• Aerospace Engineering
    AE 5903: ST Composites
    This course covers the anisotropic constitutive behavior and micromechanics of composite materials, and the mechanics of composite structures at an introductory graduate level. Topics covered will be chosen from: classification of composites (reinforcements and matrices), anisotropic elasticity, composite micromechanics, effect of reinforcement on toughness and strength of composites, laminate theory, statics and buckling of laminated beams and plates, statics of laminated shells, residual stresses and thermal effects in laminates.
  • Biomedical Engineering
    BME 595: ST:ADVANC MUSCULOSKELETAL BIOM
    This course is intended as an advanced course for engineering students, with an emphasis on applying mechanics principles to study human kinematics and kinetics and their effects at the joint, organ, and tissue levels.  Topics will include: inverse kinematics and dynamics calculations, muscle force/length and force/velocity relationships, bone and cartilage stresses and strains, and clinical biomechanics applications.  Calculations based on experimental measurements and developing, validating, and applying computational approaches will be emphasized.

     BME 595: SP TOP:CONTEMP TOP IN BIOMECHA
    This course will include an extensive review of contemporary literature on the topic of musculoskeletal biomechanics. It is intended to provide students with an appreciation of the experimental techniques and active areas of research at the interface of human movement and the musculoskeletal system.  Topics such as injury, arthroplasty, and the effects of surgical procedures will be discussed. ST:SMART MATERIALS & ACTUATION This course is intended as an advanced course for engineering students, with an emphasis on applying mechanics principles to study human kinematics and kinetics and their effects at the joint, organ, and tissue levels.  

    Topics will include: inverse kinematics and dynamics calculations, muscle force/length and force/velocity relationships, bone and cartilage stresses and strains, and clinical biomechanics applications.  Calculations based on experimental measurements and developing, validating, and applying computational approaches will be emphasized.

    BME 595: ST:SMART MATERIALS & ACTUATION
    This course is intended as an advanced course for engineering students, with an emphasis on applying mechanics principles to study human kinematics and kinetics and their effects at the joint, organ, and tissue levels.  Topics will include: inverse kinematics and dynamics calculations, muscle force/length and force/velocity relationships, bone and cartilage stresses and strains, and clinical biomechanics applications.  Calculations based on experimental measurements and developing, validating, and applying computational approaches will be emphasized.
     
  • Business, School of
    OIE 598: ST:OPTIM METH 4 BUS ANALYTICS
    This course covers mathematical optimization in greater detail beyond the foundational concepts of linear programming. A variety of optimization problem classes will be addressed, likely including integer programming, nonlinear programming, stochastic programming and global optimization. While ensuring an appropriate level of theory, the main emphasis will be the methodological and computational aspects of solving such problems arising in the operational, manufacturing, and service sectors.

    Previous course(s) in linear algebra, basic knowledge about optimization and linear programming, or consent of the instructor

    OIE 598: ST:SUSTBLE CHAIN & OPER MANAG
    This course is intended to provide students with understanding the intra- and inter-organizational implications of environmental practices and policies.  The role of organizational operational and supply chain management functions, activities, tools and methods and their relationship to the natural environment will be introduced and discussed. At the end of the course a successful student should be able to: grasp the scope of general operations and supply chain management and environmental sustainability as they relate to the firm, be able to relate to the manners in which management may respond and collaborate/cooperate with suppliers, customers, and various other stakeholders influencing and influenced by operational and supply chain activities from practical and theoretical case studies and able to evaluate various factors and understand tradeoffs in management decisions as they pertain to environmental operations and supply chain management.
  • Computer Science
    CS 525: ST ST:ALGORITHMS N BIOINF&SYS BIO
    This course will introduce the classical and state-of-the-art computational techniques and algorithms to tackle problems in structural bioinformatics, integrative bioinformatics, bioinformatics of disease, and computational systems biology. Algorithms covered in this course come from a diverse range of research areas including machine learning, data mining, network theory, AI, string and graph algorithms.  

    (Prerequisite: solid programming skills, an undergraduate or graduate course in algorithms or data mining; some basic knowledge in molecular biology and/or biochemistry is strongly suggested but is not necessary.).

    CS 525: ST:ONLINE LEARING INFRUSTRUCTR
    Online Learning Infrastructure "This course acquaints participants with the fundamental concepts and state-of-the-art computer science research in online instructional systems. Advanced interactive instructional systems serve as tutors, as learning companions or both.  

    This course introduces their design, the technology that powers them, the learning theories that motivate them and results from experimental evaluations.  We will cover both the learning theory, and how to design and build systems consist with existing theories. The course consists of weekly presentations on current advanced literature, discussions and a term project. Prerequisite: Proficiency in a high level programming language.'

    CS 525: SP TOP:INTR APP CS W/DATA&ALGO
    This is an introductory graduate course teaching core computer science topics typically found in an undergraduate Computer Science curriculum, but at a graduate-level pace.  It is primarily intended for students with little formal preparation in Computer Science to gain experience with fundamental Computer Science topics.
         
    After a review of programming concepts the focus of the course will be on data structures from the point of view of the operations performed upon the data and to apply analysis and design techniques to non-numeric algorithms that act on data structures.  The data structures covered include lists, stacks, queues, trees and graphs.  Projects will focus on the writing of programs to appropriately integrate data structures and algorithms for a variety of applications.

    This course may not be used to satisfy degree requirements for a B.S., M.S or Ph.D. degree in Computer Science or  a minor in Computer Science.  It may satisfy the requirements for other degree programs at the discretion of the program review committee for the particular degree.

    Prerequisites: Experience with at least one high-level programming language such as obtained in an undergraduate programming course.

    CS 525: SP TOP:PRIVACY PROT TECH & OTH
    This course will cover privacy from a technical viewpoint, with a strong dose of law, policy, and the real world. The focus will be on technical solutions but policy and legal privacy protections will also be covered at some depth, as will how these three aspects of privacy protections interact.

    The course will study various privacy technologies, including cryptography (very briefly), k-anonymity, differential privacy, and data provenance. We'll consider the limitations of, and attacks on, these privacy protections, and to what extent these protections realistically solve the problems.  

    Finally, we will consider privacy within the context of applications such as identity management.  Prior knowledge of cryptography, such as ECE/CS 578, Cryptography and Data Security is not assumed, but would be a welcome complement.
  • Data Science
    DS 595: SP TOP: Urban Network Analysis: Methodologies and Applications
    In recent years, urban infrastructures have undergone a fast expansion, where big urban issues emerge over time, such as pollution, traffic congestion, etc. Urban Network Analysis aims to identify and solve various urban challenges by integrating and analyzing heterogeneous urban network data sources, such as human mobility, transactions, power consumption, weather, etc. This course introduces the framework of urban network analysis, with techniques in urban sensing, data management, data analytics and services. This is a seminar style course, with discussions and weekly presentations on the state-of-the-art literature. There are two team projects involving analyzing large-scale real urban data to tackle urban challenges.

    Prerequisites: DS501 Introduction to Data Science or DS502 / MA 543 Statistical Methods for Data Science or DS 503 / CS 585 Big Data Management or an equivalent graduate level course in Data Mining, Machine Learning, or Data Management, and proficiency in a high level programming language.
  • Electrical & Computer Engineering
    ECE 549: SP TOP: MODEL-BASED DESIGN
    This course addresses the what (modeling), how (design) and why (analysis) of systems through the use of model-based design process. System models will be essential to four key aspects of the design process, derivation of executable specifications, hardware and software design based on simulations, implementation by code generation, and continuous testing and verification. Model-based design can be an effective tool to ensure safe, efficient and reliable operation of cyber-physical systems in which computation and communication are tightly integrated with physical processes.

    Topics may include modeling continuous and discrete dynamics, heterogeneous models, hybrid systems, stochastic models, models of computation, analysis and design of embedded control systems with applications in robotics, system simulation, validation and verification techniques, time-critical systems and human-in-the-loop cyber-physical systems. The examples throughout the course will be drawn from practical robot applications as robotics requires a whole system design approach at the cross-section of environmental models, physical components and algorithms. Course projects will emphasize model-based design for control of robotic systems and smart environments. Students who are not RBE majors will be encouraged to undertake projects that reflect their own engineering systems interests consistent with the specific project objectives.

    (Prerequisites: linear algebra and differential equations; embedded systems; linear systems and control theory or consent of the instructor.)
  • Financial Mathematics
    FIN 598: ST:FINANCIAL INST MKT & TECH
    This course will examine financial institutions and the relationship between U.S. capital markets and global markets.  The class is intended to help students understand the impact of financial intermediaries on the global economy, businesses, and consumers. The course will investigate the organization, structure, and performance of money and capital markets and institutions. The class will examine the major financial management issues confronting financial service firms (depository institutions, insurance companies, investment banks, mutual funds, hedge funds, and pension funds), and it will address the legal, regulatory, financial reform, and risk management issues facing these financial institutions and markets.

    Finally, the course will address the rapid evolution of the financial sector as a result of technology.  We will consider how financial technology (“FinTech”) being developed by startup technology firms and existing financial institutions may disrupt the financial sector through innovation in digital and electronic currencies, online finance and investment platforms, big data, and digital payment systems (among other topics).
  • Interactive Media & Game Development
    IMGD 509: SP TOP: GAME DESIGN WORKSHOP​
    The Game Design Workshop provides students with a series of projects and challenges to introduce game design concepts, techniques, and resources. The course will consist mainly of small in-class exercises that introduce different game design concepts as well as a larger group project in which students are provided a game design challenge with particular demands and affordances for which they will need to design a series of prototypes, test and iterate on those prototypes, and create a plan for full development. In-class time will be spent on small exercises and group workshopping and critique. No programming experience is required to take this course.
  • Mechanical Engineering
    ME 593: ST: AXIOMATIC DSGN OF MFG PROC
    This on-line only, seven week, two credit course includes an in-depth study of axiomatic design, the theory and practice.  Applications are considered primarily, although not exclusively, for the design of manufacturing processes and tools.  Axiomatic design is based on the premise that there are common aspects to all good designs. These commons aspects, stated in the independence and information axioms, facilitate the teaching and practice of engineering design as a scientific discipline.  Analysis of processes and products is considered from the perspective of supporting product and process design.  

    Fundamental methods of engineering analysis of manufacturing processes with broad applicability are developed.  Special attention is given to examples in machining (traditional, nontraditional and grinding), additive manufacturing, and to the production of surfaces.  The ability to generalize is emphasized to facilitate development of analysis and design methods with broader applicability. 

    The content is delivered in video lectures and in readings from the technical literature. The grade is from performance on homework and quizzes given and delivered on-line and on a design project on manufacturing processes.  The project will be developed in a series of assignments which will be reviewed and commented on individually.  Project topics can be from work or dissertations on many kinds of systems and services, in addition to traditional manufacturing processes and tools.  

    Credit cannot be given for this course and any of the similar, in-class versions for 3 credits, MFE520, MTE520 and ME543.

    ME 593: ST: ELEM OF AXIO DSGN MFG PROC
    This on-line only, seven week, two credit course includes an in-depth study of axiomatic design, the theory and practice.  Applications are considered primarily, although not exclusively, for the design of manufacturing processes and tools.  Axiomatic design is based on the premise that there are common aspects to all good designs.  These commons aspects, stated in the independence and information axioms, facilitate the teaching and practice of engineering design as a scientific discipline.  Analysis of processes and products is considered from the perspective of supporting product and process design.

    Fundamental methods of engineering analysis of manufacturing processes with broad applicability are developed.  Special attention is given to examples in machining (traditional, nontraditional and grinding), additive manufacturing, and to the production of surfaces.  The ability to generalize is emphasized to facilitate development of analyses and design methods with broader applicability. 

    The content is delivered in video lectures and in readings from the technical literature. The grade is from performance on homework and quizzes given and delivered on-line and on a design project on manufacturing processes.  The project will be developed in a series of assignments which will be reviewed and commented on individually.  Project topics can be from work or dissertations on many kinds of systems and services, in addition to traditional manufacturing processes and tools.  Credit cannot be given for this course and any of the similar, in-class versions for 3 credits, MFE520, MTE520 and ME543.

    ME 593: SP TOP:INTRO TO BIOMECH & RBTC
    This course introduces Biomechanics and Robotics as a unified subject addressing living and man-made "organisms". It draws deep connections between the natural and the synthetic, showing how the same principles apply to both, starting from sensing, through control, to actuation.  Those principles are illustrated in several domains, including locomotion, prosthetics, and medicine.  The following topics are addressed: Biological and Artificial sensors, actuators and control, Orthotics Biomechanics and Robotics, Prosthetic Biomechanics and Robotics: Artificial Organs and Limbs, Rehabilitation Robotics and Biomechanics: Therapy, Assistance and Clinical Evaluation, Human-Robot Interaction and Robot Aided Living for Healthier Tomorrow, Sports, Exercise and Games: Biomechanics and Robotics, Robot-aided Surgery,  Biologically Inspired Robotics and Micro-(bio)robotics, New Technologies and Methodologies in Medical Robotics and Biomechanics, Neural Control of Movement and Robotics Applications, Applied Musculoskeletal Models and Human Movement Analysis. This course meshes physics, biology, medicine and engineering and introduce students to subject that holds a promise to be one of the most influential innovative research directions defining the 21st century.

    (Recommended background: foundation of physics, linear algebra and differential equations; basic programming skills e.g. using MATLAB, undergraduate level biomechanics, robotics);
  • Physics
    PH 597: SP TOP:FUND OF BIOLOG PHYSICS
    This course will focus on biophysics of cells with an emphasis on mechanics. After an introduction to the relevant length and time scales, forces, and mechanical equilibrium in cells, the following topics will be covered: entropy and the Boltzmann distribution, two-state systems and cooperativity, biopolymers as random walks, single-molecule mechanics,  models of proteins, mechanics of cytoskeletal filaments and beam theory, membranes and cell shape, fluid mechanics in cells, diffusion and molecular crowding, reaction-diffusion systems, biopolymer dynamics, dynamics of molecular motors, ratchet models and force generation.

    PH 597: ST:APPLD DIAGNSTC MEDCL PHYSC
    The purpose of this course is to introduce diagnostic medical physics with focus on  the fundamental imaging physics principles and the clinical applications. Students will be introduced to different medical imaging modalities including general radiography, fluoroscopy, Computed Tomography, Magnetic Resonance Imaging, Ultrasound scan imaging, and nuclear medicine. The course will be composed of  both didactic lectures in the classroom and hands-on experience with the state of the art imaging equipment in a hospital.
  • Robotics Engineering
    RBE 595: SP TOP:FORMAL METHDS IN ROBOTC Mathematical models and the tools of high-level logic (first and second order) have been used to guide specification, development, and verification of software and hardware systems in robot systems and other cyber-physical systems. Because of the high cost of application and complex task specifications, formal methods are introduced for verifying and synthesizing provably correct controllers in robotics. This course provides an exposition to formal methods and their connections with control, optimization, machine learning, and game theory. Topics may include automata theory, temporal logic, abstraction-based control, hybrid systems, probabilistic model checking, deductive verification, game theory and reactive synthesis. Students are expected to propose and complete course projects demonstrating their understanding of the topics.

    Prerequisite: Foundations of probability and random variables; Linear algebra; Differential equations; control theory as in ECE 504 or RBE 502; Foundation of computer science (computational models, formal languages, complexity theory) or consent of the instructor.
     

    RBE 595 191M:  Smart Materials and Actuation
    This hands on course covers smart materials and actuation, with an emphasis on electroactive polymer (EAP) based materials and actuators, such as contractile EAPs, dielectric elastomers (DEAs), and ion-polymer metal composites (IPMCs). Piezoelectric materials and shape memory alloys (SMAs) are included in the course, as well as pneumatic actuation. Because smart materials and electroactivity are relatively new fields, the course involves literature reviews. Each team project will involve two different types of smart materials, where at least one smart material is electroactive. For the team projects, the class will be organized into groups, ensuring that each group had a mixture of different disciplines to promote lively discussion. Two papers will be required, one as a literature review and one about aspects of the team project. Much of the theory and applied research is yet to be done with smart materials, so this is a very creative course that implements design into the projects, which can include biomimicry.

    Level: Graduate level, cross-referenced through the physical sciences and engineering, and available to upper level undergraduates.

    RBE 595 191F:  Formal Methods in Robotics
    Mathematical models and the tools of high-level logic (first and second order) have been used to guide specification, development, and verification of software and hardware systems in robot systems and other cyber-physical systems. Because of the high cost of application and complex task specifications, formal methods are introduced for verifying and synthesizing provably correct controllers in robotics. This course provides an exposition to formal methods and their connections with control, optimization, machine learning, and game theory. Topics may include automata theory, temporal logic, abstraction-based control, hybrid systems, probabilistic model checking, deductive verification, game theory and reactive synthesis. Students are expected to propose and complete course projects demonstrating their understanding of the topics. 

    Prerequisite: Foundations of probability and random variables; Linear algebra; Differential equations; control theory as in ECE 504 or RBE 502; Foundation of computer science (computational models, formal languages, complexity theory) or consent of the instructor.

    RBE 595 196D:  Deep Learning (Online Course)
    This course will cover deep learning and its applications to perception in many modalities, focusing on those relevant for robotics (images (RGB and RGB-D), videos, and audio). Deep learning is a sub-field of machine learning that deals with learning hierarchical features representations in a data-driven manner, representing the input data in increasing levels of abstraction.

    The course will cover the fundamental theory behind these techniques, with topics ranging from sparse coding/filtering, autoencoders, convolutional neural networks, deep belief nets, and Deep reinforcement networks. We will cover both supervised and unsupervised variants of these algorithms, and we will work with real-world examples in perception-related tasks, including robot perception (object recognition/classification, activity recognition, loop closure, etc.), robot behavior (obstacle avoidance, grasping, navigation, etc.), and more.

    The course will involve a project where students will be able to take relevant research problems in their particular field, apply the techniques and principles learned in the course to develop an approach, and implement it to investigate how these techniques are applicable.

    RBE 595 196W:  Advanced Robotics - Parallel and Walking Mechanisms (Online Course)
    Foundations and principles of parallel and walking mechanisms. Topics include advanced spatial/3D kinematics and dynamics of parallel manipulators and legged/walking mechanisms including workspace analysis, inverse and forward kinematics and dynamics, gait analysis of walking mechanisms, motion analysis of parallel mechanisms as well as legged and walking mechanisms, stability/balance analysis of walking mechanisms, and control of parallel manipulators and walking mechanisms. The course will be useful for solving problems dealing with parallel manipulators as well as multi-legged walking mechanisms including humanoid robots, quadruped robots, hexapod robots and all other types of legged walking mechanisms. A final term project would allow students to apply all this information to design, analyze, and simulate parallel and walking mechanisms. Students taking this course are expected to have a background in kinematics and dynamics.

    RBE 595 A91:  Space and Planetary Robotics
    Space and Planetary Robotics course provides historical overview, addresses state of the art and discusses potential future directions of robotics applied to orbiting and voyaging spacecraft technologies and instrumentation, planetary landers and rovers, service, construction and industrial, autonomous and semi-autonomous, conventional and possibly self-replicating robotic systems within non-Earth based settlements, as well as human augmentation systems in the context of space and planetary exploration.

    This course is intended for graduate students and advanced undergraduate students. This is term long course. There is no prerequisite for this course. However, it is recommended that this course is taken in conjunction with either courses within minor in Astrophysics, or courses within minor in Aerospace Engineering, or select courses in Engineering Science and Aerospace Engineering such as: ES2501 Introduction to Static Systems, ES2503 Introduction to Dynamic Systems, AE2713 Astronautics, AE4713 Spacecraft Dynamics and Control, or select courses in Robotics such as RBE1001 Introduction to Robotics, the four course series RBE2001, 2002, 3001 and 3002.

    RBE 595 196N:  Advanced Robot Navigation (Online Course)
    In recent years, robots have become part of our everyday lives. Leaving the research labs to be part of the common tools of a household, tools such as robotic vacuum cleaners (iRobot Roomba, Kalorik), pool cleaners (Polaris, Maytronics), Lawn mowers (Landroid, LawnBott) and more abound. For navigating safely, these robots need the ability to localize themselves autonomously using their onboard sensors. 

    Potential applications of such systems include the automatic 3D reconstruction, 3D reconstruction of buildings, inspection and simple maintenance tasks, metric exploitation, surveillance of public places as well as in search and rescue systems. In this course, we will dive deep into the current techniques for 3D localization, mapping and navigation that are suitable for robotic applications.  

    Required prerequisites: RBE 500 - Foundations of Robotics, RBE 501 – Robot Dynamics, RBE 502 – Robot Control

  • Social Science & Policy Studies
    SS 590: ST: ENERGY AND ENVIRO DYNAMICS
    Energy and Environmental Dynamics helps students develop understanding and proficiency in system dynamics simulation of energy and environmental problems. The majority of this course is devoted to case studies that focus on energy, water and environmental problems in the western USA. Major business applications deal with boom and bust in power plant construction and a similar pattern of boom and bust in real-estate construction.

    SS 590: ST:APP MULTI MODEL IN MATH EDU
    This course examines current issues in mathematics education and introduces students to the analysis of nested data structures (e.g. students within classrooms). Readings will be drawn from book chapters on multilevel modeling and journal articles that utilize a national longitudinal data set (ECLS-K) to answer questions about student learning in mathematics education. The lab portion of this course will provide students with opportunities to learn and apply hierarchical linear modeling to longitudinal data using two computer programs (HLM and SPSS).

    SS 590: ST:Q/QMETHD ASSESS STDT LEARN
    Assessment that supports teaching and learning is the focus of this course. Participants are introduced to the five keys of quality classroom assessment (Chappuis et al.) and examine each individual key through introductory readings, classroom case studies, discussions with colleagues, activities, and personal reflections.

    Participants will go through the process of standard-based planning to define learning targets, identify misconceptions, and develop assessment plan. A variety of quantitative and qualitative assessment methods will be introduced and practiced during the course. In addition, participants will review some key documents related to assessment of student
    learning. The final course assignment is a performance assessment, in which participants are asked to design a quality assessment, employ it in their classroom (if possible), analyze results and reflect on the experience. Participants will be able to develop and receive feedback on the final project’s components during the course.

    SS 590: ST:GRNT WRITG SCIENCE & EDUC
    This course will provide the foundation to enable graduate students to find appropriate funding sources and write a competitive grant proposal in learning sciences and educational psychology research. Students will learn about the entire grant submission process, including proposal development and the peer review evaluation process. The end goal of the course is to create a high quality grant or dissertation fellowship proposal for agencies such as NSF, IES, AERA, and the Spencer Foundation.