QUANT PHYSIOLOGY II:ORGAN SYST
Students are introduced to a quantitative, engineering approach to cellular biology and mammalian physiology. Beginning with biological issues related to the cell, the course progresses to considerations of the major physiological systems of the human body (nervous, circulatory, respiratory, renal).
-
Instructor:
Barclay Morrison
CULPA: 9 h-index: 42 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.
-
Instructor:
Garud Iyengar
CULPA: 6
h-index: 30
Info
- 3 points
Advanced and Applied Linear Algebra
Advanced Linear Algebra
Advanced topics in linear algebra with applications to data analysis, algorithms, dynamics and differential equations, and more. (1) General vector spaces, linear transformations, spaces isomorphisms; (2) spectral theory - normal matrices and their spectral properties, Rayleigh quotient, Courant-Fischer Theorem, Jordan forms, eigenvalue perturbations; (3) least squares problem and the Gauss-Markov Theorem; (4) singular value decomposition, its approximation properties, matrix norms, PCA and CCA.
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.
-
Instructor:
Kyle Bishop
h-index: 42 Info - 3 points
NANOTECHNOLOGY
The science and engineering of creating materials, functional structures and devices on the nanometer scale. Carbon nanotubes, nanocrystals, quantum dots, size dependent properties, self-assembly, nanostructured materials. Devices and applications, nanofabrication. Molecular engineering, bionanotechnology. Imaging and manipulating at the atomic scale. Nanotechnology in society and industry. Offered in alternate years.
-
Instructor:
Yuan Yang
h-index: 49 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.
-
Instructor:
Katayun Barmak
CULPA: 1 h-index: 49 Info - 3 points
SYNTHESIS & PROCESSING OF MATERIALS
A course on synthesis and processing of engineering materials. Established and novel methods to produce all types of materials (including metals, semiconductors, ceramics, polymers, and composites). Fundamental and applied topics relevant to optimizing the microstructure of the materials with desired properties. Synthesis and processing of bulk, thin-film, and nano materials for various mechanical and electronic applications.
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.
-
Instructor:
Kaizheng Wang
CULPA: 1 h-index: 8 Info - 3 points
MODERN OPTICS
Ray optics, matrix formulation, wave effects, interference, Gaussian beams, Fourier optics, diffraction, image formation, electromagnetic theory of light, polarization and crystal optics, coherence, guided wave and fiber optics, optical elements, photons, selected topics in nonlinear optics.
-
Instructor:
Nanfang Yu
h-index: 48 Info - 3 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.
-
Instructor:
Donald F Ferguson
CULPA: 17 Wikipedia Info - 3 points
TRANSPORT IN FLUID MIXTURES
Develops and applies non-equilibrium thermodynamics for modeling of transport phenomena in fluids and their mixtures. Continuum balances of mass, energy and momentum for pure fluids; non-equilibrium thermodynamic development of Newtons law of viscosity and Fouriers law; applications (conduction dominated energy transport, forced and free convection energy transport in fluids); balance laws for fluid mixtures; non-equilibrium thermodynamic development of Ficks law; applications (diffusion-reaction problems, analogy between energy and mass transport processes, transport in electrolyte solutions, sedimentation).
-
Instructor:
Christopher J Durning
CULPA: 3 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.
-
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.
-
Instructor:
Kostis Kaffes
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.
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.
- 3 points
PRIN OF CONSTRUCTN TECHNIQUES
Current methods of construction, cost-effective designs, maintenance, safe work environment. Design functions, constructability, site and environmental issues.
-
Instructor:
Ibrahim Odeh
Info - 3 points
ENTREPRENEURSHP - ENG & CONSTR
ENTREPRENEURSH-ENG&CONSTR
Capstone practicum where teams develop strategies and business plans for a new enterprise in the engineering and construction industry. Identification of attractive market segments and locations; development of an entry strategy; acquisition of financing, bonding and insurance; organizational design; plans for recruiting and retaining personnel; personnel compensation/incentives. Invited industry speakers. Priority given to graduate students in Construction Engineering and Management.
-
Instructor:
Ibrahim Odeh
Info - 3 points
REAL ESTATE FIN/CONST MANAG
Introduction to financial mechanics of public and private real-estate development and management. Working from perspectives of developers, investors and taxpayers, financing of several types of real estate and infrastructure projects are covered. Basics of real-estate accounting and finance, followed by in-depth studies of private, public, and public/private-partnership projects and their financial structures. Focused on U.S.-based financing, with some international practices introduced and explored. Financial risks and rewards, and pertinent capital markets and their financing roles. Impacts and incentives of various government programs, such as LEED certification and solar power tax credits. Case studies provide opportunity to compare U.S. practices to several international methods.
-
Instructor:
Kevin J Riordan
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.
-
Instructor:
Lydia Chilton
CULPA: 3 h-index: 18 Info - 3 points
SECURITY II
Advanced security. Centralized, distributed, and cloud system security. Cryptographic protocol design choices. Hardware and software security techniques. Security testing and fuzzing. Blockchain. Human security issues. Note: May not earn credit for both W4182 and W4180 or W4187.
-
Instructor:
John S Koh
Info - 3 points
PARTIAL DIFFERENTIAL EQUATIONS
Partial Differential Equation
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.
-
Instructor:
James M Scott
h-index: 2 Info - 3 points
KINETICS OF TRANSFORMATIONS
Review of thermodynamics, irreversible thermodynamics, diffusion in crystals and noncrystalline materials, phase transformations via nucleation and growth, overall transformation analysis and time-temperature-transformation (TTT) diagrams, precipitation, grain growth, solidification, spinodal and order-disorder transformations, martensitic transformation.
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.
-
Instructor:
William Bailey
CULPA: 12 Info - 3 points
Interfacial Engineering for Sustainable
Cross disciplinary interfacial engineering principles and applications in sustainable energy and material science. Surface science and systems analysis across different technology sectors - material production and processing, waste management, device manufacture, composites, coatings, ceramics, membranes, biomaterials, and microelectronics.
-
Instructor:
Raymond Farinato
CULPA: 1 Info - 3 points
Networks, Crowds, and the Web
NETWORKS CROWDS AND THE W
Introduces fundamental ideas and algorithms on networks of information collected by online services. It covers 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.
-
Instructor:
Augustin Chaintreau
CULPA: 6
h-index: 33
Info
- 3 points
ADV DESIGN OF STEEL STRUCTURES
Review of loads and structural design approaches. Material considerations in structural steel design. Behavior and design of rolled steel, welded, cold-formed light-gauge, and composite concrete/steel members. Design of multi-story buildings and space structures.
- 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.
-
Instructor:
Eleni Drinea
CULPA: 8 Info - 3 points
Advanced Algorithms
Introduces classic and modern algorithmic ideas that are central to many areas of Computer Science. The focus is on most powerful paradigms and techniques of how to design algorithms, and how to measure their efficiency. The intent is to be broad, covering a diversity of algorithmic techniques, rather than be deep. The covered topics have all been implemented and are widely used in industry. Topics include: hashing, sketching/streaming, nearest neighbor search, graph algorithms, spectral graph theory, linear programming, models for large-scale computation, and other related topics
-
Instructor:
Alexandr Andoni
CULPA: 2 h-index: 34 Info - 3 points
Foundations of Environmental Engineering
Foundations of Env Eng
Engineering aspects of problems involving human interaction with the natural environment. Review of fundamental principles that underlie the discipline of environmental engineering, i.e. constituent transport and transformation processes in environmental media such as water, air, and ecosystems. Engineering applications for addressing environmental problems such as water quality and treatment, air pollution emissions, and hazardous waste remediation. Presented in the context of current issues facing the practicing engineers and government agencies, including legal and regulatory framework, environmental impact assessments, and natural resource management.
-
Instructor:
Kartik Chandran
CULPA: 4
Wikipedia
h-index: 51
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.
-
Instructor:
Marc W Spiegelman
CULPA: 15
Info
- 3 points
NUMERICAL METHODS/PDE'S
Numerical solution of differential equations, in particular partial differential equations arising in various fields of application. Presentation emphasizes finite difference approaches to present theory on stability, accuracy, and convergence with minimal coverage of alternate approaches (left for other courses). Method coverage includes explicit and implicit time-stepping methods, direct and iterative solvers for boundary-value problems.
-
Instructor:
Qiang Du
Wikipedia h-index: 67 Info - 3 points
ADVANCED THERMODYNAMICS
Advanced classical thermodynamics. Availability, irreversibility, generalized behavior, equations of state for nonideal gases, mixtures and solutions, phase and chemical behavior, combustion. Thermodynamic properties of ideal gases. Applications to automotive and aircraft engines, refrigeration and air conditioning, and biological systems.
-
Instructor:
Arvind Narayanaswamy
CULPA: 9
h-index: 26
Info
- 3 points
CO2 UTILIZATION AND CONVERSION
Introduction to various CO2 utilization and conversion technologies that can reduce the overall carbon footprint of commodity chemicals and materials. Fundamentals of thermodynamics, fluid mechanics, reaction kinetics, catalysis and reactor design will be discussed using technological examples such as enhanced oil recovery, shale fracking, photo and electrochemical conversion of CO2 to chemical and fuels, and formation of solid carbonates and their various uses. Life cycle analyses of potential products and utilization schemes will also be discussed, as well as the use of renewable energy for CO2 conversion.
-
Instructor:
Robert Farrauto
h-index: 52 Info - 3 points
Applied Stochastic Analysis
Provides elementary introduction to fundamental ideas in stochastic analysis for applied mathematics. Core material includes: (i) review of probability theory (including limit theorems), and introduction to discrete Markov chains and Monte Carlo methods; (ii) elementary theory of stochastic process, Ito's stochastic calculus and stochastic differential equations; (iii) introductions to probabilistic representation of elliptic partial differential equations (the Fokker-Planck equation theory); (iv) stochastic approximation algorithms; and (v) asymptotic analysis of SDEs.
-
Instructor:
Shanyin Tong
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.
-
Instructor:
Robert G Bozic
Info - 3 points
Biomechanics of Developmental Biology
BIOMECHANICS DEVELOPMENTA
Biophysical mechanisms of tissue organization
during embryonic development: conservation laws, reaction-diffusion, finite elasticity, and fluid mechanics are reviewed and applied to a broad range of topics in developmental biology, from early development to later organogenesis of the central nervous, cardiovascular, musculoskeletal, respiratory, and gastrointestinal systems. Subdivided into modules on patterning (conversion of diffusible cues into cell fates) and morphogenesis (shaping of tissues), the course will include lectures, problem sets, reading of primary literature, and a final project.
-
Instructor:
Nandan L Nerurkar
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.
-
Instructor:
Christopher J Dolan
CULPA: 4
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.
-
Instructor:
Robert G Bozic
Info - 3 points
PROJECT MANAGEMENT
Project Mgmt of Complex System
Management of complex projects and the tools that are available to assist managers with such projects. Topics include project selection, project teams and organizational issues, project monitoring and control, project risk management, project resource management, and managing multiple projects.
-
Instructor:
Moshe Rosenwein
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.
-
Instructor:
Michael Robbins
Wikipedia 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.
-
Instructor:
Uday Menon
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.
-
Instructor:
Krzysztof M Choromanski
Info - 3 points
FOUND OF NANOBIOSCI/NANOBIOTECH
Fundamentals of nanobioscience and nanobiotechnology, scientific foundations, engineering principles, current and envisioned applications. Includes discussion of intermolecular forces and bonding, of kinetics and thermodynamics of self-assembly, of nanoscale transport processes arising from actions of biomolecular motors, computation and control in biomolecular systems, and of mitochondrium as an example of a nanoscale factory.
-
Instructor:
Henry Hess
CULPA: 1 h-index: 45 Info - 3 points
DIGITAL MANUFACTURING
Additive manufacturing processes, CNC, Sheet cutting processes, Numerical control, Generative and algorithmic design. Social, economic, legal, and business implications. Course involves both theoretical exercises and a hands-on project.
-
Instructor:
Hod Lipson
Wikipedia h-index: 79 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.
-
Instructor:
Hod Lipson
Wikipedia h-index: 79 Info - 3 points
TOPICS IN SOFT MATERIALS
Self-contained treatments of selected topics in soft materials (e.g. polymers, colloids, amphiphiles, liquid crystals, glasses, powders). Topics and instructor may change from year to year. Intended for junior/senior level undergraduates and graduate students in engineering and the physical sciences.
-
Instructor:
Christopher J Durning
CULPA: 3 Info - 3 points
ASSET ALLOCATION
Models for pricing and hedging equity, fixed-income, credit-derivative securities, standard tools for hedging and risk management, models and theoretical foundations for pricing equity options (standard European, American equity options, Asian options), standard Black-Scholes model (with multiasset extension), asset allocation, portfolio optimization, investments over longtime horizons, and pricing of fixed-income derivatives (Ho-Lee, Black-Derman-Toy, Heath-Jarrow-Morton interest rate model).
-
Instructor:
Christopher A Perez
Info - 3 points
BUSINESS ANALYTICS
Prepares students to gather, describe, and analyze data, using advanced statistical tools to support operations, risk management, and response to disruptions. Analysis is done by targeting economic and financial decisions in complex systems that involve multiple partners. Topics include probability, statistics, hypothesis testing, experimentation, and forecasting.
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.
-
Instructor:
Tony B Dear
CULPA: 17
Info
- 3 points
MONTE CARLO SIMULATION METHODS
Monte Carlo Simulation
This graduate course is only for M.S. Program in Financial Engineering students. Multivariate random number generation, bootstrapping, Monte Carlo simulation, efficiency improvement techniques. Simulation output analysis, Markov-chain Monte Carlo. Applications to financial engineering. Introduction to financial engineering simulation software and exposure to modeling with real financial data. Note: Students who have taken IEOR E4404 Simulation may not register for this course for credit.
-
Instructor:
Ali Hirsa
h-index: 8 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.
-
Instructor:
Daniel Bauer
CULPA: 17
h-index: 13
Info
- 3 points
FE CONTINUOUS TIME MODELS
FE: CONTINUOUS TIME MODEL
This graduate course is only for MS program in FE students. Modeling, analysis, and computation of derivative securities. Applications of stochastic calculus and stochastic differential equations. Numerical techniques: finite-difference, binomial method, and Monte Carlo.
-
Instructor:
Xunyu Zhou
h-index: 54 Info - 3 points
STATISTICAL ANALYSIS AND TIME SERIES
STATISTICAL ANALYSIS & TIME SE
This graduate course is only for M.S. Program in Financial Engineering students. Empirical analysis of asset prices: heavy tails, test of the predictability of stock returns. Financial time series: ARMA, stochastic volatility, and GARCH models. Regression models: linear regression and test of CAPM, non-linear regression and fitting of term structures.
-
Instructor:
Agostino Capponi
h-index: 19 Info - 3 points
MACHINE LEARNING FOR DATA SCI
-
Instructor:
Nakul Verma
CULPA: 10
h-index: 16
Info
- 3 points
Computer Vision II: Learning
Advanced course in computer vision. Topics include convolutional networks and back-propagation, object and action recognition, self-supervised and few-shot learning, image synthesis and generative models, object tracking, vision and language, vision and audio, 3D representations, interpretability, and bias, ethics, and media deception.
-
Instructor:
Carl Vondrick
CULPA: 1 h-index: 24 Info - 3 points
COMPUTATIONAL ASPECTS OF ROBOTICS
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.
-
Instructor:
Tony B Dear
CULPA: 17
Info
- 3 points
COMPUTATIONAL GENOMICS
Computational techniques for analyzing genomic data including DNA, RNA, protein and gene expression data. Basic concepts in molecular biology relevant to these analyses. Emphasis on techniques from artificial intelligence and machine learning. String-matching algorithms, dynamic programming, hidden Markov models, expectation-maximization, neural networks, clustering algorithms, support vector machines. Students with life sciences backgrounds who satisfy the prerequisites are encouraged to enroll.
-
Instructor:
Itsik Pe'er
Wikipedia 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.
-
Instructor:
Nakul Verma
CULPA: 10
h-index: 16
Info
- 3 points
ATOMISTIC SIMULATIONS FOR SCIENCE AND EN
Many materials properties and chemical processes are governed by atomic-scale phenomena such as phase transformations, atomic/ionic transport, and chemical reactions. Thanks to progress in computer technology and methodological development, now there exist atomistic simulation approaches for the realistic modeling and quantitative prediction of such properties. Atomistic simulations are therefore becoming increasingly important as a complement for experimental characterization, to provide parameters for meso- and macroscale models, and for the in-silico discovery of entirely new materials. This course aims at providing a comprehensive overview of cutting-edge atomistic modeling techniques that are frequently used both in academic and industrial research and engineering. Participants will develop the ability to interpret results from atomistic simulations and to judge whether a problem can be reliably addressed with simulations. The students will also obtain basic working knowledge in standard simulation software.
-
Instructor:
Alexander Urban
h-index: 24 Info - 3 points
SPEC TOPICS IN APPLIED MATH
INTRO TO MATH OF DATA SCIENCE
May be repeated for credit. Topics and instructors from the Applied Mathematics Committee and the staff change from year to year. For advanced undergraduate students and graduate students in engineering, physical sciences, biological sciences, and other fields. Examples of topics include multi-scale analysis and Applied Harmonic Analysis.
-
Instructor:
Vladimir Kobzar
Info - 3 points
TOPICS IN COMPUTER SCIENCE
GEOMETRIC DATA ANALYSIS
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.
-
Instructor:
Andrew J Blumberg
h-index: 33 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.
-
Instructor:
Yongwhan Lim
Info - 3 points
TOPICS IN COMPUTER 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.
- 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.
-
Instructor:
Vijay Pappu
Info - 3 points
COMP MODELING-PHYSIOL SYSTEMS
Advanced computational modeling and quantitative analysis of selected physiological systems from molecules to organs. Selected systems are analyzed in depth with an emphasis on modeling methods and quantitative analysis. Topics may include cell signaling, molecular transport, excitable membranes, respiratory physiology, nerve transmission, circulatory control, auditory signal processing, muscle physiology, data collection and analysis.
-
Instructor:
Jose McFaline-Figueroa
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 DATABASE SYSTEMS
Continuation of (COMS W4111), covers the latest trends in both database research and industry. Programming projects in Python are required.
-
Instructor:
Luis Gravano
CULPA: 16
h-index: 56
Info
- 3 points
TOPICS IN SOFTWARE ENGINEERING
Topics in Software engineering arranged as the need and availability arises. Topics are usually offered on a one-time basis. Since the content of this course changes, it may be repeated for credit with advisor approval. Consult the department for section assignment.
-
Instructor:
Gail E Kaiser
CULPA: 10 Info - 3 points
Human-Computer Interaction
Human–computer interaction (HCI) studies (1) what computers are used for, (2) how people interact with computers, and (3) how either of those should change in the future. Topics include ubiquitous computing, mobile health, interaction techniques, social computing, mixed reality, accessibility, and ethics. Activities include readings, presentations, and discussions of research papers. Substantial HCI research project required.
-
Instructor:
Brian A Smith
CULPA: 2 h-index: 5 Info - 3 points
THIN FILMS AND LAYERS
Vacuum basics, deposition methods, nucleation and growth, epitaxy, critical thickness, defects properties, effect of deposition procedure, mechanical properties, adhesion, interconnects, and electromigration.
-
Instructor:
Siu-Wai Chan
h-index: 36 Info - 3 points
ADV ANALOG INTEGRATED CIRCUITS
ADV ANALOG INEGRATED CIRC
Integrated circuit device characteristics and models; temperature- and supply-independent biasing; IC operational amplifier analysis and design and their applications; feedback amplifiers, stability and frequency compensation techniques; noise in circuits and low-noise design; mismatch in circuits and low-offset design. Computer-aided analysis techniques are used in homework(s) or a design project.
-
Instructor:
Harish Krishnaswamy
Info - 3 points
ADVANCED HEAT TRANSFER
Application of analytical techniques to the solution of multidimensional steady and transient problems in heat conduction and convection. Lumped, integral, and differential formulations. Topics include use of sources and sinks, laminar/turbulent forced convection, and natural convection in internal and external geometries.
-
Instructor:
Arvind Narayanaswamy
CULPA: 9
h-index: 26
Info
- 3 points
Analog-Digital Interfaces in VLSI
Analog-to-digital and digital-to-analog conversion techniques for very large scale integrated circuits and systems. Precision sampling; quantization; A/D and D/A converter architectures and metrics; Nyquist architectures; oversampling architectures; correction techniques; system considerations. A design project is an integral part of this course.
-
Instructor:
Timothy Dickson
Info - 3 points
ROBOT LEARNING
Robots using machine learning to achieve high performance in unscripted situations. Dimensionality reduction, classification, and regression problems in robotics. Deep Learning: Convolutional Neural Networks for robot vision, Recurrent Neural Networks, and sensorimotor robot control using neural networks. Model Predictive Control using learned dynamics models for legged robots and manipulators. Reinforcement Learning in robotics: model-based and model-free methods, deep reinforcement learning, sensorimotor control using reinforcement learning.
-
Instructor:
Matei T Ciocarlie
Info - 3 points
TOPICS-INFORMATION PROCESSING
TPC: Adv Big Data & AI
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: Advanced Big Data Analytics.
-
Instructor:
Ching-Yung Lin
h-index: None Info - 3 points
TPCS-ELEC & COMPUT ENGINEERING
Future Energy: Econ-Syst
Selected topics in electrical and computer engineering. Content varies from year to year, and different topics rotate through the course numbers 6900 to 6909.
-
Instructor:
Debasis Mitra
Wikipedia h-index: 61 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.
-
Instructor:
Julia Hirschberg
CULPA: 8
h-index: 77
Info
- 3 points
TOPICS IN COMPUTER SCIENCE
FUND SPEECH RECOGNITION
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.
-
Instructor:
Homayoon Beigi
Info - 3 points
TOPICS IN COMPUTER SCIENCE
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.
-
Instructor:
Suman Jana
h-index: 33 Info -
Instructor:
Rocco Servedio
CULPA: 15
h-index: 48
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.
- 3 points