Non-COMP PG Course List (under SENG)

Course Description:
Reaction mechanisms and kinetics. Homogeneous and heterogeneous catalysis. Ideal reactors. Multiphase reactors. Interplay of reaction, mixing, heat and mass transfer. Design of reaction systems involving organics, inorganics, and polymeric materials. Experimental techniques in reaction engineering. Use of mathematical software to problem solving.

Course Description:
Separation of gaseous and liquid mixtures by adsorption. Affinity chromatography. Membrane separation technology: reverse osmosis, ultrafiltration. Electrophoresis and other product recovery methods.

Course Description:
The course will cover digital and advanced control methods such as adaptive, model predictive, and learning controls and methods of process monitoring and optimization in the context of big data environment.

Course Description:
This course provides an introduction to the application of deep learning methods in chemical and biological engineering. The course will cover the fundamental concepts and techniques in deep learning, such as deep neural networks, backpropagation, convolutional and recurrent neural networks, and transformer models. The course will focus on applying these methods to solve problems in chemical and biological engineering, including molecule and reaction property prediction, drug discovery, process monitoring and control, etc.

Course Description:
The fundamental laws of thermodynamics, properties of pure substances and mixtures, phase and chemical equilibria, intermolecular forces. Brief introduction to statistical thermodynamics, colloid and interfacial phenomena, and molecular self-assembly.

Course Description:
The course will first review some basic concepts in polymer physics and polymer chemistry. The course focuses more in polymer and materials characterization and related fabrication toward applications of advanced and functional polymers. The characterization techniques include thermal analysis of differential scanning calorimetry (DSC), dynamic thermal mechanical analysis (DTMA), thermal gravimetric analysis (TGA), scanning electron microscopy (SEM), transmission electron microscopy (TEC), optical microscopy, infrared spectroscopy (FTIR), X-ray diffraction, surface analysis, and mechanical properties and testing. MCPR's instrument demo will also be arranged.

Course Description:
The course will provide students with a general understanding of the relationship of polymer structure and properties that may help them in selection and design of polymers for their research. Applications in engineering materials, membrane separations, and bioengineering will be discussed.

Course Description:
This course introduces fundamentals of protein science as well as rational design and evolutionary approaches for engineering protein molecules. Protein fundamentals provide the basic knowledge of protein structure and function. Rational design-based protein engineering use several case studies to illustrate the role of modern computational tools in design of functional protein molecules such as catalysts, biosensors, biomaterials, etc. Protein directed evolution topics cover mechanisms of biomolecular evolution, fitness landscapes, examples of successful protein evolution, and metabolic engineering enabled by directed evolution.

Course Description:
Nanomaterials and nanotechnology have become a rapid growth area in the 21st century. This course provides an introduction to students who enter into this exciting area of research. The course will focus on major routes for the synthesis of nanostructured materials. Selected applications of nanomaterials in chemical engineering applications, such as separation and catalysis, will be studied.

Course Description:
Electrochemical energy conversion and storage technologies such as fuel cells, batteries, supercapacitors, solar cells, electrolyzers, CO2 reduction, etc. help overcome the energy and environmental problems that have become prevalent in our society. This course will focus on the principles and critical materials for each technology. Cutting-edge research areas as well as electrochemistry fundamentals will be discussed in this course.

Course Description:
Advanced reliability methods in engineering decision; Bayesian methods, system reliability and design, risk analysis, probabilistic observational method, Markov and availability models, random field, large-scale system simulation, decision with multiple objectives.

Course Description:
In-depth discussion of principles, techniques, and models of project finance in capital-intensive infrastructure projects, including international infrastructure markets; project bankability; project agreement and ancillary contracts; risk analysis and management; financial structuring, modeling and evaluation; outsourcing; case studies of various public-private partnerships in infrastructure development.

Course Description:
This course covers the principles and applications of information technology for construction management. Topics include building information modeling, database management and implementation, web-based communication and project management technologies, decision support systems, knowledge management, and data processing and analysis.

Course Description:
This course introduces essential knowledge and skills in engineering financial management. Topics cover interactions of engineering, business and society, analysis of financial statements of engineering and technology companies, engineering investment, and financial and operational management.

Course Description:
This course offers a general overview of the structural health monitoring (SHM) technologies. This structure of the course can be divided into three parts: the first part presents various non-destructive evaluation (NDT) technologies for detecting damage at material and local (structural) level, including wave-based methods, thermography testing, etc; the second part introduces vibration based SHM and system identification, which exploits the accelerations of structural response for evaluating the global structural condition; the third part introduces the fundamentals and applications of fiber optic sensing technologies in infrastructure sensing and SHM. This course both equips students with the fundamental knowledge on structural sensing and health monitoring, as well as introduces the cutting-edge applications on this topic.

Course Description:
This course introduces the limit states design method for bridges, discusses the design philosophy and code requirements and presents examples of analysis and design of bridge super-structure components (using the limit states design method).

Course Description:
Introduction to seismic engineering and seismic design and analysis of concrete structures, including seismology, seismic hazards, dynamics of SDOF and MDOF systems, seismic response spectrum, conceptual design of concrete buildings for seismic resistance, capacity design principles, seismic design of reinforced concrete beams, columns, walls and beam-column joints.

Course Description:
Wind structures; wind loads; wind induced vibrations; wind codes; wind tunnel test techniques; structural monitoring; and vibration control.

Course Description:
FEM formulation; variational and Galerkin principles for continuum; element technology; numerical integration scheme; solution of large systems of linear equations; applications to structural mechanics; fluid flow and heat transfer problems.

Course Description:
Principles of treatment for removing contaminants from drinking water and municipal wastewaters; includes equalization, neutralization, precipitation, coagulation and flocculation, sedimentation, filtration, air stripping, carbon adsorption, disinfection.

Course Description:
Chemistry applied to reactions occurring in water and wastewater, includes inorganic solution chemistry, chemical equilibrium, acids/bases, coordination chemistry, chemical kinetics, colloid chemistry, solubility and precipitation, oxidation-reduction potential.

Course Description:
Regulatory aspects of the handling and disposal of hazardous wastes, and innovative technologies for hazardous wastes treatment and contaminated soils such as bioremediation, and soil washing will be included.

Course Description:
Practical aspects of solid waste collection methods and equipment, current available disposal techniques with emphasis on complete engineering design of landfill systems, and landfill leachate treatment will be included.

Course Description:
This course provides a foundation for data analysis and statistics-aided physical diagnosis in water and climate related studies. Students will have a fundamental understanding of why climate and water research needs the assistance of statistics and probabilities. The course will cover topics including robust and resistant statistics, conditional climatology and persistence analysis, parametric probability distribution, spatiotemporal analysis, and visualization etc. with real analysis examples.

Course Description:
An introduction to turbulence, including the nature of turbulence, governing equations of turbulent flow, structure of turbulence, turbulence modeling, experimental measurements of turbulence and an introduction to computational fluid dynamics.

Course Description:
The course focuses on the physical processes in fluid systems and their mathematical representation; includes the fundamental laws of classical mechanics and thermodynamics and how these principles are applied to fluid flow problems. The processes of waves and mixing in fluids are emphasized. The type of fluid systems to be studied varies from year to year depending on the students’ interest and can range from natural to engineered systems including fluid based renewable energy systems.

Course Description:
Reviews transportation planning models and traffic analysis; examines the assignment of traffic flow on a network according to user-equilibrium and system optimal objectives; addresses formulation methods and solution techniques.

Course Description:
Overview of transportation planning process; population/employment forecasting techniques; discrete choice models; simplified transportation demand models.

Course Description:
Traffic flow fundamentals; microscopic and macroscopic traffic flow characteristics; principle and theory of traffic signals; essential modeling techniques; various traffic signal control models.

Course Description:
Discrete choice modeling and stated choice methods are used in many fields to study individual, household, and organizational behavior. This course covers advanced discrete choice model construction, estimation, and stated choice experimental design theory and practice.

Course Description:
Selected topics from recent advances in theoretical and experimental development in soil mechanics; includes stress-strain behavior of soil, consolidation settlement, drained and undrained strength slope stability problems.

Course Description:
Current practice of foundation design and analysis; includes design and analysis of bulkheads, deep excavation, tieback systems, tunneling in soft ground, buried conduits, lateral pile loading, pier foundations.

Course Description:
Advanced soil models and recent developments in numerical methods in geotechnical modeling, including constitutive laws, critical state soil mechanics, multiple yield surface models, finite elements for boundary value problems, diffusion and consolidation problems.

Course Description:
Earthquakes and characterization of ground motions, seismicity assessment, soil dynamics and site response analysis, soil liquefaction assessment and post-liquefaction analysis, seismic analysis of slopes and embankments, lateral earth pressures and retaining systems, dynamic soil-structure interaction.

Course Description:
Presents state-of-the-art geotechnical site characterization methodologies; includes basic principles of site characterization planning, drilling and sampling, soil and rock description, cone penetration test, standard penetration test, pressuremeter test, dilatometer test, geophysical methods, permeability and ground water monitoring, and fundamentals of geostatistics.

Course Description:
Fundamental principles, stress state variables, steady-state and transient flows, theory of shear strength and its measurements, soil stiffness, plastic and limit equilibrium analyses of earth pressures, slope stability and bearing capacity, critical state framework, instrumentation, engineering applications on slopes including static liquefaction of loose fill slopes, foundations, forensic studies such as slope failures.

Course Description:
Analysis of stress and strain; elastic and inelastic behavior of materials; formulation of BVP; beam on elastic foundations; torsion of noncircular thinwalled members; deformation of cylinders and spheres; inelastic analysis.

Course Description:
Fundamental concepts (workability, strength, dimension stability, and durability); updated concrete technology (micro structural engineering, development of special concretes); concrete fracture and modeling; nondestructive evaluation methods for concrete structures.

Course Description:
Introduction to the concept of micro-systems. Dimensional scaling and its implications. Multi-physics modeling. Micro-fabrication techniques. Introduction to Coventor, a numerical simulation package for micro-systems. The design, implementation and testing of a micro-device.

Course Description:
Noise analysis; Advanced op-amp design techniques; Analog VLSI building blocks: multipliers, oscillators, mixers, phase-locked loops, A/D and D/A converters; Passive filter design; Frequency scaling; Active filter design.

Course Description:
Principles and characteristics of semiconductor devices found in State-of-the-Art ICs. Emphasis is on deep-submicron MOS device design, characterization and modeling. Important issues such as short channel effects, high-field behavior, hot carrier effects, reliability and device scaling for present and future technology will be covered.

Course Description:
Process technologies in IC fabrication: epitaxial growth; chemical-vapor and physical-vapor deposition of films; thermal oxidation; diffusion; ion implantation; microlithography; wet/dry etching processes; process integration of MOS and bipolar technologies.

Course Description:
Laboratory course requiring hands-on work in fabricating MOS transistors. Process modules including photolithography, dry etching, wet etching, metal sputtering, oxidation, diffusion and low-pressure chemical-vapor deposition will be covered. Student will also learn to characterize the fabricated devices.

Course Description:
A brief review of modern optics theories, Fourier optics based devices and systems, fundamentals of laser physics, optoelectronics, nonlinear optics and laser spectroscopy.

Course Description:
Conventional and unconventional fabrication of nanostructures including electron beam lithography, nanoimprint, chemical synthesis, self-assembly, etc.; size dependent electronic and optoelectronic properties of nanomaterials; large-scale assembly and integration of nanomaterials for electronics; energy harvesting and storage devices using nanoelectronic materials.

Course Description:
Analysis of power semiconductor device technologies in the context of electric power conversion and transmission; emphasis on the understanding of the critical roles of semiconductor device technologies in power and energy conversion. The mainstream silicon and emerging semiconductor power devices technologies; material properties, device structure design, advanced fabrication techniques, and device characteristics. Critical device-circuit interaction issues and basic power electronics circuits will be covered focusing on the role of these circuits in electric power conversion and transmission.

Course Description:
Students will receive the following knowledge: Electromagnetic fields & waves, transmission line theory, Smith Chart, S-parameters, and Network Analysis; RF wireless communication systems; Properties of passive components; Impedance Matching network, RLC networks, and 2-port parameters; Microwave measurement and calibration; Simulation methods for EM passive devices: HFSS & PathWave Advanced Design System (ADS); Micron passive acoustic wave devices: resonators, filters, delay lines; Simulation methods for multi-physic devices: COMSOL; MEMS technologies for RF microsystems. This course discusses methodologies to synthesize and model the operation of several key passive components currently employed in commercial Radio Frequency (RF) microsystems. The operation, design methodologies, and equivalent circuit representations relative to RF devices will be presented.

Course Description:
The course introduces the important building blocks in modern computing systems including superscalar processor pipeline, memory hierarchies, network design in the multicore‐processors. The design techniques, evaluation metrics and optimization techniques will be discussed in detail with the example of real computer systems. The students will gain not only theoretical knowledge through lectures, but also hands‐on experiences through projects.

Course Description:
This course provides a comprehensive survey of solid-state devices developed after 2000. Topics include advanced thin-film device physics, next-generation transistors, perovskite and organic photovoltaics (including tandem configurations), memristors, in-memory computing, and sensors/organic electrochemical transistors. The course places a strong emphasis on quantitative electrical characterizations and luminescent measurement techniques, model-based reasoning, reliability and variability assessments, and device-system co-design, particularly for applications in displays, imaging, and energy.

Course Description:
Structured design styles; specification, synthesis and simulation using Hardware Descriptive Language (HDL); Structural chip design and system design; Circuit design of system building blocks: arithmetic unit, memory systems; clocking and performance issues in system design; Design-Automation tools and their applications.

Course Description:
Introduction to techniques for analyzing, engineering and testing of circuits for RF/microwave frequencies using CAD tools. The lab provides hands-on CAD/simulation, building and testing of low-noise amplifier, mixer, VCO, filter, IF AGC, detectors and other circuits discussed in lecture.

Course Description:
Crystal Lattices; lattice vibration and thermal properties of crystals; free-electron theory; electrons in periodic lattices; carrier transport; metal semiconductor contacts and semiconductor surfaces; optical processes.

Course Description:
Introduction to state-of-the-art development in the broad area of nanoelectronics, including concepts and devices for spin electronics and quantum information science. Students are expected to demonstrate the capability of applying fundamental principles to understand advanced electronic devices through hands-on homework projects.

Course Description:
Introduction of the human visual system, Colorimetry and photometry, Introduction of the modern TFTs, Modern AMLCD, AMOLED, Fluorescence and phosphorescence, Introduction of Electrophoretic displays, Color electrophoretic displays, Nano-material for displays, Electroluminescence and Photoluminescence, Quantum dot, Quantum rods, State-of-the-art development in the area of display technology: High-resolution displays (4k, 8k, and 10k), Local backlight dimming, Introduction to AR/VR display solutions, Holographic displays, Flexible displays etc.

Course Description:
High frequency circuit design for wireless applications. S-parameters, front-end amp, VCO, PLL, power amplifier, and integration issues will be covered.

Course Description:
Borel/sigma fields. Sequences of random variables and convergence. Spectral factorization. Karhunen-Loeve Expansion. Stationarity, ergodicity and spectral estimation. Mean square estimation and Kalman filtering. Entropy. System identification.

Course Description:
The aim of this course is to provide an in-depth treatment of the theoretical basis, analysis, and design of digital communication systems. The first half of the course will focus on the theoretical foundations of a basic digital communication system, including source coding, modulating and channel coding, and introductory information theory. The second half will deal with advanced techniques including orthogonal frequency division multiplexing (OFDM), multi-antenna communications, spread-spectrum communications, and cooperative communications.

Course Description:
This course introduces state-of-the-art development in the interplay between information theory, data compression, and machine learning, including source coding theory, deep generative models, neural data compression, representation learning, compressibility and learnability, and neural network compression.

Course Description:
Stochastic Optimization plays a critical role in radio resource optimization of wireless networks, optimal control theory as well as financial engineering (portfolio optimization). This course will focus on the stochastic optimization theory and the application to the design and optimization of next generation wireless systems and federated learning applications. Topics covered include (A) Physical Layer Modeling: review of information theory for wireless fading channels, MIMO spatial diversity and spatial multiplexing, (B) Theory of Stochastic Optimization: classifications and motivating examples of stochastic optimizations [Type I stochastic Optimization and Type II stochastic optimization problems], theory of Stochastic Approximation, Stochastic Gradient, (C) Applications of Type I SO: Robust optimizations and Federated Learning: (D) Applications of Type II SO: Markov Decision Process, Stochastic Stability and Delay-optimal wireless resource control.

Course Description:
Convex optimization theory with applications to communication systems and signal processing: convex sets/functions/problems; Lagrange duality and KKT conditions; saddle points and minimax problems; numerical algorithms; primal/dual decomposition methods. Applications: filter design; robust beamforming; power control in wireless systems; design of MIMO systems; GP duality in information theory; network utility maximization. For PG students in second year or above.

Course Description:
DC-DC conversion: topologies, continuous and discontinuous conduction modes, steady state analysis, loop gain analysis and relevant mathematical tools, stability and compensation; AC-DC conversion: power factor correctors.

Course Description:
Integrated circuit techniques for power management components such as voltage references, linear voltage regulators, low dropout regulators, switch mode power converters and switched-capacitor power converters.

Course Description:
The course aims to systematically introduce major issues of mixed-signal circuit designs and their applications in bio-medical and sensory systems. The first half course is dedicated to mixed-signal IC design. The course starts with 2 review classes on OPAMP design, filter design and circuit noise. Then, the course covers topics on pipelined ADC, Sigma-delta ADC, and SAR ADC. The second half course is dedicated to sensory and bio-medical IC design. The topics include bio-potential detection, implants, DNA detection, CCD, CMOS imaging, and CT/SPECT.

Course Description:
The course introduces Electronic Design Automation (EDA) techniques for VLSI digital IC design. The modern RTL to GDS-II design flow and related tools will be explained in detail. Classical automated algorithms adopted in logic synthesis, floorplanning, placement, clock tree synthesis (CTS), routing, etc. will be covered. Simulation and optimization techniques of key IC design objectives, including recent research on AI-assisted EDA, will be presented.

Course Description:
Introduces modern system theory, with applications to control, signal processing and related topics. Basic system concepts, state-space and I/O representation, properties of linear systems, controllability, observability, minimality, transfer-function matrices, state and output feedback, stability, observers, optimal regulators.

Course Description:
This course focuses on the fundamental mathematical and physical principles of computer vision. It begins by introducing the physical imaging process, encompassing crucial subjects such as color, polarization, radiometry, reflectance models, and photometric methods. Subsequently, it explores the realm of geometric multi-view vision, encompassing topics like features, multi-view stereo, optical flow, structure-from-motion, visual SLAM, and NeRF. Finally, the course delves into the domain of learning-based methods including classification, segmentation, detection, and diffusion models.

Course Description:
Extensive introduction to robot manipulation theory from a geometric viewpoint. Rigid-body kinematics; spatial and body representation of rigid-body velocities; coordinate transformations; forward kinematics of open-chain manipulators; solution of inverse kinematics; robot workspaces; nonlinear decoupling control and force control.

Course Description:
The course gives an introduction to the analysis and design of sensing, estimation and control systems in a networked setting. It consists of three parts: the first part introduces necessary background knowledge in communication networks, sensor networks, linear state estimation, MAP and ML estimators, Kalman filtering, and modern control theory; the second part focuses on analysis of network effect to remote state estimation and control; the third part presents some advanced topics including distributed state estimation and resource allocation through scheduling.

Course Description:
This course gives a comprehensive introduction to aerial robots. The goal of this course is to expose students to relevant mathematical foundations and algorithms, and train them to develop real-time software modules for aerial robotic systems. Topics to be covered include rigid-body dynamics, system modeling, control, trajectory planning, sensor fusion, and vision-based state estimation. Students will complete a series of projects which combine into an aerial robot that is capable of vision-based autonomous indoor navigation.

Course Description:
This course provides an introduction to the latest advancements in the broad area of artificial intelligence and its applications in healthcare. It covers basic concepts of deep learning as well as advanced approaches for analyzing diverse healthcare data, including medical images, clinical reports, and biological data. Through hands-on homework projects, students are expected to demonstrate their capability in applying fundamental deep learning techniques to tackle various real-world healthcare problems and challenges.

Course Description:
This is an introductory course on computational biology at the molecular level. It will cover basic biological knowledge, important biological questions, common data acquisition techniques, popular data analysis algorithms and their applications. The major content of this course is computation-oriented.

Course Description:
Introduction to Microfluidics and Biosensors; Overview of microfabrication materials & techniques; microfluidic principles; miniaturized biosensors; micro total analysis system (µTAS) & lab-on-a-chip (LOC) for clinical and research applications.

Course Description:
The course provides a high-level description of modern engineering research practices. It covers topics including research mentality, the scientific method, evaluating research topics, literature search, report writing, presenting data, publication, research management, research ethics and technology transfer.

Course Description:
The course introduces concepts, principals and techniques related to the design, planning, management and improvement of both manufacturing and service operations. Topics include demand forecasting and estimation, inventory management, production control and process improvement, queueing systems, procurement and supply chain management.

Course Description:
This course focuses on the theory and the use of deterministic optimization models for real life decision making problems. It covers linear, integer, combinatorial and nonlinear programming.

Course Description:
Poisson processes, renewal processes, Markov processes. Fundamental concepts and applications of these stochastic processes demonstrated through examples in queueing, inventory and reliability models.

Course Description:
The course introduces advanced concepts and mathematical principles in statistical inference (e.g., estimation theory, hypothesis testing, and regression models) and machine learning (e.g. classification and tree-based models, support vector machines, model selection, and unsupervised learning). This course assumes the knowledge of multivariable calculus and probability.

Course Description:
Continuum concept for deformation of solids; analysis of stress and strain; constitutive equations; solution of problems relevant to materials processing, fracture mechanics and structural analysis; energy methods and numerical solutions.

Course Description:
Tensor notation, derivation of Navier-Stokes equations, vorticity transport, viscous flow, flow separation, boundary layer, flow instability, turbulent boundary layer, stratified flow, rotating flow.

Course Description:
Numerical simulation of viscous incompressible flows and heat transfer; finite-difference and finite element methods; accuracy and stability; grid generation; stream function and primitive-variable formulations; application to internal, external flows, diffusion, convection, and dispersion problems.

Course Description:
Elementary statistical concepts; ensembles and postulates; partition functions and their properties; calculation of thermodynamic properties; kinetic theory of transport process; fluctuation-dissipation theorem; Langevin equation; mass and heat transfer in fuel cells.

Course Description:
Laminar and turbulent boundary layer heat transfer by similarity, integral and superposition methods; effects of roughness, curvature, transpiration and high turbulence; forced and free convections, free-shear flows and buoyant flows; numerical methods.

Course Description:
Relationships between microstructure and mechanical behavior in crystalline materials; temperature-dependent deformation in elasticity, viscosity and creep; embrittlement, fatigue and fracture of engineering materials; strengthening mechanisms in crystalline materials.

Course Description:
An advanced treatment of the thermodynamics, kinetics and transport properties in solids, solutions, surfaces, and heterogeneous reactions.

Course Description:
Principles of precision engineering, 3D tolerancing for precision design, flexure and nano-positioning, interferometry for precision measurement, dynamic control for precision machining of engineering materials, ductile machining for brittle materials, applications and industrial practices.

Course Description:
Basic concepts of precision machining; the well developed methods and systems of fixed and free abrasive technology for micro- and nano- precision machining and fabrication applications; methods and techniques for process control modeling and characterization; advanced applications of abrasive technology such as free form machining and micro fabrication.

Course Description:
Extensive introduction to robot manipulation theory from a geometric viewpoint. Rigid-body kinematics; spatial and body representation of rigid-body velocities; coordinate transformations; forward kinematics of open-chain manipulators; solution of inverse kinematics; robot workspaces; nonlinear decoupling control and force control.

Course Description:
Finite element formulation; variational principles for structural and continuum mechanics; numerical interpolation and integration; plane stress and plane strain analysis; plate bending and three dimensional solids; solution of large systems of algebraic equations.

Course Description:
This course presents a brief integrated view on the roles of defects in mechanical behavior of materials. The basic concepts, equations and methods used in the analysis of defects by continuum mechanics and thermodynamics approaches are introduced in the course. The important roles of defects such as cracks, dislocations, second phase inclusions, grain- and phase-boundaries in behavior of materials are described intensively with illustrative examples.

Course Description:
This is an interdisciplinary course covering the fundamental laws of the mechanics and physics of crystalline solids, the general description of a periodic structure and their specific characterization methods. The course will start with tensor analysis, and basic calculations of tensor fields. After that, basic kinematics such as deformation gradient, Cauchy-Green tensor will be introduced and defined, followed by the mathematical description of symmetry of crystals. Finally, the course will discuss reciprocal lattices and the X-ray diffraction for structural solving.

Course Description:
Physics of Scaling; energy transduction, sensing and actuation principles; micro-fabrication technology and technology fundamentals; film formation, photolithography and etching; integrated Microsystems and Microsystems packaging.

Course Description:
Capillary instabilities, centrifugal instabilities, shear instabilities, thermal-convective instabilities, normal mode decomposition, spatial vs. temporal analysis, linearization, nonlinear dynamics, routes to chaos, phase space reconstruction, transition to turbulence, and fluid-structure interactions.

Course Description:
The aims of this module are to acquaint students with the knowledge of acoustics and aerodynamically generated sound, its generation either through turbulent flow or unsteady aerodynamic force‐surface interaction, and numerical methods for accurate numerical prediction of aerodynamically generated noise as well as its propagation and far‐field characteristics. The wide applications of the subject are noise, environmental impact of noise and transport related noise.

Course Description:
Valued added processing in manufacturing systems is covered in the course. Emphasis is placed on how each process works to convert materials into shapes with the desired properties, and its relative advantages and disadvantages. Fundamental processes for metals, ceramics, polymers, composites and new processes including 3D printing methods are covered. In addition, inspection methods inclusion non-destructive examination methods, manufacturing automation; robotics; process control and quality control are covered.