جست‌وجوی استاد و پژوهشگر

Kai Polstererمشاهده پروفایل

استاد پژوهشی

• Astroinformatics
• Machine Learning
• Data Science
• +۴ مورد دیگر

Dr. Kai Polsterer is the Scientific Director of the Heidelberg Institute for Theoretical Studies (HITS) since January 2025, succeeding Tilmann Gneiting. He has been a leading researcher at HITS since 2013, heading Europe's first astroinformatics research group. His work focuses on developing machine learning methods to handle exponential data growth in astrophysics, including projects like the ERC Synergy Grant for universe mapping and exascale computing initiatives (SPACE). He collaborates across disciplines with statisticians and physicians to advance weather forecasting and cardiological analysis. Polsterer is actively involved in international organizations such as the International Astroinformatics Association (IAIA, President since 2023), IEEE Task Force on Mining Complex Astronomical Data, and the German Physical Society's AI working group. His research spans astroinformatics, data science, and interdisciplinary applications of AI. His expertise includes photometric redshift estimation, galaxy classification, and unsupervised learning techniques. Polsterer has pioneered tools like PINK (Parallelized Kohonen Maps) and contributed to projects like the LUCIFER instrument for near-infrared spectroscopy. He emphasizes open science and collaborative frameworks, such as the HiPS ecosystem for astronomical data visualization. His current role as Scientific Director reflects his leadership in advancing theoretical studies through computational and data-driven approaches. Polsterer’s contributions include over 50 peer-reviewed articles, spanning astroinformatics, machine learning applications in astronomy, and computational methodologies. He advocates for interdisciplinary research, bridging astrophysics, computer science, and medical data analysis. His ERC Synergy Grant project exemplifies his commitment to large-scale, collaborative science addressing fundamental questions in cosmology and data science.

Sarah Gallagherمشاهده پروفایل

استاد

• Astrophysics
• Extragalactic Astronomy
• Black Hole Physics
• +۴ مورد دیگر

Dr. Sarah Gallagher is a Professor of Physics and Astronomy at Western University and Director of the Institute for Earth and Space Exploration. She specializes in studying supermassive black hole growth and galaxy interactions using multi-wavelength observations from space observatories. Her work bridges astrophysics with philosophy, exploring simulation-induced selection effects in astronomy. She served as Science Advisor to the Canadian Space Agency (2018–2022), advising on science investments and pandemic response initiatives like the CanCOVID network. Her research has been recognized with awards including the Ontario Early Career Researcher Award and the Purvis Memorial Award. Key projects include the CASTOR UV space telescope mission, studies of quasar outflows, and investigations into Stephan’s Quintet galaxy group dynamics. Education details are not explicitly listed, but her research emphasizes advanced observational techniques and interdisciplinary collaboration. Scientific contributions span over 100 refereed papers leveraging data from 10+ space observatories. Research interests focus on quasar physics (e.g., accretion disks, winds), galaxy group environments, and the philosophy of astrophysical surveys. Recent work highlights molecular gas dynamics in Stephan’s Quintet and AGN variability studies with CASTOR. Awards include recognition for both scientific achievement and public engagement. Grants/Advising: Canadian Space Agency advisory roles, leadership in the CanCOVID network. Labs/Teams: Leads the Institute for Earth and Space Exploration, collaborates on international surveys like GNRIS-DQS.

Joana Oliveiraمشاهده پروفایل

مدرس ارشد

• Star Formation
• Stellar Variability
• Magellanic Clouds
• +۱ مورد دیگر

Dr. Joana Oliveira is a Senior Lecturer in Astrophysics at Keele University's School of Chemical and Physical Sciences. She researches star formation processes in low-metallicity environments, particularly in the Magellanic Clouds, using multi-wavelength observational data. Her investigations focus on how environmental factors influence stellar birth and evolution, utilizing space telescopes (Spitzer, Herschel) and ground-based facilities (VISTA, ALMA). Current projects analyze molecular cloud structures and young stellar object populations in nearby galaxies. Publications document significant contributions to understanding interstellar chemistry and massive star formation. Recent papers report detections of complex organic molecules and deuterated water in extragalactic regions. Dr. Oliveira teaches optics, thermodynamics, and astrophysics laboratories while serving as Year 2 Tutor and Study Abroad coordinator.

Morgan Fouesneauمشاهده پروفایل

پژوهشگر

• Astrophysics
• Data Science
• Machine Learning
• +۶ مورد دیگر

Morgan Fouesneau is an Astrophysicist and Senior Data Scientist at the Max Planck Institute for Astronomy (MPIA), holding a tenure position since 2021. He leads the Astronomy Data Science Department, focusing on advancing data-driven approaches in astrophysics. His roles include supporting cutting-edge research, developing foundational coding skills, and fostering collaborations in data science. Education: PhD in Astrophysics, University of Strasbourg (2010) Master's in Astrophysics, University of Strasbourg (2007) Engineer degree in Fundamental Physics, Télécom Physique Strasbourg (2007) Research Interests: Fouesneau's work bridges astrophysics and data science, emphasizing large-scale data analysis (terabyte datasets), machine learning applications, and probabilistic modeling. Key areas include star formation in galaxies, Galactic structure, and cosmological context through chemical patterns. He contributes to major projects like Gaia and 4MOST, leading software development and parameter estimation. Recent Projects: Validation of Gaia astrophysical parameters (CU8 team) 4MOST classification pipeline development (4CP) Bayesian Extinction and Stellar Tool (BEAST) Labs/Teams: Part of the Data Science Group at MPIA, contributing to interdisciplinary collaborations in nuclear physics, solar weather, and organic solar cell modeling.

Anne Medlingمشاهده پروفایل

دانشیار

• Galaxy Evolution
• Black Hole Feedback
• Integral Field Spectroscopy
• +۱ مورد دیگر

Anne Medling is an Associate Professor specializing in galaxy evolution and black hole feedback. Her research combines multiwavelength observations with simulations to study AGN feedback mechanisms and star formation quenching. She previously worked at Australian National University and Caltech. Recent JWST observations focus on molecular gas excitation in luminous infrared galaxies and developing new classification systems for galactic power sources. She maintains strong involvement in the SAMI Galaxy Survey collaboration.

• Astrophysics
• Cosmology
• Galaxy Clustering
• +۲ مورد دیگر

Manolis Plionis is Professor in the Department of Physics at Aristotle University of Thessaloniki and Director of the National Observatory of Athens. His astrophysics research focuses on observational cosmology, galaxy clustering, and dark matter phenomena. Significant projects include leadership roles in PANGEA (Panhellenic Geophysical Observatory) and AEGIS–Center for Security & Hazard's Risk Resilience. He has received international recognition including a Pew Fellowship in Marine Conservation for interdisciplinary work. Recent publications analyze galactic structures using advanced telescope data and computational models. He serves on multiple international committees including the European Space Science Committee and IUCN advisory boards.

Laura DeGrootمشاهده پروفایل

استادیار

• Galaxy morphology
• Galaxy evolution
• Astrophysics
• +۱ مورد دیگر

Dr. Laura DeGroot is an Assistant Professor of Physics at the College of Wooster, specializing in extragalactic astronomy and observational cosmology. She earned her Ph.D. (2015) and M.S. (2011) from the University of California, Riverside, following a B.S. from Michigan State University (2009). Her research centers on galaxy morphology and evolutionary patterns, utilizing advanced telescopic data analysis techniques. She employs tools like GALFIT for decomposition studies of galactic structures across cosmic time, with particular interest in halo characterization and multi-component systems. Dr. DeGroot mentors significant undergraduate research through the College's Independent Study program, guiding projects on topics ranging from galactic structure analysis to dark matter distribution. Her recent publications contribute to major astrophysical surveys including HERON and CANDELS. Courses taught include First Year Seminar: Physics Revolutions, Astronomy of Stars and Galaxies, Classical Mechanics, and Astrophysics, emphasizing observational techniques and theoretical frameworks.

• AI-based Applications
• Computer Vision
• Environmental and Energy Domain
• +۴ مورد دیگر

Prof. Martin Melchior is a Professor at FHNW University of Applied Sciences, serving as Deputy Head of the Institute for Data Science. His primary roles include lecturing in Data Science and Computer Science, supervising thesis projects, and leading research in AI applications for computer vision, environmental energy systems, and astro-informatics. He holds a PhD in Physics from ETH Zurich and has extensive experience in risk modeling and space instrumentation projects. Education highlights include a PhD in theoretical polymer science (1993-1996) and studies in physics/mathematics at ETH Zurich (1986-1992). His research focuses on machine learning in astrophysics, cosmological surveys like Euclid, and large-scale data management for space missions. Key projects include contributions to the Euclid mission's ground segment and SwissPRODEX-funded operations. Recent research interests emphasize gravitational lensing analysis, galaxy clustering, and cosmological parameter estimation via Euclid data. He has led/co-led numerous applied science projects in energy optimization, medical diagnostics, and environmental monitoring technologies. His work bridges academia and industry through collaborations with institutions like EPFL, University of Geneva, and companies such as AINEAS GmbH and Swisens AG.

Eamonn Kerinsمشاهده پروفایل

استاد

• Exoplanet Detection
• Gravitational Microlensing
• SETI Strategies
• +۳ مورد دیگر

Eamonn Kerins is a Reader in Physics and Astronomy at the University of Manchester's School of Natural Sciences, part of the Jodrell Bank Centre for Astrophysics. He leads exoplanet research initiatives including the ESA Euclid Exoplanet Science Working Group and the NASA Roman Galactic Exoplanet Survey (RGES). His work focuses on microlensing techniques, space-based surveys (Roman/Euclid), and developing tools like TransitFit for exoplanet atmosphere analysis. He pioneered the Mutual Detectability SETI strategy, applying game theory to optimize alien civilization search targets. Research spans exoplanet demographics, free-floating planets, and exomoons discovery. He leads the SPEARNET network advancing exoplanet atmosphere characterization. His STFC-funded studies include K2 Campaign 9 microlensing surveys, discovering the first space-based exoplanet (K2-2016-BLG-0005Lb). He is also ESA-Appointed Scientist for Roman mission infrastructure design. Media engagement includes BBC Breakfast appearances discussing space news, stand-up comedy as the 'Jodrell Bank Alien', and science outreach. He teaches undergraduate courses on galaxies and astrophysics labs. His work bridges cutting-edge research with public engagement, emphasizing both technical excellence and accessible science communication.

• Observational Cosmology
• Cosmic Expansion Rate
• Dark Energy and Dark Matter
• +۷ مورد دیگر

Dr. Sherry H. Suyu is an Associate Professor at the Technical University of Munich (TUM) and a Max Planck Fellow at the Max Planck Institute for Astrophysics. Her research focuses on gravitational lensing applications for cosmology, particularly in measuring the cosmic expansion rate and studying dark energy/dark matter. She leads the HOLISMOKES program funded by an ERC Consolidator Grant. Her research group at TUM School of Natural Sciences Department of Physics investigates: Dark cosmos through gravitational lensing Supernova observations and Tidal Disruption Events Bayesian inference methods for astrophysical modeling Machine learning applications in lensed system analysis Scientific achievements include: 2021 Berkeley Prize from American Astronomical Society ERC Consolidator Grant for HOLISMOKES program Discovery of 330 high-quality lens candidates in Pan-STARRS survey She teaches courses including: Experimental Physics 1 (Winter 2024/5) Gravitational Lensing (Winter 2024/5) Introduction to Nuclear/Particle/Astrophysics (Summer 2025) The group includes 13 active members and 14 alumni across 7 institutions. Current work integrates HST and LSST imaging for next-generation lens discovery.

Joel Lejaمشاهده پروفایل

استادیار

• Galaxy Formation and Evolution
• Astrostatistics
• Machine Learning in Astrophysics
• +۳ مورد دیگر

Joel Leja is the Dr. Keiko Miwa Ross Early Career Assistant Professor in the Department of Astronomy and Astrophysics at The Pennsylvania State University, with a co-hire through the Institute for Computational & Data Sciences (ICDS) and the Institute for Gravitation and the Cosmos. His research focuses on galaxy formation and evolution, combining JWST observations with advanced statistical and machine learning techniques. He earned his Ph.D. from Yale University in 2016 and a B.A. in Physics and Astrophysics from UC Berkeley in 2010. Leja leads the RUBIES and Blue Jay surveys, analyzing JWST data to study high-redshift galaxies, including 'Little Red Dots' and AGN populations. His work integrates computational models like Prospector-α to interpret galaxy photometry and spectra. Notable contributions include resolving discrepancies in cosmic star formation rates and uncovering ancient stellar populations in early galaxies. Affiliations: ICDS Faculty Fellow, Institute for Gravitation and the Cosmos member Education: Ph.D. Yale University (2016), B.A. UC Berkeley (2010) Key Projects: UNCOVER Treasury Survey, JWST deep field analysis, Prospector Bayesian framework He has been recognized as a Clarivate Highly Cited Researcher (2023) and received the Yale Brouwer Prize (2019). His outreach efforts include reverse science fairs and public lectures, such as the 2024 Ashtekar Frontiers of Science talk on JWST discoveries.

Stefan M. Wildمشاهده پروفایل

استاد مدعو

• Numerical Optimization
• Machine Learning
• Scientific Computing
• +۳ مورد دیگر

Stefan M. Wild serves as Director of the Applied Mathematics and Computational Research (AMCR) Division and Senior Scientist at Lawrence Berkeley National Laboratory, while holding an adjunct faculty position in the Industrial Engineering and Management Sciences (IEMS) department at Northwestern University's McCormick School of Engineering. He also serves as a Senior Fellow at NAISE (Northwestern Initiative for AI and Society). Dr. Wild earned his Ph.D. and M.S. in Operations Research from Cornell University (2009, 2007) and his M.S. and B.S. in Applied Mathematics from the University of Colorado, Boulder (2003, 2002). His academic journey includes an Argonne Director's Postdoctoral Fellowship (2008-2010) and the DOE Computational Science Graduate Fellowship (2005-2008). His research program focuses on developing numerical optimization and automated learning algorithms for challenging science and engineering problems at interfaces involving computer simulations, complex data, and physical experiments. Dr. Wild leads multiple community software projects including BAND, parMOO, libEnsemble, deepHyper, NUCLEI, POptUS, and surmise, with applications spanning nuclear physics, materials science, and astrophysics. His work bridges derivative-free optimization, uncertainty quantification, high-performance computing, and scientific machine learning. Dr. Wild has advised numerous postdocs who have established successful careers at national laboratories and academic institutions. His editorial responsibilities include Mathematical Programming Computation, INFORMS Journal on Computing, Data Science in Science, and SIAM Review. U.S. Department of Energy Early Career Research Award (2020) STS Forum Future Leader (2018) IDC HPC Innovation Excellence Award (2015) SIAM SIGEST Award (2014) Strategic Laboratory Leadership Program (UChicago Booth School) (2013) DOE Computational Science Graduate Fellowship (2005-2008) As AMCR Division Director, he leads a diverse team of applied mathematicians, computational scientists, and software engineers addressing some of the world's most challenging computational problems across scientific and engineering disciplines. His leadership emphasizes both technical excellence and commitment to inclusion, diversity, equity, and accountability in scientific research.

Andrew Hopkinsمشاهده پروفایل

استاد

• Astronomy
• Astrophysics
• Star Formation in Galaxies
• +۳ مورد دیگر

Andrew Hopkins is a Professor of Astronomy at Macquarie University, affiliated with the School of Mathematical and Physical Sciences and the Astrophysics and Space Technologies Research Centre. He holds an MSc (Hons I) and PhD from the University of Sydney. His research focuses on the evolution of star formation in galaxies and cosmic history, with a focus on radio astronomy and galaxy dynamics. Research highlights include leadership in Australian astronomy, including roles as President of the Astronomical Society of Australia and Acting Director of the Australian Astronomical Observatory. Recipient of prestigious fellowships (Hubble Fellowship, ARC Queen Elizabeth II Fellowship) and awards for leadership and diversity advocacy. Research Interests His work spans radio astronomy, galactic evolution, supernova remnants, and machine learning applications in source classification. Key projects include the Evolutionary Map of the Universe (EMU) survey and the TAIPAN Spectrograph initiative. Awards & Recognition Hubble Fellowship Australian Research Council Queen Elizabeth II Fellowship 2013 AHRI Gender Equity Award Silver Pleiades Awards (2014, 2016) Grants & Leadership Lead investigator on multiple projects, including MQAAAstro (2020-2022), Starbugs commercialization (2019), and Subaru/ULTIMATE instrument design (2019-2020). Active in national astronomy committees and diversity initiatives.

Adrian Bilandمشاهده پروفایل

مدرس

• Particle Physics
• Astrophysics
• High-Energy Gamma-Ray Detection
• +۳ مورد دیگر

Prof. Dr. Adrian Biland is a Lecturer at the Department of Physics at ETH Zürich, specifically affiliated with the Institute for Particle and Astrophysics. His research focuses on high-energy astrophysics, including studies of blazars, dark matter, gamma-ray detection techniques, and cosmic-ray acceleration mechanisms. He contributes to major observatories like the MAGIC telescopes and the Cherenkov Telescope Array (CTA). Key research areas include multiwavelength observations of active galactic nuclei, supernova remnants, and transient phenomena. Biland collaborates on instrumental advancements such as data standardization and open-source analysis tools for gamma-ray telescopes. His work bridges particle physics and astrophysics, emphasizing observational methods and theoretical modeling of high-energy phenomena.

• Observational Cosmology
• Theoretical Cosmology
• Galaxy Evolution
• +۳ مورد دیگر

Enrique Gaztanaga is a Professor at the Institute of Cosmology & Gravitation within the Faculty of Technology at the University of Portsmouth. He also holds a Professorship at CSIC - Instituto de Ciencias del Espacio (ICE) from 2001 to 2033. His expertise spans cosmological models, large-scale structure (LSS) analysis, galaxy distribution, and CMB-galaxy cross-correlations. He has contributed to projects like DESI and PAU surveys, focusing on precision cosmology and novel data analysis techniques. Research Interests: Cosmological Parameter Estimation Baryon Acoustic Oscillations Galaxy Clustering Redshift Space Distortions Data Compression Techniques Awards: Freedom of the City of London (2024) Collaborations: Gaztanaga is part of the DESI collaboration, contributing to large-scale structure analysis and parameter compression methods. His work involves international teams and utilizes advanced simulation tools like Velocileptors and EZmock.