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Sarah Burke-SpolaorView profile

Associate Professor

• Gravitational Wave Detection
• Binary Supermassive Black Holes
• Fast Radio Bursts (FRBs)
• +3 more

Dr. Sarah Burke-Spolaor is an Associate Professor in the Department of Physics and Astronomy at West Virginia University and a member of the Center for Gravitational Waves and Cosmology (GWAC) . Her research focuses on dynamic astrophysical phenomena , including binary supermass of mass black holes , pulsar timing arrays for gravitational wave detection , and Fast Radio Bursts (FRBs) . Key Research Areas : Gravitational wave detection via pulsar timing Observational studies of binary supermassive black holes Fast Radio Burst detection and classification Galaxy formation and merger dynamics Dr. Burke-Spolaor mentors a team of students and postdocs including Gregory Walsh, Jessica Sydnor, Reshma Thomas , and Kshitij Aggarwal , whose work includes projects like the BHBinary/Galaxy Evolution Survey and The Petabyte Project for Radio Transients . Her awards include the Alfred P. Sloan Fellowship and recognition as a CIFAR Azrieli Global Scholar . Selected Article Trends : Leading gravitational wave research through NANOGrav's 15-year data set Multi-messenger astronomy targeting binary black hole systems FRB host galaxy characterization across telescopes Exploring unconventional astrophysical transients in the Galactic bulge Advancing pulsar timing array methodologies Developing next-generation radio interferometry techniques Scientific Awards : Alfred P. Sloan Fellow CIFAR Azrieli Global Scholar

• Astrophysics
• Supernova Studies
• Machine Learning in Astronomy
• +3 more

Ashley Villar is an Assistant Professor of Astronomy at the Center for Astrophysics at Harvard University. Her research focuses on the intersection of astrophysics and machine learning, particularly in the study of supernovae, transient phenomena, and circumstellar interactions. She is actively involved in time-domain surveys and the development of advanced algorithms for classifying and analyzing astronomical transients. Current Position: Assistant Professor of Astronomy Affiliation: Harvard University Center for Astrophysics Her work integrates observational data from facilities like the Hubble Space Telescope (HST), James Webb Space Telescope (JWST), and the Vera C. Rubin Observatory to study supernova progenitors, explosion mechanisms, and circumstellar environments. Key research areas include pulsational pair instability models, binary progenitor systems, and the application of neural networks for rapid transient classification. Dr. Villar has pioneered methods such as the SPLASH classifier, Superphot+, and Maven framework to enhance automated analysis of transient events. Her contributions to the Young Supernova Experiment (YSE) have resulted in large-scale datasets and photometric classifications of over 1,500 supernovae. Notable Projects: YSE DR1 Data Release, Rubin Observatory Target-of-Opportunity programs, LIGO/Virgo follow-up campaigns Her research also addresses kilonova light-curve interpolation, gravitational wave follow-up strategies, and the detection of anomalies in variable star catalogs. She collaborates widely on multimessenger astronomy and next-generation survey strategies for transient detection.

Timothy CookView profile

Associate Professor

• Astrophysics
• Sounding Rockets
• Ultraviolet Instrumentation
• +4 more

Timothy Cook is an Associate Professor in the Department of Physics & Applied Physics at the University of Massachusetts Lowell. He holds a PhD in Astrophysics from the University of Colorado (1991) and has extensive experience in developing space-borne and ground-based instrumentation. His research focuses on ultraviolet instrumentation, sounding rockets, and novel data analysis techniques, particularly for studying astrophysical dust, exoplanetary systems, and interstellar/intergalactic material. Key projects include the PICTURE and IMAGER sounding rockets, the SPINR payload for stellar dust studies, and the SCARI interferometer for interstellar medium analysis. He has led and collaborated on multiple NASA-funded missions and grants, including roles as PI and Co-PI on projects like the CLUE experiment and DWEL lidar system. His work integrates astrophysical observations with advanced optical engineering and remote sensing technologies. Education: PhD in Astrophysics, University of Colorado Boulder, 1991 BA in Physics, Johns Hopkins University, 1985 Research Interests: Dr. Cook specializes in designing and deploying instruments for space and terrestrial environments. His expertise spans sounding rocket payloads (e.g., PICTURE-B, LITES), ultraviolet spectroscopy, coronagraphy for exoplanet detection, and lidar systems for forest canopy analysis. He also investigates interstellar dust properties and circumgalactic material using novel tomographic and interferometric techniques. His work bridges astrophysical studies with practical engineering solutions for observational challenges. Grants & Collaborations: Principal Investigator for NASA-funded projects like the Interstellar Medium Absorption Gradient Experiment Rocket (2007) Co-PI for NSF grants developing the Dual-Wavelength Echidna Lidar (DWEL) for forest biomass studies (2009) Contributed to the TERRIERS satellite mission studying Earth’s ionosphere Labs & Teams: Collaborates with interdisciplinary teams at UMass Lowell, NASA, and institutions like Boston University, leveraging expertise in optical instrumentation and data analysis.

Stephen EikenberryView profile

Professor

• Astrophysics
• Gravitational Waves
• Black Holes
• +7 more

Stephen Eikenberry is a Professor of Optics & Photonics Physics at CREOL, The College of Optics and Photonics, University of Central Florida. His academic journey includes a Ph.D. in Astronomy from Harvard University (1997), a Sherman Fairchild Postdoctoral Prize Fellowship at Caltech, and prior tenured roles at Cornell University and the University of Florida. His research focuses on black holes, neutron stars, gravitational waves, and astronomical instrumentation, with applications in biomedical imaging and spectroscopy. Key professional milestones include the 2016 Breakthrough Prize in Fundamental Physics (as part of the LIGO Science Consortium), the NSF CAREER Award (2000), and multiple University of Florida Research Foundation Professorships. He has designed advanced optical instruments and contributed to LIGO's gravitational wave discoveries. Eikenberry's research group explores astrophotonics, dark energy, and extrasolar planets. His recent work includes analyzing gravitational wave data from LIGO/Virgo and developing lunar occultation missions. He advises multiple graduate students and collaborates on international projects like the PolyOculus Array (OPA!). Education: Ph.D. in Astronomy, Harvard University (1997) Postdoctoral Fellowship at Caltech (Sherman Fairchild Prize) Awards: Breakthrough Prize in Fundamental Physics (2016) Gruber Prize for Cosmology (2016) UK Royal Astronomical Society Team Achievement Award (2016) His publications emphasize gravitational wave astronomy, cosmology, and instrument design. He has pioneered methods to constrain cosmic expansion using gravitational wave 'standard sirens' and studies correlations between fast radio bursts and gravitational wave events.

• Extragalactic Astrophysics
• Cosmology
• Weak Gravitational Lensing
• +7 more

Tim Schrabback is a Full Professor at the Institute for Astro- and Particle Physics , Faculty of Mathematics, Computer Science and Physics, University of Innsbruck . He leads research in extragalactic astrophysics, focusing on weak gravitational lensing, galaxy clusters, and cosmology through major international collaborations such as the Euclid Mission , eROSITA , DES , SPT , and HSC . His research interests include: Observational cosmology using galaxy clusters Weak and strong gravitational lensing Dark energy and large-scale structure X-ray and Sunyaev-Zel'dovich cluster surveys Machine learning applications in astrophysics Calibration of space-based instruments His recent publications (2023–2025) span high-impact journals including Astronomy & Astrophysics , Physical Review D , and Monthly Notices of the Royal Astronomical Society . The work emphasizes cosmological parameter estimation , cluster mass calibration , systematic error mitigation in weak lensing , and multi-messenger cosmology . A strong trend is the integration of data from optical, infrared, X-ray, and microwave surveys to constrain models of dark energy and modified gravity. Scientific contributions include: Leading roles in Euclid’s weak lensing and cluster science working groups Co-authorship on foundational Euclid mission papers Key contributions to eROSITA all-sky survey analysis Development of shear calibration techniques using deep learning Mass calibration of galaxy clusters via weak lensing He actively participates in advising and collaborative research, working closely with postdocs and early-career scientists such as Sebastian Grandis , Florian Kleinebreil , Henrik Jansen , and Lukas Linke . He has secured access to major datasets and leads analysis efforts in joint cluster cosmology programs. His public engagement includes frequent outreach lectures on astrophysics and telescope observation, particularly through the annual Astronacht events at the University of Innsbruck. He has also contributed to media interviews on cosmological tensions and galaxy cluster physics. He leads or participates in several research labs and teams: Euclid Weak Lensing Science Working Group eROSITA Cluster & Cosmology Working Group Institute for Astro- and Particle Physics Observing Team Alpine Cosmology Collaboration

Daniel M. ScolnicView profile

Associate Professor

• Cosmology
• Supernovae
• Dark Energy
• +3 more

Daniel M. Scolnic is an Associate Professor of Physics at Duke University's Trinity College of Arts & Sciences and holds a joint appointment in the Department of Electrical and Computer Engineering at the Pratt School of Engineering. His research focuses on cosmology, particularly using Type Ia supernovae and near-infrared observations to probe dark energy and resolve the Hubble tension. Ph.D. (2013), Johns Hopkins University B.S. (2007), Massachusetts Institute of Technology As a leading figure in supernova cosmology, Scolnic works on refining the cosmic distance ladder, studying time-evolving dark energy, and analyzing systematic uncertainties in cosmological measurements. His work leverages data from the Dark Energy Survey (DES), Pantheon+ collaboration, and James Webb Space Telescope (JWST) to address discrepancies in the Hubble constant (H₀) derived from early- and late-universe observations. His recent publications highlight advancements in inverse distance ladder techniques, host galaxy dust modeling, and the role of photometric redshifts in cosmological analyses. Notably, his team's JAGB 2.0 study improves Hubble constant constraints using JWST. Defense Science Study Group (DSSG) Clarivate Most Highly Cited Scientists Fred Kavli Plenary Lectureship Sloan Research Fellowship in Physics Department of Energy Early Career Award Packard Fellowship Scolnic leads major grants from NASA, the Packard Foundation, and the Department of Energy, including a NASA Roman Project Infrastructure Team grant (2023-2028) and a Packard Fellowship (2019-2027) to investigate cosmological tensions. He actively collaborates with the Duke Cosmology Group and contributes to the Nancy Grace Roman Space Telescope's High-Latitude Time-Domain Survey.

• Astronomical Sciences
• Space Sciences
• Particle and High Energy Physics
• +3 more

Ivan Baldry is a Professor at the Astrophysics Research Institute of Liverpool John Moores University , with a career focused on galaxy formation and cosmology. His work spans large-scale surveys like GAMA, XXL, and Euclid, emphasizing photometric redshifts, stellar mass functions, and galaxy environment interactions. PhD in Astrophysics from University of Sydney (1995-1999) Research interests center on galaxy evolution , cosmic star formation , and observational cosmology , with significant contributions to understanding galaxy bimodality and low-surface-brightness systems. His work integrates multi-wavelength data (UV to radio) and advanced clustering techniques. Key publications include studies on galaxy mass-size relations, star formation rate indicators, and the cosmic spectral energy distribution. He co-authored over a dozen GAMA project papers and contributed to Euclid mission frameworks. Scientific Awards & Professional Roles Royal Astronomical Society Group Achievement Award (2008) Fellow of the Higher Education Academy (2014) Fellow of the Royal Astronomical Society (2009) Member of Euclid Science Team (2011-present) International Member, Australian Time Assignment Committee (2015) His collaborations span institutions like the Isaac Newton Group, VISTA surveys, and the 2dF Galaxy Redshift Survey Team, with leadership in data release protocols and survey diagnostics.

• Astronomy
• Astrophysics
• Machine Learning
• +5 more

Robert Brunner serves as Professor of Astronomy at the University of Illinois at Urbana-Champaign, where he bridges astrophysical research with computational innovation. His work focuses on extracting knowledge from massive astronomical datasets through advanced statistical and machine learning techniques, while also extending methodologies to finance and agricultural applications. Research interests center on developing machine learning algorithms (random forests, deep neural networks, Bayesian estimation) for astronomical data analysis, cosmological parameter constraints via n-point clustering measurements, and hardware acceleration using GPUs/cloud systems. His interdisciplinary approach spans source classification, transient phenomena detection in surveys like SDSS and DES, and applications in financial time-series analysis and agricultural remote sensing. Recent publications (2019-2025) reveal strong cross-domain expertise: astronomical catalogs for Rubin Observatory and Spitzer surveys coexist with financial market analysis using community detection methods and agricultural computer vision systems. Key methodological threads include spatio-temporal forecasting, multimodal learning for earnings calls, and anomaly detection via extended isolation forests, demonstrating consistent innovation in handling petascale datasets across scientific boundaries.

• Fluid Mechanics
• Mathematical Modeling
• Environmental Science
• +3 more

Duncan Farrow is an Adjunct Associate Professor at the School of Physics, Mathematics and Computing, University of Western Australia. His research focuses on fluid dynamics, mathematical modeling, environmental science, biomedical engineering, astrophysics, and hydrology. He has an h-index of 17 and has contributed to over 3 citations in his field. Farrow collaborates globally on projects addressing sustainable development goals, particularly in areas impacting environmental and health sciences. Education details are not explicitly provided in the text. Research interests include free surface flows, porous media interactions, retinal hydrogen dispersal models, and galaxy environment studies. His work often bridges theoretical models with practical applications, such as in biomedical systems and environmental fluid mechanics. Key research areas: Fluid Mechanics, Mathematical Modeling, Environmental Science, Biomedical Engineering, Astrophysics, Hydrology While specific grants or advising roles are not detailed, his publications suggest active engagement in collaborative research projects. Recent studies involve fluid flow into line sinks, hydrogen diffusion in biological tissues, and mid-infrared galaxy properties analysis. No labs or teams are explicitly mentioned in the provided text.

Sotiria FotopoulouView profile

Lecturer

• Astrophysics
• Active Galactic Nuclei
• Galaxy Clusters
• +4 more

Sotiria Fotopoulou is a Lecturer in the School of Physics at the University of Bristol. Her research focuses on astrophysics, particularly in active galactic nuclei (AGN), quasars, galaxy clusters, and cosmic web structure. She contributes to the Euclid mission's scientific objectives through studies of photometric redshifts, galaxy evolution, and environmental effects. Current Project: Principal Investigator for 'Co-evolution or co-existence? Growth of supermassive black holes in next generation surveys' (2023-2024) Research Themes: Quasar census, slitless infrared spectroscopy for high-redshift objects, cosmic web reconstruction, intracluster light analysis, and gravitational lensing detection. Her work integrates Euclid data with machine learning techniques for galaxy morphology and photometric studies. Award: Recipient of Undergraduate Bursary Grant (2020)

Stephen WarrenView profile

Professor

• Observational Astronomy
• High-Redshift Quasars
• Cool Brown Dwarfs
• +3 more

Stephen Warren is a Professor of Astrophysics at Imperial College London's Department of Physics, part of the Faculty of Natural Sciences. He has been at Imperial since 1994, previously holding postdoctoral fellowships at institutions like Steward Observatory and ESO. His research focuses on observational astronomy, including surveys for high-redshift quasars, brown dwarfs, gravitational lensing, and quasar absorption lines. He led the UKIRT Infrared Deep Sky Survey as Survey Scientist until 2012 and served as Head of Astrophysics at Imperial from 2010 to 2015. Education: BA and PhD (1988) from the University of Cambridge. His academic positions include Consul for the Faculty of Natural Sciences & Education Office at Imperial College London since 2020. Research interests emphasize discovering celestial objects through surveys and understanding their properties. His work spans quasar environments, galaxy mass modeling, and brown dwarf characterization. Recent publications highlight advancements in gravitational lensing models, Milky Way vertical structure analysis, and Euclid mission predictions for high-redshift quasars. Affiliations include the Astrophysics Group, Physics of the Universe, and Space Lab at Imperial. His contributions to large surveys and observational techniques have been foundational in extragalactic astronomy and sub-stellar object classification.

Kerstin BunteView profile

Professor

• Machine Learning
• Artificial Intelligence
• XAI (Explainable Artificial Intelligence)
• +7 more

Kerstin Bunte is a Professor of Machine Learning for interdisciplinary data analysis at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute's Intelligent Systems Group. She holds an Honorary Fellowship at the University of Birmingham and leads the Intelligent Systems Group. Her research focuses on interpretable machine learning, interdisciplinary applications (e.g., astrophysics and biomedical data), and visualization techniques. Research Interests: - Machine Learning - Artificial Intelligence - Explainable AI (XAI) - Interpretable Models - Dimensionality Reduction - Data Visualization - Astrophysical Data Analysis - Medical Imaging Awards & Grants: - DSSC XS funding (2023) - NWO VIDI grant (2020) - Rosalind Franklin Fellowship (2016–present) Advising & Students: Supervised PhD students include Elisa Oostwal, Janis Norden, Matteo Marcantoni, and Petra Awad. Research spans topics like tumor segmentation in medical imaging, astrophysical structure detection, and autonomous navigation systems. Labs & Collaborations: Leads the Intelligent Systems Group, collaborating with institutions like the University of Birmingham and the University of Warwick. Work involves interdisciplinary projects combining machine learning with astronomy, biomedical sciences, and robotics.

• X-ray astronomy
• Galaxy clusters
• Inverse Compton scattering
• +10 more

Dan Wik is an Associate Professor in the Department of Physics & Astronomy at the University of Utah . His research focuses on observational X-ray astronomy, particularly galaxy clusters, inverse Compton scattering, X-ray binaries, and the X-ray background. He has extensive experience in data calibration, analysis tool development, and mission collaborations such as NuSTAR, Chandra, and XRISM. Wik holds a PhD in Astronomy from the University of Virginia (2010) and a BS in Astrophysics from Ohio University . His research interests span galaxy cluster mergers, nonthermal emission processes, high-energy astrophysics, and cross-calibration studies between X-ray observatories. Recent articles highlight his work on NuSTAR observations of galaxy clusters, X-ray binary populations in M31 and M33, inverse Compton emission constraints, and stray light background analysis techniques. His studies often integrate multiwavelength data and address cosmological implications of X-ray observations. Wik has received multiple grants from NASA for projects like Time Domain X-ray Studies of AGN and Hard Bandpass Extension of XRISM Cluster Observations . He supervises undergraduate and graduate researchers and teaches courses from general education to advanced graduate levels, including Foundations of Astronomy and High Energy Astrophysics .

Dacheng LinView profile

Research Professor

• Astrophysics
• High-Energy Astrophysics
• Black Hole Physics
• +3 more

Dacheng Lin is a Research Professor in the Department of Physics at Northeastern University (NU), where he has held this position since December 2020. Previously, he served as a Research Scientist at the University of New Hampshire (UNH) from 2014 to 2017, later becoming a Research Assistant Professor with a joint appointment in the Department of Physics and the Space Science Center within the Institute for the Study of Earth, Oceans, and Space. His academic journey includes a PhD in Physics from the Massachusetts Institute of Technology (2009) and an undergraduate degree from the University of Science and Technology of China. Dr. Lin specializes in high-energy astrophysics, focusing on black hole candidates, neutron star accretion processes, tidal disruption events, and X-ray astronomy. His research leverages multiwavelength observations and advanced spectroscopic techniques to study phenomena such as ultraluminous X-ray sources, magnetar-powered transients, and stellar disruption dynamics. Notable contributions include identifying intermediate-mass black hole candidates in dwarf galaxies and analyzing prolonged tidal disruption events. His work integrates cutting-edge telescopes like Chandra and XMM-Newton, emphasizing transient event detection and source classification. While no formal awards are listed, his research has garnered attention, including a feature in Northeastern’s news for discovering high-energy signals from billions of light years away. Dr. Lin’s advising and grant activities remain unspecified in the provided texts, though his prior roles at UNH suggest involvement in collaborative research teams and observational projects. Dr. Lin’s affiliations and research reflect a deep engagement with extragalactic phenomena and compact object astrophysics, contributing to our understanding of accretion physics and high-energy transients in the universe.

Xan Guilian Morice-AtkinsonView profile

Researcher

• Machine Learning
• Astrophysics
• Cosmology
• +5 more

Xan Guilian Morice-Atkinson is a Research Software Engineer at the University of Portsmouth's Faculty of Technology, working within the Institute of Cosmology & Gravitation and the Portsmouth AI and Data Science Centre. With a PhD in Astrophysics and Cosmology completed in 2018, Xan applies machine learning methods to astrophysical research problems, developing computational tools that advance cosmological understanding. Xan earned their PhD from the Institute of Cosmology and Gravitation in 2018, focusing on machine learning applications in astrophysics and cosmology. After completing their doctorate, they worked for several years as a Data Scientist in Air Traffic Services before returning to the ICG as a Research Software Engineer where they program computers to perform astrophysics-related tasks. Research interests span machine learning applications in astrophysics, gravitational wave analysis, cosmological simulations, and galaxy formation studies. Xan specializes in developing computational tools for astrophysical data analysis, with particular expertise in applying machine learning algorithms to classify astronomical objects and model cosmological phenomena, as evidenced by their first-author publication on machine learning interpretation for source classification. Xan's publication record shows a strong focus on applying computational methods to fundamental astrophysical problems, with recent work on gravitational wave alert systems, modified gravity emulators, and galaxy classification. Their research bridges the gap between advanced computational techniques and observational cosmology, contributing significantly to large collaborative projects like the LIGO-Virgo-KAGRA observing run and the Dark Energy Survey. Xan is currently involved as a team member in the "DDME: Data discovery made easy" project funded by the Economic and Social Research Council (June 2024 to September 2025), applying machine learning to social science databases. They have also participated in interdisciplinary work, presenting at the AI in Orthopaedics conference in September 2022, demonstrating the transferability of their computational expertise across scientific domains.