جست‌وجوی استاد و پژوهشگر

Andres Marcos Encinas Bachillerمشاهده پروفایل

استاد

• Discrete Mathematics
• Network Analysis
• Linear Algebra
• +۴ مورد دیگر

Andres Marcos Encinas Bachiller is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Faculty of Mathematics and Statistics and the Department of Mathematics. He holds a Licenciado and Doctorado in Mathematics from the same institution. Professional Category: University Titular (equivalent to Professor). Research Groups: MAPTHE (Matrix Analysis and Discrete Potential Theory), OMGRAPH (Optimization Methods on Graphs). His research focuses on discrete vector calculus, boundary and inverse problems on networks, effective resistance, and M-matrix theory. He has contributed extensively to matrix analysis and its applications in network science, particularly in electrical impedance tomography and graph theory. Recent work includes studies on tridiagonal M-matrices, group inverses, and applications in medical imaging through discrete inverse problems. His articles span linear algebra, network analysis, and combinatorial matrix theory, with a focus on theoretical and applied aspects of these fields. He has supervised doctoral research, including Álvaro Samperio Valdivieso's thesis on inverse problems in networks. His projects include developing EIT devices for breast cancer detection and optimizing methods on graphs. Collaborations involve researchers in algebra, engineering, and applied mathematics. He is actively involved in research networks, including the ALAMA network (Linear Algebra and Matrix Analysis), and has led competitive projects funded by Spanish and Catalan agencies.

• Applied Mathematics
• Materials Science
• Continuum Mechanics
• +۳ مورد دیگر

Riccarda Rossi is an Associate Professor at the Department of Information Engineering (DIMI) , University of Brescia. Her research focuses on mathematical analysis of complex systems, particularly rate-independent processes, damage mechanics, and gradient flows in metric spaces. She has contributed to theories of elastoplasticity, viscoelasticity, and fracture mechanics, emphasizing rigorous existence and uniqueness results for PDE systems. Education details are not explicitly listed, but her work spans interdisciplinary areas combining calculus of variations, nonlinear PDEs, and applied analysis. Recent research includes models for adhesive contact, phase transitions, and coupled multi-physical phenomena. Research Themes : Rate-independent systems and their viscous approximations Damage and fracture mechanics Generalized gradient flows in metric spaces Thermodynamic consistency in material models Her work frequently appears in top journals like Archive for Rational Mechanics and Analysis, SIAM Journal on Mathematical Analysis, and Mathematical Models and Methods in Applied Sciences. She has collaborated extensively with researchers such as Alexander Mielke, Giuseppe Savaré, and Marita Thomas. Rossi has organized workshops and given invited talks at international conferences on partial differential equations and calculus of variations. Current research directions include singular limits for coupled systems and non-smooth dynamics in continuum mechanics.

Bruno Chiariniمشاهده پروفایل

استاد

• Econometric Analysis
• Economic Modelling
• Stochastic Dynamic General Equilibrium Models
• +۴ مورد دیگر

Bruno Chiarini is a Full Professor of Economics at the Department of Economics and Legal Studies, University of Napoli 'Parthenope'. He holds academic appointments at multiple institutions, including the University of Rome Tor Vergata, where he teaches Industrial Economy and Strategic Behaviour. His professional roles extend beyond academia, serving as an advisor to the Italian Labour Ministry, Budget Ministry, and NARS-CIPE. He has also been involved in national research coordination (PRIN 2006 and 2008) and editorial work as Chief Editor of the Open Economic Journal. Chiarini's educational background includes degrees from the University of Rome 'La Sapienza' (Bachelor), University of Manchester (M.A.), and University of Southampton (Ph.D.). He has held visiting scholar positions at Columbia University's School of Business and Economic Department, and contributed to the Coase-Sandor Institute for Law and Economics in Chicago. His research focuses on econometric analysis, stochastic dynamic models, fiscal policy (particularly tax evasion and the informal economy), and game theory applications. He has advised governmental bodies on economic policy and regulatory frameworks, reflecting his interdisciplinary expertise in economics and legal studies.

Garud N. Iyengarمشاهده پروفایل

استاد

• Machine Learning
• Optimization
• Control Systems
• +۶ مورد دیگر

Garud N. Iyengar is the Avanessians Director of Columbia University's Data Science Institute (DSI) and a Professor of Industrial Engineering and Operations Research at The Fu Foundation School of Engineering and Applied Science. He leads over 400 affiliated faculty in DSI's research and education initiatives and co-leads Columbia's Artificial Intelligence Initiative. His research focuses on control systems, machine learning, and optimization, with applications in power systems, supply chains, causal inference, and cellular processes. He holds two patents and has authored over 90 publications. Education: BTech in Electrical Engineering from IIT (1993), PhD in Electrical Engineering from Stanford (1998). Leadership roles include Senior Vice Dean for Research at Columbia Engineering (2021-2024), department chair (2013-2019), and DSI Associate Director for Research (2017-2019). His work has been funded by NSF, ONR, and DOE. Research interests span optimization theory, machine learning applications, and interdisciplinary systems analysis. Notable projects include game-theoretic logistics modeling, blockchain in supply chains, and cellular information processing. Awards include INFORMS Fellow (2018) and Amazon Scholar (2019-2024). Grants and advising: Extensive funding history across energy systems, AI, and operations research. Active in mentoring and shaping DSI's postdoctoral and seed funding programs. Collaborates on technologies like SmartGraph AI databases and interpretable decision systems. Labs/Teams: Core contributor to DSI's interdisciplinary research ecosystem, leading teams in AI, optimization, and data-driven decision making. Involved in multi-disciplinary initiatives bridging engineering, computer science, and life sciences.

• Biophysics
• Neuroscience
• Cell Biology
• +۳ مورد دیگر

Victor Matveev is a Professor in the Department of Mathematical Sciences at New Jersey Institute of Technology (NJIT). His research focuses on biophysical modeling of calcium-dependent processes in cellular systems, particularly presynaptic calcium signaling and synaptic plasticity. He has led multiple NSF-funded projects exploring calcium dynamics, including studies on cell calcium spatiotemporal dynamics and mechanisms of synaptic facilitation. Key research areas include calcium nanodomains, synaptic vesicle fusion mechanisms, and mathematical approaches to modeling neural systems. His work bridges applied mathematics, neuroscience, and biophysics, with applications in understanding cellular communication pathways. Recent projects include the 2022 FACM conference on mathematical biology and a 2015 NSF grant studying cell calcium dynamics. He collaborates with researchers in computational neuroscience, as evidenced by contributions to the Encyclopedia of Computational Neuroscience (2022). Grants and funding history spans over two decades, with notable projects on presynaptic calcium dynamics (2004-2008), spatiotemporal calcium dynamics (2015-2018), and applied mathematics conferences (2022-2023). His research outputs combine theoretical modeling with experimental insights, yielding 39 publications and over 1,100 citations.

Rich Kerswellمشاهده پروفایل

استاد

• Fluid Mechanics
• Nonlinear Dynamics
• Turbulence
• +۶ مورد دیگر

Professor Rich Kerswell is a faculty member in the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge since 2017. Previously, he held positions at the University of Bristol (1996-2017) and Newcastle University (1992-1996), following his PhD from MIT (1992). His research focuses on general fluid mechanics, including the Navier-Stokes equations, nonlinear dynamics, turbulence transition, and geophysical/astrophysical fluid mechanics (e.g., convection, stratified flows, planetary interiors). He explores phenomena such as tidal and precessional motions, accretion disks, and the interplay between elasticity and inertia in complex fluids. Recent work emphasizes fluid instabilities in viscoelastic flows, polymer solutions, and stratified systems, leveraging machine learning techniques like autoencoders and neural networks to analyze turbulence and coherent structures. His contributions include studies on boundary condition optimization, burst event prediction, and the polymer diffusive instability in high-concentration fluids. Key trends in his articles involve advancing understanding of turbulent transition mechanisms, developing novel numerical methods for fluid modeling, and applying data-driven approaches to complex flow systems. His research bridges fundamental fluid dynamics with applications in geophysics, astrophysics, and engineering.

Sebastian Soteloمشاهده پروفایل

دانشیار

• International Trade
• Labor Economics
• Political Economy
• +۳ مورد دیگر

Sebastian Sotelo is an Associate Professor in the Department of Economics at the University of Michigan and a Research Associate at the National Bureau of Economic Research (NBER). His research focuses on international trade, labor economics, political economy, and environmental economics, with an emphasis on structural change, trade policies, and their socio-economic implications. He has conducted influential work analyzing the impact of trade liberalization, occupational trends, and corporate political speech. Research Highlights: Explores how domestic and global trade dynamics affect labor markets and economic inequality Examines environmental consequences of deforestation linked to global supply chains Investigates historical patterns of migration and economic specialization in Brazil and Latin America Develops econometric methods for analyzing trade and technology impacts Teaching & Professional Roles: Currently teaches advanced courses in international economics, trade theory, and applied econometrics at the University of Michigan Previously instructed undergraduate and graduate courses on international finance and trade policy Recipient of the AEJ: Applied Economics Best Paper Award (2023) for groundbreaking work on occupational evolution His research frequently employs quantitative methods to bridge micro and macroeconomic perspectives, with notable contributions to understanding how technological and trade-driven structural changes reshape labor markets and regional economies. Co-authored studies often address pressing policy questions related to development, sustainability, and global economic integration.

• Numerical Simulation Techniques
• Fluid Dynamics
• Heat Transfer
• +۷ مورد دیگر

Brian Helenbrook is a Professor and the Paynter-Krigman Endowed Chair in Engineering Science Simulation at Clarkson University’s Coulter School of Engineering & Applied Sciences. He also serves as Associate Dean of Continuing & Professional Education. His expertise spans numerical simulation techniques for fluid flows and heat transfer, with a focus on adaptive ALE finite element methods. Research applications include solidification modeling for silicon/aluminum manufacturing, droplet dynamics, and aerodynamic optimization of Olympic luge sleds. Education: B.S. from University of Notre Dame (1991), Ph.D. from Princeton University (1997) Postdoctoral: Stanford University (Applied Strategic Computing Initiative) Fellowships: NASA Langley (2002), NASA Kennedy (2005) Research Interests emphasize high-order accuracy simulations, multiphase flows, and interdisciplinary applications like ducted wind turbines and crystal growth. He has published 50+ peer-reviewed articles and mentored 22 graduate students (13 Ph.D., 9 M.S.). Awards include Clarkson’s Distinguished Teaching Award (2014), τβπ and πτσ teaching accolades, and membership in the Million Dollar Club recognizing $1M+ in research funding. Grants: Supported by NSF, NASA, AFOSR, NYS Energy, and industry. Active in the Center for Advanced Materials Processing (CAMP) and Institute for a Sustainable Environment. Labs/Teams: Leads projects in thermal simulation, reduced-order modeling, and fluid-structure interaction.

• Exoplanet science
• Theoretical astrophysics
• Planetary science
• +۴ مورد دیگر

Prof. Dr. Kevin Heng is a Full Professor (Chair) of Theoretical Astrophysics at Ludwig Maximilian University of Munich, leading the Munich Centre for Geoastronomy. He holds honorary professorships at University College London and University of Warwick. His research focuses on exoplanetary atmospheres, radiative transfer, and geoastronomy, blending astrophysics with geochemistry. He has pioneered studies on ultra-hot Jupiters and developed influential textbooks like Exoplanetary Atmospheres: Theoretical Concepts and Foundations (2017). Education: Ph.D. (2007) and M.S. (2005) in Astrophysics from University of Colorado Boulder; B.Sc. (2003) from National University of Singapore. Culinary School of the Rockies graduate (2006). Research Interests: Exoplanet atmospheric dynamics, radiative transfer, machine learning applications, and mission leadership (ARIEL, CHEOPS). He has secured major grants including ERC Synergy (€10M) and Consolidator (€1.98M) grants. Awards: Chambliss Astronomical Writing Award (2018), Fellow of Royal Astronomical Society (2023), and Member of Academia Europaea (2024). His work on KELT-9b's metallic atmosphere (2018) and Jupiter phase curves (2021) are landmark studies. Service: Chair of ERC panels, IAU Division F Vice-President, and organizer of Exoplanets by the Lake conferences. Leads international teams for missions like ARIEL and Twinkle. Labs/Teams: Heads the Exoplanet Theory Group at LMU, collaborating with institutions globally on atmospheric retrieval and climate modeling.

Davide Promentمشاهده پروفایل

دانشیار

• Nonlinear Dynamics
• Quantum Fluids
• Superfluids
• +۶ مورد دیگر

Davide Proment is an Associate Professor in Applied Mathematics at the University of East Anglia (UEA), affiliated with the School of Engineering, Mathematics, and Physics. He is a member of the Centre for Photonics and Quantum Science and Quantum Matter research groups. His work bridges theoretical physics and applied mathematics, focusing on nonlinear systems, quantum fluids, and turbulence dynamics. Proment holds a PhD from Università degli Studi di Torino (2010) and has held postdoctoral roles, including research on extreme seas at the European Research Council. Education : Doctor of Science (2010), Turbulence in open systems: a weakly nonlinear approach Master of Physics (2007), The Gross-Pitaevskii equation and Bose-Einstein condensates Bachelor of Science (2005), Variational approach to the three-body problem Research Interests : Focuses on quantum fluids (e.g., superfluid vortices, phonon interactions), water wave dynamics (rogue waves), nonlinear optics (solitons), and discrete systems like anharmonic chains. Employs numerical simulations and theoretical frameworks from turbulence, statistical mechanics, and integrable systems. Awards : Young Scientist Award (2019) François Frenkiel Award for Fluid Mechanics (2018) Grants & Activities : Principal investigator on projects funded by EPSRC and the London Mathematical Society Visiting researcher at Université de Lille, Observatoire de la Côte d'Azur, and Heidelberg University Labs & Collaborations : Active in quantum matter and photonics research at UEA, with collaborations in fluid dynamics, turbulence modeling, and nonlinear wave studies.

David C. Parkesمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Algorithmic Economics
• +۲ مورد دیگر

David C. Parkes is the George F. Colony Professor of Computer Science and John A. Paulson Dean at Harvard University's School of Engineering and Applied Sciences. His research in economics and computation spans multi-agent systems, market design, and AI safety. He leads the Economics and Computer Science Research Group and contributes to Harvard's Data Science Initiative. Research focuses on algorithmic game theory, differentiable economics, and multi-agent AI systems. Recent work develops deep learning methods for auction design and analyzes risks in advanced AI systems. Current projects include transformer architectures for combinatorial optimization and platform equilibrium modeling. Honors include election as AAAS Fellow (2022). He currently supervises doctoral students in multi-agent systems, algorithmic economics, and machine learning applications.

Salem Abo-Zaidمشاهده پروفایل

استاد

• Monetary Economics
• Macroeconomics
• Fiscal Policy
• +۳ مورد دیگر

Salem Abo-Zaid is a Professor of Economics at the University of Maryland, Baltimore County (UMBC), where he holds a faculty position in the Department of Economics. He earned his Ph.D. in Economics from the University of Maryland, College Park in 2011. His research focuses on Monetary Economics, Macroeconomics, Fiscal Policy, and Labor-Macro interactions, with secondary interests in International Economics and Computational Economics. Professor Abo-Zaid’s work bridges theoretical and empirical analysis, addressing topics such as monetary policy design, fiscal multipliers, credit market frictions, and labor market dynamics. Notable contributions include studies on the impact of inattention in monetary policy, the role of government spending multipliers, and the distributional effects of monetary policy. His research has been published in top-tier journals like Journal of Applied Econometrics , Macroeconomic Dynamics , and Journal of Economic Dynamics and Control . He currently serves as an Associate Editor for the Journal of Money, Credit & Banking . His recent work explores pandemic-era fiscal and monetary policy interactions, labor market adjustments, and the implications of credit constraints on economic stability. Despite his prolific publications, no scientific awards are explicitly mentioned in the provided texts. Professor Abo-Zaid’s administrative role includes contributing to departmental operations at UMBC’s Public Policy Building. No formal advisees or grants are listed, though his extensive publication record indicates active research collaboration. His research emphasizes policy-relevant analysis with applications to contemporary economic challenges.

Mads Peter Sørensenمشاهده پروفایل

استاد

• Nonlinear Dynamics
• Applied Mathematics
• Superconductivity
• +۵ مورد دیگر

Mads Peter Sørensen is a Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on nonlinear dynamics, superconductivity, and fluid dynamics, with contributions to mathematical modeling in fields such as disease dynamics, traffic flow, and acoustics. He is actively involved in interdisciplinary projects, including studies on methane cracking for carbon production and bacterial biofilm growth in microfluidic systems. His work aligns with UN Sustainable Development Goals related to sustainable energy and health. Key projects include investigations into superconducting elements, nonlinear stochastic models of molecular crystals, and ultra-short optical pulse generation. Sørensen has collaborated internationally, contributing to over 147 publications. Notable recent work includes studies on memory effects in disease modeling and nonlinear oscillations in acoustic systems. He has advised multiple research projects, including those on high-temperature superconductivity and flux dynamics. His research often integrates analytical and numerical methods, addressing both fundamental and applied challenges in nonlinear systems.

• Multi-agent systems
• Artificial intelligence
• Machine learning
• +۸ مورد دیگر

Ho-fung Leung is a Professor at the Department of Computer Science and Engineering, Faculty of Engineering, Chinese University of Hong Kong. With a prolific publication record spanning over three decades, his research has significantly contributed to the fields of artificial intelligence, multi-agent systems, and natural language processing. His educational background, though not explicitly stated in the provided text, likely includes advanced degrees in computer science or a related field, given his extensive research contributions and faculty position at a prestigious university. Professor Leung's research interests span multiple areas within artificial intelligence, with a particular focus on multi-agent systems, reinforcement learning, natural language processing, and human-computer interaction. His work often explores the intersection of theoretical foundations and practical applications, developing novel algorithms and frameworks that address real-world challenges in AI systems. He has made significant contributions to constraint satisfaction problems, trust and reputation systems in multi-agent environments, and more recently to deep learning applications in NLP and human activity recognition. His recent publications demonstrate a strong trend toward applying advanced machine learning techniques to complex problems in natural language understanding, knowledge representation, and human activity recognition. Many of his papers focus on improving the efficiency, robustness, and interpretability of AI systems through innovative architectural designs and learning paradigms. Key research themes include few-shot learning, knowledge-enhanced models, and theoretical analysis of reinforcement learning dynamics. Professor Leung has received recognition for his work through numerous publications in top-tier conferences and journals, though specific awards are not detailed in the provided information. He has supervised numerous students throughout his career, with many of his publications featuring junior researchers in first-author positions. His research group appears to focus on cutting-edge problems in AI, with current projects spanning reinforcement learning theory, knowledge graph applications, and multimodal learning systems. Collaborators include researchers from across CUHK and international institutions. Professor Leung is actively involved in multiple research projects, with recent work focusing on human activity recognition using wearable sensors, knowledge-enhanced language models, and theoretical aspects of reinforcement learning. His research continues to evolve while maintaining strong connections to foundational AI principles, demonstrating remarkable adaptability in a rapidly changing field.

• Probability Theory
• Statistical Mechanics
• Stochastic Processes
• +۴ مورد دیگر

Gioia Carinci is an Associate Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Physical, Computer and Mathematical Sciences. She teaches courses such as Probability and Statistics for Computer Science, Mathematics for Electronic Engineering, and Markov Chains for Mathematics students. Her research focuses on stochastic processes, interacting particle systems, and duality principles in non-equilibrium statistical physics. Teaching: Probability and Statistics (Computer Science) Mathematics for Electronic Engineering (Engineering) Markov Chains (Mathematics) Research Interests: Analysis of Markov chains and their convergence properties Boundary-driven non-equilibrium systems Large deviations and additivity principles Duality in stochastic processes Key Contributions: Derivation of macroscopic properties from microscopic models Study of condensation phenomena in particle systems Development of exact solutions for stationary non-equilibrium states Her work bridges probability theory, statistical mechanics, and applications in mathematical physics. She actively contributes to both theoretical advancements and interdisciplinary collaborations.