جستجوی استاد راهنمای دانشگاهی

• Evolutionary Biology
• Mathematical Biology
• Theoretical Evolutionary Theory
• +۴ مورد دیگر

Alan Grafen is an Honorary Fellow at Jesus College, University of Oxford, and holds Tutorial Fellow roles at St John’s College in Quantitative Biology. His primary affiliation is the University of Oxford’s Faculty of Biology and Medicine. He is a leading evolutionary biologist specializing in mathematical and logical models of evolutionary processes. Research Interests: Grafen’s work focuses on evolutionary theory, particularly the formalization of Darwinism, inclusive fitness, signal evolution, and sexual/kin selection. He leads the Formal Darwinism Project to mathematically formalize natural selection’s role in evolution. His models include the mathematical underpinning of Zahavi’s handicap principle and advancements in reproductive value theory. Key Contributions: Published influential works like Modern Statistics for the Life Sciences (2002) and co-authored analyses of Richard Dawkins’ evolutionary ideas. His recent articles (2018–2024) explore natural vs. sexual selection distinctions, kin recognition stability, and extensions to Fisher’s fundamental theorem. Awards and Grants: Not explicitly listed, but his work has shaped evolutionary theory. His research spans theoretical models in Nature -level journals and interdisciplinary collaborations with statisticians and biologists. Labs/Teams: Directs the Formal Darwinism Project and collaborates with evolutionary theorists globally. His work bridges mathematics and empirical biology, influencing both academic and popular science discourse.

• Stochastic Processes
• Financial Mathematics
• Systemic Risk
• +۶ مورد دیگر

Jean-Pierre Fouque is a Professor in the Department of Statistics and Applied Probability (PSTAT) at the University of California, Santa Barbara. His research focuses on stochastic processes, financial mathematics, systemic risk, and reinforcement learning, with a particular emphasis on mean field games and multi-scale stochastic models. He explores applications in portfolio optimization, risk management, and algorithmic finance. His work combines theoretical advancements in stochastic analysis with practical applications in economics and finance. Notable contributions include developing models for systemic risk in financial networks, analyzing reinforcement learning algorithms in mean-field frameworks, and studying stochastic volatility effects in derivatives pricing. Recent research trends include integrating deep learning techniques for systemic risk quantification, advancing multi-scale asymptotic methods for portfolio optimization, and investigating strategic interactions in financial systems using game-theoretic approaches. His publications frequently address topics such as stochastic volatility calibration, optimal investment strategies under uncertainty, and the dynamics of financial markets under stress scenarios. Dr. Fouque has contributed to foundational textbooks and edited volumes on systemic risk and mean field games. His interdisciplinary work bridges probability theory, mathematical finance, and computational methods, impacting both academic research and practical risk management practices.

Max Lauمشاهده پروفایل

استادیار

• Infectious Disease Dynamics
• Machine Learning
• Artificial Intelligence

Max Lau is an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Epidemiology at Emory University. His research focuses on integrating machine learning and computational methods with epidemiological and genomic data to study infectious disease dynamics. He teaches courses such as BIOS 790R (Advanced Seminar in Biostatistics) and DATA 534 (Applied Machine Learning). Dr. Lau's work emphasizes scalable Bayesian inference, graph neural networks, and stochastic modeling to address challenges in disease transmission, outbreak control, and pathogen evolution. His recent research includes developing tools like ScITree and Epilearn, and he has contributed to understanding measles dynamics, tuberculosis treatment, and livestock disease management. His academic contributions span over 30 publications since 2010, with a particular focus on phylodynamics, epidemic modeling, and vaccine strategy evaluation. His interdisciplinary approach bridges computational methods with public health applications, aiming to enhance disease prediction and intervention efficacy.

• Wireless Communications
• MIMO Systems
• Signal Processing
• +۳ مورد دیگر

Oussama Damen is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering. His research focuses on advanced wireless communication systems, particularly in MIMO (Multiple-Input Multiple-Output) systems, signal processing, and machine learning applications in telecommunications. He is actively involved in developing innovative solutions for beamforming, hybrid precoding, and distributed decoding in massive MIMO and millimeter-wave networks. Damen's work also extends to optical fiber communication, federated learning in wireless systems, and optimization of resource allocation in next-generation networks like 5G/6G. His research interests include wireless communication theory, antenna system design, channel modeling, and algorithm development for improving spectral and energy efficiency. He has contributed extensively to the theoretical foundations of MIMO detection, lattice reduction techniques, and statistical signal processing methods. Notable trends in his publications emphasize bridging theoretical performance limits with practical implementations, particularly in scenarios involving channel impairments, limited backhaul capacity, and multi-core fiber transmission. His work often addresses fairness and optimization in distributed systems, including federated learning frameworks and hybrid beamforming architectures. No scientific awards or grants are explicitly mentioned in the provided information. Damen has advised no listed students, and no specific lab affiliations are noted.

• Extreme Environmental Physiology
• Human Adaptation to Stressful Environments
• Environmental Health
• +۳ مورد دیگر

Edward Ashworth is a Postdoctoral Research Associate at the Sydney School of Health Sciences, University of Sydney. He is affiliated with the Thermal Ergonomics Laboratory and the Heat and Health Research Incubator. His research focuses on human adaptations to extreme environments, including heat, altitude, hyperbaric conditions, and space-related stressors. Key projects include improving sleep quality in hot environments and enhancing physical work capacity for outdoor workers. Edward's research interests span environmental physiology, with a focus on thermal tolerance, radiation injury mitigation, and the physiological effects of extreme conditions. He has contributed to studies involving nitrogen kinetics tracking using PET imaging, hyperbaric oxygen therapy, and robotic surgery applications. Awards: Young Investigator Award (2023), Art of Science Contest 1st Prize (2024), Australia Space Biology Summit 1st Place (2022), and Sporting Blue (Auckland University of Technology). Associations: The Physiological Society and American Physiological Society. His work integrates clinical trials, statistical research design, and translational approaches to address challenges in environmental health, cardiovascular disease, and healthy ageing. Current projects aim to optimize thermal tolerance strategies for military and occupational settings.

Ran Spieglerمشاهده پروفایل

استاد

• Economic Theory
• Behavioral Economics
• Political Economy
• +۳ مورد دیگر

Ran Spiegler is a Professor of Economics at both Tel Aviv University and University College London (UCL). He holds a PhD in Economics from Tel Aviv University (1999). His research focuses on economic theory, behavioral economics, and bounded rationality, with notable contributions to understanding decision-making under flawed causal reasoning, narrative-driven political and economic dynamics, and market behaviors influenced by limited consumer rationality. Spiegler has held roles including Member at the Institute for Advanced Study (Princeton, 2000-2001) and Prize Research Fellow at Nuffield College, Oxford (1999-2000). Education: PhD in Economics, Tel Aviv University (1999) Affiliations: Professorships at Tel Aviv University (2009–present) and UCL (2006–present) Research Interests: Spiegler’s work explores how bounded rationality shapes economic outcomes, including consumer decision-making, market competition, and the role of narratives in political mobilization. He has authored influential books like Bounded Rationality and Industrial Organization (2011) and The Curious Culture of Economic Theory (2024), which critique and expand economic theory’s methodologies. Recent Articles: His recent work examines topics such as false narratives in politics, monopolistic data practices, and competitive markets with imperfectly discerning consumers. These studies highlight interdisciplinary applications of economic theory to modern challenges like algorithmic transparency and platform economics. Awards: Prize Research Fellow, Nuffield College, Oxford (1999–2000) Grants & Labs: While specific grants are not detailed, his research is funded through institutional affiliations. He collaborates widely, with notable co-authors like Kfir Eliaz and Yair Antler.

Mei-Po Kwanمشاهده پروفایل

استاد

• Geographic Information Science (GIS)
• Environmental Health
• Urban Mobility
• +۷ مورد دیگر

Mei-Po Kwan is a distinguished academic holding multiple roles at The Chinese University of Hong Kong (CUHK). She serves as the Head of Chung Chi College, Choh-Ming Li Professor of Geography and Resource Management, Director of the Institute of Space and Earth Information Science, and Professor at The Jockey Club School of Public Health and Primary Care. Her research focuses on geospatial health, urban mobility, environmental health, and innovative GIS methods, emphasizing individual-level environmental exposure and social disparities. Education: Ph.D. Geography, University of California, Santa Barbara (1994) M.A. Urban Planning, University of California, Los Angeles (1989) B.SoSci. Geography, The Chinese University of Hong Kong (1985) Research Interests: Dr. Kwan’s work bridges health, transport, and environmental geography, leveraging cutting-edge GIS and mixed-methods approaches. Key themes include: Uncertain Geographic Context Problem (UGCoP) and Neighborhood Effect Averaging Problem (NEAP) GIS-based analysis of greenspace, air/noise pollution, and mobility Geospatial AI and real-time sensing technologies Health disparities in urban environments Grants & Awards: She has secured over $68 million in research funding, including recent grants from the Hong Kong Research Grants Council and Innovation and Technology Commission. Notable awards include Fellowships from the American Association of Geographers, Royal Geographical Society, and multiple Highly Cited Researcher recognitions (2019, 2021). Professional Service: Editor of Annals of the American Association of American Geographers , founder of the International Geospatial Health Research Network, and member of prestigious editorial boards and advisory councils. Labs & Teams: Leads the Institute of Space and Earth Information Science and collaborates on projects like the 15-minute city framework, carbon monitoring systems, and geospatial health analytics.

Melanie Weberمشاهده پروفایل

استادیار

• Geometric Machine Learning
• Optimization on Manifolds
• Non-Euclidean Machine Learning
• +۳ مورد دیگر

Melanie Weber is an Assistant Professor of Applied Mathematics and Computer Science at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS), leading the Geometric Machine Learning Group. Her research focuses on leveraging geometric structures in data for designing efficient machine learning and optimization algorithms with theoretical guarantees. She holds a PhD from Princeton University (2021) and has held fellowships at the Mathematical Institute of Oxford, Brasenose College, and the Simons Institute. Her work bridges geometry, optimization, and machine learning, with funding from NSF, Sloan Foundation, and Harvard initiatives. Education : PhD in Applied Mathematics, Princeton University (2021) BSc/MSc in Mathematics and Physics, University of Leipzig (2016) Research Interests : Dr. Weber's research integrates geometric principles into machine learning and optimization, focusing on non-Euclidean spaces, graph structures, and manifold-based methods. Key areas include optimization on Riemannian manifolds, curvature-based analysis (e.g., Ricci curvature), and developing algorithms resilient to data geometry challenges like over-smoothing in graph neural networks. Her work emphasizes theoretical foundations while addressing practical scalability in high-dimensional data. Awards & Recognition : 2024 Sloan Research Fellowship 2023 Leslie Fox Prize in Numerical Analysis 2023 NSF Grant for Geometric Optimization Grants & Funding : Supported by National Science Foundation (NSF), Alfred P. Sloan Foundation, Aramont Foundation, Harvard Dean’s Fund, and Harvard Data Science Initiative. Labs & Collaborations : Leads the Geometric Machine Learning Group at SEAS, collaborating with institutions like MIT, Max Planck Institute, and industry labs (Facebook, Google, Microsoft). Active in organizing workshops on geometric methods and curvature analysis.

Jonathan C Poberمشاهده پروفایل

دانشیار

• Cosmic Reionization
• Radio Astronomy
• Astrophysics
• +۳ مورد دیگر

Jonathan C. Pober is an Associate Professor of Physics at Brown University, leading research into the Epoch of Reionization (EoR) and Cosmic Dawn through low-frequency radio astronomy. His work focuses on detecting the highly-redshifted 21 cm line emission from neutral hydrogen during the early Universe, addressing challenges in separating this signal from astrophysical and human-generated radio interference. He develops novel analysis techniques and collaborates on cutting-edge experiments like the Murchison Widefield Array (MWA) and the Hydrogen Epoch of Reionization Array (HERA). Education: PhD in Physics, University of California, Berkeley (2013) MA in Physics, University of California, Berkeley (2010) MPhil in Physics, University of Cambridge (2008) BA in Physics, Haverford College (2007) Research Interests: Cosmic Reionization, Radio Astronomy, 21 cm Cosmology, Signal Processing, and Instrumentation Development. His lab explores methods to mitigate radio frequency interference and optimize interferometric calibration for precise EoR measurements. Teaching: Courses include Basic Physics B, Astronomy, Astrophysics and Cosmology, and Advanced Electromagnetic Theory. He emphasizes bridging theoretical concepts with observational techniques in his curriculum. Awards: NASA Roman Technology Fellow Lab & Projects: Directs the Pober Lab at Brown University, advancing experiments like FARSIDE (Farside Array for Radio Science Investigations of the Dark Ages and Exoplanets), a proposed lunar-based array to study the Dark Ages.

Zvonimir Dogicمشاهده پروفایل

دانشگاهی

• Self-Assembly of Materials
• Condensed Matter Physics
• Active Matter
• +۷ مورد دیگر

Zvonimir Dogic is a Research Associate Professor of Physics at the Martin A. Fisher School of Physics, Brandeis University. He leads the Dogic Lab, focusing on self-assembly of active and soft materials, with interdisciplinary work spanning statistical mechanics, biochemistry, and biophysics. His research explores how particle shape, chirality, and entropic forces drive emergent structures in colloidal systems and active matter. He holds a PhD from Brandeis University (2001) and has supervised numerous PhD students now in academic and industrial roles. Notable honors include the 2010 Cozzarelli Prize and the 2013 Andor Insight Award for his work on oscillating microtubule bundles. Research interests include active matter dynamics, liquid crystalline phases, and biomimetic systems. Recent work includes studies on microtubule-based active gels, chiral colloids, and self-organized cilia-like structures. His lab collaborates with institutions like Harvard, the Mayo Clinic, and the Francis Crick Institute. Key funding sources include the NSF MRSEC, W.M. Keck Foundation, and NIH. The lab’s YouTube channel and Science Blog posts highlight breakthroughs like self-propelled emulsions and entropy-driven membrane formation.

George Yinمشاهده پروفایل

استاد

• Stochastic Optimization
• Stochastic Control
• Stochastic Systems Theory
• +۴ مورد دیگر

George Yin is a Professor in the Department of Mathematics at the University of Connecticut (since 2020). Previously, he held the position of Distinguished Professor at Wayne State University (2017–2020) and has been a faculty member there since 1988. He earned his Ph.D. in Applied Mathematics from Brown University in 1987, along with M.S. degrees in Applied Mathematics and Electrical Engineering, and a B.S. in Mathematics from the University of Delaware (1983). His research focuses on stochastic optimization, control theory, stochastic systems, and numerical methods, with applications to biology, finance, and engineering. He has held editorial roles at journals such as SIAM Journal on Control and Optimization and has received prestigious awards including SIAM Fellow (2015), IEEE Fellow (2002), and IFAC Fellow (2014–2017). Key funding includes continuous NSF support since 1989, grants from the Air Force Office of Scientific Research, and others. His work spans theoretical advancements in stochastic systems and practical applications in energy systems, control engineering, and data science. He has advised numerous students and maintains active collaborations internationally. Labs/Teams: Goldenson Center for Actuarial Research, Quantitative Learning Center. Grants: NSF, AFOSR, ARO, NSA, and multiple institutional grants.

Amro Awadمشاهده پروفایل

دانشیار

• Computer Architecture
• Secure Hardware Architectures
• Memory Systems
• +۳ مورد دیگر

Amro Awad is an Associate Professor in the Department of Electrical and Computer Engineering (ECE) at North Carolina State University's College of Engineering. He previously served as an Assistant Professor at the University of Central Florida and as a Senior Member of Technical Staff at Sandia National Laboratories. Dr. Awad earned his Ph.D. and Master's in Computer Engineering from NC State and a Bachelor's from Jordan University of Science and Technology. Research Focus His research spans computer architecture and security, emphasizing secure hardware systems , memory security , and integration of emerging technologies . Key contributions include novel approaches to secure and efficient GPU memory management, FPGA resource scheduling, and DRAM simulation. Publications & Awards Dr. Awad's work appears in top-tier venues like ISCA, MICRO, ASPLOS, and HPCA. He holds six U.S. patents and received the prestigious R. Ray Bennett Faculty Fellow Award and recognition as a Goodnight Early Career Innovator . Funding & Collaborations His research group has been supported by DARPA , Sandia National Laboratories , NSF , Naval Surface Warfare Center , and Air Force Research Lab . Collaborations include AMD Research, Los Alamos National Lab, HP Labs, and Air Force Research Laboratory.

Stefano Galelliمشاهده پروفایل

دانشیار

• Environmental and Water Resources Systems Engineering
• Water Systems
• Energy and the Environment
• +۶ مورد دیگر

Stefano Galelli is a tenured Associate Professor in the School of Civil and Environmental Engineering at Cornell University, where he leads the Critical Infrastructure Systems Lab. He also holds an adjunct position as a Research Scientist at the Lamont-Doherty Earth Observatory, Columbia University. His career spans roles in Singapore, including a Postdoctoral Research Fellow at NUS (2011–2013) and faculty at the Singapore University of Technology and Design (2013–2023). Dr. Galelli earned his B.Sc. (2004), M.Sc. (2007), and Ph.D. (2011) in Environmental and Land Planning Engineering and Information Technology from Politecnico di Milano, Italy. His research focuses on the interactions between critical infrastructure systems and natural environments, emphasizing adaptive management solutions for water-energy systems. Techniques include process-based modeling, climatology, statistical learning, control theory, and optimization. He explores topics like hydro-climatic variability impacts, dam re-operation for environmental flows, and cyber-physical security in infrastructure. His contributions to journals such as Nature Sustainability, Earth’s Future, and Environmental Modelling & Software have earned him multiple awards, including the Early Career Research Excellence Award (2014) and SUTD Excellence in Research Award (2017). He has served as an editor for several journals and is recognized for advancing interdisciplinary approaches to water-energy nexus challenges. Teaching highlights include foundational mathematics courses and advanced topics in data analytics, optimization, and water-energy management. He is developing new courses on data-driven control of coupled human-natural systems and risk management for interconnected systems.

Ahmed El Alaouiمشاهده پروفایل

استادیار

• High-Dimensional Statistics
• Probability Theory
• Algorithms on Random Structures
• +۴ مورد دیگر

Ahmed El Alaoui is an Assistant Professor in the Department of Statistics and Data Science at Cornell University, with a secondary affiliation in the Department of Computer Science. He joined Cornell in 2021 after completing a postdoctoral fellowship at Stanford University under Andrea Montanari. His research focuses on high-dimensional statistics, probability theory, algorithms on random structures, and statistical physics, with particular emphasis on spin glasses and algorithmic thresholds. El Alaoui holds a PhD in Electrical Engineering and Computer Sciences from UC Berkeley (2018), advised by Michael I. Jordan, and a Master's from Ecole Normale Supérieure/Ecole des Ponts Paristech. His work bridges theoretical and applied domains, addressing challenges in high-dimensional inference, computational trade-offs, and probabilistic models. He has contributed to foundational results in random matrix theory, detection limits in spiked models, and algorithmic approaches to complex systems. His teaching includes courses on high-dimensional statistics, probability models, and theoretical computer science. He has been recognized for his innovative approaches to sampling and optimization in disordered systems, with publications in top journals like Annals of Probability and venues such as NeurIPS and FOCS. El Alaoui's research explores the interplay between statistical physics principles and algorithm design, aiming to uncover computational barriers in high-dimensional problems. His lab develops methodologies for analyzing complex systems and improving the efficiency of statistical estimation in challenging scenarios.

Alan Hammondمشاهده پروفایل

استاد

• Statistical Mechanics
• Mathematical Probability
• Probability Theory
• +۵ مورد دیگر

Alan Hammond is a Professor in the Department of Statistics at the University of California, Berkeley. His research focuses on rigorous mathematical probability techniques applied to problems in statistical mechanics, including percolation theory, polymer models, and random growth processes. He has contributed to understanding critical phenomena, phase transitions, and universality classes in stochastic systems. Hammond's work spans topics such as KPZ universality, Brownian motion, and the geometry of random media. He has investigated models like last passage percolation, self-avoiding walks, and tug-of-war games, often uncovering deep connections between stochastic processes and nonlinear PDEs. His teaching includes courses on stochastic processes and statistical theory at both graduate and undergraduate levels. Notable research highlights include studies on fractal properties of Airy processes, stability in dynamical last passage percolation, and the behavior of geodesics in random environments. His contributions bridge probability theory with applications in physics and combinatorics.