Courses

The listing of a course description here does not guarantee a course’s being offered in a particular term. Please refer to the published schedule of classes on the MyBU Student Portal for confirmation a class is actually being taught and for specific course meeting dates and times.

• ENG SE 674: Optimization Theory and Methods 2
  Introduction to optimization problems and algorithms emphasizing problem formulation, basic methodologies, and underlying mathematical structures. Classical optimization theory focusing primarily on linear optimization as well as recent advances in the field. Topics include modeling issues and formulations, linear programming and its duality theory, sensitivity analysis, large-scale optimization, integer programming, introduction to non-linear optimization, interior-point methods, and network optimization problems. Applications considered include production planning, resource allocation, network routing, transportation, fleet management, graph problems, and problems from finance and computational biology. Meets with ENG SE 524 but requires more advanced problem sets and exams. Same as ENG EC 524, ENG EC 674, ENG SE 524. Students may not receive credit for both.
• ENG SE 700: Advanced Special Topics
  Undergraduate Prerequisites: Graduate standing or consent of instructor. - Advanced study of a specific research topic in systems engineering. Intended primarily for advanced graduate students. On Demand. Var cr.
• ENG SE 701: Optimal and Robust Control
  Undergraduate Prerequisites: (ENGEC501 OR ENGME501 OR ENGSE501) - This course is aimed at an introduction (with rigorous treatment) to the fundamentals of optimal and robust control. It will be divided roughly into two parts. The first will cover aspects of robust control including model reduction, H_2 and H_ infinity control, and feedback control of uncertain systems. The second will delve into optimal control including topics such as the linear quadratic regulator, the calculus of variations, the maximum principle, and the Hamilton-Jacobi-Bellman equation. Same as ENG EC701 and ME 701. Students may not receive credits for both.
• ENG SE 710: Dynamic Programming and Stochastic Control
  Undergraduate Prerequisites: (CASMA381 OR ENGEK500 OR ENGME308) and ENGEC402, ENGEC501 or ENGME510 - Introduction to sequential decision making via dynamic programming. The principle of optimality as a unified approach to optimal control of dynamic systems and Markovian decision problems. Applications from control theory and operations research include linear-quadratic problems, the discrete Kalman Filter, inventory control, network, investment, and resource allocation models. Adaptive control and numerical solutions through successive approximation and policy iteration, suboptimal control, and neural network applications involving functional approximations and learning. Same as ENG EC 710 and ENG ME 710. Students may not receive credits for both.
• ENG SE 714: Advanced Stochastic Modeling and Simulation
  Undergraduate Prerequisites: (ENGEK500) or equivalent, knowledge of stochastic processes, or consent of the in structor. - Introduction to Markov chains, point processes, diffusion processes as models of stochastic systems of practical interest. The course focuses on numerical and simulation methods for performance evaluation, optimization, and control of such systems. Same as ENG ME 714. Students may not receive credits for both.
• ENG SE 724: Advanced Optimization Theory and Methods
  Undergraduate Prerequisites: ENGEC524 or consent of instructor. - Complements ENGEC524 by introducing advanced optimization techniques. Emphasis on nonlinear optimization and recent developments in the field. Topics include: unconstrained optimization methods such as gradient and incremental gradient, conjugate direction, Newton and quasi-Newton methods; constrained optimization methods such as projection, feasible directions, barrier and interior point methods; duality; and stochastic approximation algorithms. Introduction to modern convex optimization including semi-definite programming, conic programming, and robust optimization. Applications drawn from control, production and capacity planning, resource allocation, communication and sensor networks, and bioinformatics. Same as ENG EC 724 and ENG ME 724. Students may not receive credits for both.
• ENG SE 725: Queueing Systems
  Undergraduate Prerequisites: (ENGEK500 OR ENGEC505) or consent of instructor. - Performance modeling using queueing networks, analysis of product form and non-product form networks, numerical methods for performance evaluation, approximate models of queueing systems, optimal design and control of queueing networks. Applications from manufacturing systems, computer systems and communication networks. Same as ENG EC 725 and ENG ME 725. Students may not receive credits for both.
• ENG SE 732: Combinatorial Optimization and Graph Algorithms
  Undergraduate Prerequisites: (ENGME411 OR CASCS330) or equivalent course on optimization or algorithms. - Design data structures and efficient algorithms for priority queues, minimum spanning trees, searching in graphs, strongly connected components, shortest paths, maximum matching, and maximum network flow. Some discussion of intractable problems and distributed network algorithms. Same as ENG EC 732, ENG ME 732. Students may not receive credits for both.
• ENG SE 733: Discrete Event and Hybrid Systems
  Undergraduate Prerequisites: (ENGEK500) or equivalent or consent of instructor. - Review of system theory fundamentals distinguishing between time-driven and event-driven dynamics. Modeling of Discrete Event and Hybrid Systems; Automata, Hybrid Automata, Petri Nets, basic queueing models, and stochastic flow models. Monte Carlo computer simulation: basic structure and output analysis. Analysis, control, and optimization techniques based on Markov Decision Process theory with applications to scheduling, resource allocation, and games of chance. Perturbation Analysis and Rapid Learning methods with applications to communication networks, manufacturing systems, and command-control. Same as ENG EC 733 and ENG ME 733. Students may not receive credits for both.
• ENG SE 734: Hybrid Systems
  Undergraduate Prerequisites: (ENGSE501 OR ENGEC501 OR ENGME501) or consent of instructor - The course offers a detailed introduction to hybrid systems, which are dynamical systems combining continuous dynamics (modeled by differential equations) with discrete dynamics (modeled by automata). The covered topics include modeling, simulation, stability analysis, verification, and control of such systems. The course contains several applications from both natural and manmade environments, ranging from gene networks in biology, to networked embedded systems in avionics and automotive controls, and to motion planning and control in robotics. Same as ENG ME 734 and ENG SE 734. Students may not receive credits for both. 1st sem.
• ENG SE 740: Vision, Robotics, and Planning
  Undergraduate Prerequisites: Graduate standing or consent of instructor. - Methodologies required for constructing and operating intelligent mechanisms. Comprehensive introduction to robot kinematics for motion planning. Dynamics and control of mechanical systems. Formal treatment of differential relationships for understanding the control of forces and torques at the end effector. Discussion of robot vision and sensing and advanced topics in robot mechanics, including elastic effects and kinematic redundancy. Same as ENG ME 740. Students may not receive credits for both.
• ENG SE 755: Communication Networks Control
  Undergraduate Prerequisites: (ENGME714) or consent of instructor. - Systems and control perspective into communication networks research. Fundamental systems issues in networking. Survey of a variety of techniques that have recently been used to address networking issues, including queueing theory, optimization, large deviations, Markov decision theory, stochastic approximation, and game theory. Topics will vary from year to year, depending on recent developments in the field. Illustrative topics include: network services and layered architectures, performance analysis in networks, traffic management and congestion control, traffic modeling, admission control, flow control and TCP/IP, routing, network economics and pricing. Same as ENG EC 755. Students may not receive credit for both.
• ENG SE 762: Nonlinear Systems and Control
  Graduate Prerequisites: (ENGME501 OR ENGEC501) or consent of instructor - Introduction to the theory and design methods of non-linear control systems. Application to robotics, vibration and noise control, fluid control, manufacturing processes, and biomedical systems. Mathematical methods based on the theory of differentiable manifolds; non-linear control techniques include feedback linearization, back-stepping, forwarding, and sliding mode control. Additional course topics will include controllability and observability, Lyapunov stability and its applications, limit cycles, input-output stability, zero dynamics, center manifold theory, perturbation theory, and averaging. Same as ENG ME 762. Students may not receive credits for both.
• ENG SE 766: Advanced Scheduling Models and Methods
  Undergraduate Prerequisites: (ENGEK500 & ENGME510) - Emphasizes basic methodological tools and recent advances for the solution of scheduling problems in both deterministic and stochastic settings. Models considered include classical scheduling models, DEDS, neural nets, queueing models, flow control models, and linear programming models. Methods of control and analysis include optimal control, dynamic programming, fuzzy control, adaptive control, hierarchical control, genetic algorithms, simulated annealing, Lagrangian relaxation, and heavy traffic approximations. Examples and case studies focus on applications from manufacturing systems, computer and communication networks, and transportation systems. Same as ENG ME 766. Students may not receive credist for both.
• ENG SE 801: Teaching Practicum 1
  This course cannot be used to meet the structured course requirements. Practical teaching experience for an assigned course, includes some combination of running discussion sections, managing laboratory sections, providing some lectures, preparing homework and solution sets, exams, and grading. Attend lectures/seminars on best teaching practices. Total time commitment: up to 20 hours/week for one semester.
• ENG SE 802: Teaching Practicum 2
  This course cannot be used to meet the structured course requirements. Practical teaching experience for an assigned course, including some combination of running discussion sections, managing laboratory sections, providing some lectures, preparing homework and solution sets, exams, and grading. Attend lectures/seminars on best teaching practices. Total Time commitment: up to 20 hours/week for one semester.
• ENG SE 810: PhD Internship in Systems Engineering
  Graduate Prerequisites: Permission of advisor and an approved internship offer; at least two c omplete semesters in the SE PhD program. - This course provides SE PhD students the opportunity to include a paid internship experience as part of their professional training. The internship must be related to the student's area of study. International students require CPT authorization. Written summary required. Graded P/F. Prerequisite: Permission of advisor and an approved internship offer; at least two complete semesters in the SE PhD program. full-time (30-40 hours/week for at least 12 weeks) = 4 credits; part-time (15-20 hours/week for at least 12 weeks) = 2 credits.
• ENG SE 900: PhD Research
  Undergraduate Prerequisites: Graduate standing. - Graduate Prerequisites: Restricted to pre-prospectus PhD students. - Participation in a research project under the direction of a faculty advisor leading to the preparation and defense of a PhD prospectus.
• ENG SE 951: Independent Study
  Undergraduate Prerequisites: By petition only - Graduate students may study, under a faculty member's supervision, subjects not covered in a regularly offered course. Final report and/or written examination normally required.
• ENG SE 952: SE Mentored Project
  Graduate Prerequisites: Permission of instructor - Students who are pursuing a project to satisfy their practicum requirement for the SE without Thesis and MEng degrees will register for up to 4 credits of this course. The course may be taken more than once up to four credits (ex. two credits in Fall, two credits in Spring). Students will select a suitable project, with a mentor, that can be completed in 4 credits. The Graduate Committee must approve all proposed projects. Each student must write a project report at the end of the course that will be graded P/F by their project mentor.