Applied Math Field Faculty
Research areas: stochastic modeling and the design of scalable algorithms and incentive mechanisms for large systems; marketing and social computing, control of information flows, learning and recommendation
Research areas: structure learning and prediction of complex, high-dimensional systems arising in biological and social sciences; network modeling of high-dimensional time series and nonlinear ensemble learning methods.
Director, Center for Applied Mathematics Research areas: numerical linear algebra; microelectromechanical systems; network tomography; finite element analysis; numerical software design Rhodes Hall, Room 612 OH: by appointment Bookings page bindel@cornell.edu Office phone: 607-255-5395
Research areas: theoretical and computational solid mechanics, soft materials, active materials and biomaterials, fracture and instabilities, multiscale modeling in coupled, multi-physical systems
Research areas: model selection and averaging (aggregation) in a variety of high dimensional parametric, semi-parametric and nonparametric models, machine learning and empirical processes theory
Research areas: computational complexity theory, pseudorandomness, cryptography, combinatorics, probability
Research areas: complex systems, network science and computation; health systems; transportation; applied probability
Research areas: numerical linear algebra; computational quantum chemistry; spectral clustering and fast algorithms
Research areas: machine learning, data-driven control and decision-making, physical and social dynamics
Research areas: fluid dynamics and rheology; thermal systems; combustion; energy and the environment
Research areas: modeling and mechanism design for electoral systems; networks, geospatial, demographic data; Markov chains and discrete geometry
Research areas: causal inference, reinforcement learning, statistical machine learning with applications to healthcare
Research areas: economics of information; learning from endogenous data; market microstructure; evolution in games and markets
Research areas: optimal control theory; intelligent systems; multivariable control; feedback control of dynamic systems; sensor networks
Research areas: evolutionary biology; stochastic and dynamical systems in biology; theoretical population biology
Research areas: applied probability and scholastic processes, inventory models, queueing theory, options pricing and optimal stopping
Research areas: statistical machine learning, information theory, optimal transport, high-dimensional and nonparametric statistics
Research areas: large-scale constraint reasoning and optimization; mathematical programming; machine learning
Research areas: combinatorial scientific computing, sparse linear algebra, parallel and distributed scientific computation, and parallel systems
Research areas: reasoning about knowledge and uncertainty; qualitative reasoning; (fault-tolerant) distributed computing logic; game theory
Research areas: discrete-event simulation; simulation and optimization; applications in radiation oncology
Research areas: Dynamic optimization under uncertainty, Robust and stochastic optimization, Approximation algorithms
Research areas: fracture mechanics; high-temperature crack propagation; geomechanics; asymptotic methods
Research areas: data-driven optimization under uncertainty; casual inference; machine learning; personalization; optimization in statistics; online decision making and operations in health care
Research areas: physical modeling of semiconductor devices and processes; numerical solvers for hybrid systems (EM, mechanical, and thermal)
Research areas: mathematical biology, probability and stochastic processes, statistics and data science, dynamical systems and ordinary differential equations, scientific computing and numerical analysis
Research areas: algorithms; combinatorial optimization; computational geometry; computational biology
Research areas: design and analysis of algorithms, especially randomized and online algorithms for networked systems and electronic markets
Research areas: Logics and semantics of programming languages, algorithms and complexity, especially complexity of decision problems in logic and algebra, probabilistic computation.
