Find Academic Supervisors

Igor VladimirovView profile

Academic

• Quantum Stochastic Control
• Stochastic Robust Control
• Mathematical Systems Theory
• +3 more

Dr. Igor Vladimirov is a Senior Research Fellow at the School of Engineering, Australian National University. He holds a Ph.D. in Physics and Mathematics (1992) and an M.Sc. in Control Systems (1989) from the Moscow Institute of Physics and Technology. His research focuses on quantum stochastic control, stochastic robust control, and mathematical systems theory, with applications to quantum memory systems and nonlinear dynamics. Dr. Vladimirov has held academic positions at the University of Queensland (1997–2008), the Institute for Information Transmission Problems (1994–2007), and UNSW Canberra (2009–2016). He received the B.N. Petrov Prize (2013) and the European Control Conference Best Paper Award (2024). His work spans quantum control, stochastic systems, and statistical mechanics, with a focus on coherence preservation, robust filtering, and system stability. Research Interests: Quantum stochastic control and decoherence Stochastic robust filtering and control Nonlinear feedback systems and negative imaginary systems Statistical mechanical lattice models and transport phenomena Awards: B.N. Petrov Prize (Russian Academy of Sciences, 2013) European Control Conference Best Paper Award (2024) Notable Contributions: His recent work includes optimizing quantum memory decoherence times using mean square criteria and developing coherent quantum LQG controllers. His research bridges quantum dynamics, stochastic processes, and control theory.

Michele Coti ZelatiView profile

Professor

• Partial Differential Equations
• Infinite-Dimensional Dynamical Systems
• Fluid Dynamics
• +4 more

Michele Coti Zelati is a Royal Society University Research Fellow and Professor of Mathematics at Imperial College London's Department of Mathematics within the Faculty of Natural Sciences. Her research focuses on partial differential equations, particularly infinite-dimensional dynamical systems, fluid dynamics, and nonlocal equations, supported by grants from the EPSRC Horizon Europe Guarantee and Royal Society. She contributes to editorial boards of journals including the Journal of Functional Analysis and Proceedings of the Royal Society of Edinburgh Section A: Mathematics. Current affiliation: Imperial College London (Faculty of Natural Sciences, Department of Mathematics) Previous roles: Chapman Fellow (Imperial), Brin Postdoctoral Fellow (University of Maryland) Key research areas include: Enhanced dissipation and mixing mechanisms Stability of shear and stratified flows Stochastic effects in fluid dynamics Dynamo action and magnetic field amplification Asymptotic behavior of PDEs Scientific awards: Royal Society University Research Fellowship EPSRC Horizon Europe Guarantee grant (EP/X020886/1) Former ERC-StG STABLE-CHAOS grant She teaches courses on partial differential equations, statistical mechanics in fluid flows, and Landau damping, with historical teaching roles spanning stochastic differential equations to advanced calculus. Her work appears in top journals like Archive for Rational Mechanics and Analysis, Communications in Mathematical Physics, and Annals of PDE.

Konstantin ZuevView profile

Teaching Professor

• Statistical Data Analysis
• Network Data Analysis
• Machine Learning
• +7 more

Konstantin Zuev is a Teaching Professor of Computing and Mathematical Sciences at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science. He holds dual Ph.D.s in Mathematics (Lomonosov Moscow State University) and Civil Engineering (Hong Kong University of Science & Technology). Zuev is also the Undergraduate Option Representative for Information and Data Sciences and Graduate Minor Advisor for the same field. His research focuses on statistical data analysis, network science, machine learning, and computational methods for complex systems. His teaching includes courses like Applied Linear Algebra, Probability Models, and Statistical Inference. Zuev has received multiple prestigious awards, including the 2023 ASCIT and GSC Teaching Awards, the 2021 Humboldt Research Fellowship, and the 2019 Northrop Grumman Prize for Excellence in Teaching. His work spans interdisciplinary topics such as financial market dynamics, epidemiological modeling, and academic curriculum analysis through network theory. Zuev’s research has been published in journals like *Proceedings of the National Academy of Sciences*, *Scientific Reports*, and *Physical Review E*. He is actively involved in consulting projects with organizations like Virtualitics, Inc., focusing on applications in healthcare and network analytics. Beyond academia, he advises student groups like the Caltech Chess Club and Karate Club, reflecting his passion for fostering community engagement and mentorship.

Marco GeraciView profile

Professor

• Statistical Methods in Health Sciences
• Quantile Inference
• Random-Effects Models
• +9 more

Marco Geraci is a Professor at the Department of Methods and Models for Economy, Territory and Finance at Sapienza University of Rome . He teaches courses such as Statistics for Health Economics and Computational Tools for Finance . His research focuses on Statistical Methods in Health Sciences , including Quantile Inference , Random-Effects Models , Multivariate Statistics , and Missing Data Analysis . He also specializes in Accelerometer Data , Physical Activity , and Pediatric Oncology . His recent publications emphasize Quantile Regression applications in Public Health , Environmental Science , and Health Economics . Methodological contributions include Directional Quantile Classifiers , Functional Quantile Regression , and Laplace Distribution Projections . Themes span Biostatistics , Surgical Safety , and Maternal/Child Health Disparities .

Philippe GuyenneView profile

Professor

• Nonlinear Waves
• Water Waves
• Complex Fluids
• +9 more

Philippe Guyenne is a Professor in the Department of Mathematical Sciences at the University of Delaware, affiliated with the College of Arts & Sciences. His research focuses on nonlinear wave phenomena in fluids, with applications to oceanography and coastal engineering. Nonlinear water waves Wave breaking dynamics Complex fluid-structure interactions Hamiltonian systems Wave turbulence Biomechanics applications Guyenne employs advanced numerical methods and mathematical modeling to study wave behavior, including validation against laboratory experiments and field measurements. Recent work explores connections between surface wave dynamics and quantum mechanics analogies. His publications highlight interdisciplinary impacts in computer graphics, climate modeling, and acoustics. Research themes include: Fluid-structure interactions in bone acoustics Stochastic modeling of random topography effects Coherent wave superposition mechanisms Hamiltonian formulations for physical oceanography Optical flow estimation using fluid dynamics Weak turbulence kinetic theory

• Inverse dynamics
• Structural health monitoring
• Linear and nonlinear vibrations
• +5 more

Dr. Hamed Kalhori is a Lecturer in the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), Faculty of Engineering & Information Technology. As a Casual Academic, he contributes to teaching and research in mechanical engineering with a focus on dynamics, vibrations, and structural health monitoring. His work bridges theoretical and practical applications in civil infrastructure, aerospace systems, and composite materials. Dr. Kalhori earned his PhD in Mechanical Engineering from the University of Sydney between March 2013 and July 2017. Dr. Kalhori's research spans multiple domains within mechanical and structural engineering. His primary expertise lies in inverse dynamics problems , particularly impact force identification, where he develops advanced methodologies combining model-based approaches with machine learning techniques. He extensively investigates linear and nonlinear vibrations in various structures, from micro-plates to large-scale bridges. His work in structural health monitoring focuses on innovative approaches for bridge inspection, including drive-by assessment techniques and sensor network optimization. Additionally, he explores smart materials and structures , particularly carbon nanotube-reinforced composites and their mechanical behavior under dynamic loading conditions. Dr. Kalhori's publication record demonstrates a strong trajectory in mechanical engineering research with increasing focus on interdisciplinary approaches. His recent work shows growing integration of machine learning techniques with traditional mechanical engineering methods, particularly for solving inverse problems in structural dynamics. There's a clear progression from fundamental vibration analysis toward practical applications in infrastructure monitoring and composite material characterization. His research maintains strong connections between theoretical modeling and experimental validation across diverse structural systems. Dr. Kalhori has received notable recognition for his academic contributions: 2019 Dean's Award for Excellence in Teaching and Tutoring Multiple research grants in vibration-related fields Dr. Kalhori has secured research funding for projects related to vibration analysis and structural monitoring, including industry collaborations such as the Alstom DMU traincar crash test project (2025). He has led international research collaborations and conducted numerous workshops and short courses both locally and internationally. While the specific details of his advising relationships aren't provided in the available information, his extensive publication record and research leadership suggest active engagement with graduate students and early-career researchers. His research involves collaboration with the Centre for Autonomous Systems at UTS and Data61-CSIRO, where he previously worked as a research associate and research assistant respectively. These collaborations focus on structural health monitoring projects across New South Wales, leveraging advanced sensing technologies and computational methods for infrastructure assessment.

• Probability Theory
• Mathematical Finance
• Stochastic Analysis
• +4 more

Peter K. Friz is Einstein Professor in Mathematics at Technische Universität Berlin (TU-Berlin), where he leads research in the Probability Theory and Mathematical Finance group. He is also affiliated with the Weierstrass Institute for Applied Analysis and Stochastics (WIAS), a major research institute in Berlin focused on applied mathematics. Professor Friz's research spans several interconnected areas of mathematics and finance: Stochastic analysis and rough path theory Quantitative finance and volatility modeling Partial differential equations driven by rough paths Applications of rough path theory to financial mathematics His recent publications demonstrate a continued focus on advancing rough path theory and its applications. The research trends show increasing sophistication in handling nonlinear rough differential equations, connections to machine learning through signature methods, and deeper applications to financial modeling, particularly in volatility analysis. His work bridges pure mathematical theory with practical financial applications, maintaining relevance to industry problems while advancing theoretical foundations. Professor Friz has received significant recognition for his work: ERC Starting Grant "Rough path theory, differential equations and stochastic analysis" (2010-2016) ERC Consolidator Grant "Geometric aspects in pathwise stochastic analysis and related topics" (2016-2021) Einstein Professorship at TU-Berlin He actively mentors students and researchers, with a list of former PhD students available through his academic profile. Professor Friz coordinates the DFG research unit "Rough paths, stochastic partial differential equations and related topics" (2016-2019) and has secured substantial funding from the European Research Council, DFG, and other sources. His research group regularly hosts seminars and collaborates with institutions worldwide, including recent invited courses at Cambridge, Paris (IHP), and Bonn (HIM). Professor Friz maintains active research collaborations through his position at TU-Berlin and affiliation with WIAS, contributing to Berlin's status as a hub for mathematical finance and stochastic analysis in Europe.

• Latent Variable Models
• Dynamic Latent Variable Models
• Latent Class Methods
• +8 more

Augustin Kelava is a Professor at the Department of Quantitative Methods, Eberhard Karls University of Tübingen. He has held this position since 2018 and leads the Methods Center as Managing Director. Previously, he was Professor at the Hector Institute for Empirical Educational Research (2013-2018) and Junior Professor at Technical University of Darmstadt (2011-2013). PhD in Psychology (Goethe University Frankfurt, 2009) Diploma in Psychology (Goethe University Frankfurt, 2004) Kelava specializes in latent variable modeling, machine learning in social sciences, and educational research. His work spans dynamic latent class models, Bayesian regularization techniques, and prediction of human behavior using intensive longitudinal data. He contributes to psychometric theory (e.g., item response theory extensions) and applies these methods to diverse fields including sports science and emotion regulation. Editor of "Testtheorie und Fragebogenkonstruktion" (3rd ed., Springer, 2020) Key researcher in the Cluster of Excellence "Machine Learning in Science" Active in methodological conferences (FGME 2017, SEM 2019) Review activities for 20+ journals and foundations including Psychometrika, DFG, and SNSF His recent publications focus on integrating machine learning with psychometrics, addressing identifiability in complex models, and evaluating personality assessment validity for large language models. He collaborates with researchers across psychology, education, and computational fields.

• Quantum Nanophotonics
• Plasmonics
• Nonlinear Optics
• +8 more

Prof. Alexandra Boltasseva is the Ron and Dotty Garvin Tonjes Distinguished Professor of Electrical and Computer Engineering at Purdue University, with a courtesy appointment in Materials Engineering. She leads the Quantum Nanophotonics group at the Birck Nanotechnology Center, focusing on plasmonics, metasurfaces, epsilon-near-zero (ENZ) materials, and machine learning-assisted photonics. Her work bridges fundamental research and applications in quantum technologies, nanolasers, and integrated photonic devices. College of Engineering, Purdue University Birck Nanotechnology Center Quantum Science Center Her research interests span quantum nanophotonics , plasmonics with 2D materials , nonlinear optics , and machine learning for photonic design . Recent projects explore photonic time crystals, ENZ-enhanced quantum emitters, and refractory plasmonic materials like MXenes and titanium nitride. The 15 most recent publications highlight trends in quantum light sources (e.g., single-photon emitters in silicon nitride), machine learning applications to optimize nanostructures, and nonlinear photonic materials . Key subfields include 2D materials, photonic time crystals, ENZ optics, and plasmonic enhancement of optoelectronic performance. Scientific accolades include: Optica R. W. Wood Prize (2023) Clarivate Highly Cited Researcher (2024, 2021, 2020, 2017) National Academy of Inventors Fellow (2020) SPIE Fellow (2015) Dimitris N. Chorafas Foundation Award (2021) She advises PhD students like Soham Saha, Shaimaa Azzam, and Deesha Shah, who have received prestigious awards. Her team collaborates on quantum photonics and nanoscale energy distributions of plasmonic hot-carriers.

Patrick FlynnView profile

Assistant Professor

• Partial Differential Equations
• Kinetic Theory
• Fluid Mechanics

Patrick Flynn is an Assistant Professor at the University of California, Los Angeles (UCLA), specializing in Partial Differential Equations , Kinetic Theory , and Fluid Mechanics . His research bridges mathematical analysis with physical modeling in these domains. Research Trends : Flynn's recent publications focus on nonlinear dynamics in kinetic and fluid systems. Key topics include mixing in random fluid flows, well-posedness of kinetic equations, scattering theory for Vlasov systems, and self-organization in biophysical models. Collaborations with prominent researchers like Yan Guo, Benoit Pausader, and Huy Nguyen highlight interdisciplinary applications in plasma physics, fluid mechanics, and mathematical biology. Selected Contributions : 2024 : Studies on the Vlasov-Poisson-Landau system and random fluid mixing. 2021 : Analysis of scattering maps and surface tension limits in fluid models. 2019 : Modeling of self-organized clusters in run-and-tumble processes.

Karoline WiesnerView profile

Professor

• Complexity Sciences
• Information Theory
• Complex Systems
• +7 more

Karoline Wiesner is Professor of Complexity Sciences at the University of Potsdam and an External Faculty member. She previously served as Assistant Professor at the School of Mathematics, University of Bristol, and held postdoctoral positions at the Santa Fe Institute and the University of California, Davis. She holds a PhD in Physics from Uppsala University (2004). Her research lies at the core of complexity sciences and information theory , with applications across diverse fields such as climate systems , democratic stability , and ecological networks . She investigates the formation, maintenance, and stability of complex systems through mathematical and philosophical lenses. Key areas include the foundations of complexity, network robustness, and the role of information in dynamical systems. Her recent publications (2020–2024) demonstrate a strong trend in applying network science and information-theoretic methods to interdisciplinary problems, particularly in social and ecological systems. She frequently collaborates across disciplines, contributing to collective works on democracy and complex systems. Her co-authored book What is a Complex System? has become a foundational reference in the field. While no specific scientific awards are listed in the text, her work has received notable press coverage from outlets like PhysicsWorld and Motherboard (VICE) , highlighting its societal relevance. Karoline actively advises interdisciplinary research and contributes to major workshops, such as those at the Complexity Science Hub. She has no listed PhD students in the provided text. She leads and participates in collaborative projects focused on understanding civil conflict, democratization, and systemic risk through statistical physics and complexity theory. She is involved with research groups and initiatives centered on complexity, including the Foundations and Collective Minds themes, and contributes to the Data Analytics cluster. Her work bridges physics, philosophy, political science, and ecology, forming a transdisciplinary approach to understanding systemic stability and change.

Wen LuoView profile

Assistant Professor

• Failure Risk of Materials and Structures
• Stochastic Fracture Mechanics
• Instabilities and Buckling
• +7 more

Wen Luo is an Assistant Professor in the Department of Aerospace Engineering at Auburn University's College of Engineering. He conducts research on structural reliability for aerospace applications, focusing on failure risk modeling, stochastic fracture mechanics, and advanced composite manufacturing. His work sits at the intersection of nonlinear mechanics, reliability engineering, and next-generation aerospace structures. Education: Ph.D. in Theoretical and Applied Mechanics, Northwestern University M.S. in Theoretical and Applied Mechanics, Northwestern University B.S. in Flight Vehicle Manufacturing Engineering, Northwestern Polytechnical University Dr. Luo's research aims to design super reliable, lightweight aerospace structures to reduce the levelized cost of space systems. His lab, the Aerospace Structures Reliability Lab, investigates instabilities, buckling, and failure risks across scales, emphasizing the role of randomness in structural performance. The lab actively works on integrating reliability into the design and manufacturing processes of composite structures for space applications. Although no publications are listed in the provided text, his research direction emphasizes modeling failure risks in lightweight structures using stochastic methods and nonlinear mechanics principles. This suggests a strong focus on probabilistic structural analysis, computational mechanics, and reliability-based design optimization for aerospace systems. Scientific Awards: Dr. Luo is currently recruiting Ph.D. and undergraduate researchers interested in lightweight structures, advanced composites, and failure risk modeling. He advises prospective students to contact him directly via email. There is no mention of external grants in the text, but his lab's active recruitment and research direction suggest ongoing research funding. He leads the Aerospace Structures Reliability Lab at Auburn University, which focuses on developing next-generation, cost-effective, and highly reliable aerospace structures through interdisciplinary approaches combining mechanics, materials science, and manufacturing innovation.

• Environmental Health
• Epidemiology
• Air Pollution
• +9 more

Carlos Gould is an Assistant Professor at the University of California, San Diego (UCSD) in the Herbert Wertheim School of Public Health & Human Longevity Science. He holds a PhD in Environmental Health Sciences from Columbia University Mailman School of Public Health and completed a postdoctoral fellowship in Earth System Science at Stanford University. He received his BA in Environmental Studies from Yale University. His academic journey reflects a deep commitment to environmental health and sustainability. His research focuses on the health impacts of environmental exposures such as air pollution and temperature extremes, with a particular emphasis on vulnerable communities. He investigates interventions like the transition from traditional biomass to clean cooking fuels and the shift from gas to electric cooking, aiming to reduce pollution, improve health outcomes, and mitigate climate change. His work integrates epidemiological methods with exposure science to evaluate real-world interventions in countries including Ghana, India, Ecuador, and the United States. Gould's research directly informs public health policy and climate adaptation strategies. His recent publications span high-impact journals such as Nature , PNAS , and Environmental Health Perspectives , covering themes like wildfire smoke health effects, clean cooking transitions, and indoor air quality. His work has been widely recognized, with significant media coverage, policy references, and academic engagement. Stanford Earth Postdoctoral Fellow (2021–2023) Senior Agents of Change Fellow In the classroom, he teaches 'Introduction to Environmental and Occupational Health' and 'Data Visualization in Health Sciences' at UCSD, emphasizing real-world applications and open-source tools like R. He mentors students and fosters interdisciplinary collaborations. There is no indication of him being retired, deceased, or a former staff member; he is an active and influential faculty member in environmental health science.

Silvia CalderazzoView profile

Researcher

• Bayesian Statistics
• Clinical Trial Design
• Markov Models
• +5 more

Dr. Silvia Calderazzo is a researcher specializing in Bayesian statistics and its applications in clinical and biomedical research. Her work centers on statistical methodology for clinical trial design, dose-response modeling, and inference in complex biological systems. Research Interests: Her primary areas include Bayesian clinical trial design, Markov models, and statistical modeling of dose-response relationships. She applies advanced statistical techniques to problems in toxicology, oncology, and public health, with a strong methodological focus. Publication Trends: Her recent publications (2018–2019) show a consistent emphasis on Bayesian methods, particularly in quantifying prior information, incorporating external data in trials, and modeling biological and toxicological responses. These works appear in top journals such as JAMA , Biometrics , and Archives of Toxicology , reflecting both methodological rigor and clinical relevance. Education: PhD in Statistics, University of Warwick, UK (2017) Master degree in Statistics, University of Padua, Italy (2012) Bachelor degree in Statistics, population and society, University of Padua, Italy (2010) Scientific Awards: Advising and Grants: No information is available regarding students advised or research grants received. Labs and Teams: While specific lab affiliations are not mentioned, her collaborative publications suggest involvement in interdisciplinary research teams focused on biostatistics and translational medicine.

Jianshu CaoView profile

Professor

• Quantum Dynamics
• Single Molecule Kinetics
• Complex Liquids
• +3 more

Jianshu Cao is a Professor of Chemistry at the Massachusetts Institute of Technology (MIT). He leads the Cao Group, which focuses on theoretical models for understanding complex molecular systems, bridging quantum mechanics and experimental observables to study chemical and biological processes across time and length scales. His research spans quantum dynamics, single-molecule kinetics, complex liquids, and biomechanics, with applications in photosynthesis, nanotechnology, and biophysics. Key areas of research include quantum transport, exciton dynamics in light-harvesting systems, and the interplay between quantum coherence and biological processes. His group develops novel methods like the transfer tensor method (TTM) for simulating long-time quantum dynamics and explores cavity quantum electrodynamics (QED) effects in van der Waals systems. Collaborations involve experimental groups to validate theoretical findings in areas such as perovskite nanocrystals and malaria-infected erythrocyte biomechanics. Recent work includes studies on first-passage time fluctuation theorems, polariton dynamics in microcavities, and nonclassical state generation in light-matter systems. Cao supervises a dynamic team of postdoctoral associates, graduate students, and undergraduates, fostering interdisciplinary approaches to quantum phenomena in condensed matter and biological systems.