جستجوی استاد راهنمای دانشگاهی

Mor Armonyمشاهده پروفایل

استاد

• Operations Management
• Stochastic Modeling
• Service Operations
• +۷ مورد دیگر

Mor Armony is the Vice Dean for Faculty and Research, Harvey Golub Professor of Business Leadership, and Professor of Technology, Operations & Statistics at the Leonard N. Stern School of Business, New York University. She has been a key faculty member since 1999 and is a leading researcher in stochastic modeling and service operations. Ph.D. in Operations Research, Stanford University (1999) M.S. in Operations Research, Stanford University (1997) M.S. in Statistics, Hebrew University of Jerusalem (1996) B.S. in Mathematics and Statistics, Hebrew University of Jerusalem (1993) Her research focuses on large-scale service systems, particularly in healthcare and contact centers. She investigates patient flow in hospitals, optimization of customer experience, and control of stochastic processing systems using advanced queueing models and operations research techniques. Her work bridges theoretical rigor with practical applications in service operations management. The recent articles reflect a strong trend toward integrating behavioral aspects into operations models, such as customer impatience, strategic patient behavior, and the impact of online reviews on physician demand. Her research spans healthcare operations, call center optimization, and dynamic routing in heterogeneous systems, consistently published in top journals like Management Science , Operations Research , and Production and Operations Management . Scientific recognition includes being named the Harvey Golub Professor of Business Leadership, a distinguished title at NYU Stern. Harvey Golub Professor of Business Leadership She actively advises research projects and collaborates with scholars on topics including staffing, routing, and capacity management. Her work has been supported by ongoing academic engagement and publication, with recent projects addressing appointment scheduling with no-shows, strategic capacity withholding, and co-sourcing in call centers. She leads research in data-driven queueing science applied to hospital operations and is involved in empirical studies on digital health platforms. Her research group, the Operations Management Group at Stern, focuses on developing analytical models for complex service systems. She contributes to interdisciplinary efforts in healthcare operations and collaborates with medical researchers on improving critical care delivery and outpatient scheduling.

• Colonial Latin American History
• Religious Hybridism
• Inquisition Studies
• +۳ مورد دیگر

Martin Nesvig is a Professor at the University of Miami in the Department of History, College of Arts and Sciences. He serves as Director of Undergraduate Studies and Co-Faculty Lead for Mexico and Mesoamerica in the University of Miami’s Interdisciplinary Programs (UMIA). His research focuses on colonial Latin America, particularly religious hybridism, inquisitorial systems, and decentralized power structures in Michoacán. University of Miami, College of Arts and Sciences Department of History Director of Undergraduate Studies Mexico and Mesoamerica Co-Faculty Lead Nesvig's scholarship interrogates the complexities of religious syncretism, bureaucratic conflict, and cultural negotiation in colonial Mexico. His work challenges traditional narratives of 'spiritual conquest' by highlighting the mutual adaptation between Spanish and indigenous communities, emphasizing the role of hallucinogenic rituals, vernacular scripture, and micro-imperial governance in shaping colonial religious practices. His 2010 Charles A. Ryskamp Research Fellowship supported his project on frontier religion in Michoacán, analyzing how Spanish clergy and laity adopted indigenous practices. His publications span topics from peyote use in Catholic rituals to the political implications of prohibited books and the dynamics of postcontact cultural liminality. Notable Works: Promiscuous Power: An Unorthodox History of New Spain , Peyote, Ever Virgin: A Case of Religious Hybridism in Mexico Awards: Charles A. Ryskamp Research Fellowship Nesvig’s research reveals a colonial state perpetuated through bureaucratic litigation rather than violence, with his irreverent historiographical style challenging academic conventions. His students and colleagues engage with his critical perspectives on power, religion, and cultural identity in early modern Latin America.

Giuseppe Santucciمشاهده پروفایل

دانشیار

• Visual Analytics
• Information Visualization
• Human-Computer Interaction
• +۳ مورد دیگر

Giuseppe Santucci is an Associate Professor at the Department of Computer, Control and Management Engineering Antonio Ruberti at Sapienza University of Rome. He teaches courses on Fundamentals of Computer Science, Software Engineering, and Visual Analytics. His office is located in Room B218 at Via Ariosto 25, Rome, and his contact email is santucci@diag.uniroma1.it. Dr. Santucci's research focuses on Visual Analytics, Information Visualization, Human-Computer Interaction, and Information Retrieval. His work spans theoretical aspects of visual query languages for semantic models to practical applications in visual analytics for cybersecurity, cryptocurrencies, and deep learning explainability. He has published over 130 articles in international journals and conferences, demonstrating his significant contributions to these fields. His recent publications show a strong trend toward applying visual analytics to increasingly complex domains including cybersecurity, cryptocurrencies, and explainable AI. The work demonstrates an evolution from theoretical foundations of visual query systems to practical applications that help users understand complex data and systems. His research bridges the gap between theoretical computer science and practical user-centered solutions. Dr. Santucci has received notable recognition including: IEEE VizSec 2018 Best Paper Award Human-Computer Interaction Cybersecurity Awards 2018 He actively mentors students through thesis projects focused on information visualization and visual analytics. His PROMISE project provides a framework for students to engage in cutting-edge research in information retrieval and visual analytics. He has supervised work on topics including visual evaluation techniques, visual mappings optimization, and user studies for Infovis systems. Dr. Santucci leads the A.WA.RE (Advanced Visualization & Visual Analytics REsearch) group at Sapienza University. This group conducts research on visual analytics tools for information retrieval evaluation, cybersecurity analysis, and deep learning explainability. Their work includes developing frameworks like CryptoComparator for cryptocurrency analysis and BUCEPHALUS for cybersecurity platform analysis.

Celso Grebogiمشاهده پروفایل

استاد

• Nonlinear and complex dynamical systems
• Chaos theory
• Fractal geometry
• +۵ مورد دیگر

Professor Celso Grebogi, Sixth Century Chair in Nonlinear & Complex Systems at the University of Aberdeen, is a globally recognized leader in nonlinear dynamics , chaos theory , and systems biology . He founded the Institute for Complex Systems and Mathematical Biology and co-founded the Aberdeen-Lanzhou-Tempe Research Centre. His career spans institutions including University of Maryland, University of São Paulo, and Max-Planck-Society (External Scientific Member since 1998).

Jeffrey R. Erringtonمشاهده پروفایل

استاد

• Molecular Simulation
• Statistical Thermodynamics
• Interfacial Phenomena
• +۳ مورد دیگر

Jeffrey R. Errington is a Professor and Chair of the Department of Chemical and Biological Engineering at the University at Buffalo (SUNY). His research focuses on developing molecular simulation methods to study interfacial phenomena in complex fluids, including CO2 sequestration, enhanced oil recovery, and ionic liquid behavior. He holds a BS (1995) and PhD (1999) in Chemical Engineering from the University at Buffalo and Cornell University, respectively, and completed postdoctoral work at Princeton University. Education: BS, Chemical Engineering, University at Buffalo, 1995 PhD, Chemical Engineering, Cornell University, 1999 Research Interests: Computational methods for interfacial properties Molecular simulation of carbon capture and environmental systems Thermodynamic modeling of ionic liquids and nanomaterials Recent Work Trends: Recent articles emphasize advancing Monte Carlo and molecular dynamics techniques for studying fluid interfaces, with applications to energy storage, environmental engineering, and material science. Key themes include interfacial wetting, adsorption in nanoporous materials, and free-energy landscape analysis. Awards: NSF CAREER Award (2003) NYSTAR James D. Watson Investigator Award (2004) SUNY Chancellor’s Award for Excellence (2016) UB Exceptional Scholar Awards (2005, 2014) Leadership & Service: Director of Undergraduate Studies (2006–2014) Associate Dean for Undergraduate Education (2014–2023) Senior Associate Dean for Academic Affairs (2023–2024) Chair, CoMSEF Forum (American Institute of Chemical Engineers) His research group actively collaborates on CACHE Corporation initiatives and develops educational tools for undergraduate researchers.

Francisco Camara Pereiraمشاهده پروفایل

استاد

• Intelligent Transportation Systems
• Machine Learning
• Active Learning
• +۳ مورد دیگر

Francisco Camara Pereira is a Professor and Head of Section at the Department of Technology, Management and Economics at the Technical University of Denmark (DTU). His research focuses on Intelligent Transportation Systems, Machine Learning, and Data-Driven Decision-Making in transportation contexts. He actively contributes to advancing transportation science through interdisciplinary approaches combining simulation, optimization, and AI techniques. His work addresses challenges in public transport analysis, charging infrastructure planning, and multimodal demand prediction. Recent projects include developing graph-based optimization methods for electric vehicle networks and causal discovery frameworks for transportation systems. He supervises multiple PhD students in areas like federated learning for cyclist safety, causal graph neural networks, and socially aware AI models. Key contributions include publications on smart card data analysis for travel surveys, stochastic infrastructure expansion models, and transfer learning for bike-share systems. His research aligns with UN Sustainable Development Goals related to sustainable cities and innovation. Dr. Pereira collaborates internationally on transportation policy and infrastructure projects. His lab focuses on translating theoretical advancements into practical solutions for urban mobility challenges.

Lionel Levineمشاهده پروفایل

استاد

• Applied Mathematics
• Combinatorics and Discrete Geometry
• Probability and Statistics
• +۴ مورد دیگر

Lionel Levine is a Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences. His academic research focuses on abelian networks, interacting particle systems, and the emergence of complex patterns from simple rules. He has held prestigious fellowships, including the Simons Fellowship and Sloan Research Fellowship, and has been honored with an endowed professorship. Levine's work bridges probability theory, combinatorics, and statistical physics, with notable contributions to the study of sandpile models and internal diffusion-limited aggregation (IDLA). Education: Ph.D. in Mathematics (2007), University of California, Berkeley. Research Interests: Applied Mathematics, Combinatorics, Probability, Abelian Networks, Sandpile Models, and their intersections with computer science and statistical physics. His research explores how local rules generate large-scale structures, such as in abelian networks and sandpile models. Awards and Honors: Simons Fellowship, Sloan Research Fellowship, Endowed Professorship in the College of Arts and Sciences. Teaching: Courses include Probability Theory (MATH 6710/6720), Topics in Probability: Math for AI Safety (MATH 7710), and undergraduate mathematics courses like Strategy, Cooperation, and Conflict (MATH 1340). Grants and Funding: Supported by the National Science Foundation (NSF), Simons Foundation, Sloan Foundation, and Institute for Advanced Study. Collaborations: Collaborates with prominent researchers such as Yuval Peres, Cris Moore, and Jim Propp. His work has been published in leading journals like the Annals of Probability and Duke Mathematical Journal. Future Work: Continues investigating AI safety, causal models, and multi-agent learning, including research on mathematical frameworks for transformer circuits and hidden incentives in AI systems.

• Cognitive Science
• Psychology
• Computational Modeling
• +۶ مورد دیگر

Andrew Perfors is a Professor of Psychology at the University of Melbourne, leading the Computational Cognitive Science Lab and directing the Complex Human Data Hub. His research focuses on quantitative approaches to higher-order cognition, including concepts, language, decision-making, and misinformation dynamics. He holds a PhD from MIT and degrees from Stanford University. Education: PhD in Brain & Cognitive Sciences, Massachusetts Institute of Technology (2008) MA in Linguistics, Stanford University (2000) Bachelor of Science in Symbolic Systems, Stanford University (1999) Research Interests: He investigates computational models of cognition, cultural and social evolution, and the spread of misinformation. Recent work emphasizes the cognitive mechanisms underlying inductive reasoning, sampling assumptions, and trust in information. Key Projects: Understanding Information and Trust: From the Individual to the Population (2018–2025) Bridging the Meaning Gap: Computational Approach to Semantic Variation (2023–2027) Awards: Recipient of multiple best paper awards for contributions to cognitive science and computational linguistics. Labs & Groups: Leads the Complex Human Data Hub and co-leads the Computational Cognitive Science Lab, focusing on interdisciplinary research in human behavior and data science.

Ting Huمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Bioinformatics
• Data Mining
• +۷ مورد دیگر

Dr. Ting Hu is an Associate Professor in the School of Computing at Queen's University, affiliated with the Faculty of Arts and Science. She leads the Machine Intelligence & Biocomputing (MIB) Laboratory, focusing on bio-inspired AI and bioinformatics. Her research bridges evolutionary computing, machine learning, and biomedical data analysis. Dr. Hu holds a PhD in Computer Science from Memorial University and completed postdoctoral training at Dartmouth College. She teaches courses with strong student evaluations, winning the Howard Staveley Teaching Award (2019-2020) and recognition as a Mental Health Champion (2023). Education: B.Sc. in Computational Mathematics, Wuhan University M.Sc. in Computer Science, Wuhan University PhD in Computer Science, Memorial University Postdoctoral Fellowship, Geisel School of Medicine, Dartmouth College Research Interests: Evolutionary algorithms and genetic programming Interpretable and explainable AI Biomedical data mining (metabolomics, genomics) Complex network analysis Applications in precision medicine and disease prediction Awards & Recognition: Queen's AMS Undergraduate Mentorship Award (2025) IEEE CIBCB Best Student Award (2022) Howard Staveley Teaching Award (2019-2020) NSERC Discovery Grant Reviewer (2019) Memorial University's Best Professor Award (2016) Lab & Collaborations: MIB Lab develops tools like geneDRAGNN (graph neural networks for gene-disease prioritization) Active roles in IEEE Computational Intelligence Society and EuroGP Advances include vaccination strategies via graph-RL and interpretable clustering methods

Daniel M. Royمشاهده پروفایل

استاد

• Machine Learning
• Statistics
• Probabilistic Programming
• +۷ مورد دیگر

Daniel M. Roy is a Professor at the University of Toronto with cross-appointments in the Departments of Computer Science and Electrical and Computer Engineering. He serves as Associate Chair, Statistics, and is a Research Director at the Vector Institute and a CIFAR Canada AI Chair. His research focuses on foundational principles of prediction, inference, and decision-making under uncertainty, spanning machine learning, statistics, mathematical logic, applied probability, and computer science. He has contributed to learning theory, statistical network analysis, probabilistic programming, and Bayesian nonparametric statistics. Education: Ph.D. in Computer Science from MIT (2011), advised by Leslie Kaelbling. Postdoctoral fellowships at the University of Cambridge (Newton International Fellow and Research Fellow). His research explores information theories of learning , online learning , and nonstandard foundations for decision theory . Recent work includes best paper awards at ICML 2024 and advancements in probabilistic programming systems like Church. His publications address problems in generalization bounds, causal bandits, neural network theory, and exchangeable random structures. Scientific Awards include the MIT/EECS George M. Sprowls Doctoral Dissertation Award and the ICML 2024 Best Paper Award. He advises students and postdocs across statistics, computer science, and machine learning, with alumni now holding positions at institutions like Princeton, Imperial College London, and the University of Chicago.

Patrick H. Maddenمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• VLSI Design Automation
• Algorithms
• +۳ مورد دیگر

Patrick H. Madden is an Associate Professor and Director of the MS Information Systems program at the School of Computing, Binghamton University. His research focuses on combinatorial optimization, VLSI physical design automation, and algorithmic solutions for NP-Hard problems. He is also involved in interdisciplinary work in cryptography and biology-related optimization. Education: BS and MS from New Mexico Institute of Mining and Technology PhD from University of California, Los Angeles (UCLA) Professional Roles: Chair of ACM/SIGDA (Design Automation Special Interest Group) Chair of Design Automation Conference (DAC) Sponsors Committee Advisor to Binghamton ACM Student Chapter Coach for ICPC Programming Contest Teams Member of Watson School Graduation Committee Research Contributions: Leads the Optimality Research Group, developing optimization algorithms for VLSI CAD and medical software applications. Notable contributions include the Feng Shui placement tool and medical reference apps for iOS/Android platforms. Awards: SUNY Chancellor's Award for Excellence in Professional Service (2015) Grants & Collaborations: Collaborates with Prof. Monte McCollum (Cinema Department) on hybrid cinema projects and Dr. Joshua Steinberg (Physician) on medical software. Active in ACM committees and EDA conferences (DAC, ICCAD, ISPD). Labs/Teams: Directs the Optimality Research Group and oversees medical software collaborations through CS441/580 projects.

Yuval Noah Harariمشاهده پروفایل

مدرس

• World History
• Medieval History
• Military History
• +۷ مورد دیگر

Yuval Noah Harari is a historian, philosopher, and lecturer at the Department of History at the Hebrew University of Jerusalem. Born in Haifa, Israel in 1976, he received his PhD from the University of Oxford in 2002. He is best known as the author of the internationally acclaimed books Sapiens: A Brief History of Humankind (2014), Homo Deus: A Brief History of Tomorrow (2016), 21 Lessons for the 21st Century (2018), Nexus: A Brief History of Information Networks from the Stone Age to Artificial Intelligence , and the Unstoppable Us children's series. Harari's research focuses on macro-historical questions including the relationship between history and biology, the essential difference between Homo sapiens and other animals, justice in history, historical directionality, human happiness throughout history, and the ethical questions raised by science and technology in the 21st century. His work bridges history, biology, philosophy, and economics, taking both macro and micro perspectives to understand not only what happened and why, but also how it felt for individuals. His books have sold over 45 million copies in 65 languages, with Sapiens alone selling 25 million copies since its publication. He is considered one of the world's most influential public intellectuals today. Harari has given keynote speeches at major international forums including the World Economic Forum in Davos and has presented as a digital avatar in a TED talk. Sapiens spent 96 consecutive weeks in the top 3 of the Sunday Times bestseller list Co-founded Sapienship, an international social impact company focused on education and storytelling, with his husband Itzik Yahav Regularly speaks at major international events on topics of technology, history, and the future of humanity Harari's recent work focuses on the challenges of the information age, particularly the crisis of truth and trust in an era of disinformation and artificial intelligence. He explores how humans can navigate the complex ethical questions raised by emerging technologies while maintaining democratic values and human dignity.

Christopher Mullerمشاهده پروفایل

استاد

• Incarceration
• Racial Inequality
• Historical Sociology
• +۴ مورد دیگر

Christopher Muller is a Professor of Sociology at Harvard University, where he has been since 2023. Previously, he taught at the University of California, Berkeley. His research focuses on the political economy of incarceration in the U.S., examining how agricultural labor markets, migration, and struggles over land and labor have shaped racial and class inequality in incarceration. He also studies environmental inequality and disparities in infectious disease mortality. Current Position: Professor of Sociology at Harvard University (on leave 2025-26) Former Position: Professor at UC Berkeley His research explores long-term patterns of incarceration, particularly the historically lower Black incarceration rates in the South compared to the North and the shift in the early 1970s. He investigates connections between incarceration, slavery, peonage, and agricultural economic shifts. His work highlights how labor demand and social exclusion shape incarceration trends. Key areas of interest include historical sociology, criminology, and the intersections of race, class, and punishment. His recent work documents declining racial disparities but rising educational inequality in incarceration rates since the 21st century. Scientific Awards: None explicitly listed in provided texts Advising/Grants: Not detailed in the provided materials He is affiliated with Harvard’s Crime and Punishment, Health and Population, and Race, Ethnicity and Immigration research clusters.

• Agent-Based Modeling
• Socio-Economic Dynamics
• Environmental Resilience
• +۵ مورد دیگر

Dr. Debraj Roy is a Visiting Professor at the University of Amsterdam (UvA), affiliated with the Faculty of Science, Mathematics and Computer Science and the Informatics Institute. His research focuses on agent-based modeling, socio-economic dynamics, environmental resilience, and blockchain technology. He investigates complex systems such as urban slums, disaster recovery, and climate adaptation using computational methods like remote sensing and machine learning. His work bridges theory and practice, offering insights into policy design for sustainable development and social equity. Key research interests include slum dynamics, poverty traps, and the application of blockchain oracles for decentralized systems. He employs advanced techniques such as global sensitivity analysis and manifold learning to explore multi-scale socio-environmental challenges. His recent articles highlight trends in carbon pricing, flood risk valuation, and multi-agent systems. Earlier work concentrated on urban inequality in cities like Bangalore and Mexico City, leveraging geospatial and statistical tools. No scientific awards or grants are explicitly listed. His advising and team collaborations are unspecified in the provided text.

John Millerمشاهده پروفایل

استاد

• Complex Adaptive Systems
• Economic Theory
• Game Theory
• +۴ مورد دیگر

John Miller is a Professor of Economics and Social Science at Carnegie Mellon University (CMU) and a Research Professor at the Santa Fe Institute. His work focuses on complex adaptive systems, computational modeling, and social dynamics. He holds a Ph.D. in Economics from the University of Michigan (1988) and has held academic positions since 1990. Miller’s research explores emergent patterns in social systems through agent-based models, experimental economics, and nonlinear dynamics. His research interests span complex adaptive systems, game theory, auction markets, and behavioral economics. Notable contributions include foundational work on computational social science, the Standing Ovation Problem, and cooperative behavior analysis. Miller has authored influential books such as Complex Adaptive Systems: An Introduction to Computational Models of Social Life and A Crude Look at the Whole . He has received awards including the Elliot Dunlap Smith Award for Teaching Excellence and has led initiatives like the Open Learning Initiative. Miller’s academic leadership roles include Director of Graduate Studies at CMU and Faculty Director of the Omidyar Fellows Program at Santa Fe Institute. His work bridges economics, computer science, and interdisciplinary complexity research.