Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

Effective communication with the patients and their relatives, taking medical history and performing physical examination, improving physical examination skills, evaluation of signs and symptoms of the diseases, selection of the most appropriate laboratory or diagnostic tests, a reasonable analysis of patient data, and reporting patient information. To have critical knowledge about the diagnosis and management of common, foremost acute/chronic medical illnesses. Ability to select and interpret laboratory tests and imaging modalities and rational drug therapies. (8 weeks; compulsory on-call nights and weekends)

The aim of the course is to give qualified Industrial Engineering students a unique opportunity to serve as undergraduate teaching assistants (TA) as a part of their undergraduate experience. Students are responsible for running review and problem sessions, holding office hours and supervising laboratories for Industrial Engineering core and area courses.

The aim of the course is to give qualified Industrial Engineering students a unique opportunity to serve as undergraduate teaching assistants (TA) as a part of their undergraduate experience. Students are responsible for running review and problem sessions, holding office hours and supervising laboratories for Industrial Engineering core and area courses.

The aim of the course is to give qualified Industrial Engineering students a unique opportunity to serve as undergraduate teaching assistants (TA) as a part of their undergraduate experience. Students are responsible for running review and problem sessions, holding office hours and supervising laboratories for Industrial Engineering core and area courses.

The aim of the course is to give qualified Industrial Engineering students a unique opportunity to serve as undergraduate teaching assistants (TA) as a part of their undergraduate experience. Students are responsible for running review and problem sessions, holding office hours and supervising laboratories for Industrial Engineering core and area courses.

The aim of the course is to give qualified Industrial Engineering students a unique opportunity to serve as undergraduate teaching assistants (TA) as a part of their undergraduate experience. Students are responsible for running review and problem sessions, holding office hours and supervising laboratories for Industrial Engineering core and area courses.

Financial accounting principles and cost systems for engineering economic analyses. Cost-volume-profit analyses, discounted cash flow and budgeting techniques.

Basic parametric statistics such as estimation, confidence intervals, and hypothesis testing. Distribution fitting, goodness of fit tests. Independence tests and contingency tables. Simple linear regression and correlation analysis. Nonlinear and multiple regression, analysis of categorical data. Industrial engineering applications in quality control and demand forecasting. Statistical software packages and computer implementations.

Introduction to modeling concepts and optimization; setting upoptimization models from problem description; linear programming problem formulation; simplex method, duality and sensitivity analysis; applications of mathematical programming in engineering and management with computer implementations.

Introduction to modeling concepts and optimization; setting upoptimization models from problem description; linear programming problem formulation; simplex method, duality and sensitivity analysis; applications of mathematical programming in engineering and management with computer implementations.

Introduction of simulation models to analyze the behavior of complex stochastic systems. Modeling time and randomness, model validation. Generation of stochastic inputs, random variate generation. Implementation of models arising from case studies via simulation languages and software. Output analysis, variance reduction techniques. Monte Carlo and Quasi Monte Carlo Methods.

Quantitative models for decision-making with focus on tactical and operational decisions in manufacturing environments. Aggregate planning, inventory control, forecasting, project management, production scheduling, manpower and capacity planning, location and layout planning, manufacturing resource planning (MRP) and just-in-time (JIT) systems.

Modeling and analysis of large-scale and complex systems; mathematical model building; the solution of these models with computational tools and post-optimality analysis for decision-making problems arising in a wide range of real-life applications; building effective linear, nonlinear, integer, network and stochastic programming models; using optimization software for the solution of these models and interpretation of the computer output; applications in transportation and logistics planning, data mining, scheduling in large systems, supply-chain management, financial engineering, and telecommunications systems planning.

Distinctions of service operations. Measuring and benchmarking productivity: Data Envelopment Analysis (theory and applications). Service Quality. Capacity management and design in services. Capacity-constrained services and demand management (revenue management and optimization). Workflow analysis,productivity and quality management,response time (queuing) analysis. Customer relationship and loyalty issues (data-mining). Applications of analysis tools to several sectors such as health care, call centers, financial services, hotels and airlines.

Overview of industrial engineering and operations research applications in healthcare. Capacity planning and management in hospitals. Evaluating effects of interventions on the spread of infectious diseases. Analyzing the effects of resource allocation policies. Analysis of screening policies and their effects. Developing medical decision modeling to build decision support systems.

Formulation of integer and combinatorial optimization problems Introduction to logistics systems; logistics network design, location models; warehouse design, tactical decisions, operational decisions; transportation management; planning and managing freight transportation; fleet management, vehicle routing problem.

A capstone design course where students apply engineering and science knowledge in an industrial engineering design project proposed by companies from different sectors. Development, design, implementation and management of a project in teams under realistic constraints and conditions. Emphasis on communication, teamwork and presentation skills.

A capstone design project on an industrially relevant problem. Students work on teams in consultation with various faculty and industrial members.