Course Website: Moodle
Brief Course Description:
This course provides an introduction to the theory and methods of causal inference, focusing on how to draw valid conclusions about cause-and-effect relationships from data. Topics include counterfactual reasoning, potential outcomes, randomized experiments, observational studies, confounding, selection bias, and identification strategies. Students will learn key methodological tools such as regression adjustment, matching, instrumental variables, difference-in-differences, and causal graphs (directed acyclic graphs). Emphasis is placed on both conceptual understanding and practical application, with examples from the social sciences, medicine, economics, and public policy. By the end of the course, students will be able to critically assess causal claims, design empirical strategies for causal estimation, and apply modern statistical methods to real-world data.
Prerequisite: Advance course on statistics and machine learning (such as 097209).
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Course Website: Moodle and References website
Brief Course Description:
Service systems currently make up 60-80% of western economies. Important examples are healthcare systems (hospitals), financial services (banks), and telephone and internet services. The course will provide a framework for modeling service systems and techniques that are used to design, analyze, and operate service systems. In this course, a service system is viewed as a stochastic network. Thus the main theoretical framework is queueing theory, which primarily involves a large class of stochastic models. However, the subject matter is highly multi-disciplinary; hence alternative frameworks are useful as well, including ones from Statistics, Psychology, and Marketing.
Prerequisite: A course on stochastic modeling/processes (such as 094314).
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Course Website: Moodle and References website
Brief Course Description:
Services are a large and important part of the world economy. Worldwide, services account for 65% of GDP and 49% of employment; in the United States the numbers are 77% and 79%, respectively (World Bank 2019). It is therefore imperative to develop efficient and effective operations of services. The management of service operations faces quite different constraints, and targets different objectives, than manufacturing operations. The course examines both traditional and new approaches for achieving operational competitiveness in service businesses. It covers service processes at both the strategic and operational decision-making levels, with an emphasis on the latter.
The course covers the following topics: the service concept and operations strategy, the design of effective service delivery systems, capacity management (matching supply and demand) and the optimization of workflows.
Prerequisite: A core course in Statistics (098740).
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097135 – Multidisciplinary research in Service Engineering – Undergraduate and graduate course
Course Website: Moodle
Brief Course Description:
In this course, we will focus on examining service systems from multiple aspects. We will examine them from Behavioral, Economical, Data Science, and Operations Research perspectives. We will do that by discussing research papers that come from the different disciplines mentioned above. Using these papers, we will look into new developments in the field of service science. Emphasis will be placed on research methodologies such as data science, experiments, and queueing theory.
Prerequisite: Service Engineering (096324).
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Course Website: Moodle
Brief Course Description:
Modeling of inventory systems for various products, for the finite and infinite horizon, under deterministic or stochastic conditions, and with special constraints. Planning multi-echelon inventory systems and supply chains. Models for managing and controlling supply chains.
Prerequisite: Probability (094411/094412) and Deterministic models in operations research (094131)
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Course Website: Moodle
Brief Course Description:
Health care systems, in general, and hospitals, in particular, are major determinants of our quality of life. They also require a significant fraction of our resources and, at the same time, they suffer from (quoting a physician research partner) “a ridiculous number of inefficiencies; thus everybody—patients, families, nurses, doctors, and administrators are frustrated.” In (too) many instances, this frustration is caused and exacerbated by delays—“waiting for something to happen”; in turn, these delays and the corresponding queues signal inefficiencies. Healthcare systems hence present a propitious ground for research and courses in Operations Research (OR), Industrial Engineering, Informations Systems, and Statistics. This would ideally culminate in reduced congestion (crowding) and its accompanying important benefits: clinical, financial, psychological, and social.
In this course, we shall examine the healthcare industry from an operational viewpoint. Specifically, we shall use theory and methods of Service Engineering to analyze healthcare organizations, combining both qualitative and quantitative principles, towards developing solutions to problems that are prevalent and significant in the healthcare industry.
Prerequisite: Service Engineering (096324).