for Nuclear and High Energy Physics (Nikhef) in Amsterdam. His academic focus spans gravitational-wave detection, binary evolution, and computational astrophysics, with active roles in the Virgo, LIGO, and Einstein Telescope collaborations. Research Interests: His work centers on gravitational-wave data analysis, neutron star and black hole coalescences, common-envelope evolution, and multi-messenger astronomy. He employs heavy computing and Bayesian statistics for empirical modeling of astrophysical phenomena. Teaching: He teaches Introduction to Astrophysics and Stellar Evolution in Utrecht University's physics bachelor program. Publications: His recent articles (2019–2025) predominantly explore gravitational-wave detection methodologies, dark matter searches, and solar position algorithms. Key themes include machine learning applications in astrophysics, multi-instrument data analysis, and open-source software development for scientific computation. Ancillary Activities: He founded hemel.waarnemen.com , a popular Dutch astronomy website with 1–2 million annual visits, providing observational guides for celestial phenomena in Belgium and the Netherlands.
Jacob Dunningham is a Professor of Physics at the University of Sussex within the School of Mathematical and Physical Sciences, Department of Physics & Astronomy. He holds multiple leadership positions including Executive Director of the South East Physics Network (SEPnet), Deputy Director of the Sussex Centre for Quantum Technologies, and Departmental Head of Research and Knowledge Exchange. Previously, he served as Head of the Department of Physics & Astronomy from 2018-2020. Professor Dunningham's research focuses on quantum information, quantum optics, Bose-Einstein condensation, and metrology, with particular emphasis on how fundamental quantum physics can be exploited in practical schemes and new technologies. His work bridges theoretical quantum physics with practical applications in quantum sensing and quantum technologies. His recent publications reveal a strong trend toward quantum sensing networks, atom interferometry, and quantum-enhanced measurement techniques with applications in precision measurement, gravitational physics, and fundamental constant verification. His research increasingly incorporates practical implementations of quantum protocols for real-world applications. Scientific recognition includes: Fellow of the Institute of Physics Darden Junior Research Fellowship at Merton College Oxford EPSRC Advanced Research Fellowship Professor Dunningham has been the main supervisor for 14 PhD students and has secured substantial research funding from organizations including the Royal Society, DSTL, STFC, and EPSRC. His teaching responsibilities include Atomic Physics, Skills in Physics, and 'Quarks to the Cosmos' courses. He leads research within the Sussex Centre for Quantum Technologies, focusing on developing quantum-enhanced sensors, quantum communication protocols, and fundamental investigations of quantum phenomena with practical applications. His work often involves collaborative projects with national and international partners across academia and defense sectors.
Jean-René Cudell is a Professor at the University of Liège's Department of Astrophysics, Geophysics and Oceanography. His academic affiliations include: Current: University of Liège (Professor) Past: University of Wisconsin–Madison (Research Assistant, 1983-1987) McGill University (PostDoc, 1993-1995) Brown University (Visiting Researcher, 1995) His research spans fundamental physics domains with particular emphasis on: Gravitational wave astrophysics : Developing detection algorithms for LIGO-Virgo collaborations Particle cosmology : Investigating dark matter and cosmic anisotropies Quantum field theory : Studying strong-interaction physics and scattering models Recent publications demonstrate three primary research arcs: (1) gravitational lensing and detector characterization for Advanced LIGO/Virgo; (2) machine learning approaches for early inspiral detection; and (3) unitarisation models for high-energy particle collisions. His 265 publications show consistent focus on theoretical and observational aspects of extreme astrophysical phenomena. Professor Cudell maintains active involvement in large-scale physics collaborations, contributing to gravitational wave searches and theoretical particle physics without recorded awards or formal research lab infrastructure.
