Chair   Donald Drew
Chair of the Graduate Committee   William Siegmann
Department Home Page   http://www.math.rpi.edu/index.html

Through the centuries, mathematics has been a central feature of our intellectual and technological development. Today its role in the physical sciences and engineering is well established. Its role in the life and social sciences, medicine, management, and the arts is undergoing remarkable growth—a virtual mathematization of the culture. The Department of Mathematical Sciences is directly engaged in this process through its educational and research programs. Our focus is the study and development of mathematical and computational methods and their application to problems of contemporary significance to our society.

The Department of Mathematical Sciences provides an in-depth education in both the foundations of mathematical thought as well in the applications of mathematics to real-life phenomena. For this reason, we offer a baccalaureate degree with a specialization in mathematics, applied mathematics, mathematics of computation, or operations research. The department’s programs are also designed to provide a broad spectrum of opportunities for students. This flexibility allows students and advisers to tailor programs to individual objectives and talents. As a result, the curricula are equally advantageous for individuals who will seek immediate employment upon graduation, for those who plan graduate-level education in the mathematical sciences, and for those who will apply their education to pursuits outside the mathematical arena. Our graduates have entered careers in law, medicine, engineering, management, and psychology, as well as in pure and applied mathematics, computer science, and operations research.

At the graduate level, Rensselaer is especially well-known as a center for advanced study and research in applied mathematics. The department’s M.S. and Ph.D. programs emphasize:

• Methods of applied mathematics, including ordinary and partial differential equations, approximation theory, asymptotic analysis, functional analysis, and numerical analysis;
• Applications in the physical sciences, biological sciences, and engineering;
• Scientific computing;
• Mathematical programming, including nonlinear, combinatorial, and multiple objective optimization and their applications.

At the highest level, continual interplay between the construction of the mathematical model and the solution of the resulting mathematical problem characterizes applied mathematics. The ideal applied mathematician, therefore, must be knowledgeable both in mathematics and in at least one field in which problem areas are found. A sound knowledge of the application area assists in constructing suitable models, and a high level of mathematical judgment and expertise may be required to solve the resulting mathematical problems.

Research Innovations and Initiatives

Faculty research activities in the Department of Mathematical Sciences center on applied mathematics, analysis, scientific computing, mathematical programming, and operations research. The faculty’s interest in applied research often leads to a synthesis of techniques from two or more research areas. Further, the formulation, solution, and interpretation of a problem often contain ideas that can be applied to problems in other areas. Focusing different research areas on real problems and the diversity of applications of real problem solutions creates an atmosphere of interaction and cooperation within the department and the university, as well as with other major research institutions.

Numerical Analysis and Scientific Computation   Investigations range from the study of fundamental problems in linear algebra to the development and analysis of numerical schemes for solving particular physical or life science problems. Research activities include the numerical solution of optimization problems, inverse eigenvalue problems, and free-boundary problems; finite difference and finite element methods for stiff initial and boundary-value problems; and methods of resolving problems involving composite materials. Applications of these studies include reacting flows, shockwave propagation, semiconductor performance, biomathematics, acoustic signal propagation, and incompressible flow in various geometries.

Inverse Problems   This research involves the recovery of internal biological, mechanical, electric, or magnetic properties of a system from boundary, spectral, or scattering data. The physical system is modeled by a partial differential or ordinary differential equation with specific unknown terms representing, for example, stiffness in an elastic system or electric permittivity in an electromagnetic system. The goal of this work is to find the unknown properties from indirect measurements. Current research applies functional analysis, perturbation theory, numerical analysis, and optimization to determine optimal datasets, to study the nonlinear dependence of the unknown physical quantities on the available data, and to obtain approximations of the nonlinear operators that will yield efficient reconstruction algorithms. There is a significant role for modeling, analysis, scientific computation, and algorithm development to obtain solutions to these problems.

Dynamical Systems   This research concentrates on the theory of dynamical systems and its applications in physics and engineering. Dynamical systems arise as mathematical models in various applications such as mechanics, optics, electric circuits, solid-state physics, fluid dynamics, optimal control, and other fields. This research aims to discover and explain new and important phenomena found in experimental and numerical studies. Often involved is modeling a real-life problem by a dynamical system and then applying the ideas and methods of the theory to explain and predict complex behavior. Theoretical research is conducted in chaotic dynamics, Hamiltonian systems (KAM theory and applications, theoretical mechanics), bifurcation theory, and related fields. Mathematical methods used come from analysis, topology, differential geometry, combinatorics, and other fields. Computation may be used as an experimental tool.

Wave Propagation   These studies focus on the behavior of acoustic wave propagation. A major area of interest is underwater sound transmissions. Mathematical models are being developed and analyzed to describe the influences of ocean environmental features (such as internal waves and sediment variations) on the study of the propagation of signals in both frequency and time domains, and to improve the accuracy of known numerical methods. Improved numerical and asymptotic methods are derived and tested, providing new ways to extract information from complex propagation environments. Stochastic propagation effects are modeled and analyzed, and results are used to explain variability observed by ocean scientists. Results are extended and applied to acoustic propagation environments ranging from the atmospheres of Jupiter and the Earth to the upper layer of the Earth’s crust.

Mathematical Programming and Operations Research   Mathematical programming endeavors to find optimal solutions for a broad range of problems including medical, financial, scientific, and engineering problems. Research is conducted on the development, evaluation, and comparison of serial and parallel algorithms for a variety of mathematical programming problems. Current research topics include interior point methods for linear, integer, and nonlinear programming; branch-and-bound and branch-and-cut approaches to integer programming problems; column generation methods; financial optimization; and genetic algorithms and tabu search. Also under investigation are mathematical programming approaches to problems in artificial intelligence such as machine learning, neural networks, support vector machines, pattern recognition, and planning. This research also considers combining operations research and artificial intelligence problem-solving methods, scalability of these methods to large problems in data mining, mathematical programming approaches to other areas in computer science such as database query optimization, and stochastic programming.

Biomathematics   Mathematical biology is a very active area of applied mathematical research. This is an interdisciplinary endeavor, with a strong interaction with biological and biomedical scientists. Projects of current interest include cardiac imaging and the use of computer graphics to construct pictures of the heart, mechanoreception, and mathematical modeling of biological systems that transform mechanical stimuli (e.g., sound, touch, etc.) into ionic or neural signals. Also being studied are nonlinear ionic diffusion in polyelectrolytic gels and the mechanics of multiphasic tissues like cartilage and the cornea. Numerical analysis, asymptotics, and functional analysis are used to investigate mathematically posed problems resulting from the models.

Fluid Mechanics   Methods of applied mathematics are being used to study how fluids behave under a wide spectrum of conditions. The physical problems usually lead to partial differential equations, which may be linear or nonlinear. Current problems deal with fluid mechanics in engineering systems, the flow and stability of two-phase mixtures, the transition from laminar to turbulent flow in boundary layers, fluid mechanical models of atmospheric events and the theory of flow in a gas centrifuge. Studies also include the evolution of non-Newtonian (e.g., polymer) fluid flow.

Combustion Theory   Investigations include mathematical modeling of combustion and flame propagation phenomena, and analysis of the resulting systems of nonlinear ordinary and partial differential equations. Topics of current interest are bifurcation and stability of reactive systems, evolution and interaction of waves in reactive gases, combustion and vortex breakdown in swirling flows, and transition from deflagration to detonation in granular explosives.

Applied Geometry   Included are problems dealing with surface design, curve design, robot path planning, packing, tiling, computational geometry, and artificial intelligence as it applies to geometry. Students take advantage of related courses in electrical engineering, mechanical engineering, computer science, and mathematics.

Approximation Theory   This branch of mathematics strives to understand the fundamental limits in optimally representing different signal types. “Signals” here may mean a database of digital audio signal, a collection of digital mammograms, solutions of a class of integral equations, or triangulated compact surfaces acquired by a 3-D scanner. These signals are typically modeled mathematically based on their intrinsic smoothness or oscillatory characteristics. Current research effort involves the design and analysis of various multiresolution techniques that have provable optimality properties for these models. Such optimal representations are invariably the key ingredients to successful data compression, estimation, and computer-aided geometric design. Exploited tools range from mathematical analysis (e.g., Littlewood-Paley theory) to fast numerical algorithms, to information theory, to algebraic and differential geometry, and to spline and subdivision theory.

Complex Systems   This includes an investigation into nonlinear phenomena that arise in such diverse areas as semiconductor laser theory, nonlinear and fiber optics, surface water waves, acoustic waves and gas lasers. Although these topics are seemingly disconnected and have different physical characteristics, they all can be viewed as complex systems composed out of interacting particles or waves. There is a general theoretical framework for their description called weak turbulence theory. The research in this area involves development of weak turbulence theory and how to use this theory to study complex systems.

Bioinformatics   The massive volume of new data being produced by genome sequencing projects point to an increasing need for bioinformatics. This is a highly interdisciplinary field, involving faculty in mathematical sciences, biology, computer science, chemistry and several departments in the school of engineering. RPI has established a joint bioinformatics center with the nearby Wadsworth Laboratories in the New York state Department of Public Health. Current activities at RPI comprise the development and application of algorithms that aim to solve biological problems using DNA and amino acid sequence, structure, and related information. Some of the problems addressed are the search for patterns in biomolecular sequences that are functionally important, such as transcription binding sites; the prediction of structure or function from nucleic acid or protein sequence data; the development of methods and databases to classify large amounts of biological information, and the development of algorithms and software that are important for current biotechnology applications.

Faculty

Departmental faculty listings are accurate as of the date generated for inclusion in this catalog. For the most up-to-date listing of faculty positions, including end-of-year promotions, please refer to the Faculty Roster section of this catalog, which is current as of the May 2002 Board of Trustees meeting.

Professors
Boyce, W.E.—Ph.D. (Carnegie Institute of Technology); applied mathematics, mathematics education (emeritus).
Cheney, M.—Ph.D. (Indiana University); inverse problems, wave propagation, applications in engineering and biology, partial differential equations.
Drew, D.A.—Ph.D. (Rensselaer Polytechnic Institute); applied mathematics, fluid mechanics.
Ecker, J.G.—Ph.D. (University of Michigan); mathematical programming, multiobjective programming, geometric programming, mathematical programming applications, ellipsoid algorithms.
Fleishman, B.A.—Ph.D. (New York University); nonlinear differential equations, mathematics education (emeritus).
Habetler, G.J.—(Carnegie Institute of Technology); functional analysis, numerical analysis (emeritus).
Handelman, G.H.—Ph.D. (Brown University); applied mathematics, elasticity, wave propagation, mathematical biology (emeritus).
Herron, I.—Ph.D. (Johns Hopkins University); applied mathematics, fluid mechanics, hydrodynamics, stability.
Holmes, M.—Ph.D. (University of California, Los Angeles); perturbation methods, biomathematics, nonlinear continuum mechanics.
Isaacson, D.—Ph.D. (New York University); mathematical physics, biomedical applications.
Jacobson, M.J.—Ph.D. (Carnegie Institute of Technology); applied mathematics, acoustic and electromagnetic wave propagation (emeritus).
Kapila, A.—Ph.D. (Cornell University); applied mathematics, combustion, fluid mechanics.
Lim, C.C.—Ph.D. (Brown University); mathematical modeling, vortex dynamics, applications of graph theory.
Luchins, E.H.—Ph.D. (University of Oregon); algebra, mathematics of psychology, mathematics education, number theory, history of mathematics, women in mathematics (emeritus).
McLaughlin, H.W.—Ph.D. (University of Maryland); applied geometry.
McLaughlin, J.R.—Ph.D. (University of California, Riverside); inverse vibration and inverse scattering problems, wave propagation, analysis, applied mathematics.
Roytburd, V.—Ph.D. (University of California, Berkeley); applied mathematics, combustion theory.
Rubenfeld, L.A.—Ph.D. (New York University); applied mathematics, mathematics, science education.
Siegmann, W.L.—Ph.D. (Massachusetts Institute of Technology); applied mathematics, wave propagation.
Zuker, M. – Ph.D. (Massachusetts Institute of Technology); bioinformatics.

Associate Professors
Bennett, K.P.—Ph.D. (University of Wisconsin); mathematical programming, operations research, machine learning, data mining, artificial intelligence.
Kovacic, G.—Ph.D. (California Institute of Technology); applied mathematics, nonlinear dynamics, nonlinear optics.
Mitchell, J.E.—Ph.D. (Cornell University); mathematical programming, integer programming, interior point methods, column generation methods, financial optimization, stochastic programming.
Piper, B.R.—Ph.D. (University of Utah); computer-aided geometric design, numerical analysis, computer graphics.
Schwendeman, D.W.—Ph.D. (California Institute of Technology); applied mathematics, scientific computing.

Assistant Professors
Kramer, P.R.—Ph.D. (Princeton University); turbulent diffusion, stochastic processes.
Lvov, Y.—Ph.D. (University of Arizona); mathematical physics and nonlinear phenomena.
Nolan, C.J.—Ph.D. (Rice University); medical and seismic imaging using microlocal analysis.
Yu, T.P.-Y.—Ph.D. (Stanford University); wavelets and applications in signal and image reconstruction.

Clinical Assistant Professors
Blackford J.T.—Ph.D. (Ohio State University); algebraic coding theory, combinatories, codes over rings.
Kiehl, M.—Ph.D. (Rensselaer Polytechnic Institute); biomathematics.
Schmidt, D.A.—Ph.D. (Rensselaer Polytechnic Institute); graph theory, qualitative matrix analysis, mathematics education.

Joint Appointments with Computer Science—Professors
Flaherty, J.E.—Ph.D. (Polytechnic Institute of Brooklyn); scientific computation, numerical analysis, applied mathematics.
Rogers, E.H.—Ph.D. (Carnegie Institute of Technology); VLSI architecture, computer applications (emeritus).

Undergraduate Programs

Mathematics has always been the cornerstone of scientific development. Rensselaer’s aim is to provide an education in mathematics, both as a subject in itself and as a discipline to aid in the development of other social and scientific fields. The undergraduate mathematics program educates students in a variety of mathematical areas. The flexibility in this program, with its numerous options, permits selection of courses ranging from pure theory (which builds a foundation for more advanced studies), to applied subjects focusing on mathematical modeling and the solution of real-world problems. In particular, Rensselaer’s Department of Mathematical Sciences is one of the few American programs with a strong faculty orientation toward mathematics applications. Reflecting this emphasis are the many undergraduate courses dealing with areas of mathematical applications and the applied flavor with which department faculty typically teach them.

Baccalaureate Programs

Four curricula leading to a B.S. in Mathematics have been designed to permit the construction of programs that reflect individual student interests and career objectives. These curricula include:

• Mathematics—a traditional program emphasizing the elements of pure and applied mathematics.
• Applied Mathematics—emphasizing both the modeling of physical phenomena and methods of analyzing the resulting mathematical problems.
• Mathematics of Computation—a program bridging mathematics and computer science, with emphasis on numerical methods for solution of problems in science and engineering.
• Mathematics of Operations Research—emphasizing the use of mathematics in developing and studying analytical models of discrete systems, especially those that arise in management, engineering, and social sciences.

These four curricula share several common features. First, they each contain nine free electives that permit students to design unique programs. These electives also allow students to concentrate on a subject in addition to mathematics, to obtain a broad-based education, or to complement their mathematics program. A second common feature is the Humanities and Social Sciences requirement of 24 credits. Finally, completion of all four curricula requires a total of 124 credits.

An immediate choice among these four curricula is not necessary, since for the first two years, all mathematics students follow the same basic curriculum. This initial two-year course of study is outlined below and is followed by sample junior/senior curricula for each of the department’s four undergraduate programs. Additional details and up-to-date descriptions of the mathematics courses, including special topics courses, are available at the department’s Web site, http://www.math.rpi.edu/index.html.

The First Two Years

In the above curriculum, the first-year seminar courses MATH-1900 and MATH-1910 are not required, but are strongly recommended. This weekly seminar course for math majors presents interesting and challenging mathematical problems and ideas for discussion. Also deserving particular attention is MATH-2700, a second semester sophomore course that provides a good background for junior and senior mathematics courses.

The science electives must include at least three different School of Science disciplines outside of math. Since CSCI-1100 is already required, the science electives must include two or more other disciplines. Also, two of these science electives must be in the same discipline. Note that mathematical science includes all courses with MATH and MATP codes (and any course cross listed with a MATH or MATP course), computer science includes all courses coded CSCI (and any course cross listed with a CSCI course), and courses coded PHYS and ASTR are considered separate disciplines.

Mathematics Curriculum

The above curriculum provides a broad and basic education in mathematics. It is especially suited to those intending to continue on to graduate education in mathematics or some other scientific and engineering field. Considerable flexibility is built into this program to allow students and their advisers to tailor programs to individual objectives. As a result, by choosing appropriate mathematical options, the curriculum is equally useful to those seeking immediate employment upon graduation.

Students should note that the mathematics options listed above are any 4000-level or higher course from the Department of Mathematical Sciences. Those planning to go on to graduate work should be sure to take MATH-4100.

Applied Mathematics Curriculum

The above curriculum stresses courses that involve the construction, analysis, and evaluation of mathematical models of real-world problems and those areas of mathematics most widely used to solve them. Thus, it prepares students to deal with mathematical problems that arise in science, engineering, or management. Applied mathematics students enjoy considerable flexibility, but are urged to acquire a solid background in the three principal areas of applied mathematics, which are modeling, analysis or solution methods, and numerical analysis.

Students should note that the mathematics options listed above are any 4000-level or higher course from the Department of Mathematical Sciences. It is recommended that students take PHYS-1100 and PHYS-1200 and those who may continue on to graduate school should considered taking MATH-4210 and MATH-4100.

Mathematics of Computation Curriculum

Computers and computational methods play an important role in all fields of science and engineering. Thus, the above curriculum focuses on the mathematical development, analysis, and application of numerical methods. Surrounding this main focus are courses that build mathematical expertise in analysis, modeling, and applications. This curriculum also allows the flexibility to pursue courses in computer science and other fields of science and engineering.

Students should note that the mathematics options listed above are any 4000-level or higher course from the Department of Mathematical Sciences. The computation option is either MATH-4820 or MATP-4820. The CS options are any 2000-level or higher courses from Computer Science (i.e., courses coded CSCI and not cross listed with any math course).

It is also recommended that students take PHYS-1100, PHYS-1200, and CSCI-1200. Those planning to continue on to graduate school should consider taking MATH-4210.

Mathematics of Operations Research Curriculum

The above curriculum emphasizes the use of mathematics for developing and studying analytical models of systems. These models are used to form better decisions in areas such as management, engineering, and the social sciences. In mathematical programming, a problem is modeled as an objective function with constraints on the possible solutions, then the resulting model is optimized. The models are solved using computer programs. Algebra, analysis, and discrete mathematics all play a role in analyzing the models and in developing computer algorithms to solve them. Frequently, the inputs and outcomes of the model are not known with certainty, thus probability and statistics are used.

Students should note that the mathematics options listed above are any 4000-level or higher course from the Department of Mathematical Sciences, plus up to two 4000-level or higher courses from Decision Science (DSES) or Computer Science (CSCI). In other words, of the four mathematics options, a minimum of two must be coded MATH or MATP.

Also, the or option in this curriculum is either MATP-4600 or MATP-4820.

Minor Programs

Students not majoring in mathematics may receive a minor in math by taking four courses at the 4000 level or above from the MATH and MATP course groups. These courses should form a coherent program and have the prior approval of the chairman of the Department of Mathematical Sciences.

Dual Major Programs

The requirements for a dual major are described in the introduction to the Mathematical Sciences Department. Interest in such programs are increasing, and recent combinations have included math and physics, math and computer science, and math and psychology. Typical schedules for such combinations can be found at the department’s Web site under dual majors.

Accelerated Programs

Qualified students may earn a B.S. and M.S. degree in the same or different areas in a shorter-than-usual time. They may do so through the use of advanced placement credit, by taking additional courses during the fall and spring semesters, and/or by taking summer courses.

For example, a student with advanced placement credit for Calculus I and II may earn the B.S. and M.S. degrees within four years by taking an additional course each regular fall and spring semester. Since a student may take up to 21 credit hours per semester at no additional charge, it may be possible to earn both degrees for the cost of a B.S. alone. As a second example, rather than taking more courses during the academic year, a student may earn two degrees in four years by taking eight courses distributed over three summers.

Such a joint degree program requires that the student apply to and be accepted by the Office of Graduate Education at an appropriate stage. A wide variety of joint degree programs can be arranged depending on the student’s background, interests, and desired rate of progress. The interested student should consult the faculty adviser to design an optimum program.

Graduate Programs

The Department of Mathematical Sciences offers programs leading to the M.S. and Ph.D. degrees. Each curriculum is highly flexible, and each student’s program of study is individually designed.

A departmental colloquium series, in which both mathematics faculty and guest lecturers present current research work, supplements course work. In addition, graduate students organize a weekly seminar, in which they present material from their research. Moreover, each semester, faculty and students organize informal seminars that explore topics of mutual interest. Through formal course work, these additional activities, and individual contact with the faculty, students become familiar with all departmental research activities. The department’s Web site also provides an overview of these research activities and lists the faculty working in each area.

Undergraduates with backgrounds in mathematics or any related major with significant mathematical content are admissible to the graduate program.

Master’s Programs

The department offers the M.S. degree in both Applied Mathematics and Mathematics.

Applied Mathematics

The emphasis of this program is on mathematics and how it is employed to study science, engineering, or management problems. It stresses construction, analysis, and evaluation of mathematical models of real-world problems, and those areas of mathematics that are most widely used to solve them. The requirements for this degree allow students to prepare for entry into the Ph.D. program in applied mathematics or for employment in business, industry, or government.

The student must meet the Office of Graduate Education requirements and follow a plan of study acceptable to this office and the Department of Mathematical Sciences. Each student’s program of study must include:

• At least four graduate (6000) level courses of four credits each, of which at least two must be in math (MATH- 6xxx or MATP-6xxx).
• At least four courses coded MATH or MATP of four credits each.
• At least one three- or four-credit course at the 4000 or 6000 level outside the department (i.e., not coded MATH or MATP and not cross listed with any department course), selected in consultation with the math adviser.
• Each student must participate in a capstone professional experience, by registering for and completing one of the following alternatives: 1) a Master’s Project in Mathematics, MATH-6980; 2) a Master’s Practicum, MATH-6970, such as a graduate cooperative internership or active participation in the Applied Mathematics Industry Workshop (a department faculty member must approve your plans in advance and must certify its satisfactory completion); 3) two 6000-level MATH courses, with second digit either 4, 5, 6, 7 or 8 (one may be an appropriate Special Topics course MATH-696x, subject to advsior’s approval); 4) two 6000-level MATP courses (one may be an appropriate Special Topics course MATP-696x, subject to adviser’s approval).

Mathematics

The student must meet the Office of Graduate Education requirements and follow a plan of study acceptable to this office and the Department of Mathematical Sciences. The plan of study should represent a reasonably broad program in mathematics and must contain:

• At least four graduate (6000) level courses of four credits each, of which at least two must have numbers in the range MATH-6000 to MATH-6390.
• At least four courses coded MATH or MATP of four credits each.
• Each student must participate in a capstone professional experience, by registering for and completing one of the following alternatives: 1) a Master’s Project in Mathematics, MATH-6980; 2) a Master’s Practicum, MATH-6970, such as a graduate cooperative internship (a department faculty member must approve your plans in advance and must certify its satisfactory completion); 3) two 6000-level MATH courses, with second digit either 0, 1, 2, or 3 (one may be an appropriate Special Topics course MATH-696x, subject to adviser’s approval).

Doctoral Programs

Students working for the doctorate must demonstrate high achievement both in scholarship and in independent research. All programs must follow the general rules of the Office of Graduate Education.

The Ph.D. degree results from following a program of study in mathematics or in applied mathematics. In either case, the student’s program of study must include:

• At least six, four-credit (nonthesis) graduate mathematics courses (i.e., those with numbers MATH-6xxx or MATP-6xxx)
• At least one three- or four-credit course at the graduate (6000) level outside the department (i.e., not coded MATH or MATP and not cross listed with any department course), selected in consultation with the math adviser
• At most 30 thesis/research credits
• All doctoral students must pass a written preliminary exam as well as an oral qualifying examination, and complete an oral candidacy presentation. Descriptions of these requirements can be found on the department’s Web site.

Any deviations from these requirements must have the approval of the Department’s Graduate Committee.

Course Descriptions

Courses directly related to all Mathematical Sciences curricula are described in the Course Description section of this catalog under the department code MATH or MATP.