جستجوی استاد راهنمای دانشگاهی

• Numerical Relativity
• Gravitational Wave Astronomy
• Black Hole Dynamics
• +۴ مورد دیگر

Harald Pfeiffer is a Professor at the University of Potsdam and Group Leader in the Astrophysical and Cosmological Relativity department at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute) in Potsdam. His research focuses on numerical relativity and gravitational wave astrophysics, particularly simulations of black hole and neutron star mergers to interpret observations from detectors like LIGO and Virgo. He holds a PhD from Cornell University and has held academic roles at the Canadian Institute for Theoretical Astrophysics (2009–2017). Notably, he was elected a Fellow of the American Physical Society in 2023 for his contributions to numerical relativity. His expertise includes developing computational tools to solve Einstein’s equations on supercomputers and analyzing gravitational wave data. Key interests include understanding spacetime behavior during mergers, improving waveform models, and preparing for future detectors like LISA. He collaborates extensively with international initiatives such as the LIGO Scientific Collaboration. Selected Awards: Fellow of the American Physical Society (2023) Research and Grants: His work bridges theoretical advances and observational data, contributing to waveform catalogs and detector sensitivity improvements. He leads a team advancing numerical relativity techniques for next-generation gravitational wave astronomy. Labs/Teams: Leads the Astrophysical and Cosmological Relativity group at the Max Planck Institute, fostering interdisciplinary research in gravitational wave science.

Jeremy Bowlesمشاهده پروفایل

مدرس

• Political Economy of Development
• Sub-Saharan Africa
• State-Building Processes
• +۳ مورد دیگر

Dr. Jeremy Bowles is a Lecturer in Comparative Politics at the Department of Political Science, University College London (UCL). His research focuses on the political economy of development, particularly in sub-Saharan Africa, examining interactions between state-building processes and distributive politics. Prior to UCL, he held a Postdoctoral Fellowship at Stanford University's King Center on Global Development and earned his Ph.D. from Harvard University. His work has been supported by institutions like J-PAL and USAID. Education: B.A. and M.Sc. from the University of Oxford Ph.D. in Government from Harvard University (2021) Postdoctoral Fellowship at Stanford University His research explores how distributive conflicts shape state-building and electoral accountability in weakly institutionalized contexts. Key themes include taxation systems in Tanzania, elite politics in post-colonial states, and the role of social media in African autocracies. He employs experimental and observational methods to study governance challenges in developing democracies. His publications appear in top journals like the American Political Science Review and American Journal of Political Science . Recent work addresses misinformation dynamics, electoral accountability, and post-pandemic policy responses in Zimbabwe. Teaching focuses on African governance and political economy models. Grants and partnerships include collaborations with the International Growth Centre (IGC) and Stanford Impact Labs.

Patrick Wuمشاهده پروفایل

استاد

• AI/ML
• Natural Language Processing
• Computational Social Science
• +۳ مورد دیگر

Patrick Wu is a Professor in the Department of Computer Science at American University, with additional affiliations as Faculty Fellow at the Center for Data Science and Faculty Affiliate at the Center for Security, Innovation, and New Technology. He holds a PhD in Political Science and Scientific Computing from the University of Michigan, an MA in Statistics from Michigan, and a BA in Political Science and Statistics from the University of Chicago. His research develops AI/ML and natural language processing approaches for computational social science, focusing on: Political elite and non-elite ideology measurement Affective polarization on social media platforms Detection of hateful/abusive speech and memes Application of large language models to political science research Recent work explores innovative methods for political attitude measurement using LLMs, in-context learning techniques for social media analysis, and frameworks for multimodal representation learning. His publications demonstrate consistent innovation in applying NLP and machine learning to political discourse analysis, with emerging focus on generative AI's impact on political science education and methodology. Wu teaches courses including Object-Oriented Programming and topics in Natural Language Processing/Text as Data.

Stuart Reevesمشاهده پروفایل

دانشیار

• Human-computer interaction
• Collaborative computing
• Design research
• +۴ مورد دیگر

Stuart Reeves is an Associate Professor at the School of Computer Science, University of Nottingham, UK. He is a member of the Mixed Reality Lab, Horizon research institute, Centre for Doctoral Training (CDT), and Social Interaction and Technology (SIT) Special Interest Group. Reeves serves as an elected member of the University of Nottingham Senate with his term extending until 2026. His academic career spans over two decades with significant contributions to human-computer interaction, particularly focusing on social and collaborative technologies in real-world contexts. Reeves' research interests primarily focus on human-computer interaction, collaborative computing, design research, and the application of ethnomethodology and conversation analysis (EMCA) to technology studies. His work examines how people interact with diverse interactive devices and systems in real-world situations and places, with particular attention to public spaces, video gaming contexts, and collaborative work environments. Reeves has developed significant expertise in understanding spectatorship within interactive spaces and the 'work' involved in technological engagements. His publication record demonstrates consistent high-impact contributions to the field, with recent research focusing on robots and AI technologies in action, particularly examining how autonomous robots interact with humans in public streets. Reeves has received multiple prestigious awards including the HRI 2024 Best Paper Award for his work on public robot encounters and previous Best Paper Awards at CHI 2005 and CHI 2008. HRI 2024 Best Paper Award for 'Encountering autonomous robots on public streets' CHI 2015 Honourable Mention Award CHI 2008 Best Paper Award CHI 2005 Best Paper Award CHI 2012 Honourable Mention Award CHI 2020 Best Paper Award Reeves has secured substantial research funding including an EPSRC Early Career Fellowship, multiple EPSRC grants, and international collaborations. His teaching responsibilities include undergraduate and postgraduate supervision across various computer science modules, with a focus on sensor-based systems and software design principles. He maintains an active presence in the research community through publications, conference participation, and his Medium page where he shares insights on research methodology and practice.

Tara Reichمشاهده پروفایل

دانشیار

• Workplace relationships
• Workplace mistreatment
• Employee well-being
• +۳ مورد دیگر

Tara Reich is an Associate Professor in Organisational Behaviour and Human Resource Management at King's Business School, King's College London. She previously held positions at the London School of Economics (2011-2018) and the University of Surrey (2018-2019). Her research focuses on workplace relationships, particularly the psychological impacts of workplace mistreatment and observer reactions to such behaviors. She teaches core modules on the Human Resource Management & Organizational Analysis MSc and an elective on the Business Management BSc. Education: PhD in Organizational Behaviour, University of Manitoba, Canada (2011) Research Interests: Workplace mistreatment mechanisms and consequences Observer perspectives on workplace deviance Employee well-being and psychological safety Work-family interface dynamics Publications Trends: Her work consistently examines how workplace aggression, incivility, and harassment affect observers and targets, with notable contributions to understanding observer reactions to counterproductive work behavior. Recent studies explore ethical leadership's role in shaping moral identity and workplace ostracism dynamics. Advising & Grants: Currently accepting PhD students in organizational behavior and HRM. Active in securing research grants focused on workplace mistreatment and organizational psychology.

Sriraam Natarajanمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Healthcare Applications
• +۵ مورد دیگر

Sriraam Natarajan is a Professor and Director of the Center for Machine Learning and StaRLing Lab at The University of Texas at Dallas (UTD), part of the Erik Jonsson School of Engineering & Computer Science. He holds additional roles as a hessian.AI Fellow at TU Darmstadt and an RBCDSAI Distinguished Faculty Fellow at IIT Madras. His expertise spans Artificial Intelligence, Machine Learning, and their applications in healthcare, with a focus on Relational Learning, Reinforcement Learning, and Graphical Models. He has been honored as an AAAI Fellow (2025), elected to the AAAI Executive Council, and recognized with the UTD Outstanding Graduate Teaching Award. Education: Completed his PhD in Computer Science at Oregon State University in 2007 under Prof. Prasad Tadepalli. Postdoctoral work at the University of Wisconsin-Madison with Professors Jude Shavlik and David Page. Previously served as faculty at Indiana University and Wake Forest School of Medicine. Research: Active in developing AI systems for healthcare, including predictive models for gestational diabetes and cardiac arrest in children. His work emphasizes integrating human knowledge into machine learning (e.g., Human-in-the-Loop systems) and advancing statistical relational AI frameworks like Markov Logic Networks and Probabilistic Circuits. Publications: Over 100 peer-reviewed articles, including notable works on causal learning, relational reinforcement learning, and knowledge graph construction. Recent focuses include explainable AI and scalable probabilistic models. Awards: AAAI Fellow, RBCDSAI Distinguished Fellowship, UTD Teaching Excellence Award. Advising and Collaboration: Mentored over 30 students, many now in academia and top institutions like IBM Research, Facebook, and Microsoft. Collaborates globally on projects like GLAD (Glocalized Anomaly Detection) and StaRLing Lab initiatives. Labs/Teams: Leads the StaRLing Lab, focusing on statistical relational AI, and directs UTD's Center for Machine Learning. Engaged in interdisciplinary projects with healthcare, robotics, and data science communities.

• Statistical methodology
• Social network analysis
• Healthcare quality measurement
• +۸ مورد دیگر

James O'Malley is a Professor at The Dartmouth Institute for Health Policy and Clinical Practice and Professor of Biomedical Data Science at the Geisel School of Medicine, Dartmouth College. He holds the prestigious Peggy Y. Thomson Professorship in the Evaluative Clinical Sciences and serves as an Adjunct Professor of Computer Science, demonstrating his interdisciplinary expertise spanning statistics, healthcare policy, and computer science. Dr. O'Malley earned his B.Sc. (Hons) in Statistics from the University of Canterbury, New Zealand (1994), M.S. in Applied Statistics from Purdue University (1999), and Ph.D. in Statistics from the University of Canterbury (1999), followed by a Postdoctoral Fellowship in Biostatistics at Harvard Medical School (2001). His research spans statistical methodology and healthcare applications, with methodological contributions in statistical inference for social networks , multivariate hierarchical models , comparative effectiveness research , and Bayesian analysis . These methods address critical healthcare problems including health-social network relationships , healthcare quality measurement , medical technology diffusion , and comparative effectiveness in vascular surgery, cardiology, and mental health . His work bridges theoretical statistics with practical healthcare challenges through collaborations with physicians, epidemiologists, and health services researchers. Dr. O'Malley's recent publications reveal a strong emphasis on healthcare network analysis, comparative effectiveness research, and methodological innovations. His work examines physician networks and patient outcomes, evaluates surgical interventions, identifies healthcare disparities, and develops novel statistical approaches for complex healthcare data, with significant contributions appearing in high-impact journals across multiple disciplines. Mid-career Excellence award from the Health Policy Section of the ASA Elected fellow of the ASA (2012) ISPOR Award for Excellence in Methodology (2019) Peggy Y. Thomson Professorship (2021) 2025 Research Excellence Award for Senior Faculty in the Foundational Sciences As a dedicated mentor, Dr. O'Malley has supervised numerous post-doctoral fellows and PhD students across multiple programs. He currently leads major research initiatives including NIH/NLM R01LM014233 on Geographic Variations in Health Care, serves as PI for cores in NIH/NIA projects on healthcare inequity in Alzheimer's Disease and Rural Health Care Delivery Science, and contributes to multiple substantial grants totaling millions of dollars. He previously chaired the Health Policy Statistics Section of the ASA and co-chaired the 2011 International Conference on Health Policy Statistics. Dr. O'Malley co-organized the Dartmouth Interdisciplinary Network Research (DINR) seminar series (2014-2020) and serves as an Associate Editor for Statistics in Medicine and Observational Studies, demonstrating his commitment to advancing methodological research and fostering interdisciplinary collaboration in health services research.

B. Pablo Montagnesمشاهده پروفایل

دانشیار

• Formal Political Theory
• Political Economy
• Public Policy Analysis
• +۳ مورد دیگر

B. Pablo Montagnes is an Associate Professor of Political Science and Quantitative Theory and Methods at Emory University. He holds a Ph.D. in Managerial Economics and Strategy from the Kellogg School of Management, Northwestern University (2010). Before joining Emory in 2015, he was an Assistant Professor at the Harris School of Public Policy, University of Chicago. His research focuses on formal political theory and political economy, with a particular emphasis on strategic behavior in legislative settings, regulatory policy, and public opinion dynamics. Key topics include partisan approval rates, legislative bargaining, and the design of organizational and market mechanisms. Montagnes has published in leading journals such as the Journal of Politics , American Economic Review , and Proceedings of the National Academy of Sciences (PNAS) . Education: Ph.D. in Managerial Economics and Strategy, Kellogg School of Management, Northwestern University (2010) Previous Affiliation: Harris School of Public Policy, University of Chicago (Assistant Professor) Teaching: QTM 110 (Scientific Methods), QTM 315 (Game Theory) Montagnes’ work addresses questions like how regulatory uncertainty affects firm investment, the strategic implications of sequential voting in legislatures, and the reliability of survey-based partisan approval metrics. His recent projects explore polarization incentives, internal labor markets, and the role of lobbyists in policy gatekeeping. He currently holds an office at 311 Tarbutton Hall, Emory University, and can be contacted via email . No awards are explicitly listed in the provided materials.

Renita Colemanمشاهده پروفایل

دانشیار

• Agenda-Setting
• Race and Ethnicity
• Visual Communication
• +۳ 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.

John E. Carlstromمشاهده پروفایل

استاد

• Cosmology
• Experimental Astrophysics
• Observational Cosmology
• +۷ مورد دیگر

John E. Carlstrom is the Subrahmanyan Chandrasekhar Distinguished Service Professor and Chair of the Departments of Astronomy & Astrophysics and Physics at the University of Chicago. He leads the South Pole Telescope (SPT) project and co-chairs the CMB-S4 collaboration, focusing on observational cosmology and the cosmic microwave background (CMB). His work bridges the University of Chicago with Argonne National Laboratory, the Enrico Fermi Institute, and the Kavli Institute for Cosmological Physics. Education: PhD, University of California, Berkeley (1988) AB, Vassar College Carlstrom’s research centers on using the CMB to study the universe’s origin and evolution, including inflation, dark energy, and neutrino masses. His team employs advanced instruments like the SPTpol and SPT-3G cameras to map CMB polarization and detect galaxy clusters via the Sunyaev-Zeldovich effect. Recent projects include the Event Horizon Telescope’s black hole imaging and NSF-funded CMB-S4 development. Scientific Awards: MacArthur Fellowship (1998) Gruber Prize in Cosmology (2015) Breakthrough Prize in Fundamental Physics (2019) Dannie Heineman Prize for Astrophysics (2024) Arthur L. Kelly Faculty Prize (2024) Elected to AAAS (2000) and NAS (2002) He directs the SPT Group, which collaborates with Argonne National Laboratory on superconducting detector fabrication. His work has shaped major initiatives like the Dark Energy Survey and the Giant Magellan Telescope, influencing the Astro2020 decadal survey. Carlstrom mentors graduate students in physics and astrophysics, advancing precision cosmology through cutting-edge instrumentation.

Roman Kremsمشاهده پروفایل

استاد

• Quantum Physics
• Machine Learning
• Quantum Chemistry
• +۳ مورد دیگر

Roman Krems is a Professor and Distinguished University Scholar at the University of British Columbia (UBC) in the Department of Chemistry, with affiliations to the Stewart Blusson Quantum Matter Institute. His research focuses on the intersection of quantum physics, machine learning, and chemistry, particularly in quantum materials and quantum technologies such as quantum computing and sensing. Key Roles: Professor at UBC (2013–present), Distinguished University Scholar (2017–present) Education: Ph.D. from Göteborg University (2002), Postdoctoral Fellow at Harvard-MIT Center for Ultracold Atoms (2003–05) Research Interests include: Quantum machine learning (QML) for solving complex physics problems Quantum scattering theory in electromagnetic fields Applications of quantum computing to chemistry Developing machine learning algorithms for quantum dynamics Recent publications highlight advancements in extrapolating quantum observables, Gaussian process models for collision dynamics, and quantum walks in disordered systems. His work bridges theoretical physics, computational methods, and experimental applications in cold molecule research. Scientific Awards include the UBC Killam Teaching Prize (2017), election as Fellow of the American Physical Society (2015), and the Keith Laidler Award (2013). He has held editorial board positions for journals such as Machine Learning: Science & Technology and New Journal of Physics . Research Group members include graduate students and postdocs working on quantum technologies, machine learning, and molecular scattering. He also contributes to outreach through invited talks and seminars at institutions like MIT and Lawrence Berkeley National Laboratory.

• International Relations
• Political Science
• Global Governance
• +۳ مورد دیگر

Inken von Borzyskowski is a Professor of International Relations at the University of Oxford's Department of Politics and International Relations (DPIR) and a Fellow at St Catherine’s College. She serves as Co-Coordinator of the DPIR International Relations Colloquium and holds roles on the editorial boards of International Studies Quarterly and Global Governance , as well as the Board of Directors at the Academic Council on the United Nations System (ACUNS). Her academic journey includes previous positions at University College London (UCL), Florida State University, and postdoctoral research at institutions like the Free University Berlin, Duke University, and the Hertie School. Dr. von Borzyskowski earned her PhD in International Relations, Methodology, and Comparative Politics from the University of Wisconsin-Madison in 2014. She holds an M.A. from Free University Berlin and has conducted extensive research and teaching across various institutions, including the Social Science Research Center (WZB) in Berlin and Duke University. Her research focuses on the intersection of international organizations and domestic governance, particularly the effects of international organizations on domestic conflict and elections. Key areas include international democracy assistance, election violence, and membership politics (withdrawals and suspensions). Her first book, The Credibility Challenge: How Democracy Aid Influences Election Violence (Cornell University Press, 2019), explores how international election monitoring and assistance impact electoral violence dynamics. Her second book, Exit from International Organizations (Cambridge University Press, forthcoming), examines state withdrawal from international bodies. Dr. von Borzyskowski’s research has garnered prestigious recognitions, including the British Academy Mid-Career Fellowship, the Philip Leverhulme Prize, and the APSA Best Article Award. Her work has been supported by grants from institutions like the U.S. Institute of Peace and the World Bank. She advises graduate students such as Rohan Watt and Christian Uta and contributes to policy-related initiatives, including co-authoring USIP Peace Briefs on election violence prevention in Liberia and Kenya. She is actively involved in academic networks, including roles at the American Political Science Association (APSA) and International Studies Association (ISA), and advocates for rigorous methodological approaches in studying international organizations and their domestic impacts.

Hanno Hilbigمشاهده پروفایل

استادیار

• Comparative Politics
• Political Economy
• Democratic Institutions
• +۴ مورد دیگر

Hanno Hilbig is an Assistant Professor of Political Science at the University of California, Davis. He holds a PhD from Harvard University’s Department of Government (2022) and an MS in Economics from Humboldt University Berlin. His research focuses on the interplay between structural economic changes—such as labor markets, housing crises, and energy transitions—and their political impacts in advanced democracies. He employs causal inference methods for observational data, using designs like natural experiments and large-scale administrative datasets. Key research areas include voter preferences, policymaking processes, and democratic institutions. His work addresses topics such as public housing budget tradeoffs, refugee labor market integration, and the effects of local newspaper decline on polarization. He has published in top journals like the American Journal of Political Science , British Journal of Political Science , and Journal of Politics . His recent articles explore themes such as green party support following natural disasters, the role of wealth disparities in radical right voting, and the consequences of rent control policies. Hilbig co-leads collaborative projects like the German Election Database (GERDA) and investigates refugee integration dynamics. His research bridges quantitative methods with substantive political questions, emphasizing policy relevance and democratic stability.

• Creative Writing
• Creative Nonfiction
• Science Fiction
• +۸ مورد دیگر

Sarah E. Einstein is an Associate Professor in the Department of English at the University of Tennessee at Chattanooga (UTC). She is a creative nonfiction writer and academic whose work interrogates the intersection of Jewish and Appalachian identities, ethical research methodologies in personal writing, and narrative structure. Education: PhD in Creative Writing from Ohio University (2016), MFA in Creative Nonfiction from West Virginia University (2011) Her research explores: Ethical boundaries when writing about friends/family Travel as a research methodology in narrative nonfiction Authorial selfhood in first-person writing Hybrid identities (Jewish/Appalachian) Her recent publications include a 2025 Judith Magazine essay on selfhood, 2022 Hippocampus and Brevity articles on research ethics, and a 2016 Assay journal piece analyzing authorial responsibility. Key themes across her work: cultural hybridity, memory ethics, and narrative voice in nonfiction. Academic Recognition: Pushcart Prize winner AWP Prize for Creative Nonfiction recipient Featured in Best of the Net anthology As organizer for UTC's Urban League STEAM Enrichment Program (2021-2025), she has mentored students in narrative design. Current service roles include Faculty Senate President Elect (2025-2026) and General Education Committee membership (2024-2025).

Genevera Allenمشاهده پروفایل

دانشیار

• Statistical Machine Learning
• Interpretable Machine Learning
• Data Integration
• +۸ مورد دیگر

Genevera Allen is an Associate Professor of Electrical and Computer Engineering, Statistics, and Computer Science at Rice University. She is also an Investigator at the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital and Baylor College of Medicine, and the Founding Director of the Rice D2K Lab, a hub for data science education and real-world problem-solving. Education: Ph.D. in Statistics from Stanford University (2010), B.A. in Statistics from Rice University (2006). Her research develops statistical machine learning tools for reproducible discoveries in neuroscience and bioinformatics, focusing on interpretable models, graphical networks, and data integration. She pioneers methods for high-dimensional and multi-modal data, including convex clustering, sparse PCA, and fairness-aware algorithms. The 15 most recent publications span statistical machine learning theory, neuroscience applications, and bioinformatics. Key trends include graphical model estimation, convex optimization for clustering, latent variable adjustment, and ethical AI frameworks. Applications emphasize neuroimaging and single-cell genomics. Scientific Awards: NSF Career Award (2016), Duncan Achievement Award (2021), Curriculum Innovation Award (2020), Research and Teaching Excellence Award (2017), Forbes 30 Under 30 (2014), elected Fellow ASA (2022), Member ISI (2021). Dr. Allen leads the Rice D2K Lab, which connects students with industry and academic data science projects. She serves as Editor for the Journal of Machine Learning Research and Springer Texts in Statistics . Her teaching innovations include client-sponsored capstone programs and courses on machine learning.