جست‌وجوی استاد و پژوهشگر

Rajeev Tyagiمشاهده پروفایل

استاد

• Competitive Marketing Strategies
• Distribution Channels
• New Products
• +۷ مورد دیگر

Rajeev Tyagi is a Professor of Marketing and holds the Walter B. Gerken Chair in Enterprise and Society at the Paul Merage School of Business, University of California, Irvine. He has been a faculty member since 1996, progressing from Assistant Professor to full Professor, and has held significant leadership roles including Interim Dean and Senior Associate Dean for Academic Affairs. PhD, MA, Marketing – The Wharton School, University of Pennsylvania (1996) MBA – Indian Institute of Management, Calcutta (1992) BE, Electronics Engineering – National Institute of Technology, Surat (1988) His research focuses on the economics of marketing strategy, particularly competitive marketing strategies, distribution channels, and new product introduction. He develops quantitative and game-theoretic models to analyze strategic interactions in markets. His work spans pricing, product positioning, channel design, and consumer welfare implications of technological change. His recent publications in Marketing Science , Management Science , and Journal of Marketing Research reflect a consistent focus on strategic decision-making in competitive environments. Key themes include bundling of time-sensitive events, channel decentralization benefits, pricing under uncertainty, and the impact of entry on market dynamics. His research often reveals counterintuitive outcomes, such as how technological advances can reduce consumer surplus or how entry can soften competition through strategic differentiation. Multiple school- and university-wide awards for excellence in teaching Rajeev Tyagi teaches courses at the PhD, MBA, and Master’s levels, including Marketing Analytics, Marketing Strategies in High-Tech Markets, New Product Development, Business Economics, and Multivariate Statistics. While specific advisees are not listed, his extensive publication record with co-authors suggests active mentorship and collaboration. His research has been supported by his academic appointments and institutional affiliations, with no external grants explicitly mentioned. He maintains an active research agenda, with publications as recent as 2022, indicating ongoing scholarly contributions. His work bridges theoretical rigor with practical implications for marketing and strategy.

• Computational Linguistics
• Natural Language Processing
• Natural Language Generation
• +۵ مورد دیگر

Leo Wanner is a prominent Professor at Universitat Pompeu Fabra's Department of Information and Communication Technologies, specializing in Natural Language Processing. With a research career spanning over three decades, he has made significant contributions to computational linguistics, particularly in natural language generation, collocations, and hate speech detection. He has served as editor for multiple editions of the International Conference on Computational Linguistics (COLING) including the 2025 edition. Wanner's research interests encompass a wide range of topics in computational linguistics, with recent work focusing on hate speech detection, multilingual processing, and the capabilities of large language models. His work bridges theoretical linguistics with practical applications, addressing challenges in lexical semantics, syntax, and discourse analysis. Notably, he has pioneered research in collocation processing and has contributed to the development of frameworks for analyzing thematic progression in texts. His publication record demonstrates consistent productivity with significant contributions across multiple subfields. Recent work shows a strong focus on contemporary challenges in NLP, particularly hate speech detection and the capabilities of large language models. His research often takes a multilingual perspective, addressing challenges across different language families including Romance and Slavic languages. Wanner has led significant research projects including the development of FORGe, a multilingual deep sentence generator based on the Meaning-Text Theory, which achieved top performance in the WebNLG challenge. His work on multilingual surface realization has established important benchmarks in the field through shared tasks that have engaged researchers worldwide. As an academic leader, Wanner has mentored numerous researchers and contributed to building research infrastructure through corpus development and annotation schema design. His work on collocation resources, thematic progression analysis, and hate speech detection frameworks has provided valuable resources for the broader NLP community.

• Graph Representation Learning
• Deep Learning
• Reinforcement Learning
• +۷ مورد دیگر

Jian Tang is an Assistant Professor at HEC Montreal and the Montreal Institute for Learning Algorithms (MILA), as well as an Associate Professor at the Department of Computer Science and Operations Research (DIRO) at Université de Montréal. He is also affiliated with IVADO (Institut de valorisation des données) as a member. His research spans multiple institutions including collaborations with leading biology labs worldwide and access to extensive computational resources through industry partners. Ph.D. in Computer Science, Peking University (2009-2014) Visiting Ph.D. student, University of Michigan (2011.10-2013.8) B.S. in Mathematics, Beijing Normal University (2005-2009) Professor Tang's research focuses on the intersection of deep learning and graph theory, with particular emphasis on geometric deep learning, knowledge graph reasoning, and applications in drug discovery. His work bridges symbolic and neural approaches to create robust reasoning systems that can handle complex structured data. He has pioneered techniques in graph representation learning that have significantly advanced the field of molecular property prediction and protein design. His publication record shows a clear trajectory toward applying geometric deep learning to biological problems, with a growing emphasis on protein design, molecular conformation generation, and multi-omics analysis. Recent work demonstrates sophisticated integration of 3D geometry with deep learning architectures to model complex biomolecular interactions. Canada CIFAR Artificial Intelligence Chairs (CCAI Chair) Tencent AI Lab Rhino-Bird Gift Fund Amazon Faculty Research Award Microsoft-Mila collaboration grant National Research Council Canada (NRC) Collaborative Research and Development Grant Professor Tang actively mentors doctoral and master's students, with six recent graduates working on cutting-edge topics including graph neural networks for reasoning, protein design, and molecular representation learning. His research is supported by substantial funding from industry partners including Microsoft, Amazon, and Tencent, as well as government agencies like NRC. He collaborates extensively with biology labs worldwide, applying AI to solve real-world biomedical challenges. He leads a research group focused on geometric deep learning for drug discovery, with active projects in protein design using geometric-aware models and large language models for multi-omics analysis. The group has access to thousands of GPUs through industry collaborations, enabling large-scale experiments in molecular simulation and generative modeling.

Kinohi Nishikawaمشاهده پروفایل

دانشیار

• African American Literature
• Book History
• Print Culture
• +۷ مورد دیگر

Kinohi Nishikawa is an Associate Professor jointly appointed in the Department of African American Studies and the Department of English at Princeton University. His scholarly work bridges literary criticism, book history, and African American cultural studies, with a strong emphasis on the material forms of literature. A.B., Dartmouth College (summa cum laude, High Honors in English) M.A., Literature, Duke University Ph.D., Literature, Duke University His research focuses on 20th- and 21st-century African American literature, particularly the roles of book design, publishing practices, and paratextual elements in shaping literary reception. He explores how print culture, independent presses, and visual aesthetics contribute to Black literary expression and archival formation. His work intersects with Black aesthetic theory, humor, and popular culture. His recent publications reveal a consistent thematic thread: the materiality of African American texts. Across journals like PMLA , American Literary History , and Papers of the Bibliographical Society of America , he investigates how design, format, and publishing context influence meaning-making in works by authors such as Ralph Ellison, Gwendolyn Brooks, Ishmael Reed, and Percival Everett. Nishikawa is actively involved in public scholarship, curating the Black Independent Film series at the Princeton Garden Theatre and advising on the Sites of Memory exhibition of the Toni Morrison Papers. He is co-authoring a book with Professor Autumn Womack on Morrison’s archiving practices. Curator, Black Independent Film series, Princeton Garden Theatre Advisor, Sites of Memory exhibition, Toni Morrison Papers Collaborator on Morrison archiving project with Autumn Womack

Anne Danielsenمشاهده پروفایل

استاد

• Popular Music
• African-American Music
• Rhythm and Sound Analysis
• +۵ مورد دیگر

Anne Danielsen is a Professor and Deputy Head at the RITMO Center for Interdisciplinary Studies of Rhythm, Time, and Motion at the University of Oslo. Her research bridges musicology, cognitive science, and interdisciplinary studies, focusing on rhythm, music production, and the intersection of music, media, and technology. University: University of Oslo Role: Professor Projects: TIME (NFR TOP RESEARCH), RITMO (NFR Center of Excellence) Danielsen’s work explores microrhythm , groove , and temporal perception in music, with a particular emphasis on popular and African-American music . She investigates how music cognition interacts with sonic features and body posture in performance, integrating psychological and acoustic analysis . Her recent projects include MusicLab Copenhagen , a dataset for interdisciplinary concert research, and studies on beta oscillations and pupil responses in groove perception. Danielsen collaborates across disciplines, examining how personality traits and genetic factors influence musical sensibility through twin studies. In music production , she analyzes how digital audio workstations transform rhythmic structures and investigates acoustic chamber design for sound experiments. Her research also addresses gender patterns in music mediation and the cultural implications of rhythmic aesthetics.

Bert de Vriesمشاهده پروفایل

استاد

• Bayesian Machine Learning
• Signal Processing
• Biomedical Applications
• +۳ مورد دیگر

Bert de Vries is a Professor at the Signal Processing Systems Group at Eindhoven University of Technology (TU/e), where he has been employed since January 2012. He maintains a dual career, also working at GN Hearing in the hearing aids industry since April 1999, where he holds both research and managerial roles. His academic journey began at TU/e, where he earned his MSc in Electrical Engineering in 1986, followed by a PhD from the University of Florida in 1991. Between 1992 and 1999, he worked at Sarnoff Research Center in Princeton, NJ, contributing to diverse signal and image processing projects. Professor de Vries's research centers on Bayesian Machine Learning, with particular focus on the Free Energy Principle and its applications to engineering problems. His work bridges theoretical neuroscience with practical signal processing systems, especially in biomedical applications. He directs the BIASlab research team at TU/e, which develops probabilistic programming tools including RxInfer.jl, ForneyLab.jl, GraphPPL.jl, ReactiveMP.jl, and Rocket.jl. His research spans active inference, variational message passing, probabilistic programming, and Bayesian neural networks, with applications ranging from hearing aids to multi-agent systems. Analysis of his recent publications reveals a strong trend toward practical implementations of Bayesian inference frameworks, particularly through Julia-based probabilistic programming tools. His work shows increasing focus on active inference applications, message passing algorithms, and the intersection of Riemannian geometry with probabilistic modeling. The research demonstrates consistent progression from theoretical foundations toward real-world engineering applications, particularly in biomedical signal processing and autonomous systems. Professor de Vries teaches a graduate-level course on Bayesian Machine Learning at TU/e and actively contributes to open-source software development through his GitHub profile (bertdv), with recent activity as recent as August 2025. His research team has developed several influential probabilistic programming libraries that have gained significant attention in the machine learning community. The BIASlab research group continues to advance the state of the art in Bayesian inference methods with applications in hearing technology, robotics, and signal processing.

Lisa Hanssonمشاهده پروفایل

استاد

• Transport Policy and Governance
• Urban Sustainable Transport/Mobility
• Socio-technical Change
• +۳ مورد دیگر

Lisa Hansson is a Professor of Community Planning at Molde University College, specializing in urban governance and transport policy. She is affiliated with the Logistics Department and actively contributes to sustainable mobility, socio-technical change, and multi-level governance research. PhD in Science and Technology Studies (2011), Linköping University MSc in Political Science/Public Administration (2005), Gothenburg University BA in Human Geography/Urban Planning (2003), Karlstad and Gothenburg Universities Her research focuses on sustainable transport systems, visual representation in planning, and policy adaptation. She leads externally funded projects like LEAD (Digital Twins for logistics) and SNAPSHOT (e-commerce transport), with partners including SINTEF and K2 Sweden. Her work bridges political science and transport governance, challenging economic-technical discourses. Recent articles analyze equity in 15-minute city planning, social justice in transport protests, and regulatory governance for autonomous vehicles. She chairs the WCTRS SIG G1 Transport Governance group and serves on the Thredbo Conference Committee. 2023: Co-authored Public Participation in Transport in Times of Change (Emerald) 2021: Chapter on Transport Policy and Governance (Elsevier) 2020: Editorial in Transportation Research Part A Lisa teaches MA/BA courses like Smart Mobility, European Transport Policy, and Future Cities. She supports Master’s and PhD research in sustainable urban development and transport policy.

David A. Petersonمشاهده پروفایل

دانشیار

• Linguistics
• Morphosyntactic Typology
• Comparative Tibeto-Burman
• +۲ مورد دیگر

David A. Peterson is an Associate Professor of Linguistics at Dartmouth College , specializing in morphosyntactic typology , comparative Tibeto-Burman , and language documentation . His academic work bridges theoretical and descriptive linguistics. Education : B.A. from University of Alaska at Fairbanks, M.A. and Ph.D. from University of California at Berkeley His research focuses on the structural analysis of Kuki-Chin languages within the Tibeto-Burman family, emphasizing historical contingency, participant marking, and endangered language preservation. He teaches foundational courses in linguistics, including LING 1 (Introductory Linguistics), LING 24 (Discourse Analysis), LING 25 (Typology), and LING 26 (Morphology). Recent publications highlight his expertise in Tibeto-Burman subgrouping, typological patterns, and endangered language documentation. Current works in progress include comparative grammar studies of Kuki-Chin languages and reference grammars for Khumi, Mru, and Rengmitca.

Jacob Monroeمشاهده پروفایل

استادیار

• Machine Learning
• Molecular Simulation
• Statistical Mechanics
• +۴ مورد دیگر

Jacob Monroe is an Assistant Professor at the University of Arkansas in the Ralph E. Martin Department of Chemical Engineering. He earned his B.S. from the University of Virginia (2014) and Ph.D. from the University of California, Santa Barbara (2019), followed by an NRC Postdoctoral Fellowship at NIST. His research integrates machine learning with statistical mechanics to enable predictive molecular simulations of biomaterials. Education: B.S. (2014) and Ph.D. (2019) in Chemical Engineering Research Interests focus on: VAE-based multiscale simulation techniques Advanced solvation free energy calculations Computational design of membrane and chromatographic interfaces Protein self-assembly and water-mediated interactions Publication Trends demonstrate expertise in merging machine learning with molecular simulation to address thermodynamic challenges in biomaterial systems. His work spans applications in renewable energy , pharmaceutical formulation , and eco-friendly electronics . Scientific Awards : DOE Early Career Award (2023) NRC Postdoctoral Fellowship (2019) NSF Graduate Research Fellowship (2015) AICHE COMSEF Graduate Student Award (2017) Laboratory : Leads the Monroe Molecular Simulation Group, which specializes in developing machine learning methods grounded in statistical mechanics for biomolecular modeling. Recent projects include salt aggregation analysis in water-purification membranes and protein-interface binding energy predictions.

• Cardiac Imaging
• Magnetic Resonance Imaging
• Computed Tomography
• +۶ مورد دیگر

Ronald M Peshock is a Professor of Radiology and Internal Medicine at the University of Texas Southwestern Medical Center (UTSW), with a career spanning over four decades since completing medical school at UT Southwestern in 1976. His academic journey includes Internal Medicine training at Parkland Health & Hospital System (internship 1977, residency 1979) followed by a Cardiology fellowship (1982). Dr. Peshock's research focuses on cardiac imaging, particularly using MRI and CT technologies to assess cardiovascular risk and disease. His work heavily involves the Dallas Heart Study, examining left ventricular hypertrophy, atherosclerosis, and cardiovascular risk factors across diverse populations. In recent years, he has become a prominent researcher in artificial intelligence applications for radiology, with numerous publications on AI implementation in clinical workflows, diagnostic accuracy improvement, and integration of AI into radiology training programs. His publication record shows consistent productivity from 1979 through 2025, with 218 total publications according to available records. Recent work demonstrates particular expertise in cardiac CT, pulmonary embolism imaging, and developing quantitative imaging biomarkers for cardiovascular disease. His Scopus profile indicates an h-index of 67 with 14,914 citations, reflecting significant scholarly impact in his fields. Dr. Peshock maintains active clinical and research affiliations with Parkland Health & Hospital System and serves as a key researcher in the Dallas Heart Study. His work examining ethnic differences in cardiovascular disease, left ventricular hypertrophy patterns, and aortic stiffness has contributed significantly to cardiovascular imaging literature.

Federico Beccaمشاهده پروفایل

دانشیار

• Theoretical Physics
• Condensed Matter Physics
• Strongly Correlated Systems
• +۴ مورد دیگر

Federico Becca is an Associate Professor in the Department of Physics at the University of Trieste . He is a theoretical condensed matter physicist specializing in strongly correlated electronic systems , with a focus on spin liquids , superconductivity , and topological phases . His research employs quantum Monte Carlo and exact diagonalizations to study lattice models like the Hubbard and Heisenberg models . Education: Laurea in Physics, Università La Sapienza, Roma (1996) PhD in Condensed Matter, ISAS-SISSA, Trieste (2000) Research Interests: Prof. Becca’s work centers on Mott insulators , spin-liquid phases , and superconductivity in systems with magnetic frustration and strong electron correlations. He investigates unconventional electronic states in reduced dimensions and explores the interplay between spin-phonon interactions and quantum phase transitions . Scientific Collaborations: Alberto Parola (Insubria University) Michele Fabrizio (SISSA) Roser Valenti (University of Frankfurt) Didier Poilblanc (University of Toulouse) Yasir Iqbal (Indian Institute of Technology Madras) Current Projects: Unravelling the intertwined correlated states of matter in moiré superlattices (funded by MINISTERO DELL'UNIVERSITA' E DELLA RICERCA). He also leads the "Studio computazionale del modelli di Kane and Mele" project as a Scholar at risk.

Ellen Rathjeمشاهده پروفایل

استاد

• Geotechnical Engineering
• Earthquake Engineering
• Seismic Response Analysis
• +۵ مورد دیگر

Ellen Rathje is a Professor and Janet S. Cockrell Centennial Chair in Engineering at the University of Texas at Austin's Department of Civil, Architectural, and Environmental Engineering within the Cockrell School of Engineering. Her expertise spans geotechnical engineering with a focus on earthquake engineering, seismic response of earth structures, and liquefaction evaluation. She leads research initiatives such as DesignSafe cyberinfrastructure and TexNet Seismological Network, advancing geohazard risk assessment and computational modeling. Education: Ph.D. (1997), M.S. (1994), and B.S. (1993) in Civil Engineering from University of California, Berkeley and Cornell University. Research Interests: Dr. Rathje investigates earthquake-induced ground failures, including lateral spreading, liquefaction, and slope instabilities. Her work integrates machine learning, finite element analysis, and geospatial data to enhance predictive models for infrastructure resilience. Recent projects address induced seismicity in energy-producing regions, site amplification in Central and Eastern North America, and tailings dam failure mechanisms. Awards: Recipient of the 2022 Ralph B. Peck Award, 2018 William B. Joyner Lecture Award, and 2016 ASCE Fellow distinction. Her work has advanced open science through DesignSafe's cyberinfrastructure, supporting natural hazards research collaboration. Technical Contributions: Developed hybrid finite-element/material point methods for granular collapse modeling, probabilistic frameworks for regional landslide assessments, and neural network-based site amplification models. Active in post-earthquake reconnaissance through GEER (Geotechnical Extreme Events Reconnaissance) and TexNet operations.

Michael Vermeuelمشاهده پروفایل

استادیار

• Atmospheric Chemistry
• Air Quality
• Climate Science
• +۳ مورد دیگر

Dr. Michael Vermeuel is an Assistant Professor in the Department of Earth, Atmospheric, and Planetary Sciences at Purdue University. He leads the AIR CheM (Atmospheric Interdisciplinary Research in Chemistry and Meteorology) group, focusing on reactive atmospheric gases impacting air quality, climate, and ecosystems. His work combines field observations, chemical transport modeling, and laboratory studies. Education: PhD in Chemistry (2021), University of Wisconsin – Madison MS in Chemistry (2017), University of Wisconsin – Madison BS in Chemistry (2015), The College of New Jersey Research Interests: Dr. Vermeuel’s group investigates the sources and fates of atmospheric chemicals using advanced techniques such as chemical ionization mass spectrometry and micrometeorological flux measurements. Key areas include ozone deposition dynamics, VOC cycling in forests, and marine-abiotic VOC sources. His work bridges laboratory experiments, field campaigns (e.g., FROG-NY, FluCS), and model development to address environmental challenges. Awards: AGU James R. Holton Award (2024) His lab emphasizes interdisciplinary collaboration, with projects addressing urban pollution, wildfire impacts, and climate feedbacks. Current research includes the Fluxes of Reactive Organic Gases in New York (FROG-NY) and the Flux Closure Study (FluCS) at Manitou Experimental Forest.

Annette D'Onofrioمشاهده پروفایل

دانشیار

• Sociolinguistics
• Phonetics
• Psycholinguistics
• +۴ مورد دیگر

Annette D'Onofrio is an Associate Professor in the Linguistics Department at Northwestern University. Her research bridges sociolinguistics and psycholinguistics, focusing on how social meaning is constructed through phonetic variation. She investigates topics like raciolinguistic expectations, geographic dialect features, and the cognitive representation of sociolinguistic signs. Key research areas include phonetic perception in bilingual contexts, the interplay between language ideologies and place-linked variation (e.g., Chicago Jewish communities), and the role of persona in shaping linguistic perception. Her work often employs experimental methods to explore how social information influences phonetic categorization and speech evaluation. Recent studies examine geographic dialect perceptions in New Orleans, the dynamics of the Northern Cities Shift in Chicago, and the sociophonetic analysis of presidential campaign rhetoric. Her research also addresses iconicity in phonological variation and the cognitive underpinnings of sociolinguistic signs. Though no specific grants or advising roles are listed, her work consistently highlights the intersection of social identity and linguistic structure. She holds a PhD in Linguistics and maintains a Google Scholar profile with over 20 peer-reviewed articles since 2012.

Abigail Bighamمشاهده پروفایل

دانشیار

• Human Population Genetics
• Molecular Evolution
• Natural Selection in Human Genome
• +۴ مورد دیگر

Abigail Bigham is an Associate Professor and Vice Chair for Undergraduate Studies in the Department of Anthropology at the University of California, Los Angeles (UCLA). Her research focuses on human population genetics, molecular evolution, and high-altitude adaptation, particularly in Andean and Tibetan populations. She holds a PhD in Anthropology from Penn State University (2008) and a BA in Anthropology from the University of Arizona (2001). Her team investigates genetic and epigenetic mechanisms underlying adaptation to hypoxia, diet, and infectious diseases. Key research areas include the genetic basis of altitude-related traits like hemoglobin concentration, pulmonary function, and metabolic adaptations. Her lab also explores the evolutionary impact of dietary changes (e.g., potato-rich diets in the Andes) and immune responses to pathogens such as HIV and dengue. Recent work includes epigenetic studies of high-altitude acclimatization and the functional validation of adaptive alleles. Dr. Bigham’s projects often involve interdisciplinary collaborations, integrating genomic data with physiological measurements and anthropological fieldwork. She has conducted field studies in Peru, Tibet, Guatemala, and Nepal, focusing on indigenous populations to understand how genetic variation contributes to survival in extreme environments. Her lab’s website (https://bigham-lab.anthro.ucla.edu/) provides access to datasets and research tools. Her academic contributions span over 50 peer-reviewed articles and grants addressing high-altitude physiology, evolutionary genetics, and global health. She actively advocates for ethical discussions on race and genetics, challenging simplistic biological determinism through public outreach and educational initiatives.