Operations Research 1 OPERATIONS RESEARCH Lecturers Anastasiya Protasov Charles Puelz Contact Information Mohammad Sarraf Joshaghani Computational and Applied Mathematics https://www.caam.rice.edu/ Pfeiffer Postdoctoral Instructors 2117 Duncan Hall Mario Bencomo 713-348-4805 Tyler Perini Illya V. Hicks Department Chair Professor, Joint Appointment [email protected] John Edward Akin Adjunct Professors Operations Research (OPRE) is a major offered by the Computational and Richard Carter Applied Mathematics Department. The OPRE major offers undergraduate Amr El-Bakry students an education that emphasizes models for decision-making Roland Glowinski in complex systems, and tools for making the best possible decisions. Detlef Hohl The Operations Research major will provide students with both a deep Hector Klie set of analytical skills and contextual knowledge of important problem domains, such as healthcare and energy. Program graduates will have the knowledge and tools to help companies and governments make the best Adjunct Associate Professors possible decisions in changing and uncertain environments. Edward Castillo C. David Fuller Bachelor's Program • Bachelor of Arts (BA) Degree with a Major in Operations Research Adjunct Assistant Professors (https://ga.rice.edu/programs-study/departments-programs/ Sebastian Acosta engineering/operations-research/operations-research-ba/) Randy Davila David T. Fuentes Operations Research does not currently offer an academic program at the Paul Hand graduate level. Taewoo Lee Craig Rusin Chair For Rice University degree-granting programs: Illya V. Hicks To view the list of official course offerings, please see Rice’s Course Catalog (https://courses.rice.edu/admweb/!SWKSCAT.cat? Professors p_action=cata) Maarten V. de Hoop To view the most recent semester’s course schedule, please see Rice's Matthias Heinkenschloss Course Schedule (https://courses.rice.edu/admweb/!SWKSCAT.cat) Illya V. Hicks Beatrice M. Rivière Computational & Applied Mathematics Andrew J. Schaefer Richard A. Tapia (CAAM) CAAM 210 - INTRODUCTION TO ENGINEERING COMPUTATION Assistant Professor Short Title: INTRO TO ENG COMPUTATION Department: Computational & Applied Math Jesse Chan Grade Mode: Standard Letter Course Type: Lecture/Laboratory Professors Emeriti Distribution Group: Distribution Group III Robert E. Bixby Credit Hours: 3 Steven J. Cox Restrictions: Enrollment is limited to Undergraduate, Undergraduate Sam H. Davis, Jr. Professional or Visiting Undergraduate level students. John E. Dennis Course Level: Undergraduate Lower-Level Henry H. Rachford, Jr. Description: Modeling, Simulation, and Visualization via MATLAB. Danny C. Sorensen Numerical methods: Newton's method in one and several dimensions. William W. Symes Gaussian elimination and optimization. Application to problems in Chao-Cheng Wang science and engineering. Lectures are held Monday and Wednesdays. In a Yin Zhang laboratory component held on Fridays, students work in small groups on computational projects led by a Rice Learning Assistant. Recommended Prerequisite(s): MATH 101. 2020-2021 General Announcements PDF Generated 08/16/21 2 Operations Research CAAM 238 - SPECIAL TOPICS CAAM 378 - INTRODUCTION TO OPERATIONS RESEARCH AND Short Title: SPECIAL TOPICS OPTIMIZATION Department: Computational & Applied Math Short Title: INTRO TO O.R. AND OPTIMIZATION Grade Mode: Standard Letter Department: Computational & Applied Math Course Type: Internship/Practicum, Laboratory, Lecture, Seminar, Grade Mode: Standard Letter Independent Study Course Type: Lecture Credit Hours: 1-4 Distribution Group: Distribution Group III Restrictions: Enrollment is limited to Undergraduate, Undergraduate Credit Hours: 3 Professional or Visiting Undergraduate level students. Restrictions: Enrollment is limited to Undergraduate, Undergraduate Course Level: Undergraduate Lower-Level Professional or Visiting Undergraduate level students. Description: Topics and credit hours vary each semester. Contact Course Level: Undergraduate Upper-Level department for current semester's topic(s). Repeatable for Credit. Description: Formulation of mathematical models of complex decisions CAAM 334 - MATRIX ANALYSIS FOR DATA SCIENCE arising in management, economics, and engineering. Models using linear, Short Title: MATRIX ANALYSIS DATA SCIENCE nonlinear, stochastic and integer programming, as well as networks. Department: Computational & Applied Math Linear programming duality and its modeling implications. Overview of Grade Mode: Standard Letter basic solution methods for these optimization models. Recommended Course Type: Lecture Prerequisite(s): MATH 212 and (CAAM 335 OR MATH 211 OR MATH 355). Distribution Group: Distribution Group III CAAM 382 - STOCHASTIC MODELS Credit Hours: 3 Short Title: STOCHASTIC MODELS Restrictions: Enrollment is limited to Undergraduate, Undergraduate Department: Computational & Applied Math Professional or Visiting Undergraduate level students. Grade Mode: Standard Letter Course Level: Undergraduate Upper-Level Course Type: Lecture Description: Solution of linear systems and linear least squares problems. Credit Hours: 3 Eigenvalue problem and singular value decomposition. Introduction to Restrictions: Enrollment is limited to Undergraduate, Undergraduate gradient based methods. Applications to data science. Recommended Professional or Visiting Undergraduate level students. Prerequisite(s): (MATH 212 or MATH 222) and (CAAM 210 or COMP 140 Course Level: Undergraduate Upper-Level or STAT 405) Mutually Exclusive: Cannot register for CAAM 334 if student Prerequisite(s): MATH 102 or MATH 106 has credit for CAAM 335. Description: Fundamentals of stochastic modeling. Topics include CAAM 335 - MATRIX ANALYSIS discrete & continuous time Markov models, Poisson processes, renewal Short Title: MATRIX ANALYSIS theory, queueing systems, reliability, Markov decision processes, optimal Department: Computational & Applied Math design and control. Recommended Prerequisite(s): (STAT 280 or 305 or Grade Mode: Standard Letter 310 or 315) and MATH 212 and (CAAM 210 or COMP 140) and (CAAM 335 Course Type: Lecture or MATH 355) Distribution Group: Distribution Group III CAAM 415 - THEORETICAL NEUROSCIENCE: FROM CELLS TO LEARNING Credit Hours: 3 SYSTEMS Restrictions: Enrollment is limited to Undergraduate, Undergraduate Short Title: THEORETICAL NEUROSCIENCE Professional or Visiting Undergraduate level students. Department: Computational & Applied Math Course Level: Undergraduate Upper-Level Grade Mode: Standard Letter Description: Equilibria and the solution of linear systems and linear Course Type: Lecture least squares problems. Eigenvalue problem and its application to solve Credit Hours: 3 dynamical systems. Singular value decomposition and its application. Restrictions: Enrollment is limited to Undergraduate, Undergraduate Recommended Prerequisite(s): (MATH 212 or MATH 222) and (COMP 140 Professional or Visiting Undergraduate level students. or CAAM 210) Mutually Exclusive: Cannot register for CAAM 335 if Course Level: Undergraduate Upper-Level student has credit for CAAM 334. Description: We present the theoretical foundations of cellular and CAAM 336 - DIFFERENTIAL EQUATIONS IN SCIENCE AND ENGINEERING systems neuroscience from distinctly quantitative point of view. We develop the mathematical and computational tools as they are needed Short Title: DIFF EQUATIONS SCI & ENG Department: Computational & Applied Math to model, analyze, visualize and interpret a broad range of experimental Grade Mode: Standard Letter data. Cross-list: ELEC 488, NEUR 415. Graduate/Undergraduate Course Type: Lecture Equivalency: CAAM 615. Recommended Prerequisite(s): CAAM 210 Distribution Group: Distribution Group III or MATH 211 or CAAM 335 or MATH 355. Mutually Exclusive: Cannot Credit Hours: 3 register for CAAM 415 if student has credit for CAAM 615. Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level Description: Classical and numerical solution techniques for ordinary and partial differential equations. Fourier series and the finite element method for initial and boundary value problems arising in diffusion and wave propagation phenomena. Recommended Prerequisite(s): (MATH 212 or MATH 222) AND CAAM 210. 2020-2021 General Announcements PDF Generated 08/16/21 Operations Research 3 CAAM 416 - NEURAL COMPUTATION CAAM 435 - DYNAMICAL SYSTEMS Short Title: NEURAL COMPUTATION Short Title: DYNAMICAL SYSTEMS Department: Computational & Applied Math Department: Computational & Applied Math Grade Mode: Standard Letter Grade Mode: Standard Letter Course Type: Lecture Course Type: Lecture Credit Hours: 3 Credit Hours: 3 Restrictions: Enrollment is limited to Undergraduate, Undergraduate Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level Course Level: Undergraduate Upper-Level Description: How does the brain work? Understanding the brain requires Description: Existence and uniqueness for solutions of ordinary sophisticated theories to make sense of the collective actions of billions differential equations and difference equations, linear systems, nonlinear of neurons and trillions of synapses. Word theories are not enough; we systems, stability, periodic solutions, bifurcation theory. Theory and need mathematical theories. The goal of this course is to