Graduate Study in the Mathematical Sciences at Cornell
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This illustration, developed by David Hiebeler, shows a population (red) on fragmented landscapes with spatially structured heterogeneities. The population achieves greater density in highly clustered landscapes.
Since several related but distinct graduate programs in the mathematical sciences are available at Cornell University, this information has been prepared to help prospective students decide which would be most appropriate for them. Faculty members representing six graduate fields have assembled information that they believe will be useful to applicants with various backgrounds in the applied sciences, engineering, or mathematics. Information on the following fields is listed below:
The faculty members who have contributed this material recognize that many of the sciences involve a large component of mathematics, but they feel that the six areas discussed here represent the core of the mathematical sciences at Cornell. In each case, a brief description of the graduate program is given. Also included is a list of over 150 professors who are members of the six graduate fields. Many of these faculty members are associated with more than one field, a fact that reflects the many interrelations among these areas.
While four of the six fields are associated most closely with traditional departments, the programs in applied mathematics and in statistics are associated with university centers for interdisciplinary study. Such centers encourage and sponsor interdisciplinary research projects, conferences, and seminars and host visiting scholars. One other center is relevant to study in the mathematical sciences, although it does not enroll students. The Center for Theory and Simulation in Science and Engineering promotes computational science and interdisciplinary work involving high-performance computing and visualization.
Application for admission is made to a specific graduate field (although transfer to another field is possible pending acceptance by the new field). Application materials and general information about graduate study at Cornell, including the opportunities for assistantships, degree requirements, and tuition, are available from: The Graduate School, Cornell University, Caldwell Hall, Ithaca, New York 14853-2602. They may also be found at http://www.gradschool.cornell.edu.
Applied Mathematics
The forty to forty-five graduate students in the Field of Applied Mathematics are the responsibility of a faculty of eighty applied mathematicians drawn from fourteen departments in engineering and the sciences, including mathematics, computer science, electrical engineering, operations research and theoretical and applied mechanics. Activities are coordinated through Cornell's Center for Applied Mathematics, which was established to promote research and advanced study and to bring together students and faculty members who have interests in the various branches of the subject.
Graduate students are admitted to this field from a number of educational backgrounds, including engineering and the physical sciences as well as mathematics. Normally, only those applying for candidacy for the Ph.D. degree are considered.
The program of study includes advanced courses in pure mathematics, particularly analysis and algebra; thorough grounding in mathematical methods; and studies in subject areas in which significant applications of mathematics are made. Examples of these areas are classical mechanics, quantum mechanics, electromagnetic theory, physical chemistry, elasticity and plasticity, fluid mechanics, aerodynamics, magnetofluid dynamics, operations research, combinatorics, game theory, probability, information theory, thermodynamics and statistical physics, structure of matter, solid-state physics, astronomy, astrophysics, cosmology, theory of control, computer science, mathematical biology, and mathematical economics.
Doctoral-degree work is normally completed within three to five years. Currently, about half of the students are supported as teaching assistants, and the remainder have fellowships or research assistantships.
The Center for Applied Mathematics has a network of Linux computers with sophisticated software packages.
For more information contact: Director of Graduate Studies, Center for Applied Mathematics, Cornell University, 657 Frank H. T. Rhodes Hall, Ithaca, New York 14853-3801. Phone: 607-255-4335; e-mail: appliedmath@cornell.edu; web site: http://www.cam. cornell.edu.
Computer Science
The Field of Computer Science has about 125 Ph.D. graduate students, 100 M.Eng. students, and 44 faculty members. The main research areas are theory of computation, systems, programming languages, databases, digital libraries, scientific computing, graphics, artificial intelligence, and computational biology.
Theory of computation is concerned with fundamental problems of computer science. Over the years, Cornell researchers in this area have been in the forefront of work in computational complexity, analysis of algorithms, algorithmic game theory, semantics, and program verification. There is also considerable interaction with researchers in other areas of computer science and mathematics. During the past three years, US News and World Report has ranked Cornell number one among computer science programs in this area.
Current research in systems at Cornell involves the use of concurrent and distributed systems to investigate issues such as fault tolerance, network quality of service, security, replicated data management, and network quality of service. Cornell's effort in these areas combines formal and practical work in a way that distinguishes the department from others. Current topics include issues of security in adaptive networks, where code or protocols are dynamically adapted to changing conditions, and issues associated with guaranteed quality of service in the emerging "next generation internet".
In the area of programming languages, the Cornell's focus is on language-based security, programming methodology, program verification, programming environments, and programming-language design. A significant effort focuses on relationships between programming language constructs, type theory, and constructive logics. Recent work includes study of languages and systems support for mobile code. Again, there is an emphasis on combining formal and practical work. The department is widely viewed as being one of the top two or three in this area.
In the area of databases, the focus is on data mining, data stream processing, distributed data management for sensor networks and peer-to-peer networks, and techniques for handling structured and unstructured date in query processing. The database group is also interacting with researchers in other disciplines as considers applications of data mining technology to the sciences.Cornell is the home of a major Digital Library effort to develop a National Digital Library for education in science, mathematics, engineering, and technology. This involves considering issues such as interoperability, automated collection, and sustainability.
Research in scientific computing is in matrix computations, nonlinear optimization, and the solution of partial differential equations, with emphasis on design of new algorithms and applications in chemistry, biology, fluid mechanics, finance, and other fields. Our focus is on efficient and robust algorithms with eye toward modern high performance parallel and multi-threaded architectures.
In the field of graphics, emphasis is on realistic image rendering, light reflection models, interactive graphic techniques, user interfaces, parallel processing for real-time graphics simulations, medical imaging, and the uses of computer graphics as applied to art, architecture, and photography.
Current areas of activity in the areas of artificial intelligence include machine learning, reasoning with imprecise or probabilistic information, theorem proving, multi-agent systems, fast reasoning methods, and natural language processing, particularly the development of corpus-based, statistical, machine-learning approaches to language processing and information retrieval.
A new but important area for the department is concerned with computational biology, which represents a growth area within the university as a whole. Research in the department currently focuses on computational prediction of the structure, function, and dynamics of biomolecules, bioinformatics, and biological sequence analysis.
Excellent facilities are available in the Department of Computer Science, which has, at the present time, over 300 computers. Most of these are engineering workstations, but the others range from micros to specialized high-end parallel processors.
For more information contact: Director of Graduate Studies, Computer Science, Cornell University, 4126 Upson Hall, Ithaca, New York 14853-7501. Phone: 607/255-8593. The web site (http://www.cs.cornell.edu) has a great deal of material including application materials, online demos of software, and short interviews with researchers.
Mathematics
The graduate program in the Field of Mathematics leads to the Ph.D. degree. The program generally takes most students about five years to complete. One feature that makes the program especially attractive is the broad range of interests of the faculty. In addition to the usual areas of algebra, analysis, geometry, the department has outstanding groups in the areas of algebraic geometry, combinatorics, dynamical systems, logic, Lie groups, probability and partial differential equations, including their numerical treatment and topology. The field also maintains close ties with distinguished graduate programs in the Fields of Applied Mathematics, Computer Science, Operations Research and Statistics.
There is a multicultural group of seventy graduate students enrolled in the Field of Mathematics at Cornell. The field has over forty-three faculty members, which ensures that students receive a great deal of individual attention.
In the past, the field has been able to arrange financial support, in the form of teaching assistantships, fellowships, or research assistantships, for every graduate student who is making satisfactory progress, and this is expected to continue.
For more information, contact: Director of Graduate Studies, Department of Mathematics, Cornell University, Malott Hall, Ithaca, New York 14853. Telephone: 607-255-6757; e-mail: gradinfo@math.cornell.edu., web address: http://www.math.cornell.edu
Operations Research
The graduate Field of Operations Research offers the Ph.D. degree with concentrations in applied probability and statistics, optimization (mathematical programming), and manufacturing systems engineering. The emphasis is on operations research as a mathematical science; graduates are provided with a strong analytical base for advanced research in theory and methodology and for application of operations research methodology in industry and government.
Approximately thirty faculty members belong to the field. The broad range of their research interests includes stochastic processes, queuing and storage theory, stochastic control, probabilistic methods in physics and engineering, time-series analysis, probabilistic models in finance, design of experiments, biomedical statistics, quality control and reliability, statistical decision theory, nonparametric statistics, regression methods, scheduling, supply chain management and e-commerce, inventory and logistics control, simulation, computational biology, combinatorics, linear programming, graph theory and network flows, matroid theory, fixed-point methods, integer programming and combinatorial optimization, analysis of heuristics, convex polyhedra, nonlinear programming, and parallel optimization algorithms.
There are approximately fourty students in the Ph.D. program, which usually is completed in three to five years. Computing facilities include networked PC and Sun workstation laboratories.
For more information contact: Director of Graduate Studies, Operations Research, Cornell University, Frank H. T. Rhodes Hall, Ithaca, New York 14853-3801. Telephone: 607-255-9128; web address: http://www.orie.cornell.edu.
Statistics
Many different graduate programs in statistics, ranging from the theoretical to the more applied, are available at Cornell. Programs in theoretical probability and mathematical statistics have a curriculum tied to mathematics and usually require an undergraduate major in mathematics. Others emphasize the application of statistics and can be tied to the health and biological sciences, to education, to the social sciences, or to the physical and engineering sciences; they stress methods of collecting and interpreting data and the use of computers, but they also include training in applied mathematics and probability.
Areas of study that are particularly strong are applied stochastic processes, biometry, computer-intensive statistics, decision theory, social statistics, experimental design, linear-model theory, reliability and life testing, resampling techniques, sequential analysis, survival analysis, and theoretical probability. Some thirty-four faculty members teach an extensive range of courses and actively pursue research interests in these and other related areas.
For more information contact: Director of Graduate Studies, Statistics, Cornell University, Malott Hall, Ithaca, New York 14853-2602. Phone: 607-255-8066; e-mail: csc@cornell. edu; web address: http://www.stat.cornell.edu.
Theoretical and Applied Mechanics
The graduate Field of Theoretical and Applied Mechanics at Cornell offers students a broad education in the mechanics of rigid and deformable bodies (solid and fluid), applied mathematics at an advanced level, and modern experimental techniques. By acquiring a strong background in fundamentals, graduates of the program are able to carry out analytical or experimental research of high quality and are prepared to handle many modern engineering problems of an interdisciplinary nature.
The principal areas of teaching and research are solid mechanics, fluid mechanics, dynamics and space mechanics, and mechanics of materials. Members of the field teach six courses in applied mathematics at the graduate level. The development of related mathematical methods is an important part of the research programs. Topics now being studied include: bifurcations and chaotic motions in dynamical systems; nonlinear elasticity in connection with the study of stress-induced phase transformations in solids; continuation methods in the study of existence and stability of finite deformations of nonlinearly elastic solids and structures; interface failure of composite materials and crazing in polymer glasses; mathematical models of nonlinear systems in physics and biology, such as lasers, superconducting Josephson junctions, AIDS immunology, and synchronization of biological oscillators; probabilistic and percolation methods for the prediction of mechanical properties and failure in aggregates of grains or fibers and composites; and high-performance computation of large-scale nonlinear bifurcation problems with symmetry.
All students majoring in the field are required to minor in at least one other field of the Graduate School, chosen according to their research interests and needs. Minors frequently selected include aerospace engineering, applied mathematics, mechanical engineering, physics, materials science, and structural engineering. The Field of Theoretical and Applied Mechanics has no rigid course requirements, so that highly individual programs can be planned by a student together with his or her major and minor advisers. The field has between thirty and thirty-five graduate students.
For more information contact: Director of Graduate Studies, Theoretical and Applied Mechanics, Cornell University, Kimball Hall, Ithaca, New York 14853-1502. Phone: 607-255-0988; e-mail: tam_grad@cornell.edu; web address: http://www.tam.cornell.edu.
Faculty Interests
The letter code indicates affiliation: A-Applied Mathematics; C-Computer Science; M -Mathematics; O-Operations Research; S-Statistics; T-Theoretical and Applied Mechanics. Many of the professors listed are also members of other graduate fields in engineering disciplines and the sciences.
O,S Tanya Apanasovich: generalized linear mixed models, spatial statistics, and nonparametric and semiparametric regression methods C William Y. Arms: digital libraries, electronic publishing O,S Krishna Athreye stochastic processes T Shefford P. Baker: mechanical properties, micro- and nano-mechanics, thin films, nanoidentation, dislocations C Graeme Bailey: computer science (M.Eng. only) * C Kavita Bala: interactive rendering, global illumination algorithms, image-based modeling and rendering M Dan Barbasch: representation theory of semi-simple Lie groups M Yuri Berest: PDE, algebra; mathematical physics A,S Toby Berger: information theory, data and video compression, communication networks, random processes A,M,O Louis J. Billera: geometric and algebraic combinatorics A,C Ken Birman: distributed systems, fault-tolerance network systems, distributed systems theory, large-scale netowrk applications A,O Robert G. Bland: linear programming, combinatorial optimization, networks and matroids A Adam W. Bojanczyk: parallel numerical methods, matrix-based signal and image processing M Kenneth S. Brown: algebra, group theory, topology S John Bunge: point processes, semi-Markov processes, species problems C Martin Burtscher: high-performance processor architecture; instruction-level parallelism, value prediction, data compression, computer optimization, programming language implementation T Joseph A. Burns: solar system dynamics, celestial mechanics, planetary satellites and rings, dust A,S Carlos Bustamante: statistical genetics/genomics, Bayesian statistics, computational statistics, hierarchical models, MCMC, bioinformatics T K.Bingham Cady: dynamics, fluid mechanics C Claire Cardie: nature language processing, machine learning, artificial intelligence C Richard Caruana: machine learning and data mining, medical decision-making and bioinformatics, feature selection, missing values, inductive transfer, artificial neural networks, memory-based learning A David A. Caughey: computational fluid dynamics, aerodynamics M Stephen U. Chase: homological algebra, algebraic number theory M Zheng-Qing Chen: probability theory, partial differential equations C Leslie Chew: A Hsiao-Dong Chiang: nonlinear circuits and systems, power systems, artificial neural_networks, control systems, optimization theory A,C,O Thomas Coleman: numerical optimization, computational finance, parallel computation A,M Robert Connelly: geometry, rigidity and topology A,C Robert L. Constable: computational complexity, formal semantics applied logic, automated reasoning A Raffaello D'Andrea: robust and optmal control T Paul R. Dawson: modeling of manufacturing processes, microstructure evolution during manufacturing A David Delchamps: dynamical systems, control theory, stochastic systems, cognitive science C Alan J. Demers: information processing M R. Keith Dennis: commutative and noncommutative algebra, algebraic K-theory S Thomas DiCiccio: likelihood inference, resampling methods, asymptotic approximations, linear models A,M,O,S Richard Durrett: probability theory and its application to ecology and genetics A,M,O,S Eugene B. Dynkin: probability theory, mathematical economics, stochastic processes M Clifford J. Earle: complex variables, Teichmuller spaces C Shimon Edelman: vision, computational biology O Mark Eisner: operations research A,C Ron Elber: scientific computing A Stephen Ellner: theoretical population biology, evolutionary biology A Viet Elser: crystallography, quasicrystals, quasi-periodic minimal surfaces A Gregory S. Ezra: theoretical chemistry, chemical physics A,S Terrence L. Fine: foundations of probability, modeling random phenomena, artificial neural nets C Paul Francis: computer science, information organization and retrieval, operating systems A,C,O Eric Friedman: game theory, information technology, cost allocation C Johannes Gehrke: operating systems, information organizations and retrieval C Carla Gomes: artificial intelligence, computer science C Donald P. Greenberg: realistic image synthesis, modeling, scientific visualization, computer-aided design, image processing C David Gries: program methodology and related areas, logic, computer science A,M Leonard Gross: functional analysis,analysis on path spaces A,M,T John Guckenheimer: dynamical systems, differential equations, mathematical biology A,O,S Xin Guo: applied probability, stochastic optimization and control, financial mathematics A,C Zygmunt Haas: wireless and mobile networks S Ali Hadi: muiltivariate analysis, regression diagnostics, outliers, causal networks A,C Joseph Halpern: logics, artificial intelligence, distributed computing, reasoning about uncertainty C Juris Hartmanis: theory of computation M Allen E. Hatcher: geometry, topology A,M,T Timothy J. Healey: nonlinear elasticity, symmetry and bifurcation theory, elliptic partial differential equations A,C Sheila Hemami: visual communication, application-specific image and video processing and compression, multirate coding, joint optimization of network and coding parameters M David W. Henderson: geometry, mathematics education O Shane Henderson: discrete-event simulation, simulation and optimization, applications in radiation oncology S Yongmiao Hong: testing serial independence, testing volatility spillover, nonparametric entropy-based testing C John Hopcroft: theoretical underpinnings of access to information including spectral analysis, large graphs and web searching A,M John H. Hubbard: analysis,differential equations, differential geometry A,T Chung-Yuen Hui: elasticity and inelasticity, facture, polymers C Daniel P. Huttenlocher: computer vision M,S J.T.Gene Hwang: statistics,confidence set theory M Iouli Iliashenko: dynamical systems O P. L. Jackson: production and inventory management, manufacturing economics A,O Robert Jarrow: mathematical economics A,T James T. Jenkins: continuum mechanics C Thorsten Joachims: machine learning, text-mining, statistical learning theory, information access A C.Richard Johnson, Jr.: adaptive receiver design for broadband communication technologies M Peter J. Kahn: algebraic and differential topology A E.Kan: physical modeling of semiconductor devices and processes, numerical solvers for hybrid systems (EM, mechanical and thermal) C Uri Keich: S Nicholas Kiefer: econometrics, decision theory, stochastic modeling A,C,O Jon Kleinberg: algorithms, combinatorial optimization, computational geometry, computational biology A Donald Koch: fluid dynamics, stochastic processes in suspensions A,C,M Dexter Kozen: theory of computation, proof-carrying code, computational complexity, analysis of algorithms, program logic and semantics T Richard H. Lance: engineering plasticity, composites design, computer-enhanced learning C Bruce Land: M,S Gregory Lawler: random walk and Brownian motion; process arising in statistical physics C Lillian Lee: natural language processing A,T Sidney Leibovich: fluid dynamics, physics of strongly swirling flows, convective motion of liquids A Simon A. Levin (Adjunct): mathematical biology, ecology, epidemiology, evolutionary theory A,O Adrian Lewis: C Yuying Li: numerical optimization and scientific computing C Hod Lipson: computer-aided design and design automation; artificial intelligence; rapid prototyping; evolutionary computation; evolutionary robotics; artificial life A Philip L.-F. Liu: fluid dynamics, nonlinear water waves A Roger Loring: chemical applications of equilibrium and nonequilibrium statistical mechanics A Makul K. Majumdar: mathematical economics A Rajit Manohar: asynchronous VLSI design, computer architecture, concurrency theory C Stephen Marschner: appearance models for natural materials; 3D scanning; processing scanned geometric data; image-based appearance measurements for 3D objects C Jose Martinez: appearance models for natural materials; 3D scanning; processing scanned geometric data; image-based appearance measurements for 3D objects C Sally McKee: computer science A Tappan Mitra: economic growth, infinite horizon dynamic optimization, chaotic amd random dynamical systems in economics T Francis C. Moon: magnetoelasticiy, dynamics of solids and structures, chaotic dynamics, experimental mechanics C J. Gregory Morrisett: development of programming language and computer technology, specifically high-level language facilities for reliable, secure, and high-performance systems software O John A. Muckstadt: inventory control, logistics T Subrata Mukherjee: modeling of manufacturing processes, nonlinear computational mechanics, optimization, micro-electro-mechanical (MEM) structures M Camil Muscalu: harmonic analysis and partial differential equations C Andrew Myers: programming languages A,C,M Anil Nerode: mathematical logic, recursive functions, computer science M, S Michael Nussbaum: statistics T Katerina Papoulia: computational solid mechanics, time dependent materials, damage and fracture in solids A Thomas W. Parks: digital-signal processing, image enlargement, enhancement and restoration M Irena Peeva: algebra A,T Leigh Phoenix: long-term reliability of fibrous materials, statistical failure processes in composites C Keshav Pingali: compilers, parallel computation, programming languages A Stephen B. Pope: turbulence, combustion, computational fluid mechanics, stochastic processes A,O,M,S Philip E. Protter: financial asset pricing theory and credit risk, stochastic analysis and numerical analysis, weak convergence, Markov processes M Ravi K. Ramakrishna: algebra C Radu Rugina program analysis with emphasis on pointer analysis; automatic parallelization techniques A,T,M Richard H. Rand: dynamical systems, computer algebra, biomechanics A,O,M James M. Renegar: complexity of algorithms, mathematical programming A,O,S Sidney I. Resnick: applied probability and time-series analysis, extreme value theory, heavy-tail analysis T Phoebus Rosakis: finite elasticity, continuum mechanics, elastic modeling of defects in solids O Robin O. Roundy: production planning and scheduling, inventory management C Radu Rugina: program analysis with emphasis on pointer analysis; automatic parallelization techniques T Andy Ruina: biomechanics of walking, biking and rowing, friction, solid mechanics O,S David Ruppert: robust estimation, data transformation,stochastic approximation A,O Paat Rusmeivichientong data mining, probabilistic inference and decentralized decision-making T Wolfgang H. Sachse: mechanics of materials, nondestructive testing techniques, wave propagation, physical acoustics A,M Laurent Saloff-Coste: analysis and probability A,O,S Gennady Samorodnitsky: applied probability, stable processes, long-range dependence communication networks, financial models, risk theory A,M Alfred H. Schatz: numerical solutions of partial differential equations C Fred B. Schneider: distributed systems security and fault-tolerance, mobile code, concurrent programming, operating systems S Steven J. Schwager: multivariate analysis,data analysis A,C Bart Selman: artificial intelligence and experimental computer science M Shankar Sen: algebraic number theory C Phoebe Sengers: culturally embedded computing; human-computer interaction; everyday computing; affective computing; interactive art; autonomous agents A Sergio Servetto: information theory, communication networks A James Sethna: theoretical condensed-matter physics, materials science, spatially extended dynamical systems A David Shalloway: algorithms for perturbative protein folding dynamics C Jayavel Shanmugasundaram: internet data management, databse systems, transaction processing in emerging system architectures A Karl Shell: economic theory, mathematical economics A,C,O David Shmoys: complexity theory, combinatorial optimization, approximation algorithms, computational biology A,O Christine Shoemaker: numerical optimization, stochastic dynamic programming, heuristic optimization, applications to environmental systems M Richard A. Shore: mathematical logic, recursion theory, set theory M Reyer Sjamaar: symplectic geometry, stratified spaces C Emin Sirer: systems A,M John Smillie: dynamical systems M Birgit Speh: Lie groups, automorphic forms C William Speight: clustered-based parellel computing, user-level networks, operating sytem design, shared memory parallel computing S Robert Strawderman: survial analysis, event history analysis, stochastic processes, asymptotic approximations, statitical computing A Jery R. Stedinger: risk analysis, stochastic hydrology, water resource systems A Paul Steen: hydrodynamic stability, nonlinear fluid dynamics A,M Michael Stillman: algebraic geometry, computational algebra M Robert S. Strichartz: harmonic analysis, partial differential equations A,T Steven H. Strogatz: nonlinear dynamics, applications in physics, engineering, and biology S Steven Schwager multivariate analysis, data analysis M Edward Swartz: combinatorics and discrete geometry A,C,O Eva Tardos: design and analysis of algorithms, with emphasis on combinatorial optimization and their applications to various problems A James S. Thorp: optimal control with application to power systems M William Thurston: topology, geometry A,O Michael J. Todd: mathematical programming, combinatorics, interior-point algorithms A Lang Tong: statistical signal processing, communication systems and networking, adaptive receiver design-estimation theory O Huseyin Topaloglu: dynamic fleet management, stochastic programming, appropriate dynamic programming C Sam Toueg: distributed computing, fault tolerance A,O Leslie E. Trotter: combinatorial optimization, discrete mathematics O,S Bruce W. Turnbull: biomedical statistics, quality control, reliability theory A,M Alexander Vladimirsky: numerical methods, dynamical systems, nonlinear PDEs, control theory A,C Charles F. Van Loan: matrix computations, scientific computing C Robert Van Renesse: distributed computing, fault-tolerance, distributed multimedia systems A,C,O Stephen A. Vavasis: numerical analysis, optimization S Paul F. Velleman: statistical computing, robust exploratory methods S Timothy Vogelsang: time-series analysis, trend function hypothesis testing M Karen Vogtmann: topology, geometric group theory A,M Lars B. Wahlbin: numerical solutions of partial differential equations A,T Z.Jane Wang: fluids in physics and biology, biomathematics, statistical physics, scientific computing and modeling O,S Martin Wells: decision theory, social statistics, survival analysis M James E. West: geometric topology, infinite-dimensional topology A Stephen Wicker: wireless information networks, digital communication systems, error-control coding A Benjamin Widom: physical chemistry, statistical mechanics C David Williamson: algorithms, combinatorial optimization, computer science A David Winkler: life history theory, models of dispersal A,C Golan Yona: computational molecular biology, machine learning C Ramin Zabih: computer vision, multimedia T Alan T. Zehnder: fracture experimental mechanics, optical and infrared techniques, mechanics of materials O Rachel Zhang: production and inventory control, supply chain management