جست‌وجوی استاد و پژوهشگر

Paulina Łęska-Bayraktarمشاهده پروفایل

استادیار

• Syntax
• Comparative Linguistics
• Formal Semantics
• +۷ مورد دیگر

Paulina Łęska-Bayraktar is an Assistant Professor in the Department of English-Polish Comparative Linguistics at the Faculty of English, Adam Mickiewicz University in Poznań, where she conducts research and teaches in formal syntax and comparative linguistics. Her academic foundation is deeply rooted in the same institution, reflecting a sustained commitment to linguistic scholarship in Poland. Her educational background includes: B.A. in English Linguistics, Adam Mickiewicz University in Poznań (2012) M.A. in English Linguistics, Adam Mickiewicz University in Poznań (2014) Ph.D. in English Linguistics, Adam Mickiewicz University in Poznań (2019) Her research interests lie at the intersection of syntax, semantics, and cognitive grammar, with a strong focus on generative approaches to Slavic languages—particularly Polish. She investigates complex syntactic phenomena such as binding theory, pronoun distribution, quantifier scope, agreement, and the structure of relative and nominal clauses. Her work combines formal theoretical analysis with empirical data, often drawing on acceptability judgments and psycholinguistic methodologies. The trends in her recent publications reveal a sustained engagement with the syntax of Polish, especially in non-canonical constructions involving dative arguments, experiencers, and pronominal clusters. Her work contributes significantly to the understanding of how universal syntactic principles manifest in Slavic morphosyntax, and she frequently collaborates with leading scholars like Prof. Jacek Witkoś. She has received research funding from the Polish National Science Center through multiple grants, including OPUS, Beethoven, and Miniatura projects, which have supported her investigations into nominal expressions, pronouns, and anaphora in Polish. These grants underscore the national recognition of her research contributions. Paulina Łęska-Bayraktar actively participates in the international linguistics community, presenting her work at major conferences such as Formal Approaches to Slavic Linguistics (FASL), Formal Description of Slavic Languages (FDSL), and the Poznań Linguistic Meeting. She is also involved in collaborative research teams and has co-authored works with scholars from Humboldt-Universität zu Berlin and other institutions. Her academic presence is further strengthened by her profiles on ORCID and ResearchGate.

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۸ مورد دیگر

Katerina Fragkiadaki is the JPMorgan Chase Associate Professor of Computer Science in the Machine Learning Department at Carnegie Mellon University. She works at the intersection of Artificial Intelligence, Computer Vision, Machine Learning, Language Understanding, and Robotics. PhD from GRASP Lab, University of Pennsylvania Postdoctoral researcher at UC Berkeley (with Jitendra Malik) and Google Research Recipient of NSF CAREER, DARPA Young Investigator, Amazon, Google, Sony, UPMC, and AFOSR awards Organizer of CoRL 2023 Workshop on Generalist Robots ICLR 2024 Program Chair, multiple area chair roles Her research group focuses on developing machines that autonomously improve world models through human-environment interactions, with specific emphasis on: Representation learning and video understanding 2D/3D unified vision-language models Generative simulation and reinforcement learning Real2Sim/Sim2Real robot learning Continual learning and spatial common sense 3D scene reconstruction and dynamics Recent publications highlight advancements in: 3D mesh generation with compositional transformers Unified 2D/3D perception frameworks Physics-aware generative models Diffusion-based robotic manipulation policies Embodied agents with memory prompting Awards include: 2024: DARPA Young Investigator Award 2023: Amazon Faculty Award 2022: Sony Faculty Research Award 2021: UPMC Faculty Research Award 2020: NSF CAREER Award 2019: Google Faculty Award Key collaborations span institutions including UC Berkeley, Google Research, Stanford, MIT, and University of Tsukuba. Her work bridges theoretical innovation with practical applications in: Autonomous robot manipulation 4D world modeling Language-grounded perception Visual dynamics prediction Embodied program synthesis Physics-based simulation engines

Thomas Hartmanمشاهده پروفایل

استاد

• Quantum Gravity
• Quantum Field Theory
• String Theory
• +۴ مورد دیگر

Thomas Hartman is a Professor of Physics in the College of Arts and Sciences at Cornell University. He received his A.B. in Physics from Princeton University in 2004 and his Ph.D. in Physics from Harvard University in 2010. His professional journey includes being a Member of the School of Natural Sciences at the Institute for Advanced Study (2010-2013), Research Associate at the Kavli Institute for Theoretical Physics, UCSB (2013-2014), Assistant Professor at Cornell University (2014-2020), Associate Professor at Cornell University (2020-2022), and Professor at Cornell University (2022-present). Hartman's research focuses on theoretical aspects of quantum gravity and quantum field theory, with particular emphasis on black hole information and strongly interacting quantum fields. His work explores four major interconnected areas: gauge/gravity duality (examining how quantum field theory degrees of freedom organize into fluctuating spacetime), black hole information paradox (investigating the relationship between classical black hole solutions and quantum statistical systems), new approaches to quantum field theory using dualities and entanglement dynamics, and the physics of de Sitter space with implications for early universe cosmology. His research employs techniques from string theory, holographic duality, general relativity, and quantum information theory. Analysis of Hartman's publication record reveals a strong focus on resolving fundamental questions in quantum gravity, particularly through the development of replica wormhole techniques that address the black hole information paradox. His work spans both highly mathematical approaches to quantum gravity and connections to potentially observable phenomena, with increasing emphasis on connections between quantum information science and gravitational physics in recent years. Member, School of Natural Sciences, Institute for Advanced Study, 2010-2013 Hartman has advised graduate students including Jeevan Chandra Namburi and Wan Zhen Chua, contributing to the next generation of theoretical physicists. His research group actively investigates the emergence of spacetime from quantum information principles and develops new mathematical frameworks for understanding quantum gravity. The group maintains strong connections with other leading institutions through collaborative projects and participates in major theoretical physics initiatives including Snowmass planning for future research directions in high energy physics. Hartman's research program represents a vital bridge between abstract theoretical concepts in quantum gravity and potential experimental tests, working to develop frameworks that could ultimately connect quantum gravity to observable phenomena in both high-energy physics and cosmological observations.

Hidetoshi Katoriمشاهده پروفایل

استاد

• Physics
• Atomic Physics
• Quantum Optics
• +۴ مورد دیگر

Hidetoshi Katori is a Japanese physicist and Professor at the University of Tokyo , renowned for his pioneering work in optical lattice atomic clocks and quantum metrology . Since 2011, he has served as Chief Scientist at the Quantum Metrology Laboratory, RIKEN , advancing precision measurements and ground-breaking experiments in fundamental physics. Key Achievements : Invention of the Magic Wavelength Technique , enabling ultra-precise optical lattice clocks; measurement of gravitational redshift using transportable strontium clocks on Tokyo Skytree. Education : University of Tokyo (alma mater). Research Interests : Katori’s work spans atomic physics , quantum optics , and metrology , focusing on high-precision timekeeping, quantum state control, and testing general relativity via experimental physics. Publications highlight his contributions to optical clocks , quantum technologies , and precision measurement , with recent advancements in cryogenic lattice clocks and transportable clock systems. Scientific Awards : I. I. Rabi Award (2008) Asahi Prize (2012) Nishina Memorial Prize (2013) Medal with Purple Ribbon (2014) Japan Academy Prize (2015) Micius Quantum Prize (2020) Breakthrough Prize in Fundamental Physics (2022) Honda Prize (2022) Katori leads the Katori & Ushijima Laboratory at the University of Tokyo, collaborating on quantum metrology projects and mentoring researchers. His work has been recognized in the Asian Scientist 100 and through grants supporting advanced clock development.

Raquel Fernándezمشاهده پروفایل

استاد

• Computational Linguistics
• Dialogue Systems
• Cognitive Science
• +۳ مورد دیگر

Raquel Fernández is Full Professor of Computational Linguistics and Dialogue Systems at the University of Amsterdam, where she leads the Dialogue Modelling Group at the Institute for Logic, Language & Computation (ILLC). As Vice-Director for Research at ILLC and a Fellow of the ELLIS Society, she bridges computational linguistics, cognitive science, and artificial intelligence through her research on language use in multimodal and conversational contexts. PhD in Computational Linguistics from King's College London Prior research positions at University of Potsdam and Stanford University's CSLI Her work explores how cognitive constraints, social interaction, and perception shape language use, with a focus on: Visually-grounded language processing Multimodal dialogue modeling Model uncertainty and calibration Language grounding in multimodal data Language learning and semantic change Dialogue reference resolution Recent publications analyze multimodal reasoning limitations, cross-lingual knowledge consistency, and uncertainty modeling in dialogue systems. She has received multiple accolades including an ERC Consolidator Grant , NWO VENI/VIDI/Aspasia fellowships , and EMNLP/GenBench awards . Outstanding Paper Award (EMNLP 2023) Best Data Award (GenBench Workshop 2023) ELLIS Society Fellow ERC Consolidator Grant #819455 recipient NWO VENI/VIDI/Aspasia awardee As a leader in academic service, she serves on the SIGDAT Executive Committee and chairs multiple conference committees. Her lab develops models for multimodal dialogue, visual storytelling, and grounded language understanding.

Andre Wibisonoمشاهده پروفایل

استادیار

• Machine Learning
• Optimization
• Sampling
• +۴ مورد دیگر

Andre Wibisono serves as Assistant Professor in Yale University's Department of Computer Science with a secondary appointment in Statistics & Data Science, joining the faculty in 2021 after postdoctoral research at University of Wisconsin-Madison and Georgia Institute of Technology. His educational background includes: Ph.D. in Computer Science, UC Berkeley M.A. in Statistics, UC Berkeley M.Eng. in Computer Science, MIT S.B. in Mathematics and Computer Science, MIT Wibisono's research focuses on algorithm design for machine learning through optimization, sampling, and game theory , leveraging dynamical systems and information theory to develop accelerated discrete-time algorithms from continuous dynamics. His work provides theoretical foundations for efficient machine learning systems with applications in generative modeling and constrained optimization. Recent publications (2023-2025) demonstrate consistent innovation in Hamiltonian-based optimization , constrained-space sampling , and min-max game convergence , characterized by rigorous mathematical analysis connecting continuous dynamics to discrete algorithms. Key trends include randomized integration for acceleration, phi-divergence convergence guarantees, and symplectic geometry applications to mirror descent. Scientific recognition includes: NSF CAREER Award for developing algorithmic frameworks bridging continuous and discrete dynamics He actively mentors current students (Siddharth Mitra, Kaylee Yang, Jane Lee, Qiang Fu, Peter Wang) and has guided two postdocs to faculty positions. Research is funded through the NSF CAREER award and collaborative CIF grants focused on Hamiltonian dynamics for sampling and optimization. His Yale research group develops theoretical foundations for next-generation machine learning algorithms, emphasizing mathematical rigor in optimization and sampling with applications to generative modeling and constrained inference problems.

• Computational Imaging
• Artificial Intelligence
• Inverse Problems
• +۷ مورد دیگر

Aviad Levis is an Assistant Professor at the University of Toronto's Department of Computer Science, starting July 2024. He is affiliated with the Dunlap Astronomical Data Science and Technology Group (DADDAA) and collaborates with the Toronto Computational Imaging Group alongside Kyros Kutulakos and David Lindell. Previously, he was a postdoctoral researcher at Caltech's Computing + Mathematical Sciences department under Katherine Bouman, working with the Event Horizon Telescope (EHT) collaboration. PhD in Electrical Engineering from the Technion (supervised by Yoav Schechner) Research focuses on computational imaging tools at the intersection of AI and physics Develops algorithms for 3D tomography in both cloud physics and black hole imaging Recipient of ERC Synergy grant for CloudCT space mission His research spans two major domains: Computational Climate Imaging through cloud tomography to improve climate models, and Black Hole Imaging with the EHT collaboration. He pioneered methodologies for 3D cloud structure recovery using scattered sunlight and contributes to dynamic 3D reconstructions of black hole environments. Current interests include non-linear inverse problems, equation discovery from data, and ML-accelerated scientific simulations. Recent publications highlight advancements in atmospheric tomography and black hole emission modeling. His work on CloudCT involves coordinated nano-satellites for 3D cloud imaging, while EHT contributions include first images of Sagittarius A* (2022) and ongoing development of algorithms for 3D structure recovery. The ERC Synergy grant underscores his impact on climate imaging technology. Personal Website Work Email

• Autonomous Systems
• V2X Communication
• Cooperative Perception
• +۳ مورد دیگر

Dr. Mao Shan is a Senior Research Fellow at the Australian Centre for Robotics, part of The University of Sydney. He holds a PhD from The University of Sydney (2014) and has held research positions at Nanyang Technological University (2016-2017) and the Australian Centre for Robotics (2014-2016). His research focuses on autonomous systems, V2X communication, cooperative perception, and sensor fusion. Current students include Yaoqi HUANG, Henry LYU, Zhenxing MING, Nguyen TRAN, Tzu-yun TSENG, and Yupeng WANG. His work spans robotics, intelligent transportation systems, and control systems. Recent publications emphasize 3D object detection, cooperative perception frameworks, and autonomous navigation. He has contributed to the development of the University of Sydney Campus Dataset for robust autonomy testing and led cooperative perception projects funded by iMOVE CRC (2018). His research bridges theoretical advancements with practical applications in autonomous vehicles and multi-robot systems. Labs and affiliations include the Australian Centre for Robotics and the Intelligent Transport Systems Group. His interdisciplinary approach integrates probabilistic modeling, sensor fusion, and machine learning to address challenges in autonomous systems.

• Machine Learning
• Artificial Intelligence
• Combinatorial Optimization
• +۱۳ مورد دیگر

Yiming Yang is a Professor at the Language Technologies Institute and Machine Learning Department within the School of Computer Science at Carnegie Mellon University , where he has held faculty positions since 2003. His research spans foundational and applied aspects of machine learning , artificial intelligence , and scientific computing . Professor, Carnegie Mellon University (2003–Present) Associate Professor, Carnegie Mellon University (1996–2003) Yang's research focuses on LLM-based problem-solving agents , combinatorial optimization , and scalable oversight frameworks . His work explores diffusion models, Langevin dynamics, and Fourier neural operators for NP-hard problems, while advancing reinforcement learning techniques for self-play supervision and principle-driven fine-tuning of large language models. Recent publications highlight his contributions to code synthesis , PDE solving , and multi-agent reinforcement learning . Key methodologies include demonstration-guided control, retrieval-augmented reasoning, and test-time scaling laws. His team has developed frameworks like FEEDER for efficient in-context learning and μTransfer-FNO for zero-shot hyperparameter transfer in PDE solvers. Notable scientific achievements include: Best Student Paper Runner Up (2013) Best Theoretical Paper Award (1994) Best Theoretical Paper Award (1993) Yang has mentored over 20 PhD students and postdocs, including Shengyu Feng , Zhiqing Sun , and Aman Madaan , across domains like graph learning , extreme multi-label classification , and language model alignment .

Alvin J. K. Chuaمشاهده پروفایل

استادیار

• Gravitational-Wave Astronomy
• General Relativity
• Machine Learning for Science
• +۳ مورد دیگر

Dr. Alvin J. K. Chua is an Assistant Professor at the National University of Singapore (NUS) under the NUS Presidential Young Professorship. He holds a joint appointment in the Department of Mathematics and a courtesy appointment in the Department of Statistics and Data Science. His research focuses on gravitational-wave astronomy , particularly extreme mass ratio inspirals (EMRIs) as key sources for the LISA mission. He develops computational and statistical methods for modeling GW sources and analyzing detector data, with recent work on machine learning and Bayesian inference techniques. His selected publications highlight advancements in modeling beyond-vacuum-GR effects in EMRIs non-local parameter degeneracies rapid relativistic waveform generation neural networks for GW inference statistical sampling on manifolds These works span gravitational-wave astrophysics , computational relativity , and applied statistics . Scientific recognition includes the NUS Presidential Young Professorship. He collaborates with the LISA Consortium and the North American Nanohertz Observatory for Gravitational Waves (NANOGrav).

Lucien Hardyمشاهده پروفایل

استاد پژوهشی

• Quantum Foundations
• Theoretical Physics
• Quantum Gravity
• +۵ مورد دیگر

Lucien Hardy is a Research Professor at the Perimeter Institute for Theoretical Physics, focusing on Quantum Foundations. He holds a PhD from Durham University (1992) under Euan J. Squires. His research spans operational approaches to Quantum Theory, Quantum Gravity, and General Relativity, emphasizing frameworks like the causaloid and duotensor formalisms. Hardy introduced concepts such as indefinite causal structure and the Quantum Equivalence Principle, aiming to unify quantum theory with gravity. He has also explored experimental tests involving human decision-making in Bell experiments. Key contributions include Hardy's theorem (1992) and axiomatic reconstructions of Quantum Theory (2001). Education: PhD in Mathematical Physics, Durham University, 1992 Research Interests: Operational formulations of Quantum Theory and General Relativity Indefinite causal structures and quantum gravity Time symmetry in operational theories Causaloid and diagrammatic calculus frameworks Quantum foundations experiments (e.g., human-involving Bell tests) Awards & Fellowships: Royal Society University Research Fellow, 1997–2002 Royal Society Postdoctoral Fellow, 1993–1994 Grants: Quantum Information Structure of Spacetime (QISS) Grant, John Templeton Foundation (2019–2025) NSERC Discovery Grant, 2020 Labs/Teams: Core researcher in the Quantum Foundations group at Perimeter Institute, contributing to theoretical frameworks and experimental proposals.

Eleonora Di Valentinoمشاهده پروفایل

پژوهشگر ارشد

• Cosmology
• Dark Energy
• Dark Matter
• +۳ مورد دیگر

Dr. Eleonora Di Valentino is a Senior Research Fellow at the University of Sheffield's School of Mathematical and Physical Sciences, specializing in cosmology and fundamental physics. Her research focuses on resolving cosmological tensions, particularly the Hubble constant discrepancy, by exploring dynamical dark energy models, dark matter interactions, and cosmic microwave background (CMB) anomalies. She leads analyses combining cutting-edge datasets like DESI BAO and gravitational wave observations to probe the universe's evolution. Key research interests include: Interacting dark energy models and their observational signatures CMB anisotropies and their implications for early universe physics Neutrino mass constraints and dark matter thermodynamics Modified gravity approaches to cosmological tensions Multimessenger cosmology using BAO and gravitational wave data Her work highlights trends in addressing the Hubble tension via late-time dark sector interactions and non-standard dark matter behavior. She actively contributes to collaborative projects like the CosmoVerse initiative and the Dark Energy Survey (DES). Dr. Di Valentino's research group affiliation is the Cosmology, Relativity, and Gravitation (CRAG) group, where she develops novel methodologies for cosmological parameter estimation and model testing.

• Gravitational Wave Data Analysis
• Cosmological Parameter Estimation
• LISA Data Analysis
• +۳ مورد دیگر

Dr. Jonathan Gair is a Group Leader in the Astrophysical and Cosmological Relativity Division at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute) in Potsdam, Germany. Previously, he served as Professor of Astrostatistics at the University of Edinburgh (2018-2019) and as Reader (Associate Professor) in Statistics at the same institution (2015-2018). Dr. Gair's research focuses on gravitational wave data analysis and its applications to cosmology and fundamental physics. His work spans multiple areas of gravitational wave astronomy, with particular emphasis on: Developing and applying new methodologies for gravitational wave data analysis Using gravitational wave observations to derive cosmological parameters, particularly the Hubble constant Developing data analysis tools for the LISA space-based gravitational wave detector Exploring the scientific potential of gravitational wave observations for testing general relativity Creating computationally efficient techniques for parameter inference in gravitational wave astronomy Dr. Gair plays a leading role within the LIGO/Virgo collaboration in deriving cosmological constraints from gravitational wave observations. He currently chairs the LISA Science Group, overseeing the development of data analysis tools for the planned ESA-led LISA mission. His research has significantly contributed to our understanding of how gravitational wave observations can serve as "standard sirens" for measuring cosmic distances and probing the expansion history of the universe. Dr. Gair's work involves both theoretical development and practical application of data analysis techniques. He has developed methods for handling selection effects in rate estimation of gravitational wave events, techniques for mapping gravitational wave backgrounds using methods adapted from cosmic microwave background analysis, and approaches for incorporating model uncertainties into gravitational wave parameter estimation.

Kent Yagiمشاهده پروفایل

دانشیار

• Theoretical Astrophysics
• Gravity and Cosmology
• Gravitational Physics
• +۶ مورد دیگر

Kent Yagi is an Associate Professor in the Physics Department at the University of Virginia, specializing in theoretical astrophysics, gravity, and cosmology. His research focuses on using gravitational waves from compact objects like black holes and neutron stars to probe fundamental physics, including testing General Relativity in strong-field regimes and determining the equation of state of nuclear matter. Position: Associate Professor (2023-present), previously Assistant Professor (2017-2023) Education: Ph.D. in Physics from Kyoto University (2012) Prior positions: Postdoctoral Research Scholar at Princeton University (2015-2017), Postdoctoral Research Associate at Montana State University (2012-2015) Yagi's research centers on theoretical modeling of neutron stars and gravitational wave physics. He is particularly known for discovering the 'I-Love-Q' universal relations among neutron star observables that are insensitive to the equation of state. His work enables testing strong-field gravity and probing nuclear physics through gravitational wave observations. He also investigates binary pulsar systems as precision laboratories for testing gravitational theories beyond General Relativity. His research has significant implications for multi-messenger astronomy, connecting gravitational wave observations with electromagnetic counterparts to extract fundamental physics. The field has evolved rapidly since the first gravitational wave detection in 2015, and Yagi's theoretical predictions have helped shape how we interpret these observations to test gravity and nuclear physics in extreme conditions. NSF CAREER Award (2023) Sloan Research Fellowship (2019) IUPAP Young Scientist Prize (2019) Mead Honored Faculty (2018-2019) Yagi leads an active research group at UVA with multiple graduate and undergraduate students. His group collaborates with researchers across departments, including high energy physicists, nuclear physicists, astronomers, and researchers at the National Radio Astronomy Observatory. Current research directions include multi-band gravitational wave tests of general relativity, constraining nuclear matter parameters with GW170817, and developing parameterized post-Einsteinian gravitational waveform models for various modified gravity theories. The group has received multiple student research fellowships and awards, demonstrating strong mentorship and training of the next generation of physicists.

Daniel Holzمشاهده پروفایل

استاد

• Gravitational Wave Astrophysics
• Cosmology
• Black Holes
• +۳ مورد دیگر

Daniel Holz is a Professor of Physics and Astronomy & Astrophysics at the University of Chicago, affiliated with the Enrico Fermi Institute, Kavli Institute for Cosmological Physics, and the College. His research focuses on gravitational wave astrophysics, cosmology, and black hole dynamics, contributing to major discoveries like GW150914 and GW170817 as part of the LIGO collaboration. He holds a BA from Princeton and a PhD from the University of Chicago, with postdoctoral fellowships at the Albert Einstein Institute (Germany), Kavli Institutes in Santa Barbara and Chicago, and a Richard Feynman Fellowship at Los Alamos National Laboratory. Research interests include gravitational-wave standard sirens for cosmology, black hole-neutron star mergers, and testing general relativity. Awards include the NSF CAREER Award, Quantrell Teaching Award, and Breakthrough/Gruber Prizes (via LIGO). He chairs the Bulletin of the Atomic Scientists' Science and Security Board, guiding the Doomsday Clock, and directs the UChicago Existential Risk Laboratory (XLab), addressing nuclear, climate, and AI risks. His lab and collaborations leverage multi-messenger astronomy and advanced data analysis techniques. Notable contributions include pioneering gravitational-wave cosmology methods and advancing understanding of cosmic expansion tensions.