Machine learning for environmental engin
MACH LRN FOR ENV ENG & SC
Aimed at understanding and testing state-of?the-art methods in machine learning applied to environmental sciences and engineering problems. Potential applications include but are not limited to remote sensing, and environmental and geophysical fluid dynamics. Includes testing "vanilla" ML algorithms, feedforward neural networks, random forests, shallow vs deep networks, and the details of machine learning techniques.
- 3 points
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
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:
Yaren Kaya
Info - 3 points
OPT MODELS & METHODS FOR FE
Linear, quadratic, nonlinear, dynamic, and stochastic programming. Some discrete optimization techniques will also be introduced. The theory underlying the various optimization methods is covered. The emphasis is on modeling and the choice of appropriate optimization methods. Applications from financial engineering are discussed.
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Instructor:
Tianyi Lin
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
PROTECTN OF INDUST/INTELL PROP
To expose engineers, scientists and technology managers to areas of the law they are most likely to be in contact with during their career. Principles are illustrated with various case studies together with active student participation.
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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.
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:
Latha Venkataraman
CULPA: 4 Wikipedia h-index: 55 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:
Katayun Barmak
CULPA: 1 h-index: 49 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
BIOSTATISTICS FOR ENGINEERS
Fundamental concepts of probability and statistics applied to biology and medicine. Probability distributions, hypothesis testing and inference, summarizing data and testing for trends. Signal detection theory and the receiver operator characteristic. Lectures accompanied by data analysis assignments using MATLAB as well as discussion of case studies in biomedicine.
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Instructor:
Nuttida Rungratsameetaweemana
Info - 4 points
INTRODUCTION TO DATABASES
The fundamentals of database design and application development using databases: entity-relationship modeling, logical design of relational databases, relational data definition and manipulation languages, SQL, XML, query processing, physical database tuning, transaction processing, security. Programming projects are required.
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Instructor:
Donald F Ferguson
CULPA: 17 Wikipedia Info - 3 points
LASER PHYSICS
Optical resonators, interaction of radiation and atomic systems, theory of laser oscillation, specific laser systems, rate processes, modulation, detection, harmonic generation, and applications.
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Instructor:
Nanfang Yu
h-index: 48 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:
Roxana Geambasu
CULPA: 2 Wikipedia h-index: 20 Info - 3 points
PROGRAMMING LANG & TRANSLATORS
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:
Baishakhi Ray
CULPA: 3 h-index: 24 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:
Ethan Katz-Bassett
h-index: 31 Info - 3 points
MANAGING ENG & CONST PROCESSES
Introduction to the principles, methods and tools necessary to manage design and construction processes. Elements of planning, estimating, scheduling, bidding and contractual relationships. Valuation of project cash flows. Critical path method. Survey of construction procedures. Cost control and effectiveness. Field supervision.
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Instructor:
Ibrahim Odeh
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
PRIN OF CONSTRUCTN TECHNIQUES
Current methods of construction, cost-effective designs, maintenance, safe work environment. Design functions, constructability, site and environmental issues.
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Instructor:
Ibrahim Odeh
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
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:
Yaren Kaya
Info - 3 points
Cloud Computing
CLOUD COMPUTING
Software engineering skills necessary for developing cloud computing and software-as-a-service applications, covering topics such as service-oriented architectures, message-driven applications, and platform integration. Includes theoretical study, practical application, and collaborative project work.
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Instructor:
Donald F Ferguson
CULPA: 17 Wikipedia Info - 3 points
ADVANCED SOFTWARE ENGINEERING
Advanced Software Engineering
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
USER INTERFACE DESIGN
Introduction to the theory and practice of computer user interface design, emphasizing the software design of graphical user interfaces. Topics include basic interaction devices and techniques, human factors, interaction styles, dialogue design, and software infrastructure. Design and programming projects are required.
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Instructor:
Brian A Smith
CULPA: 2 h-index: 5 Info - 3 points
SECURITY I
Introduction to security. Threat models. Operating system security features. Vulnerabilities and tools. Firewalls, virtual private networks, viruses. Mobile and app security. Usable security. Note: May not earn credit for both W4181 and W4180 or W4187.
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Instructor:
Suman Jana
h-index: 33 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:
James M Scott
h-index: 2 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
FUNCTNS OF A COMPLEX VARIABLE
Complex numbers, functions of a complex variable, differentiation and integration in the complex plane. Analytic functions, Cauchy integral theorem and formula, Taylor and Laurent series, poles and residues, branch points, evaluation of contour integrals. Conformal mapping, Schwarz-Christoffel transformation. Applications to physical problems.
ANALOG FILTER SYNTHESIS/DESIGN
Approximation techniques for magnitude, phase, and delay specifications, transfer function realization sensitivity, passive LC filters, active RC filters, MOSFET-C filters, Gm-C filters, switched-capacitor filters, automatic tuning techniques for integrated filters. Filter noise. A design project is an integral part of the course.
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Instructor:
Timothy Dickson
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
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:
Alexandr Andoni
CULPA: 2 h-index: 34 Info - 3 points
INTRO-COMPUTATIONAL COMPLEXITY
Develops a quantitative theory of the computational difficulty of problems in terms of the resources (e.g. time, space) needed to solve them. Classification of problems into complexity classes, reductions, and completeness. Power and limitations of different modes of computation such as nondeterminism, randomization, interaction, and parallelism.
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Instructor:
Xi Chen
CULPA: 7
Wikipedia
h-index: 64
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
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
COMPUT MATH:INTRO-NUMERCL METH
Programming experience in Python extremely useful. Introduction to fundamental algorithms and analysis of numerical methods commonly used by scientists, mathematicians and engineers. Designed to give a fundamental understanding of the building blocks of scientific computing that will be used in more advanced courses in scientific computing and numerical methods for PDEs (e.g. APMA E4301, E4302). Topics include numerical solutions of algebraic systems, linear least-squares, eigenvalue problems, solution of non-linear systems, optimization, interpolation, numerical integration and differentiation, initial value problems and boundary value problems for systems of ODEs. All programming exercises will be in Python.
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Instructor:
Marc W Spiegelman
CULPA: 15
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
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
ANALOG ELECTRONIC CIRCUITS
Differential and multistage amplifiers; small-signal analysis; biasing techniques; frequency response; negative feedback; stability criteria; frequency compensation techniques. Analog layout techniques. An extensive design project is an integral part of the course.
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Instructor:
Peter Kinget
CULPA: 1 h-index: 47 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
QUANTITATIVE CORPORATE FINANCE
Required for students in the Undergraduate Advanced Track. Key measures and analytical tools to assess the financial performance of a firm and perform the economic evaluation of industrial projects. Deterministic mathematical programming models for capital budgeting. Concepts in utility theory, game theory and real options analysis.
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Instructor:
David Derosa
CULPA: 4 h-index: 9 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.
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Instructor:
Henry Lam
h-index: 17 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
Statistical machine learning for genomic
Statistical ML for genomi
Introduction to statistical machine learning methods using applications in genomic data and in particular high-dimensional single-cell data. Concepts of molecular biology relevant to genomic technologies, challenges of high-dimensional genomic data analysis, bioinformatics preprocessing pipelines, dimensionality reduction, unsupervised learning, clustering, probabilistic modeling, hidden Markov models, Gibbs sampling, deep neural networks, gene regulation. Programming assignments and final project will be required.
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Instructor:
Elham Azizi
h-index: 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
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.
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Instructor:
Nicolas W Chbat
Info - 3 points
DATA ANALYTICS
IEOR students only; priority to MSBA students. Survey tools available in Python for getting, cleaning, and analyzing data. Obtain data from files (csv, html, json, xml) and databases (Mysql, PostgreSQL, NoSQL), cover the rudiments of data cleaning, and examine data analysis, machine learning, and data visualization packages (NumPy, pandas, Scikit-lern, bokeh) available in Python. Brief overview of natural language processing, network analysis, and big data tools available in Python. Contains a group project component that will require students to gather, store, and analyze a data set of their choosing.
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Instructor:
Uday Menon
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
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
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
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:
David D Yao
CULPA: 5
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
STOCHASTIC MODELS FOR FIN ENG
This graduate course is only for M.S. Program in Financial Engineering students, offered during the summer session. Review of elements of probability theory, Poisson processes, exponential distribution, renewal theory, Wald’s equation. Introduction to discrete-time Markov chains and applications to queueing theory, inventory models, branching processes.
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Instructor:
David D Yao
CULPA: 5
Info
- 3 points
NATURAL LANGUAGE PROCESSING
Computational approaches to natural language generation and understanding. Recommended preparation: some previous or concurrent exposure to AI or Machine Learning. Topics include information extraction, summarization, machine translation, dialogue systems, and emotional speech. Particular attention is given to robust techniques that can handle understanding and generation for the large amounts of text on the Web or in other large corpora. Programming exercises in several of these areas.
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Instructor:
Daniel Bauer
CULPA: 17
h-index: 13
Info
- 3 points
FOUNDATIONS FR FINANCIAL ENGIN
This graduate course is only for M.S. Program in Financial Engineering students, offered during the summer session. Discrete-time models of equity, bond, credit, and foreign-exchange markets. Introduction to derivative markets. Pricing and hedging of derivative securities. Complete and incomplete markets. Introduction to portfolio optimization and the capital asset pricing model.
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Instructor:
Wenpin Tang
h-index: 6 Info - 3 points
CREDIT RISK/CREDIT DERIVATIVES
Introduction to quantitative modeling of credit risk, with a focus on the pricing of credit derivatives. Focus on the pricing of single-name credit derivatives (credit default swaps) and collateralized debt obligations (CDOs). Detail topics include default and credit risk, multiname default barrier models and multiname reduced form models.
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Instructor:
Agostino Capponi
h-index: 19 Info - 3 points
FOR EXCH/RELATD DERIVATVS INST
FOREIGN EXCH/RELTD DERIVATIVES
Foreign exchange market and its related derivative instruments—the latter being forward contracts, futures, options, and exotic options. What is unusual about foreign exchange is that although it can rightfully claim to be the largest of all financial markets, it remains an area where very few have any meaningful experience. Virtually everyone has traded stocks, bonds, and mutual funds. Comparatively few individuals have ever traded foreign exchange. In part that is because foreign exchange is an interbank market. Ironically the foreign exchange markets may be the best place to trade derivatives and to invent new derivatives—given the massive two-way flow of trading that goes through bank dealing rooms virtually 24 hours a day. And most of that is transacted at razor-thin margins, at least comparatively speaking, a fact that makes the foreign exchange market an ideal platform for derivatives. The emphasis is on familiarizing the student with the nature of the foreign exchange market and those factors that make it special among financial markets, enabling the student to gain a deeper understanding of the related market for derivatives on foreign exchange.
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Instructor:
David Derosa
CULPA: 4 h-index: 9 Info - 1.5 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
MACHINE LEARNING
Topics from generative and discriminative machine learning including least squares methods, support vector machines, kernel methods, neural networks, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models and hidden Markov models. Algorithms implemented in MATLAB.
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Instructor:
Nakul Verma
CULPA: 10
h-index: 16
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:
John Wright
CULPA: 1 h-index: 44 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
MATH MACH LEARN SIG RECOG
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:
Homayoon S Beigi
Info - 3 points
TOPICS IN COMPUTER SCIENCE
ELEMENTS FOR DATA SCIENCE
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:
Andi Cupallari
Info - 3 points
TOPICS IN COMPUTER SCIENCE
APPLIED MACHINE LEARNING
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:
Vijay Pappu
Info - 3 points
EXPLORATORY DATA ANALYSIS/VISUAL
EXPLORATORY DATA ANALYS/
This course is covers the following topics: fundamentals of data visualization, layered grammer of graphics, perception of discrete and continuous variables, intreoduction to Mondran, mosaic pots, parallel coordinate plots, introduction to ggobi, linked pots, brushing, dynamic graphics, model visualization, clustering and classification.
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Instructor:
Joyce T Robbins
CULPA: 5
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.
ADVANCED MECHANICS OF FLUIDS
Eulerian and Lagrangian descriptions of motion. Stress and strain rate tensors, vorticity, integral and differential equations of mass, momentum, and energy conservation. Potential flow.
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Instructor:
Gerard A Ateshian
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
INTRO TO CONTROL THEORY
A graduate-level introduction to classical and modern feedback control that does not presume an undergraduate background in control. Scalar and matrix differential equation models and solutions in terms of state transition matrices. Transfer functions and transfer function matrices, block diagram manipulations, closed loop response. Proportional, rate, and integral controllers, and compensators. Design by root locus and frequency response. Controllability and observability. Luenberger observers, pole placement, and linear-quadratic cost controllers.
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Instructor:
Nicolas W Chbat
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
COMPUTER COMMUNICATNS NETWORKS
Analytical approach to the design of (data) communication networks. Necessary tools for performance analysis and design of network protocols and algorithms. Practical engineering applications in layered Internet protocols in Data link layer, Network layer, and Transport layer. Review of relevant aspects of stochastic processes, control, and optimization.
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Instructor:
Javad Ghaderi
h-index: 17 Info - 3 points
INTERNET ECON, ENG & SOCIETY
Mathematical models, analyses of economics and networking interdependencies in the internet. Topics include microeconomics of pricing and regulations in communications industry, game theory in revenue allocations, ISP settlements, network externalities, two-sided markets. Economic principles in networking and network design, decentralized vs. centralized resource allocation, “price of anarchy,” congestion control. Case studies of topical internet issues. Societal and industry implications of internet evolution.
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Instructor:
Debasis Mitra
Wikipedia h-index: 61 Info - 3 points
TOPICS IN SIGNAL PROCESSING
TPC:REINFORCEMENT LEARNING
Advanced topics in signal processing, such as multidimensional signal processing, image feature extraction, image/video editing and indexing, advanced digital filter design, multirate signal processing, adaptive signal processing, and wave-form coding of signals. Content varies from year to year, and different topics rotate through the course numbers 6880 to 6889.
- 3 points
TOPICS-INFORMATION PROCESSING
TPC:BIG DATA ANALYTICS
Advanced topics spanning electrical engineering and computer science such as speech processing and recognition, image and multimedia content analysis, and other areas drawing on signal processing, information theory, machine learning, pattern recognition, and related topics. Content varies from year to year, and different topics rotate through the course numbers 6890 to 6899. Topic: Big Data Analytics.
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Instructor:
Ching-Yung Lin
h-index: None Info - 3 points
TOPICS IN COMPUTER SCIENCE
ADV SPOKEN LANGUAGE PROCESSING
Selected topics in computer science (advanced level). 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:
Julia Hirschberg
CULPA: 8
h-index: 77
Info
- 3 points
TOPICS IN COMPUTER SCIENCE
ENGR WEB3 BLOCKCHAIN APPS
Selected topics in computer science (advanced level). 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:
Ronghui Gu
h-index: 11 Info - 3 points
TOPICS IN COMPUTER SCIENCE
DESIGN FOR GENERATIVE AI
Selected topics in computer science (advanced level). 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:
Lydia Chilton
CULPA: 3 h-index: 18 Info - 3 points
TOPICS IN COMPUTER SCIENCE
HIGH PERF MACH LEARNING
Selected topics in computer science (advanced level). 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:
Kaoutar El Maghraoui
Info - 3 points
TOPICS IN COMPUTER SCIENCE
PRACT DEEP LEARNING SYS PERF
Selected topics in computer science (advanced level). 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:
Parijat Dube
Info - 3 points