جست‌وجوی استاد و پژوهشگر

Andrew Huddlestonمشاهده پروفایل

استاد

• Post-Kantian Philosophy
• Nietzsche Studies
• Aesthetics
• +۶ مورد دیگر

Andrew Huddleston is Professor of Philosophy and Director of the Centre for Research in Post-Kantian Philosophy at the University of Warwick. He previously taught at Birkbeck College, University of London and Exeter College, Oxford. He holds a PhD from Princeton University. His research focuses on post-Kantian philosophy (Nietzsche, German Idealism, Romanticism) and intersects with aesthetics, social philosophy, and ethics. His 2019 monograph, Nietzsche on the Decadence and Flourishing of Culture , challenges individualist interpretations of Nietzsche, arguing for a more socially-oriented understanding of cultural flourishing. Current work explores the 'Religion of Art' concept in European thought, examining art's role as a religious substitute in a secular age. Education: BA from Brown University and Pembroke College, Cambridge; PhD from Princeton University (supervised by Alexander Nehamas). Research trends in recent articles emphasize Nietzschean moral psychology (ressentiment), narratives of cultural decadence, and the interplay between aesthetics and existential concerns. His work also engages with Adorno's critical theory and Hegel's philosophy of comedy. Editorial roles include serving as Book Reviews Editor for European Journal of Philosophy , Editorial Board member of British Journal for the History of Philosophy , and area editor for Ergo . He is also Treasurer of the Royal Musical Association Music & Philosophy Study Group. Teaching responsibilities include modules on Nietzsche's Beyond Good and Evil , the 'Religion of Art' in post-Kantian philosophy, and convening the MA in Continental Philosophy.

Stephen Broadمشاهده پروفایل

استاد

• Historical Musicology
• Music Education
• Music Practice in Scotland
• +۳ مورد دیگر

Professor Stephen Broad is a musicologist and educator serving as Director of Research and Knowledge Exchange at the Royal Conservatoire of Scotland. He holds a DPhil from the University of Oxford and has extensive experience in historical musicology, music education, and policy development. His research focuses on Olivier Messiaen, 1930s French music culture, and music practice in Scotland. Broad has authored/co-authored influential reports like What’s Going On? , which informed the Scottish Youth Music Initiative, and chairs the European Platform for Artistic Research in Music (EPARM). Education: DPhil in Historical Musicology, University of Oxford (2001) MA in Music and Physics, University of Glasgow (1997) Research Interests: Historical Musicology: Messiaen’s early career, French musical traditions, and music historiography Music Education: Pedagogy in diverse contexts, policy development, and workforce training Practice-Based Research: Philosophical frameworks and interdisciplinary methodologies Awards & Roles: External Examiner at Royal Academy of Music, Royal College of Music, and others Editorial boards for Music Education Research and Practice-Based Research Journal Recipient of grants including the Scottish Government’s £1m Musical Instrument Fund Advising & Grants: Supervised over 10 doctoral projects in musicology, performance, and education Contributed to policy initiatives like Creative Scotland’s music development programs Labs/Teams: Leads the Sciences, Humanities and Arts Research Exchange (SHARE) and chairs EPARM, fostering international collaboration in artistic research.

Yizhou Sunمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Graph Neural Networks
• +۳ مورد دیگر

Professor Yizhou Sun is affiliated with the University of California Los Angeles (UCLA) and the Henry Samueli School of Engineering and Applied Science . Her academic work focuses on Machine Learning , Artificial Intelligence , and Graph Neural Networks within the Computer Science department. Her research spans High-Level Synthesis , Causal Inference , and Computational Biology , with recent publications addressing neural network compression, language model safety, and dynamical system modeling. The trends in her recent 2025 and 2024 publications emphasize Deep Learning , Graph Theory , and Language Model Optimization , reflecting interdisciplinary applications in Biomedical Data , Hardware Design , and Physical Simulation .

Aaron Schurgerمشاهده پروفایل

استادیار

• Neuroscience
• Cognitive Neuroscience
• Consciousness Studies
• +۳ مورد دیگر

Dr. Aaron Schurger is an Assistant Professor in the Psychology Department at Chapman University’s Crean College of Health and Behavioral Sciences. He is also a member of the Institute for Interdisciplinary Brain and Behavioral Sciences. Schurger holds a BA from Indiana University, and MA and PhD from Princeton University. His research focuses on the neuroscience of volition, consciousness, and decision-making, particularly exploring the readiness potential (RP) and its implications for free will debates. His work challenges classical interpretations of the RP using computational models, suggesting it reflects stochastic neural processes rather than preconscious decisions. Recent contributions include studies on the origins of the RP in spiking neural networks, critiques of causal structure theories of consciousness, and interdisciplinary analyses of free will. His findings emphasize that the RP may not indicate preconscious decision-making but instead arise from natural neural fluctuations during decision thresholds. Schurger collaborates across neuroscience, philosophy, and cognitive science, contributing to debates on consciousness, action initiation, and neural correlates of subjective experience. His research also addresses methodological rigor in studying unconscious processing and integrates computational models with empirical data, as seen in studies on movement timing and neural stability during perception. While no specific grants or labs are explicitly listed, his affiliations suggest involvement in interdisciplinary projects at Chapman.

Johanna Ziegelمشاهده پروفایل

استاد

• Statistical Forecasting
• Probability Theory
• Financial Risk Management
• +۳ مورد دیگر

Johanna Ziegel is a Professor of Statistics at ETH Zurich, Switzerland, since 2024, and a Visiting Scientist at the Heidelberg Institute for Theoretical Studies (HITS). Previously, she held positions at the University of Bern, where she was promoted to Full Professor in 2023. Her research focuses on decision-theoretically sound methods for forecast evaluation, probabilistic forecasting, risk measures in finance, and applications in meteorology, medicine, and climate science. She is actively involved in editorial roles for journals like Bernoulli , JASA: Theory & Methods , and SIAM Journal on Financial Mathematics . Education: PhD in Stereological Analysis of Spatial Structures from ETH Zurich (2010), supervised by Paul Embrechts and Eva B. Vedel Jensen. Postdoctoral research at the University of Melbourne and Heidelberg University. Research Interests: Forecast evaluation, elicitable functionals, risk measures, isotonic regression, statistical calibration, and applications in finance, climate science, and biostatistics. Her work bridges theoretical statistics with practical challenges in uncertainty quantification and decision-making under uncertainty. Advising & Collaborations: Supervised 7 PhD students and mentored several postdocs. Collaborates with the Computational Statistics group at HITS and the Oeschger Centre for Climate Change Research. Her group explores distributional regression under order constraints and novel methods for forecast comparison. Recognition: Credit Suisse Award for Best Teaching (2022), H.I.T. Program for Academic Leadership (2021–2022). Active in professional service, including the Bernoulli Society Council and editorial boards.

Junier Olivaمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Nonparametric Statistics
• +۸ مورد دیگر

Junier Oliva is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill and Lead Faculty of the Master of Applied Data Science program. His research focuses on machine learning, artificial intelligence, and nonparametric statistics, particularly in high-dimensional density estimation, sequential modeling, and learning from complex/structured data. He holds a B.S., M.S., and Ph.D. in Computer Science from Carnegie Mellon University, with prior industry experience at Yahoo! and Uber ATG. Research Interests: Machine learning, artificial intelligence, nonparametric statistics, deep learning, statistical data mining, signal processing, kernel methods, and scalability. His work bridges machine and human learning via collective approaches, emphasizing simple yet flexible models for massive datasets. Awards/Grants: $592K AIM-AHEAD/NIH Grant for Human+AI Collaboration $594K NSF Grant for Scientific Discovery $500K NSF Grant for 'Machine Detectives' Project ACM BCB Best Paper Award (2022) for transparent single-cell classification work Labs/Teams: Director of the LUPA Lab, which develops machine learning techniques for holistic data understanding across domains like healthcare, earth science, and computer vision.

Oded Regevمشاهده پروفایل

استاد

• Theoretical Computer Science
• Lattice-based Cryptography
• Quantum Computation
• +۳ مورد دیگر

Oded Regev is a Silver Professor at the Courant Institute of Mathematical Sciences, New York University. He has previously held positions at Tel Aviv University and École Normale Supérieure, Paris (CNRS). His research spans theoretical computer science, cryptography, quantum computation, and machine learning applications in biological discovery. Education: PhD in Computer Science, Tel Aviv University (2001) Regev is renowned for his work in lattice-based cryptography, including the introduction of the Learning With Errors (LWE) problem and Gaussian measures. He also leads research using interpretable machine learning to decode RNA splicing logic and nuclear speckle dynamics, with implications in disease and therapeutics. His recent articles focus on quantum factoring, RNA localization, and geometric lattice bounds. Scientific Awards: European Research Council (ERC) Starting Grant (2008) 2018 Gödel Prize 2019 Simons Investigator Award Best Paper Awards: STOC 2003, Eurocrypt 2006 Regev mentors students and postdocs in both theoretical computer science and computational biology. His lab has secured funding from NSF, NIH, and Additional Ventures. He co-founded the TCS+ online seminar series and serves as Associate Editor-in-Chief for Theory of Computing .

Attila Balázsمشاهده پروفایل

مدرس

• Geophysics
• Tectonics
• Sedimentary Geology
• +۵ مورد دیگر

Dr. Attila Balázs is a Senior Researcher and Lecturer at ETH Zurich's Institute of Geophysics, affiliated with the Department of Earth and Planetary Sciences. His research integrates numerical modeling with geological data to investigate tectonic-surface process interactions, focusing on orogen-basin systems and continental deformation. Key contributions include studies on back-arc basins, transform faults, and the Tibetan Plateau's uplift mechanisms. He holds the 2020 Flinn-Hart Award and an ETH Zurich Postdoctoral Fellowship. His work emphasizes geodynamic processes such as mantle delamination, slab dynamics, and crustal deformation patterns. Balázs collaborates with the Geophysical Fluid Dynamics Group and maintains an active research portfolio spanning field observations, seismic analysis, and 3D numerical simulations. Research Foci: Tectonic modeling, basin evolution, mantle dynamics, and crustal rheology Key Regions: Pannonian Basin, Tibetan Plateau, Adriatic Sea, Himalayas His articles highlight interdisciplinary approaches to understanding continental and oceanic tectonics, with recent emphasis on transform fault mechanics, triple junction dynamics, and the interplay between tectonics and climate.

Fattane Zarrinkalamمشاهده پروفایل

استادیار

• Social Media Mining
• Semantic Technologies
• User Modeling
• +۶ مورد دیگر

Fattane Zarrinkalam is an Assistant Professor in the School of Engineering at the University of Guelph. She holds a PhD from Ferdowsi University of Mashhad, Iran, and completed a Postdoctoral Research Fellowship at Ryerson University (2018–2020). Her research focuses on social media mining, semantic technologies, and user modeling, with applications in healthcare, legal tech, and e-commerce. She is a Vector Institute Postgraduate Affiliate and serves on editorial boards for journals like Information Processing & Management and IEEE Transactions on Network Science and Engineering . Her work emphasizes actionable insights from social data, including sarcasm detection, user interest prediction, and fairness in social media analytics. Zarrinkalam has contributed to over 30 peer-reviewed publications and holds multiple patents in data analysis and social media sentiment modeling. Education: PhD, Ferdowsi University of Mashhad, Iran Postdoctoral Fellowship, Ryerson University Research Scientist, Thomson Reuters Labs Research Interests: Semantic interpretation of social content User modeling via temporal analysis Social good applications (e.g., mental health, telecommunication) Fairness in social media mining Recent Work Trends: Her articles span network representation learning, dynamic user interest prediction, and interdisciplinary applications. Notable themes include neural networks for sarcasm detection, heterogeneous graph embeddings, and leveraging Twitter data for psychological insights. Awards & Service: Co-chair, International Workshop on Mining Actionable Insights from Social Networks (MAISoN) Editorial board roles for top journals Labs & Teams: Involved in interdisciplinary collaborations at the Vector Institute and partnerships with industry on legal tech and social analytics projects.

• Machine Learning
• Natural Language Processing
• Computational Linguistics
• +۳ مورد دیگر

Jordan Boyd-Graber is a Full Professor at the University of Maryland, affiliated with the Department of Computer Science and the University of Maryland Institute for Advanced Computer Studies (UMIACS). His research focuses on machine learning, natural language processing, computational linguistics, topic models, and question answering. He has made significant contributions to the development of interactive topic modeling systems and evaluations of large language models. His work often bridges theoretical advancements with practical applications, such as improving human-AI collaboration and enhancing the interpretability of machine learning models. Boyd-Graber’s research also addresses challenges in adversarial examples, calibration of models, and the ethical implications of AI systems. His recent publications span cutting-edge topics like evaluating topic models through ProxAnn, mitigating hallucinations in vision-language models, and exploring human-AI complementarity in question answering. He collaborates extensively with researchers in computer science, linguistics, and social sciences to advance interdisciplinary applications of NLP and ML.

Loris D'Antoniمشاهده پروفایل

دانشیار

• Programming Languages
• Software Verification
• Program Synthesis
• +۴ مورد دیگر

Loris D'Antoni is an Associate Professor in the Department of Computer Science and Engineering at the University of California at San Diego (UCSD) . He is also a Visiting Academic at Amazon Web Services (AWS) . His research focuses on helping people write trustworthy software through techniques in program synthesis, formal verification, and machine learning robustness. Bachelor and Master in Computer Science from University of Torino (2008, 2010) PhD in Computer Science from University of Pennsylvania (2015) His research integrates programming languages , automata theory , and formal methods to ensure software reliability. Recent work explores semantics-guided synthesis and specification-aligned LLMs , with applications in network security, machine learning fairness, and automated code repair. Key trends in his publications include program synthesis , formal verification , and trustworthy AI systems . He has contributed to tools like AutomataTutor and SemGuS , a framework for customizable synthesis problems using constrained Horn clauses. Phillip R. Certain-Gary D. Sandefur Distinguished Faculty Award NSF CAREER Award Microsoft Research Faculty Fellowship Google and Facebook Faculty Awards Best Paper Award at ICDCN 2023 Distinguished Paper Award at SBES 2021 D'Antoni actively contributes to academic community service as a committee member in PLDI , OOPSLA , POPL , and CAV . He leads the Programming Systems Group at UCSD and collaborates with SemGuS research team on synthesis frameworks.

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Maciej Zięba is an academic researcher affiliated with the Faculty of Information and Communication Technology at Wrocław University of Science and Technology, specifically within the Department of Artificial Intelligence . His work spans machine learning, deep learning, and computer vision, with a focus on hyperspectral imaging, autonomous systems, and 3D modeling. Recent research includes uncertainty-aware sensor deployment for autonomous vehicles, low-light image enhancement algorithms, and probabilistic regression frameworks for tabular data. He has co-authored publications on flow-based models, hypernetworks, and neural radiance fields (NeRF) applied to 3D face rendering. Contact: maciej.zieba@pwr.edu.pl

• Observational cosmology
• Galactic astronomy
• Exoplanet science
• +۵ مورد دیگر

David W. Hogg is Professor of Physics and Data Science in the Center for Cosmology and Particle Physics in the Department of Physics at New York University. He serves as Senior Research Scientist in the Astronomical Data Group in the Center for Computational Astrophysics of the Flatiron Institute and maintains an affiliation with the Max-Planck-Institut für Astronomie in Heidelberg. His primary research focuses on observational cosmology, particularly approaches that use galaxies to infer physical properties of the Universe. He also conducts significant research on stellar kinematics in the Milky Way and the measurement and discovery of exoplanets. Across all domains, Hogg develops engineering systems and statistical methodologies that enable large-scale astrophysical projects for both his research group and the broader community. Recent work demonstrates expertise in robust statistical methods, particularly dimensionality reduction techniques like Robust-HMF. His research bridges theoretical statistics with practical applications in major astronomical surveys including Gaia, SDSS-V, and SPHEREx. He frequently explores connections between Bayesian and frequentist approaches to astronomical data analysis, with recent work on nuisance parameter integration, anomaly detection, and robust matrix factorization. Research supported by NYU, NASA, NSF, Moore Foundation, Sloan Foundation Additional support from Max Planck Society, Humboldt Foundation, ERC, Simons Foundation Hogg is actively involved in major astronomical projects including Astrometry.net, Gaia, and SDSS, with long-term comprehensive goals of analyzing all galaxies, stars, and astronomical images. His work emphasizes open science principles, reproducible research practices, and the development of publicly accessible tools for the astronomical community.

Mariya Tonevaمشاهده پروفایل

پژوهشگر

• Machine Learning
• Natural Language Processing
• Neuroscience
• +۵ مورد دیگر

Mariya Toneva is a tenure-track faculty member at the Max Planck Institute for Software Systems , conducting groundbreaking research at the intersection of Machine Learning , Natural Language Processing , and Neuroscience . She leads the Bridging AI and Neuroscience (BrAIN) group , focusing on computational models that align AI systems with human brain processes. Her work aims to enhance both AI capabilities and neuroscience understanding through this cross-disciplinary approach. Actively recruiting postdocs, PhDs, and research interns in areas like code/text representation, brain-AI alignment, and neuroimaging data analysis Collaborator on NIH-funded projects using fMRI and neuropixel data Research Themes : Her group explores neural mechanisms of language processing, event segmentation in narratives, memory reactivation via music, and effective human-AI collaboration frameworks. Key methods include LLM analysis, cross-modal similarity metrics, and naturalistic task-based fMRI studies. Key Publications (2024-2025): Brain-tuned speech models (INTERSPEECH 2025) Cognitive event boundaries in LLMs (Behavioral Research Methods 2025) Music-induced memory reactivation (biorxiv 2024) LLM-brain alignment reasons (EMNLP 2024) Advising : Mentors PhD candidates Omer Moussa (speech processing), Camila Kolling (representational similarity), and Gabriele Merlin (LLM alignment). Collaborates with institutions like MIT, NYU, and ETH Zurich.

Karina Gibertمشاهده پروفایل

استاد

• Data Science
• Artificial Intelligence
• Ethics in AI
• +۷ مورد دیگر

Karina Gibert is a Full Professor at Universitat Politècnica de Catalunya (UPC), specifically at the Faculty of Computer Science of Barcelona (FIB) in the Department of Statistics and Operations Research. With a permanent teaching position since 1990, she contributes to research and education with a focus on Data Science, Artificial Intelligence, Explainable AI, and Ethics in AI. Full Professor, UPC (since 1990) PhD in Informatics Engineering Postgraduate in Higher Education Teaching Director and co-founder of IDEAI research center Dean of the Official Professional College on Informatics Engineering of Catalonia Active in bridging the gender gap in STEAM through multiple initiatives Her research focuses on extracting strategic knowledge from data and intelligent systems with ethical and explainable perspectives. She has led various projects including Diet4You for personalized diets, INSESS-COVID19 for social vulnerability analysis, Top Rosies Talent for female AI development, and ciutadanIA for AI culture promotion. Her work spans health, environment, sustainability, tourism, and social technology applications. As an editor of Environmental Modeling and Software journal and active academic, she contributes to international conferences, working groups, and research collaborations. Her service includes membership on various ethics and AI strategy committees and advisory boards. Women Tech Award 2023 National Informatics Engineering Award in Digital Dissemination 2022 Ada Byron Award 2022 Honorific Mention of Creu Casas award 2021 donaTIC 2018 Award Finalist at AMETIC Awards 2021 Finalist of European Social Services Awards 2021