QUANTITATIVE PHYSIOLOGY I
Physiological systems at the cellular and molecular level are examined in a highly quantitative context. Topics include chemical kinetics, molecular binding and enzymatic processes, molecular motors, biological membranes, and muscles.
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Instructor:
Lance Kam
CULPA: 7
h-index: 38
Info
- 3 points
CORPORATE FINANCE FOR ENGINEERS
Introduction to the economic evaluation of industrial projects. Economic equivalence and criteria. Deterministic approaches to economic analysis. Multiple projects and constraints. Analysis and choice under risk and uncertainty.
OPTIMIZATION MODELS AND METHODS
A graduate course only for MS&E, IE, and OR students. This is also required for students in the Undergraduate Advanced Track. For students who have not studied linear programming. Some of the main methods used in IEOR applications involving deterministic models: linear programming, the simplex method, nonlinear, integer and dynamic programming.
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Instructor:
Yuri Faenza
h-index: 11 Info - 3 points
OPTIMIZATION MODELS AND METHODS
A graduate course only for MS&E, IE, and OR students. This is also required for students in the Undergraduate Advanced Track. For students who have not studied linear programming. Some of the main methods used in IEOR applications involving deterministic models: linear programming, the simplex method, nonlinear, integer and dynamic programming.
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Instructor:
Yuri Faenza
h-index: 11 Info - 3 points
APPLIED LINEAR ALGEBRA
Fundamentals of Linear Algebra including vector and Matrix algebra, solution of linear systems, existence and uniqueness, gaussian elimination, gauss-jordan elimination, the matrix inverse, elementary matrices and the LU factorization, computational cost of solutions. Vector spaces and subspaces, linear independence, basis and dimension. The 4 fundamental subspaces of a matrix. Orthogonal projection onto a subspace and solution of Linear Least Squares problems, unitary matrices, inner products, orthogonalization algorithms and the QR factorization, applications. Determinants and applications. Eigen problems including diagonalization, symmetric matrices, positive-definite systems, eigen factorization and applications to dynamical systems and iterative maps. Introduction to the singular value decomposition and its applications.
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Instructor:
Marc W Spiegelman
CULPA: 15
Info
- 3 points
APPLIED LINEAR ALGEBRA
Fundamentals of Linear Algebra including vector and Matrix algebra, solution of linear systems, existence and uniqueness, gaussian elimination, gauss-jordan elimination, the matrix inverse, elementary matrices and the LU factorization, computational cost of solutions. Vector spaces and subspaces, linear independence, basis and dimension. The 4 fundamental subspaces of a matrix. Orthogonal projection onto a subspace and solution of Linear Least Squares problems, unitary matrices, inner products, orthogonalization algorithms and the QR factorization, applications. Determinants and applications. Eigen problems including diagonalization, symmetric matrices, positive-definite systems, eigen factorization and applications to dynamical systems and iterative maps. Introduction to the singular value decomposition and its applications.
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Instructor:
Marc W Spiegelman
CULPA: 15
Info
- 3 points
MATH METHODS IN CHEMICAL ENGIN
Mathematical description of chemical engineering problems and the application of selected methods for their solution. General modeling principles, including model hierarchies. Linear and nonlinear ordinary differential equations and their systems, including those with variable coefficients. Partial differential equations in Cartesian and curvilinear coordinates for the solution of chemical engineering problems.
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Instructor:
Robert G Bozic
Info - 3 points
Agentic AI for Operations Research and F
Agentic AI for OR & FE
Introduces agentic AI systems for decision-making in operations research and financial engineering. Covers large language models, retrieval-augmented generation, conversational agents, semantic workflows, and streaming architectures. Emphasizes hands-on design and deployment of end-to-end agentic pipelines, integrating forecasting, optimization, and reasoning in operational problems and financial engineering applications. Applications include supply chain risk, energy systems, inventory management, and portfolio management.
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Instructor:
Agostino Capponi
h-index: 19 Info - 3 points
PROTECTN OF INDUST/INTELL PROP
Exposes scientists and engineers to the development, protection, and exploitation of intellectual property rights. Legal processes for obtaining and defending intellectual property rights are detailed. Best practices for innovation and commercialization are explored. Methods for valuation and monetization of intellectual property are illustrated through application of basic accounting and financial principles to case studies.
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Instructor:
Kenneth Spall
Info - 3 points
Applied Analysis
Elementary introduction to fundamental concepts and techniques in classical analysis; applications of such techniques in different topics in applied mathematics. Brief review of essential concepts and techniques in elementary analysis; elementary properties of metric and normed spaces; completeness, compactness, and their consequences; continuous functions and their properties; Contracting Mapping Theorem and its applications; elementary properties of Hilbert and Banach spaces; bounded linear operators in Hilbert spaces; Fourier series and their applications.
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Instructor:
Liliana Borcea
Info - 3 points
Applied Analysis
Elementary introduction to fundamental concepts and techniques in classical analysis; applications of such techniques in different topics in applied mathematics. Brief review of essential concepts and techniques in elementary analysis; elementary properties of metric and normed spaces; completeness, compactness, and their consequences; continuous functions and their properties; Contracting Mapping Theorem and its applications; elementary properties of Hilbert and Banach spaces; bounded linear operators in Hilbert spaces; Fourier series and their applications.
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Instructor:
Liliana Borcea
Info - 3 points
QUANTUM PHYSICS OF MATTER
Basic theory of quantum mechanics, well and barrier problems, the harmonic oscillator, angular momentum identical particles, quantum statistics, perturbation theory and applications to the quantum physics of atoms, molecules, and solids.
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Instructor:
Alexander Gaeta
Wikipedia h-index: 89 Info - 3 points
CRYSTALLOGRAPHY
A first course on crystallography. Crystal symmetry, Bravais lattices, point groups, space groups. Diffraction and diffracted intensities. Exposition of typical crystal structures in engineering materials, including metals, ceramics, and semiconductors. Crystalline anisotropy.
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Instructor:
William Bailey
CULPA: 12 Info - 3 points
Advanced Solid State Devices and Materia
Adv Solid State Device &
Crystal structure and energy band theory of solids. Carrier concentration and transport in semiconductors. P-n junction and junction transistors. Semiconductor surface and MOS transistors. Optical effects and optoelectronic devices. Fabrication of devices and the effect of process variation and distribution statistics on device and circuit performance. Course shares lectures with ELEN E3106, but the work requirements differ. Undergraduate students are not eligible to register.
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Instructor:
Savannah Eisner
Info - 3 points
STOCHASTIC MODELS
Some of the main stochastic models used in engineering and operations research applications: discrete-time Markov chains, Poisson processes, birth and death processes and other continuous Markov chains, renewal reward processes. Applications: queueing, reliability, inventory, and finance.
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Instructor:
David D Yao
CULPA: 5
Info
- 3 points
STOCHASTIC MODELS
Some of the main stochastic models used in engineering and operations research applications: discrete-time Markov chains, Poisson processes, birth and death processes and other continuous Markov chains, renewal reward processes. Applications: queueing, reliability, inventory, and finance.
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Instructor:
David D Yao
CULPA: 5
Info
- 3 points
SUPPLY CHAIN ANALYTICS
Supply chain management, model design of a supply chain network, inventories, stock systems, commonly used inventory models, supply contracts, value of information and information sharing, risk pooling, design for postponement, managing product variety, information technology and supply chain management; international and environmental issues. Note: replaced IEOR E4000 beginning in fall 2018.
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Instructor:
Vineet Goyal
h-index: 21 Info - 3 points
MECHANISMS OF TRANSPORT
Continuum frame-work for modeling non-equilibrium phenomena in fluids with clear connections to the molecular/microscopic mechanisms for conductive transport. Continuum balances of mass and momentum; continuum-level development of conductive momentum flux (stress tensor) for simple fluids; applications of continuum framework for simple fluids (lubrication flows, creeping flows). Microscopic developments of the stress for simple and/or complex fluids; kinetic theory and/or liquid state models for transport coefficients in simple fluids; Langevin/Fokker- Plank/Smoluchowski framework for the stress in complex fluids; stress in active matter; applications for complex fluids.
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Instructor:
Christopher J Durning
CULPA: 3 Info - 3 points
UNCERTAIN/RISK-CIVIL INF SYST
Introduction to basic probability; hazard function; reliability function; stochastic models of natural and technological hazards; extreme value distributions; Monte Carlo simulation techniques; fundamentals of integrated risk assessment and risk management; topics in risk-based insurance; case studies involving civil infrastructure systems, environmental systems, mechanical and aerospace systems, construction management. Not open to undergraduate students.
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Instructor:
Ioannis Kougioumtzoglou
h-index: 26 Info - 3 points
UNCERTAIN/RISK-CIVIL INF SYST
Introduction to basic probability; hazard function; reliability function; stochastic models of natural and technological hazards; extreme value distributions; Monte Carlo simulation techniques; fundamentals of integrated risk assessment and risk management; topics in risk-based insurance; case studies involving civil infrastructure systems, environmental systems, mechanical and aerospace systems, construction management. Not open to undergraduate students.
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Instructor:
Ioannis Kougioumtzoglou
h-index: 26 Info - 3 points
FUND-LARGE-SCALE DIST SYSTEMS
Prerequisites: (COMS W3134 or COMS W3136 or COMS W3137) and (COMS W3157 or COMS W4118 or CSEE W4119) Design and implementation of large-scale distributed and cloud systems. Teaches abstractions, design and implementation techniques that enable the building of fast, scalable, fault-tolerant distributed systems. Topics include distributed communication models (e.g. sockets, remote procedure calls, distributed shared memory), distributed synchronization (clock synchronization, logical clocks, distributed mutex), distributed file systems, replication, consistency models, fault tolerance, distributed transactions, agreement and commitment, Paxos-based consensus, MapReduce infrastructures, scalable distributed databases. Combines concepts and algorithms with descriptions of real-world implementations at Google, Facebook, Yahoo, Microsoft, LinkedIn, etc.
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Instructor:
Hubertus Franke
Info - 3 points
PROGRAMMING LANG & TRANSLATORS
Modern programming languages and compiler design. Imperative, object-oriented, declarative, functional, and scripting languages. Language syntax, control structures, data types, procedures and parameters, binding, scope, run-time organization, and exception handling. Implementation of language translation tools including compilers and interpreters. Lexical, syntactic and semantic analysis; code generation; introduction to code optimization. Teams implement a language and its compiler.
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Instructor:
Ronghui Gu
h-index: 11 Info - 3 points
OPERATING SYSTEMS I
Design and implementation of operating systems. Topics include process management, process synchronization and interprocess communication, memory management, virtual memory, interrupt handling, processor scheduling, device management, I/O, and file systems. Case study of the UNIX operating system. A programming project is required.
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Instructor:
Jason Nieh
CULPA: 23
Wikipedia
h-index: 50
Info
- 3 points
COMPUTER NETWORKS
Introduction to computer networks and the technical foundations of the Internet, including applications, protocols, local area networks, algorithms for routing and congestion control, security, elementary performance evaluation. Several written and programming assignments required.
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Instructor:
Henning G Schulzrinne
CULPA: 12 Info - 3 points
SOLAR ENERGY & STORAGE
SOLAR ENERGY & STORAGE
Lecture series by Julian Chen
Nature of solar radiation as electromagnetic waves and photons. Availability of solar radiation at different times and at various places in the world. Thermodynamics of solar energy. Elements of quantum mechanics for the understanding of solar cells, photosynthesis, and electrochemistry. Theory, design, manufacturing, and installation of solar cells. Lithium-ion rechargeable batteries and other energy-storage devices. Architecture of buildings to utilize solar energy.
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Instructor:
Julian Chen
Info - 3 points
ADV CHEM ENGI THERMODYNAMICS
The course provides a rigorous and advanced foundation in chemical engineering thermodynamics suitable for chemical engineering PhD students expected to undertake diverse research projects. Topics include Intermolecular interactions, non-ideal systems, mixtures, phase equilibria and phase transitions and interfacial thermodynamics.
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Instructor:
Sanat Kumar
CULPA: 4 h-index: 79 Info - 3 points
DESIGN OF CONSTRUCTION SYSTEMS
Introduction to the design of systems that support construction activities and operations. Determination of design loads during construction. Design of excavation support systems, earth retaining systems, temporary supports and underpinning, concrete formwork and shoring systems. Cranes and erection systems. Tunneling systems. Instrumentation and monitoring. Students prepare and present term projects.
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Instructor:
Vincent Tirolo
Info - 3 points
DESIGN OF CONSTRUCTION SYSTEMS
Introduction to the design of systems that support construction activities and operations. Determination of design loads during construction. Design of excavation support systems, earth retaining systems, temporary supports and underpinning, concrete formwork and shoring systems. Cranes and erection systems. Tunneling systems. Instrumentation and monitoring. Students prepare and present term projects.
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Instructor:
Vincent Tirolo
Info - 3 points
CAPITAL FACILITY PLANNING/FIN
Planning and financing of capital facilities with a strong emphasis upon civil infrastructure systems. Project feasibility and evaluation. Design of project delivery systems to encourage best value, innovation and private sector participation. Fundamentals of engineering economy and project finance. Elements of life cycle cost estimation and decision analysis. Environmental, institutional, social and political factors. Case studies from transportation, water supply and wastewater treatment.
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Instructor:
Muqing Liu
Info - 3 points
INTL CONSTRUCTION MGMT
Complex global construction industry environment. Social, cultural, technological, and political risks; technical, financial, and contractual risk. Understanding of successful global project delivery principals and skills for construction professionals. Industry efforts and trends to support global operational mechanism. Global Case Studies. Engage with industry expert professionals. Student group projects with active ongoing global initiatives.
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Instructor:
Ibrahim Odeh
Info - 3 points
Construction Engineering and Management
CEM Industry Field Studie
Expose students to various aspects of project management in the construction industry, enhance learning experience with real-world challenges and prepare for internships and future employment. Run for two semesters. First semester focuses on Traditional Project Management, and second semester focuses on Agile Project Management. For class project, development of a Project Management Plan (PMP) and an Operations Dashboard based on real-life examples of contracts (traditional project management) and operational excellence initiatives (agile project management).
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Instructor:
Ibrahim Odeh
Info - 1-3 points
INTRO-PROBABILITY & STATISTICS
Covers the following topics: fundamentals of probability theory and statistical inference used in engineering and applied science; Probabilistic models, random variables, useful distributions, expectations, law of large numbers, central limit theorem; Statistical inference: pint and confidence interval estimation, hypothesis tests, linear regression. For IEOR graduate students.
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Instructor:
Eric Stratman
Info - 3 points
INTRO-PROBABILITY & STATISTICS
Covers the following topics: fundamentals of probability theory and statistical inference used in engineering and applied science; Probabilistic models, random variables, useful distributions, expectations, law of large numbers, central limit theorem; Statistical inference: pint and confidence interval estimation, hypothesis tests, linear regression. For IEOR graduate students.
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Instructor:
Eric Stratman
Info - 3 points
Advanced Software Engineering
ADVANCED SOFTWARE ENGINEE
Software lifecycle using frameworks, libraries and services. Major emphasis on software testing. Centers on a team project.
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Instructor:
Gail E Kaiser
CULPA: 10 Info - 3 points
Machine Learning for Biomolecular and Ce
Machine learning bio cell
Introduction to machine learning techniques with applications to biological systems, emphasizing cell-biological molecular mechanisms and applications, and computational simulation. Overview of biology. Introduction to biological neurons and neural networks, learning and memory. Parallels between biological and artificial neural networks. Deep neural networks are introduced, hands-on computational experience for students. Big data from experiments or computational simulations: machine learning to extract mechanisms, dimensional reduction. Deep learning applications include drug discovery, protein structure prediction, molecular coarse-graining for simulations, and acceleration of molecular dynamics simulations.
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Instructor:
Ben O'Shaughnessy
CULPA: 3 Info - 3 points
MALWARE ANALYSIS&REVERSE ENGINEERING
Hands-on analysis of malware. How hackers package and hide malware and viruses to evade analysis. Disassemblers, debuggers, and other tools for reverse engineering. Deep study of Windows Internals and x86 assembly.
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Instructor:
Michael S Sikorski
CULPA: 2 Info - 3 points
PARTIAL DIFFERENTIAL EQUATIONS
Techniques of solution of partial differential equations. Separation of the variables. Orthogonality and characteristic functions, nonhomogeneous boundary value problems. Solutions in orthogonal curvilinear coordinate systems. Applications of Fourier integrals, Fourier and Laplace transforms. Problems from the fields of vibrations, heat conduction, electricity, fluid dynamics, and wave propagation are considered.
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Instructor:
Qiang Du
Wikipedia h-index: 67 Info - 3 points
PARTIAL DIFFERENTIAL EQUATIONS
Techniques of solution of partial differential equations. Separation of the variables. Orthogonality and characteristic functions, nonhomogeneous boundary value problems. Solutions in orthogonal curvilinear coordinate systems. Applications of Fourier integrals, Fourier and Laplace transforms. Problems from the fields of vibrations, heat conduction, electricity, fluid dynamics, and wave propagation are considered.
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Instructor:
Qiang Du
Wikipedia h-index: 67 Info - 3 points
THEORY CRYSTALLIN MAT: PHONONS
Phenomenological theoretical understanding of vibrational behavior of crystalline materials; introducing all key concepts at classical level before quantizing the Hamiltonian. Basic notions of Group Theory introduced and exploited: irreducible representations, Great Orthogonality Theorem, character tables, degeneration, product groups, selection rules, etc. Both translational and point symmetry employed to block diagonalize the Hamiltonian and compute observables related to vibrations/phonons. Topics include band structures, density of states, band gap formation, nonlinear (anharmonic) phenomena, elasticity, thermal conductivity, heat capacity, optical properties, ferroelectricty. Illustrated using both minimal model Hamiltonians in addition to accurate Hamiltonians for real materials (e.g., Graphene)
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Instructor:
Chris A Marianetti
Info - 3 points
THEORY OF VIBRATIONS
Frequencies and modes of discrete and continuous elastic systems. Forced vibrations-steady-state and transient motion. Effect of damping. Exact and approximate methods. Applications.
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Instructor:
Raimondo Betti
CULPA: 4
h-index: 31
Info
- 3 points
MECH BEHAVIOR OF MATERIALS
Review of states of stress and strain and their relations in elastic, plastic, and viscous materials. Dislocation and elastic-plastic concepts introduced to explain work hardening, various materials-strengthening mechanisms, ductility, and toughness. Macroscopic and microstructural aspects of brittle and ductile fracture mechanics, creep and fatigue phenomena. Case studies used throughout, including flow and fracture of structural alloys, polymers, hybrid materials, composite materials, ceramics, and electronic materials devices. Materials reliability and fracture prevention emphasized.
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Instructor:
Ismail C Noyan
CULPA: 7
Info
- 3 points
Networks, Crowds, and the Web
NETWORKS CROWDS AND THE W
Introduction of fundamental ideas and algorithms on networks of information collected by online services. Properties pervasive in large networks, dynamics of individuals that lead to large collective phenomena, mechanisms underlying the web economy, and results and tools informing societal impact of algorithms on privacy, polarization and discrimination covered.
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Instructor:
Augustin Chaintreau
CULPA: 6
h-index: 33
Info
- 3 points
ANALYSIS OF ALGORITHMS I
Prerequisites: (COMS W3134 or COMS W3136COMS W3137) and (COMS W3203) Introduction to the design and analysis of efficient algorithms. Topics include models of computation, efficient sorting and searching, algorithms for algebraic problems, graph algorithms, dynamic programming, probabilistic methods, approximation algorithms, and NP-completeness.
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Instructor:
Xi Chen
CULPA: 7
Wikipedia
h-index: 64
Info
- 3 points
MULTI-HAZARD DESIGN OF STRUCTURES
Fundamental considerations of wave mechanics; design philosophies; reliability and risk concepts; basics of fluid mechanics; design of structures subjected to blast; elements of seismic design; elements of fire design; flood considerations; advanced analysis in support of structural design.
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Instructor:
Virginia Mosquera
Info - 3 points
GEOTECHNCL ENGNEERNG FUNDMNTLS
Bearing capacity and settlement of shallow and deep foundations; earth pressure theories; retaining walls and reinforced soil retaining walls; sheet pile walls; braced excavation; slope stability.
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Instructor:
Songtao Yang
Info - 3 points
ALGORITHMS FOR DATA SCIENCE
Methods for organizing data, e.g. hashing, trees, queues, lists,priority queues. Streaming algorithms for computing statistics on the data. Sorting and searching. Basic graph models and algorithms for searching, shortest paths, and matching. Dynamic programming. Linear and convex programming. Floating point arithmetic, stability of numerical algorithms, Eigenvalues, singular values, PCA, gradient descent, stochastic gradient descent, and block coordinate descent. Conjugate gradient, Newton and quasi-Newton methods. Large scale applications from signal processing, collaborative filtering, recommendations systems, etc.
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Instructor:
Eleni Drinea
CULPA: 8 Info - 3 points
ALGORITHMS FOR DATA SCIENCE
Methods for organizing data, e.g. hashing, trees, queues, lists,priority queues. Streaming algorithms for computing statistics on the data. Sorting and searching. Basic graph models and algorithms for searching, shortest paths, and matching. Dynamic programming. Linear and convex programming. Floating point arithmetic, stability of numerical algorithms, Eigenvalues, singular values, PCA, gradient descent, stochastic gradient descent, and block coordinate descent. Conjugate gradient, Newton and quasi-Newton methods. Large scale applications from signal processing, collaborative filtering, recommendations systems, etc.
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Instructor:
Eleni Drinea
CULPA: 8 Info - 3 points
Applied Machine Learning in Civil Engine
APPLIED ML IN CIVIL ENG
Utilization of data in everyday civil infrastructure. Optimization of decision-making for owners, facility managers, and policy-makers based on predictive results. Provides students with basic understanding of machine learning concepts and methods to formulate civil engineering problems to prediction problems. Introduces students to classic machine learning algorithms, deep learning algorithms, algorithmic thinking, and probabilistic views, and their applications in existing civil engineering problems.
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Instructor:
Zhengbo Zou
Info - 3 points
ELECTROCHEM MATLS & DEVS
Overview of electrochemical processes and applications from perspectives of materials and devices. Thermodynamics and principles of electrochemistry, methods to characterize electrochemical processes, application of electrochemical materials and devices, including batteries, supercapacitors, fuel cells, electrochemical sensor, focus on link between material structure, composition, and properties with electrochemical performance.
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Instructor:
Yuan Yang
h-index: 49 Info - 3 points
INTRO TO CARBON MANAGEMENT
Introduction to natural and anthropogenic carbon cycle, and carbon - climate. Rationale and need to manage carbon and tools with which to do so (basic science, psychology, economics and policy background, negotiations - society; emphasis on interdisciplinary and inter-dependent approach). Simple carbon emission model to estimate the impacts of a specific intervention with regards to national, per capita and global emissions. Student-led case studies (e.g. reforestation, biofuels, CCS, efficiency, alternative energy) to illustrate necessary systems approach required to tackle global challenges.
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Instructor:
Sara T Hamilton
Info - 3 points
INTRO TO PLASMA PHYSICS
Definition of a plasma. Plasmas in laboratories and nature, plasma production. Motion of charged particles in electric and magnetic fields, adiabatic invariants. Heuristic treatment of collisions, diffusion, transport, and resistivity. Plasma as a conducting fluid. Electrostatic and magnetostatic equilibria of plasmas. Waves in cold plasmas. Demonstration of laboratory plasma behavior, measurement of plasma properties. Illustrative problems in fusion, space, and nonneutral or beam plasmas.
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Instructor:
Carlos Paz Soldan
h-index: 28 Info - 3 points
CARBON STORAGE
This course is intended to provide a quantitative introduction to storage of carbon derived from greenhouse gases, mainly CO2, with a focus on geological carbon storage and mineralization in saline aquifers, depleted hydrocarbon reservoirs, and “reactive” subsurface formations (rocks rich in Fe, Ca, and Mg) as well and other natural and engineered storage reservoirs (e.g., terrestrial storage, ocean storage, building materials). Course modules cover fundamental processes such as geochemical fluid-rock interactions and fluid flow, transport, and trapping of supercritical and/or dissolved CO2 in the context of pore-scale properties to field-scale example storage reservoirs and specific integrative problems such as reservoir characterization and modeling techniques, estimating storage capacity, and regulations and monitoring.
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Instructor:
Shaina Kelly
Info - 3 points
SOLID BIOMECHANICS
Applications of continuum mechanics to the understanding of various biological tissues properties. The structure, function, and mechanical properties of various tissues in biolgical systems, such as blood vessels, muscle, skin, brain tissue, bone, tendon, cartilage, ligaments, etc. are examined. The establishment of basic governing mechanical principles and constitutive relations for each tissue. Experimental determination of various tissue properties. Medical and clinical implications of tissue mechanical behavior.
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Instructor:
X. Edward Guo
CULPA: 2 h-index: 70 Info - 3 points
ADVANCED CHEMICAL KINETICS
Complex reactive systems. Catalysis. Heterogeneous systems, with an emphasis on coupled chemical kinetics and transport phenomena. Reactions at interfaces (surfaces, aerosols, bubbles). Reactions in solution.
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Instructor:
Robert G Bozic
Info - 3 points
SIMULATION
Generation of random numbers from given distributions; variance reduction; statistical output analysis; introduction to simulation languages; application to financial, telecommunications, computer, and production systems. Graduate students must register for 3 points. Undergraduate students must register for 4 points. Note: Students who have taken IEOR E4703 Monte Carlo simulation may not register for this course for credit. Recitation section required.
SIMULATION
Generation of random numbers from given distributions; variance reduction; statistical output analysis; introduction to simulation languages; application to financial, telecommunications, computer, and production systems. Graduate students must register for 3 points. Undergraduate students must register for 4 points. Note: Students who have taken IEOR E4703 Monte Carlo simulation may not register for this course for credit. Recitation section required.
GAME THEOR MODELS OF OPERATION
Required for undergraduate students majoring in OR:FE and OR. A mathematically rigorous study of game theory and auctions, and their application to operations management. Topics include introductory game theory, private value auction, revenue equivalence, mechanism design, optimal auction, multiple-unit auctions, combinatorial auctions, incentives, and supply chain coordination with contracts. No previous knowledge of game theory is required.
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Instructor:
Jay Sethuraman
CULPA: 10 Info - 3 points
GAME THEOR MODELS OF OPERATION
Required for undergraduate students majoring in OR:FE and OR. A mathematically rigorous study of game theory and auctions, and their application to operations management. Topics include introductory game theory, private value auction, revenue equivalence, mechanism design, optimal auction, multiple-unit auctions, combinatorial auctions, incentives, and supply chain coordination with contracts. No previous knowledge of game theory is required.
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Instructor:
Jay Sethuraman
CULPA: 10 Info - 3 points
OPTICAL SYSTEMS
Introduction to optical systems based on physical design and engineering principles. Fundamental geometrical and wave optics with specific emphasis on developing analytical and numerical tools used in optical engineering design. Focus on applications that employ optical systems and networks, including examples in holographic imaging, tomography, Fourier imaging, confocal microscopy, optical signal processing, fiber optic communication systems, optical interconnects and networks.
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Instructor:
Christine P Hendon
Wikipedia h-index: 21 Info - 3 points
PROCESS SAFETY
Aimed at seniors and graduate students. Provides classroom experience on chemical engineering process safety as well as Safety in Chemical Engineering certification. Process safety and process control emphasized. Application of basic chemical engineering concepts to chemical reactivity hazards, industrial hygiene, risk assessment, inherently safer design, hazard operability analysis, and engineering ethics. Application of safety to full spectrum of chemical engineering operations.
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Instructor:
Robert G Bozic
Info - 3 points
POWER SYSTEMS ANALYSIS
Modeling of power networks, steady-state and transient behaviors, control and optimization, electricity market, and smart grid.
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Instructor:
Ahmed Mousa
Info - 3 points
Industry Projects in Analytics & Operati
Industry Projs in Analyti
Teams of students work on real-world projects in analytics. Focus on three aspects of analytics: identifying client analytical requirements; assembling, cleaning and organizing data; identifying and implementing analytical techniques (e.g., statistics and/or machine learning); and delivering results in a client-friendly format. Each project has a defined goal and pre-identified data to analyze in one semester. Client facing class. Class requires 10 hours of time per week and possible client visits on Fridays.
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Instructor:
Michael Robbins
Wikipedia Info - 3 points
DATA SCIENCE FOR MECHANICAL SYSTEMS
Introduction to the practical application of data science, machine learning, and artificial intelligence and their application in Mechanical Engineering. A review of relevant programming tools necessary for applying data science is provided, as well as a detailed review of data infrastructure and database construction for data science. A series of industry case studies from experts in the field of data science will be presented.
- TR 10:10 a.m.-11:25 a.m.
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Instructor:
Changyao Chen
Info - 3 points
ANALYTICS ON THE CLOUD
To introduce students to programming issues around working with clouds for data analytics. Class will learn how to work with infrastructure of cloud platforms, and discussion about distributed computing, focus of course is on programming. Topics covered include MapReduce, parallelism, rewriting of algorithms (statistical, OR, and machine learning) for the cloud, and basics of porting applications so that they run on the cloud.
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Instructor:
Hardeep Johar
Info - 3 points
DATA MINING
Course covers major statistical learning methods for data mining under both supervised and unsupervised settings. Topics covered include linear regression and classification, model selection and regularization, tree-based methods, support vector machines, and unsupervised learning. Students learn about principles underlying each method, how to determine which methods are most suited to applied settings, concepts behind model fitting and parameter tuning, and how to apply methods in practice and assess their performance. Emphasizes roles of statistical modeling and optimization in data mining.
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Instructor:
Krzysztof M Choromanski
Info - 3 points
CATALYSIS OF EMISSIONS CONTROL
Fundamentals of heterogeneous catalysis including modern catalytic preparation techniques. Analysis and design of catalytic emissions control systems. Introduction to current industrial catalytic solutions for controlling gaseous emissions. Introduction to future catalytically enabled control technologies.
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Instructor:
Robert Farrauto
h-index: 52 Info - 3 points
TOPICS IN OPERATIONS RESEARCH
FINANCE & STRUCTURING FOR DS
Special topics arranged as the need and availability arises. Topics are usually offered on a one-time basis. Since the content of this course changes each time it is offered, it may be repeated for credit. Consult the department for section assignment.
- 3 points
Continuous Control Systems
Introduction to continuous systems with the treatment of classical and state-space formulations. Mathematical concepts, complex variables, integral transforms and their inverses, differential equations, and relevant linear algebra. Classical feedback control, time/frequency domain design, stability analysis, Laplace transform formulation and solutions, block diagram simplifcation and manipulation, signal ow graphs, modeling physical systems and linearization. state-space formulation and modeling, in parallel with classical single-input single-output formulation, connections between the two formulations. Transient and steady state analysis, methods of stability analysis, such as root locus methods, Nyquist stability criterion, Routh-Hurwitz criterion, pole/zero placement, Bode plot analysis, Nichols chart analysis, phase lead and lag compensators, controllability, observability, realization of canonical forms, state estimation in multivariable systems, time-variant systems. Introduction to advanced stability analysis such as Lyapunov stability and simple optimal control formulation. May not take for credit if already received credit for EEME E3601.
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Instructor:
Ali Dadgar
Info - 3 points
QUANTITATIVE RISK MANAGEMENT
Risk management models and tools; measure risk using statistical and stochastic methods, hedging and diversification. Examples include insurance risk, financial risk, and operational risk. Topics covered include VaR, estimating rare events, extreme value analysis, time series estimation of extremal events; axioms of risk measures, hedging using financial options, credit risk modeling, and various insurance risk models.
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Instructor:
Agostino Capponi
h-index: 19 Info - 3 points
INTRODUCTION TO ROBOTICS
Overview of robot applications and capabilities. Linear algebra, kinematics, statics, and dynamics of robot manipulators. Survey of sensor technology: force, proximity, vision, compliant manipulators. Motion planning and artificial intelligence; manipulator programming requirements and languages.
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Instructor:
Sunil Agrawal
Wikipedia h-index: 65 Info - 3 points
INTRODUCTION TO ROBOTICS
Overview of robot applications and capabilities. Linear algebra, kinematics, statics, and dynamics of robot manipulators. Survey of sensor technology: force, proximity, vision, compliant manipulators. Motion planning and artificial intelligence; manipulator programming requirements and languages.
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Instructor:
Sunil Agrawal
Wikipedia h-index: 65 Info - 3 points
ADV MANUFACTURING PROCESSES
Principles of nontraditional manufacturing, nontraditional transport and media. Emphasis on laser assisted materials processing, laser material interactions with applications to laser material removal, forming, and surface modification. Introduction to electrochemical machining, electrical discharge machining and abrasive water jet machining.
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Instructor:
Sinisa Vukelic
CULPA: 2 h-index: 11 Info - 3 points
ROBOTICS STUDIO
Hands-on studio class exposing students to practical aspects of the design, fabrication, and programming of physical robotic systems. Students experience entire robot creation process, covering conceptual design, detailed design, simulation and modeling, digital manufacturing, electronics and sensor design, and software programming.
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Instructor:
Hod Lipson
Wikipedia h-index: 79 Info - 3 points
PRICING MODELS FOR FIN ENGIN
Required for undergraduate students majoring in OR:FE. Characteristics of commodities or credit derivatives. Case study and pricing of structures and products. Topics covered include swaps, credit derivatives, single tranche CDO, hedging, convertible arbitrage, FX, leverage leases, debt markets, and commodities.
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Instructor:
Michael Miller
CULPA: 18 h-index: 14 Info - 3 points
BUSINESS ANALYTICS
This course focuses on how to identify, evaluate, and capture business analytic opportunities that create value. The course covers basic analytic methods alongside case studies on organizations that successfully deployed these techniques. The first part of the course is on using data to develop insights and predictive capabilities with machine learning techniques. The second part focuses on the use of A/B testing, causal inference, ethics, and optimization to support decision-making.
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Instructor:
Uday Menon
Info - 3 points
INTRO TO FINANCIAL ENGINEERING
Prerequisite(s): IEOR E4106 or E3106. Required for undergraduate students majoring in OR:FE. Introduction to investment and financial instruments via portfolio theory and derivative securities, using basic operations research/engineering methodology. Portfolio theory, arbitrage; Markowitz model, market equilibrium, and the capital asset pricing model. General models for asset price fluctuations in discrete and continuous time. Elementary introduction to Brownian motion and geometric Brownian motion. Option theory; Black-Scholes equation and call option formula. Computational methods such as Monte Carlo simulation.
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Instructor:
Xunyu Zhou
h-index: 54 Info - 3 points
ARTIFICIAL INTELLIGENCE
Prior knowledge of Python is recommended. Provides a broad understanding of the basic techniques for building intelligent computer systems. Topics include state-space problem representations, problem reduction and and-or graphs, game playing and heuristic search, predicate calculus, and resolution theorem proving, AI systems and languages for knowledge representation, machine learning and concept formation and other topics such as natural language processing may be included as time permits.
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Instructor:
Ansaf Salleb-Aouissi
CULPA: 21 h-index: 16 Info - 3 points
ARTIFICIAL INTELLIGENCE
Prior knowledge of Python is recommended. Provides a broad understanding of the basic techniques for building intelligent computer systems. Topics include state-space problem representations, problem reduction and and-or graphs, game playing and heuristic search, predicate calculus, and resolution theorem proving, AI systems and languages for knowledge representation, machine learning and concept formation and other topics such as natural language processing may be included as time permits.
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Instructor:
Ansaf Salleb-Aouissi
CULPA: 21 h-index: 16 Info - 3 points
NATURAL LANGUAGE PROCESSING
Computational approaches to the analysis, understanding, and generation of natural language text at scale. Emphasis on machine learning techniques for NLP, including deep learning and large language models. Applications may include information extraction, sentiment analysis, question answering, summarization, machine translation, and conversational AI. Discussion of datasets, benchmarking and evaluation, interpretability, and ethical considerations.
Due to significant overlap in content, only one of COMS 4705 or Barnard COMS 3705BC may be taken for credit.
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Instructor:
John Hewitt
Info - 3 points
COMPUTATIONAL ASPECTS OF ROBOTICS
COMPUTATNL ASPECTS OF ROB
Introduction to fundamental problems and algorithms in robotics. Topics include configuration spaces, motion and sensor models, search and sampling-based planning, state estimation, localization and mapping, perception, and learning.
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Instructor:
Tony B Dear
CULPA: 17
Info
- 3 points
STRUCTURED&HYBRID PRODUCTS
Conceptual and practical understanding of structured and hybrid products from the standpoint of relevant risk factors, design goals and characteristics, pricing, hedging, and risk management. Detailed analysis of the underlying cash-flows, embedded derivative instruments, and various structural features of these transactions, both from the investor and issuer perspectives, and analysis of the impact of the prevailing market conditions and parameters on their pricing and risk characteristics. Numerical methods for valuing and managing risk of structured/hybrid products and their embedded derivatives and their application to equity, interest rates, commodities and currencies, inflation, and credit-related products. Conceptual and mathematical principles underlying these techniques, and practical issues that arise in their implementations in Python and other programming environments. Special contractual provisions encountered in structured and hybrid transactions, and incorporation of yield curves, volatility smile, and other features of the underlying processes into pricing and implementation framework for these products.
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Instructor:
Alireza Javaheri
Info - 3 points
Applied Financial Risk Management
Applied Financial Risk Mg
Introduces risk management principles, practical implementation and applications, standard market, liquidity, and credit risk measurement techniques, and their drawbacks and limitations. Note: restricted to IEOR students only.
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Instructor:
Allan M Malz
CULPA: 1 Info - 3 points
SOUND AND HEARING
Introductory acoustics, basics of waves and discrete mechanical systems. The mechanics of hearing - how sound is transmitted through the external and middle ear to the inner ear, and the mechanical processing of sound within the inner ear.
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Instructor:
Elizabeth Olson
h-index: 28 Info - 3 points
Machine Learning for Functional Genomics
ML for Functional Genomic
This course will introduce modern probabilistic machine learning methods using applications in data analysis tasks from functional genomics, where massively-parallel sequencing is used to measure the state of cells: e.g. what genes are being expressed, what regions of DNA (“chromatin”) are active (“open”) or bound by specific proteins.
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Instructor:
David A Knowles
h-index: 35 Info - 3 points
Neural Networks & Deep Learning
NEURAL NETWORKS DEEP LEAR
Foundational concepts, methods, applications, and recent advances in neural network algorithms.
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Instructor:
Richard Zemel
Wikipedia Info - 3 points
DIGITAL SIGNAL PROCESSING
Digital filtering in time and frequency domain, including properties of discrete-time signals and systems, sampling theory, transform analysis, system structures, IIR and FIR filter design techniques, the discrete Fourier transform, fast Fourier transforms.
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Instructor:
Guido H Jajamovich
Info - 3 points
ENVIRONMENTAL MICROBIOLOGY
Basic microbiological principles; microbial metabolism; identification and interactions of microbial populations responsible for the biotransformation of pollutants; mathematical modeling of microbially mediated processes; biotechnology and engineering applications using microbial systems for pollution control.
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Instructor:
Kartik Chandran
CULPA: 4
Wikipedia
h-index: 51
Info
- 3 points
TOPICS IN COMPUTER SCIENCE
PARALLEL FUNCTIONAL PROGRAMMIN
Selected topics in computer science. Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
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Instructor:
Stephen A Edwards
CULPA: 21
h-index: 35
Info
- 3 points
TOPICS IN COMPUTER SCIENCE
COMPETITIVE PROGRAMMING
Selected topics in computer science. Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
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Instructor:
Yongwhan Lim
Info - 3 points
PROBABILITY & STAT FOR DATA SC
This course covers the following topics: Fundamentals of probability theory and statistical inference used in data science; Probabilistic models, random variables, useful distributions, expectations, law of large numbers, central limit theorem; Statistical inference; point and confidence interval estimation, hypothesis tests, linear regression.
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Instructor:
Dobrin Marchev
Info - 3 points
RESEARCH SEMINAR
An M.S. degree requirement. Students attend at least three Applied Mathematics research seminars within the Department of Applied Physics and Applied Mathematics and submit reports on each.
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Instructor:
Qiang Du
Wikipedia h-index: 67 Info - 0 points
Advanced Topics in Theoretical Computer
INTRO PROPERTY TESTING
Selected topics in theoretical computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check "topics courses" webpage on the department website for more information on each section.
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Instructor:
Xi Chen
CULPA: 7
Wikipedia
h-index: 64
Info
- 3-4 points
MILLIMETER-WAVE IC DESIGN
Principles behind the implementation of millimeter-wave (30GHz-300GHz) wireless circuits and systems in silicon-based technologies. Silicon-based active and passive devices for millimeter-wave operation, millimeter-wave low-noise amplifiers, power amplifiers, oscillators and VCOs, oscillator phase noise theory, mixers and frequency dividers for PLLs. A design project is an integral part of the course.
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Instructor:
Harish Krishnaswamy
Info - 3 points
MILLIMETER-WAVE IC DESIGN
Principles behind the implementation of millimeter-wave (30GHz-300GHz) wireless circuits and systems in silicon-based technologies. Silicon-based active and passive devices for millimeter-wave operation, millimeter-wave low-noise amplifiers, power amplifiers, oscillators and VCOs, oscillator phase noise theory, mixers and frequency dividers for PLLs. A design project is an integral part of the course.
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Instructor:
Harish Krishnaswamy
Info - 3 points
Nonlinear and Adaptive Control
Nonlinear dynamics: Euler-Lagrange equations, Hamilton’s principle, variational calculus; nonlinear systems: fundamentals, examples, stability Notions, linear systems and linearization, frequency domain analysis, discrete time systems, absolute stability, input-to-state stabililty, control design: control Lyapunov functions, sliding mode control, control barrier functions; adaptive control: self-tuning regular, model reference adaptive control, feedback linearization, extremum seeking control, model predictive control, observer design: extended, unscented, and mixture model Kalman filters, moving horizon estimation, high-gain observers; repetitive processes: iterative learning control, learning-adaptive control, repetitive control; optimal control: continuous setting, discrete time setting, constrained optimal control, linear matrix inequality (LMI) constraints, dynamic programming and backward recursion.
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Instructor:
Homayoon Beigi
Info - 3 points
Machine Learning and High-Dimensional Da
Mchn lrning&Hgh-dmntnl da
Discusses recent advances in fields of machine learning: kernel methods, neural networks (various generative adversarial net architectures), and reinforcement learning (with applications in robotics). Quasi Monte Carlo methods in the context of approximating RBF kernels via orthogonal transforms (instances of the structured technique). Will discuss techniques such as TD(0), TD(λ), LSTDQ, LSPI, DQN.
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Instructor:
Krzysztof M Choromanski
Info - 3 points
TOPICS DATA-DRIVEN ANAL & COMP
Selected advanced topics in data-driven analysis and computation. Content varies from year to year, and different topics rotate through the course numbers 6690 to 6699.
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Instructor:
Predrag R Jelenkovic
CULPA: 1 h-index: 35 Info - 3 points
Advanced Spoken Language Processing
ADV SPOKEN LANG PROC
Applications of spoken language processing, including text-to-speech and dialogue systems. Analysis of speech and text, including entrainment, empathy, personality, emotion, humor, sarcasm, deception, trust, radicalization, and charisma.
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Instructor:
Julia Hirschberg
CULPA: 8
h-index: 77
Info
- 3 points
Advanced Spoken Language Processing
ADV SPOKEN LANG PROC
Applications of spoken language processing, including text-to-speech and dialogue systems. Analysis of speech and text, including entrainment, empathy, personality, emotion, humor, sarcasm, deception, trust, radicalization, and charisma.
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Instructor:
Julia Hirschberg
CULPA: 8
h-index: 77
Info
- 3 points