جستجوی استاد راهنمای دانشگاهی

Dean Eckles is an Associate Professor of Marketing at MIT Sloan School of Management and serves as an Associate Director of the MIT Institute for Data, Systems, and Society (IDSS). He is also affiliated with the MIT Schwarzman College of Computing through the Institute for Data, Systems & Society and its Statistics and Data Science Center. Additionally, he leads the analytics research area at the Initiative on the Digital Economy and organizes the annual Conference on Digital Experimentation (CODE@MIT). His educational background includes a BA in philosophy, BS and MS in cognitive science, MS in statistics, and PhD in communication, all from Stanford University. Prior to joining MIT, Eckles worked as a scientist at Facebook, where he contributed to areas including News Feed, messaging, advertising, tools for randomized experiments, and survey methods. He previously held research positions at Nokia and Yahoo. Eckles's research primarily focuses on social influence mediated by interactive technologies, examining how communication technologies mediate, amplify, and direct social influence. His work spans multiple specific areas including social interactions, contagion, and interventions in networks; experimental design and inference in networks; and methods for causal inference. His research often combines social science with advanced statistical methods. His notable publications include research on long ties in social networks and their relationship to economic prosperity, how network structure affects social contagions, and algorithmic transparency in social media platforms. His work has appeared in prestigious journals including PNAS and Nature Human Behaviour, and he has provided expert testimony before the US Senate on algorithmic ranking. Long ties, disruptive life events and economic prosperity (PNAS) Long ties accelerate noisy threshold-based contagions (Nature Human Behaviour) Algorithmic transparency and assessing effects of algorithmic ranking (Senate testimony) Eckles actively shares his research through social media platforms including Bluesky, Twitter, and Mastodon, as well as through his blog and contributions to the Gelman et al. blog. His work bridges academic research with practical applications in technology and policy.

• Social Influence
• Network Analysis
• Causal Inference
• +۴ مورد دیگر

Dr. Herb Lin is the Hank J. Holland Fellow in Cyber Policy and Security at the Hoover Institution and Senior Research Scholar for Cyber Policy and Security at the Center for International Security and Cooperation (CISAC), both at Stanford University. He also serves as Chief Scientist, Emeritus for the Computer Science and Telecommunications Board of the National Academies, where he worked from 1990 to 2014, and as Adjunct Senior Research Scholar and Senior Fellow in Cybersecurity at Columbia University's Saltzman Institute for War and Peace Studies. Dr. Lin received his doctorate in physics from MIT, providing him with a strong technical foundation that informs his policy work at the intersection of technology and national security. His academic background bridges the gap between deep technical understanding and policy application in the cybersecurity domain. Dr. Lin's research focuses on the policy dimensions of cybersecurity and cyberspace, with particular emphasis on offensive cyber operations as instruments of national policy, information warfare, and influence operations affecting national security. His work addresses critical challenges at the intersection of emerging technologies like artificial intelligence, quantum computing, and their implications for nuclear security, election integrity, and democratic processes. He has been instrumental in analyzing how cyber capabilities are transforming traditional security paradigms and how policy frameworks must adapt to these changes. His extensive publication record reveals a consistent focus on the evolving relationship between cyber capabilities and national security strategy. Lin's work demonstrates increasing attention to the implications of artificial intelligence for warfare, the vulnerabilities created by quantum computing for current cryptographic systems, and the growing threat of cyber-enabled information warfare to democratic institutions. His research trajectory shows a progression from traditional cybersecurity issues toward the broader implications of digital technologies for national and international security. Member of Science and Security Board of Bulletin of the Atomic Scientists Served on President Obama's Commission on Enhancing National Cybersecurity (2016) Regular congressional testimony on cybersecurity matters Contributor to Stanford Emerging Technology Review As a mentor and collaborator, Dr. Lin works extensively with policymakers, military officials, and technology experts to translate complex cybersecurity concepts into actionable policy recommendations. His approach emphasizes practical solutions to emerging threats while recognizing the technical limitations and policy constraints that shape real-world security outcomes. Dr. Lin is associated with multiple research initiatives including Stanford's Center for International Security and Cooperation and the Stanford Emerging Technology Review, which aim to connect technological advances with policy considerations for national security decision-makers.

• Cybersecurity Policy
• Information Warfare
• Nuclear Security
• +۴ مورد دیگر

Manex Aguirrezabal Zabaleta is an Associate Professor in the Department of Nordic Studies and Linguistics at the University of Copenhagen. He previously held positions as a Postdoc (2017-2019) and Assistant Professor at the same institution. His educational background includes: PhD in Natural Language Processing from the University of the Basque Country (UPV/EHU), conducted at the IXA NLP group. Master's degree in Natural Language Processing from UPV/EHU. Bachelor's degree in Computer Science (5 years) from UPV/EHU. Dr. Aguirrezabal's research focuses on the computational analysis of poetry , particularly stress patterns in English. He explores whether computers can effectively analyze poetic structures, a field with roots in the 1980s but revitalized by modern techniques. Additionally, he investigates language generation , computational morphology and phonology , and finite-state methods . His work bridges traditional linguistic inquiry with cutting-edge natural language processing. Recent publications (2023-2024) demonstrate a diverse engagement with computational linguistics, including poetry generation, multimodal corpus development, clickbait analysis, and fact-checking. His research often employs zero-shot learning and language models, reflecting current trends in AI-driven linguistic analysis. He has contributed to international collaborations such as ParlaMint (multilingual parliamentary corpora) and the GEHM Zoom corpus. While specific grant details are not provided, his active publication record indicates ongoing research support. Dr. Aguirrezabal maintains a strong connection to his Basque heritage, having pursued his early education in the Basque language.

• Natural Language Processing
• Computational Linguistics
• Poetry Analysis
• +۴ مورد دیگر

Bruce Ackerman is Sterling Professor of Law and Political Science at Yale University, holding one of the most prestigious academic positions at Yale. He has made significant contributions to constitutional law, political philosophy, and public policy over his distinguished career. His educational background includes an LL.B. from Yale (1967) and a B.A. from Harvard (1964). Ackerman has received numerous honors including the Henry Phillips Prize for lifetime achievement in Jurisprudence (2002), an Honorary Doctorate from the University of Milan (2023), and recognition as a Commander of the French Order of Merit. Ackerman's research focuses on American Constitutionalism, Comparative Constitutionalism, and Theories of Justice. His groundbreaking work includes the three-volume series We the People , which explores great turning points in American constitutional history. His scholarship has had global impact, influencing constitutional reforms in France, Brazil, Britain, and other countries. His recent work examines the constitutional challenges posed by the internet revolution and digital age. His publications reveal consistent engagement with constitutional crises across different nations and time periods, with particular attention to emergency powers, presidential authority, and democratic resilience. Ackerman's work connects historical constitutional development with contemporary challenges to democratic institutions. Commander of the French Order of Merit Henry Phillips Prize for lifetime achievement in Jurisprudence (2002) Honorary Doctorate from University of Milan (2023) Member of the American Law Institute Member of the American Academy of Arts and Sciences Named Leading Global Thinker by Foreign Policy magazine Ackerman has advised numerous governments and constitutional bodies worldwide. His work Before the Next Attack served as basis for French constitutional reform on emergency powers, while The Stakeholder Society influenced wealth distribution reforms in Brazil and Britain. He continues to actively engage with current constitutional challenges through scholarly publications, media commentary, and direct consultation with constitutional institutions globally.

• American Constitutionalism
• Comparative Constitutionalism
• Theories of Justice
• +۶ مورد دیگر

Dr. Chunyan Mu serves as a Senior Lecturer in the School of Natural and Computing Sciences at the University of Aberdeen, actively contributing to both academic instruction and cutting-edge research in computing science while currently accepting new PhD students. Her research program centers on Trustworthy AI and Safe Autonomy, with specialized expertise in formal verification of responsibility, accountability, and privacy mechanisms within multi-agent systems. She investigates resilience frameworks for autonomous intelligent systems and develops advanced methodologies for information flow security analysis, bridging theoretical computer science with practical security implementations. Analysis of her publication trajectory (2014-2025) reveals consistent innovation in applying formal methods to security-critical systems. Key thematic developments include probabilistic strategy logic for observability analysis, quantitative verification of opacity properties, and game-theoretic approaches to security verification, demonstrating increasing sophistication in handling multi-agent accountability and system resilience challenges. Dr. Mu currently supervises PhD candidates and offers a fully funded doctoral position focused on formal verification of safety properties in autonomous systems, providing comprehensive financial support including tuition coverage, £20,780 annual stipend, and dedicated research funding for candidates with strong backgrounds in formal methods and artificial intelligence.

• Artificial Intelligence
• Computer Security
• Multi-Agent Systems
• +۳ مورد دیگر

Gene Cooperman is a Professor at the Khoury College of Computer Sciences at Northeastern University, with an affiliation in the College of Engineering. His research focuses on high-performance computing (HPC), transparent checkpoint-restart systems, and model checking. He leads the High Performance Computing Laboratory, where he explores checkpointing technologies like DMTCP, MANA for MPI, and CRAC for CUDA, aiming to enhance HPC workflows on supercomputers such as NERSC's Perlmutter. His work bridges distributed computing, parallel algorithms, and system software to address challenges in fault tolerance, scalability, and resource management. Cooperman has advised 10 PhD students and co-authored over 125 refereed publications, contributing to projects like Geant4-MultiThreaded and Roomy for disk-based computation. His teaching includes courses on computer systems and HPC seminars. Education: Background in computational algebra and parallel computing, transitioning to HPC systems and checkpointing. Research Themes: Transparent checkpointing, MPI agnostic solutions, CUDA integration, and HPC resource optimization. Recent articles emphasize MPI checkpointing, reversible debugging (FReD), and CUDA support, reflecting trends in distributed and GPU-accelerated systems. His grants include NSF, NERSC/DOE, and MemVerge funding. Cooperman collaborates with institutions like CERN and NERSC, advancing applications in particle physics simulations and supercomputing. Current students include Aayushi Gautam, Jiajun Cao, Rohan Garg, and Twinkle Jain.

• High-Performance Computing
• Computer Systems
• Transparent Checkpointing
• +۴ مورد دیگر

Norman Sadeh is a Professor in the School of Computer Science at Carnegie Mellon University (CMU), where he has made significant contributions to cybersecurity, privacy, and AI research. He has co-founded and co-directed several groundbreaking graduate programs at CMU, including the Privacy Engineering Program (2012-present), the Ph.D. Program in Societal Computing (2003-2013), and the MBA track in Technology Strategy and Product Management (2005-2017). Carnegie Mellon University, School of Computer Science Software and Societal Systems Department CyLab Security and Privacy Institute Manufacturing Futures Institute Dr. Sadeh received his Ph.D. in Computer Science at CMU with a major in Artificial Intelligence and a minor in Operations Research. He holds an M.Sc. in computer science from the University of Southern California and a BS/MS degree in electrical engineering and applied physics from the Free University of Brussels (Belgium) as 'Ingénieur Civil Physicien.' Professor Sadeh's research spans cybersecurity, online privacy, Human-AI Interaction, AI governance, mobile computing, the Internet of Things, user-oriented machine learning, and language technologies. He is particularly known for his pioneering work on AI-based privacy enhancing technologies, including privacy assistants, automated privacy compliance tools, and NLP-based privacy solutions. His work has influenced the design of privacy features at major technology companies including Apple, Google, and Facebook/Meta, as well as privacy policies at regulatory agencies like the Federal Trade Commission and the California Office of the Attorney General. Analysis of his recent publications shows a strong focus on practical privacy solutions, particularly in mobile and IoT contexts, with an emphasis on making privacy more usable and understandable for end users. His work bridges technical innovation with policy implications, addressing both the technological and human aspects of privacy protection. 2018 Outstanding Entrepreneur of the Year award from the Pittsburgh Venture Capital Association Test of time award by the AAAI Conference on Web and Social Media (ICWSM) Gartner Group's Magic Quadrant leader in Security Awareness Computer-Based Training for 4 consecutive years Deloitte's Technology Fast 500 recognition for 3 consecutive years Professor Sadeh has advised numerous students, including PhD candidates like Aerin (Shikhun) Zhang, whose dissertation focused on understanding diverse privacy attitudes. His research has been funded through various grants, including NSF SaTC projects, and has resulted in technologies that protect tens of millions of users worldwide. He also founded Wombat Security Technologies, which was acquired by Proofpoint in 2018 and whose technologies are used by over 75% of Fortune 100 companies. Professor Sadeh leads several research initiatives including the Privacy Engineering Program, the Usable Privacy Policy Project, the Personalized Privacy Assistant Project, and CMU's Privacy Infrastructure for the Internet of Things. His Mobile Commerce Lab and E-Supply Chain Management Lab have produced influential research that has been commercialized by major organizations including IBM, Raytheon, Boeing, and the U.S. Army.

• cybersecurity
• online privacy
• Human-AI Interaction
• +۱۱ مورد دیگر

Michael Pyrcz is a Professor in the Hildebrand Department of Petroleum and Geosystems Engineering and holds the rank of Associate Professor in the Jackson School of Geosciences at the University of Texas at Austin. He is the recipient of the B. J. Lancaster Professorship in Petroleum Engineering and the George H. Fancher Centennial Teaching Fellowship in Petroleum Engineering. His research focuses on subsurface data analytics, geostatistics, and machine learning applications in energy systems and CO2 sequestration. Pyrcz teaches widely, including through online lectures and GitHub workflows, and has authored over 50 peer-reviewed publications and a textbook on spatial data analytics. His work integrates machine learning with geoscience challenges, such as uncertainty quantification in reservoir modeling and CO2 storage site evaluation. He leads initiatives in energy data analytics through the Freshman Research Initiative and collaborates with industry on workflow development. Key research areas include generative AI for subsurface models, stochastic methods for fracture networks, and anomaly detection in geologic monitoring. Education: Background in petroleum engineering and geosciences (details not explicitly provided). Grants/Advising: Extensive industry collaboration and mentorship roles at Chevron prior to UT Austin. Labs/Teams: Maintains active GitHub repositories (GeostatsGuy), YouTube lecture series (GeostatsGuyLectures), and social media outreach (X/GeostatsGuy).

• Subsurface Data Analytics
• Geostatistics
• Machine Learning
• +۳ مورد دیگر

Ignasi Sau Valls is a Directeur de Recherche (DR2) at CNRS, affiliated with the LIRMM laboratory at Université de Montpellier, France. He is a member of the AlGCo team, focusing on algorithms for graphs and combinatorics. His academic background includes dual degrees in Mathematics and Telecommunications Engineering from UPC (Barcelona), a PhD in joint supervision between UPC and Projet Mascotte (Sophia Antipolis), and a postdoctoral position at the Technion (Israel). He has been with CNRS since 2010 and was promoted to his current role in October 2024. He also served as a Visiting Professor at UFC (Brazil) from 2016–2017. His research interests lie primarily in Graph Theory and Parameterized Complexity , with a focus on structural graph properties, kernelization, and algorithm design. He has made significant contributions to problems involving minor-closed graph classes, treewidth, and graph modification. His work bridges theoretical foundations with algorithmic applications, particularly in discrete optimization and network problems. The recent articles highlight a strong trend in parameterized algorithms, especially for graph modification, kernelization, and structural graph problems. Topics such as hitting minors, dynamic programming on tree decompositions, and edge contractions reflect a deep engagement with structural parameterizations and fixed-parameter tractability. His publications frequently appear in top-tier journals like SIAM Journal on Computing, Journal of Combinatorial Theory, and Algorithmica, as well as major conferences such as ICALP, SODA, and IPEC. Best paper award of Track C of ICALP'10 Best student paper award of WG'09 Ignasi Sau has been a principal investigator of the ANR JCJC project ELIT (ANR-20-CE48-0008-01), funded with 169k€ from 2021 to 2026. He serves as an editor for DMTCS and Information and Computation , and has held significant organizational roles, including PC member of numerous conferences (MFCS, WG, IPEC, COCOON) and as co-chair and main organizer of WG 2019, ICGT 2022, and JCALM 2023. He has delivered invited courses at international schools in France, Argentina, and Brazil. He is actively involved in the research community through editorial duties, conference organization, and collaborative research. His lab affiliation is the AlGCo team at LIRMM, a leading group in algorithmic graph theory and combinatorics.

• Graph Theory
• Parameterized Complexity
• Algorithmic Graph Theory
• +۵ مورد دیگر

Qiaoning Carol Zhang serves as Assistant Professor of Human Systems Engineering within The Polytechnic School at Arizona State University's Ira A. Fulton Schools of Engineering. Her research investigates the critical intersection of human perception, social contexts, and emerging technologies including artificial intelligence, robotics, and automated vehicles, with emphasis on creating intuitive, user-friendly, and inclusive systems. Her academic foundation includes: Ph.D. in Information, University of Michigan (2023) M.S. in Industrial and Operations Engineering, University of Michigan (2018) B.S. in Industrial Engineering, Hunan University (2016) Dr. Zhang's research program centers on understanding how individual differences and social dynamics shape technology interactions. Key focus areas include Human-AI Collaboration , Human-Robot Interaction , Human Factors in Automated Vehicles , and User Experience Design . Her work employs interdisciplinary methodologies to ensure technology adapts to diverse user needs across complex socio-technical environments, particularly in transportation and healthcare robotics. Analysis of her 15 most recent publications (2021-2025) reveals dominant themes in trust dynamics within automated vehicles, with significant attention to explainable AI interfaces. Research consistently examines how voice characteristics (gender, similarity), explanation modalities, and individual differences (age, personality) impact cognitive and affective trust. Recent work extends to healthcare robotics for elderly populations using Kano model analysis to identify critical user requirements. No scientific awards are documented in the provided materials. Dr. Zhang actively recruits Ph.D. candidates and undergraduate/master's researchers with backgrounds in human-computer interaction, data science, and interdisciplinary fields (design, computer science, cognitive science). She emphasizes opportunities in transportation technology, healthcare robotics, AI, and UX research/design, requiring applicants to submit CVs, research statements, and representative work samples. While specific grants aren't detailed, her research scope indicates substantial funding in human factors and emerging technology domains. Her research team focuses on developing empathetic technology through projects examining trust calibration in automated vehicles and healthcare robot design for older adults. Current initiatives include voice interface optimization for diverse user groups and Kano model applications in home healthcare robotics, aiming to bridge technical capabilities with human-centered design principles.

• Human-AI Collaboration
• Human-Robot Interaction
• Human Factors in Automated Vehicles
• +۴ مورد دیگر

Daniel Webster is Bloomberg Professor of American Health in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health. He is also affiliated with the Urban Health Institute, the Johns Hopkins Center for Gun Violence Solutions, the Johns Hopkins Center for Injury Research and Policy, and the Center for Mental Health and Addiction Policy Research. Dr. Webster is one of the nation’s leading experts on firearm policy and the prevention of gun violence. His research interests include violence and violence prevention, firearm injuries, gun policy, policy evaluation, domestic violence, youth violence, and opioid abuse. He has led extensive research on the effects of firearm and alcohol policies, policing strategies, street outreach, conflict mediation, and school-based curricula. His recent publications focus on public health approaches to gun violence, the impact of purchaser licensing and background check laws, firearm injury hospitalizations, police shootings, and the deregulation of civilian gun carrying. These works reveal a strong trend in evaluating state-level firearm policies using longitudinal data and mixed-methods designs to inform public health and criminal justice policy. Inaugural Bloomberg Professor of American Health, 2018 Johns Hopkins University Distinguished Alumni Award, 2017 Baltimore City Health Equity Leadership Award, 2016 David Rall Award for Science-Based Advocacy, American Public Health Association, 2015 Finalist, Marylander of the Year, The Baltimore Sun, 2013 Delta Omega Honorary Society in Public Health – Alpha Chapter, Faculty induction, 2005 Educator of the Year, Maryland Network Against Domestic Violence, 2004 Dr. Webster has led numerous federally and foundation-funded research projects, including evaluations of city-level gun violence prevention initiatives, the Lethality Assessment Program, California’s domestic violence firearm intervention, and Baltimore policing strategies. He has advised on national and state-level policy and is a sought-after expert in public health advocacy. He teaches Understanding and Preventing Violence and Crafting Effective Solutions to Gun Violence: A Problem-Solving Seminar. He is a Distinguished Scholar at the Johns Hopkins Center for Gun Violence Solutions, where he continues to lead research and policy engagement efforts. His work is supported by interdisciplinary teams and collaborations across public health, criminology, law, and social work.

• Gun violence prevention
• Firearm policy
• Public health policy
• +۱۲ مورد دیگر

Carsten Rott is a Professor in the Department of Physics & Astronomy at the University of Utah and holds the Jack W. Keuffel Memorial Chair until December 2025. His academic journey began with a Ph.D. in Physics from Purdue University (2004), preceded by undergraduate studies at the Universität Hannover. Rott has held academic positions at institutions including The Ohio State University (CCAPP Senior Fellow 2009-2013), Penn State University (postdoc 2005-2008), and Sungkyunkwan University in South Korea (Assistant Professor 2013-2017, Associate Professor 2017-2025). He has been a member of the IceCube Neutrino Telescope collaboration since 2005 and serves on committees like the IceCube-Gen2 Coordination Committee and JSNS2 Speakers Board. His research spans Particle Physics , Neutrino Astronomy , and Dark Matter Detection . Key projects include analyzing IceCube data for sterile neutrino signatures, studying cosmic-ray anisotropy, and investigating terrestrial gamma-ray flashes. Notable achievements include the Bruno Rossi Prize (2021) for high-energy astrophysics contributions. Rott's work involves multimessenger observations (neutrinos, gamma-rays, radio signals) and detector calibration innovations, such as those for the JSNS2 experiment. Recent publications focus on atmospheric neutrino oscillation parameters, TGF spectroscopy, and dark matter constraints. He employs machine learning techniques (CNNs) for event reconstruction and leads initiatives like the IceCube Master Class for student engagement. Grants include funding for IceCube upgrades (2024-2026) and Hyper-Kamiokande collaborations (2023-2026). As department chair since 2023, Rott continues to bridge experimental particle physics with astrophysical discoveries.

• Particle Physics
• Astrophysics
• Neutrino Physics
• +۵ مورد دیگر

Cynthia Sturton serves as Associate Professor and Peter Thacher Grauer Scholar in the Department of Computer Science at the University of North Carolina at Chapel Hill. She leads the Hardware Security @ UNC research laboratory focused on developing formal verification tools for hardware security analysis. Her educational background includes a Ph.D. (2013) and M.S. from UC Berkeley, and a B.S.Eng. from Arizona State University. Her research centers on hardware security, applied formal methods, and symbolic execution techniques for identifying security vulnerabilities in processor designs before fabrication. Sturton's research demonstrates consistent innovation in hardware security verification, particularly through tools like Sylvia (symbolic execution for Verilog) and SylQ-SV (SystemVerilog analysis with query caching). Her work bridges theoretical formal methods with practical security applications, addressing critical challenges like path explosion and security property generation at scale. Nominated for Best Paper award at IEEE/ACM MICRO 2018 Intel Hardware Security Academic Award, 2nd place ($50,000) at IEEE Symposium on Security and Privacy 2020 Selected as Top Picks in Hardware and Embedded Security 2021 She advises multiple graduate students including Rui Zhang and Calvin Deutschbein, and has secured significant research funding from NSF (Grants 1816637, 651276), Semiconductor Research Corporation, Intel, Google, and UNC Chapel Hill. Her Hardware Security @ UNC lab develops critical tools for security property generation and vulnerability detection in hardware designs.

• Hardware Security
• Formal Methods
• Computer Security
• +۴ مورد دیگر

Véronique Hoste is Senior Full Professor of Computational Linguistics at Ghent University's Faculty of Arts and Philosophy, where she serves as Department Head of Translation, Interpreting and Communication and Director of the LT3 language technology research team. She also holds the position of Research Director for the Faculty of Arts and Philosophy. Her educational background includes a PhD in Computational Linguistics from the University of Antwerp (2005) focused on optimization in machine learning for coreference resolution. Key research areas encompass machine learning for natural language processing, semantic and discourse modeling, including specialized work in event detection, entity/event coreference resolution, irony detection, and emotion analysis. Hoste's publication trends reveal strong interdisciplinary focus, with recent work bridging NLP with crisis communication, digital humanities, and ethical AI. Her team develops high-quality datasets (e.g., EmoTwiCS for emotion trajectories) and collaborates extensively with commercial partners on projects like SentEMO for aspect-based sentiment analysis. Current research emphasizes multimodal emotion analysis, fuzzy rough set methods for sentiment detection, and cross-document event coreference. Elected member of the Royal Flemish Academy of Belgium for Science and the Arts (KVAB) Francqui Chair appointment by Université Libre de Bruxelles (2023-2024) Co-founded LT3 spin-off AlfaSent (2024) for customer feedback analysis Authored first Dutch-language book on NLP: "Taaltechnologie ontrafeld" She actively supervises multiple PhD students on projects including Common-sense knowledge in irony detection (Common-sense), cross-document event coreference (Encore), and empathy modeling in conversational agents (FlandersAI). Her team secures funding through interdisciplinary collaborations like NewsDNA for news recommendation and METRICS for emotion trajectory analysis. Hoste also engages in public outreach through the "AI at school" initiative and advises on language technology integration in high school curricula. The LT3 laboratory under her leadership maintains strong industry partnerships and develops practical NLP tools including EmotioNL and Automatic Term Extraction systems, while advancing core research through projects like CLARIAH-VL for data curation.

• Computational Linguistics
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Renita Coleman is an Associate Professor at the University of Texas at Austin's School of Journalism and Media, where she has taught since 2005 after achieving tenure in 2009. With expertise in agenda-setting theory, visual communication, and media ethics, she has authored over 30 peer-reviewed articles and two influential books: 'Designing Experiments for the Social Sciences' (2018) and 'The Moral Media' (2005). Her research examines how visual elements shape ethical reasoning and public perception in news media. Her academic credentials include: Ph.D. in Journalism, University of Missouri (2001) M.A. in Journalism, University of Missouri (1997) B.S. in Journalism, University of Florida (1979) Coleman's research program centers on the intersection of visual communication and moral decision-making in journalism. She investigates how photographs influence ethical reasoning among journalists, the framing of health news through visual elements, and racial dynamics in journalistic ethics. Her work employs experimental methods to analyze affective agenda-setting, where emotional responses to visual stimuli shape public priorities. This approach bridges communication theory with practical journalism ethics. Recent publications reveal intensifying focus on polarization mechanisms, climate change communication, and fact-checking efficacy. Coleman's scholarship increasingly examines how adaptive framing strategies overcome audience resistance, particularly regarding scientific consensus issues. Her methodological rigor in experimental design provides robust evidence for how visual and emotional elements drive media effects beyond traditional textual analysis. Professor Coleman has received extensive recognition for scholarly excellence: Multiple AEJMC top paper awards across divisions (2002-2014) Teacher of the Year at LSU (2002-2004) Ranked #1 for AEJMC convention productivity (1999-2008) She teaches doctoral seminars in qualitative methods and experimental design while mentoring graduate students in visual communication and ethics research. As associate editor of Journalism & Mass Communication Quarterly, she shapes scholarly discourse in the field. Though specific grant funding isn't detailed in available materials, her sustained publication record demonstrates consistent research activity. Coleman's background as a 15-year newspaper professional (including roles at the Raleigh News & Observer and Orlando Sentinel) informs her applied research perspective.

• Agenda-Setting
• Race and Ethnicity
• Visual Communication
• +۳ مورد دیگر