AI AND THE FUTURE OF CITIES
- Department: Architecture, Planning and Preservation
- T 5 p.m.-7 p.m.
- 3 points
OPTIMIZATION II
An introduction to combinatorial optimization, network flows and discrete algorithms. Shortest path problems, maximum flow problems. Matching problems, bipartite and cardinality nonbipartite. Introduction to discrete algorithms and complexity theory: NP-completeness and approximation algorithms.
- Department: Industrial Engineering and Operations Research
- TR 10:10 a.m.-11:25 a.m.
-
Instructor:
Clifford Stein
CULPA: 31 Wikipedia h-index: 53 Info - 4.5 points
Pediatric Nurse Practitioner Clinical Pr
PNP CLINICAL PRACTICUM
This is the first clinical experience with pediatric patients for the PNP student. The student will be responsible for developing objectives and sharing them with the preceptor. The skills needed to obtain a good history and physical will be honed and further developed. When possible, the student will proactively seek opportunities to practice clinical skills of vision screening, hearing screening and venous access. The student will develop their skills in developmental and mental health screening.
- Department: Nursing
-
Instructor:
Sabrina Opiola McCauley
Info - 1 points
CONVEX OPTIMIZATION
Convex sets and functions, and operations preserving convexity. Convex optimization problems. Convex duality. Applications of convex optimization problems ranging from signal processing and information theory to revenue management. Convex optimization in Banach spaces. Algorithms for solving constrained convex optimization problems.
- Department: Industrial Engineering and Operations Research
- MW 4:10 p.m.-5:25 p.m.
- None None-None
-
Instructor:
Bento Natura
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.
- Department: Mechanical Engineering
- MW 10:10 a.m.-11:25 a.m.
-
Instructor:
Matei T Ciocarlie
Info - 3 points
CLIMATE JUSTICE IN OUR OWN BACKYARD
- Department: Architecture, Planning and Preservation
- R 5 p.m.-7 p.m.
-
Instructor:
Thaddeus Pawlowski
Info - 3 points
Pediatric Primary Care Nursing I: Didact
PED PRIMARY CARE NURSING
Pediatric Primary Care Nursing I is designed to prepare the student to provide primary care to infants, toddlers, and preschoolers so that children may meet their optimal physical, intellectual, and emotional growth and development. The content focuses on health promotion, illness prevention, and the treatment of episodic problems from infancy through preschool.
- Department: Nursing
- M 10 a.m.-12:50 p.m.
-
Instructor:
Clare C McKegney
Info - 3 points
Writing and Delivering Speeches for Poli
Writing & Delivering Spee
MIA Policy Skills II Core.
This introductory course equips students with the fundamentals of persuasive speechwriting and public speaking for political, business, and nonprofit contexts. Students will explore the classical canons of rhetoric and apply them to contemporary speechwriting, developing both the art and science of persuasion.
Following an initial session on theory, the course focuses on building practical skills through writing, editing, and delivering original speeches. Topics include voice and message alignment, tailoring speeches to audiences and occasions, persuasive delivery techniques, and ethical considerations in shaping public discourse.
- Department: International and Public Affairs
- W 5:10 p.m.-7 p.m.
-
Instructor:
James P Holtje
Info - 1.5 points
Communications Tools for Advocacy
MIA Policy Skills II Core.
This course builds on the writing and presentation skills developed in the first part of the SIPA Skills Course by exploring how these skills may be deployed in the broader context of organizational communications, with a focus on policy advocacy.
It will introduce students to a set of key communications tools that can drive effective policy advocacy by turning well-crafted, focused messages into impact. It will focus on the practical tactics that form part of an effective strategic communications plan, from handling one-to-one broadcast interviews to utilizing advocacy reports and publications targeting policymakers, to organizing events, media stunts, and leveraging celebrity spokespeople.
Students will produce and workshop their own video interviews, and conclude the course by developing a communications campaign plan, both in support of the policy memo/issue developed at the end of Policy Skills Part One. The objective is to introduce students to the scope of Comms work, both to develop their own skills and their understanding of how a Comms department approaches its mission.
- Department: International and Public Affairs
- T 3:10 p.m.-5 p.m.
-
Instructor:
Jonathan Birchall
Info - 1.5 points
Visual Storytelling
MIA Policy Skills II Core.
This course provides students with a foundation in the principles and practices of video journalism and multimedia narrative. Against a backdrop of rapidly evolving platforms, technologies, and generative AI tools, students will learn how to create compelling, credible video content that cuts through the noise of the contemporary media landscape. Led by experienced journalists from PBS NewsHour and the Thomson Reuters Foundation, the class offers a blend of hands-on technical training, theoretical exploration of media production, and critical reflection on the social, ethical, and narrative dimensions of visual communication. Students will produce, film, write, and edit a portfolio of original video stories, using smartphones, digital cameras, and Adobe Premiere. Coursework includes individual and collaborative assignments, culminating in a final video essay project and pitch. In addition to developing technical skills, students will gain experience in story development, audience engagement, and content distribution.
- Department: International and Public Affairs
- M 5:10 p.m.-7 p.m.
-
Instructor:
Christopher Booker
Info - 1.5 points
Writing about Policy
MIA Policy Skills II Core.
This course equips students with the journalistic tools necessary to communicate policy ideas to broad public audiences. Through a combination of seminar discussions and workshop-based learning, students develop fluency in multiple forms of opinion writing, including op-eds, essays, blogs, and newsletters. Weekly writing assignments guide students in translating specialized policy expertise into persuasive, accessible prose suitable for publication in student and professional media outlets.
Participants will learn to craft compelling narratives that bridge the gap between expert analysis and public discourse, while cultivating editorial skills through constructive peer feedback. The course emphasizes revision as a core element of the writing process and encourages students to experiment with different genres and styles.
- Department: International and Public Affairs
- T 10 a.m.-11:50 a.m.
-
Instructor:
Liza Featherstone
Wikipedia Info - 1.5 points
U.S. Higher Education: History, Present
In this seminar we will discuss past, present, and future challenges facing colleges and universities and their constituencies. The course may be taken for credit or audited.
Topics include the origins of the modern research university; problems of equity and access in the post-secondary educational system; the place of teaching in graduate training; the changing character of humanistic scholarship; the role of colleges and universities as engines of—or obstructions to—social mobility; past and current challenges to intellectual inquiry and academic freedom.
We will hear from visiting speakers on these topics as well as on questions regarding possible career choices for graduate students facing a shrinking market for traditional tenure-track teaching positions.
- Department: English and Comparative Literature
- T 6:10 p.m.-8 p.m.
- 4 points
Macroeconometrics
Lecture
The course aims to analyze dynamic, multivariate interactions in evolutionary and non-stationary processes. The course first considers stationary univariate time-series processes and then extend the analysis to non-stationary processes and multivariate processes. The course covers a review of linear dynamic time-series models and focus on the concept of cointegration, as many applications lend themselves to dynamic systems of equilibrium-correction relations. In the final analysis, the course is aimed at presenting a certain number of econometric techniques the mastery of which is becoming increasingly inevitable in professional circles.
- Department: MPA IN ECON POLICY MANAGEMENT
- R 1:10 p.m.-3 p.m.
-
Instructor:
Noha Emara
CULPA: 7 Info - 3 points
Macroeconometrics
Recitation
The course aims to analyze dynamic, multivariate interactions in evolutionary and non-stationary processes. The course first considers stationary univariate time-series processes and then extend the analysis to non-stationary processes and multivariate processes. The course covers a review of linear dynamic time-series models and focus on the concept of cointegration, as many applications lend themselves to dynamic systems of equilibrium-correction relations. In the final analysis, the course is aimed at presenting a certain number of econometric techniques the mastery of which is becoming increasingly inevitable in professional circles.
- Department: MPA IN ECON POLICY MANAGEMENT
- W 3:10 p.m.-5 p.m.
- 0 points
Data Driven Approaches for Campaigns and
Data Driven Approaches-Ca
MIA and MPA Policy Skills II Core. Pre-req: Quant I. Priority Registration: MIA and MPA.
We will examine the evolution and revolution in data-driven politics as practiced by leading campaigns and advocacy efforts. The course will provide an overview of key issues in public opinion polling, large-scale microtargeting, randomized controlled trial testing, the application of behavioral science and modern statistical techniques, as well as the current and emerging uses of large language models. Our primary focus will be on developments in U.S. political and advocacy campaigns, but we will also examine the international applications of these tools. The course is designed to provide an informative yet critical overview of an area where it is often difficult to separate hype from expertise. The purpose of the course is to prepare students to understand the strengths and limitations of evidence-based approaches, analytics, and current applications of artificial intelligence. The course provides concrete and practical knowledge of some of the key tools in use in campaigns and advocacy. Students will be encouraged throughout the course to view developments in political analytics as an example of how emerging techniques can be applied and misapplied in a range of organizations and efforts. Students will have opportunities to work on specific advocacy or organizational issues of their own interest, developing approaches to the use of new data and analytics tools that may be of use as they consider specific careers in a range of fields. Students will have the opportunity to design, field, and analyze their own polling questions.
Students will be required to make extensive use of current AI tools, even as those tools change during the course. The course will encourage the use of these tools to support rigorous statistical reasoning while requiring students to understand the appropriate use of methods that are now at least superficially easier to apply. It is strongly recommended that students have completed Quantitative Analysis before taking this course. The class will include outside speakers with expertise in polling, analytics, the use of AI in politics, and other areas.
Mark Steitz is a Washington, DC based communications and analytics strategist. He founded TSD Communications and co founded Catalist (large scale voter data), The Analyst Institute (evidence based voter contact), and QRS New Media (communications technology). He served on the Advisory Board of th
- Department: Data Science for Policy
- M 3:10 p.m.-5 p.m.
- 1.5 points
PROTOTYPING IN URBAN TECH
- Department: Architecture, Planning and Preservation
- T 3 p.m.-5 p.m.
-
Instructor:
James S Piacentini
Info - 3 points
PROJECT MANAGEMENT
- Department: Architecture, Planning and Preservation
- M 11 a.m.-1 p.m.
-
Instructor:
Charles C Stewart
Info - 1.5 points
RESEARCH PROJECT
May be repeated for credit. A special investigation of a problem in nuclear engineering, medical physics, applied mathematics, applied physics, and/or plasma physics consisting of independent work on the part of the student and embodied in a formal report.
- Department: Applied Physics and Applied Mathematics
-
Instructor:
Liliana Borcea
Info -
Instructor:
Carlos Paz Soldan
h-index: 28 Info -
Instructor:
Kui Ren
CULPA: 2 Info - 1-6 points
Empirical Econometric Project
This course aims to provide students with further instruction on how (1) to motivate detailed empirical analysis on a research question of their choice, (2) to justify and to design appropriate econometric tests using relevant time-series, cross-sectional, or panel data, etc., and (3) to draw accurate inferences—as well as direct policy implications—from their results for a wide audience. To meet this objective, the key course requirement is to write an empirical policy paper that details (1)–(3) in no more than 5000 words total (including exhibits, references, etc.), geared not for academics but for economic policymakers or other practitioners. Also, students will be required to report their findings to their instructor, advisors, and fellow students during 10- to 15-minute slide presentations toward the end of the semester.
- Department: MPA IN ECON POLICY MANAGEMENT
- M 8 a.m.-9:50 a.m.
-
Instructor:
John Benson Durham
Info - 1.5 points
Python for Public Policy
MIA and MPA Policy Skills II Core. Priority Registration: MIA and MPA.
This 7-week mini course exposes the students to the application and use of Python for data analytics in public policy setting. The course teaches introductory technical programming skills that allow students to learn Python and apply code on pertinent public policy data. The majority of the class content will utilize the New York City 311 Service Requests dataset. It’s a rich dataset that can be explored from many angles relevant to real-world public policy and program management responsibilities.
- Department: Data Science for Policy
- T 10 a.m.-11:50 a.m.
- T 1:10 p.m.-3 p.m.
-
Instructor:
Aidan Feldman
Info - 1.5 points
Data Analytics for Public Policy, Admin
Intro to Data Analytics
MIA and MPA Policy Skills II Core. Priority Registration: MIA and MPA.
This course provides a practical introduction to the core concepts, techniques, and tools used to analyze data for effective decision-making. Designed for students with little to no background in statistics, mathematics, or statistical software, the course emphasizes intuitive understanding and hands-on learning. Through interactive exercises and real-world datasets, students will explore both qualitative and quantitative methods for extracting insights, identifying patterns, and building evidence-based recommendations. The course focuses on developing analytical reasoning and applied skills that can be used across a range of policy and professional contexts.
- Department: Data Science for Policy
- M 7:10 p.m.-9 p.m.
-
Instructor:
Poranee Kingpetcharat
Info - 1.5 points
Database Design, Management, and Securit
Database Design Mgmt & Se
MIA and MPA Policy Skills II Core. Priority Registration: MIA and MPA.
This advanced course provides a comprehensive introduction to the principles and practices of effective database design, management, and security. Students will gain a strong foundation in information organization, data storage, and database administration, with attention to key topics such as data warehousing, governance, security, privacy, and alternative database models.
The course emphasizes the relational database model and includes practical instruction in Structured Query Language (SQL), data modeling, and integrity constraints. Students will learn to design, build, and manage databases while addressing contemporary issues in security and privacy. Prior experience with basic programming and data structures is recommended.
- Department: Data Science for Policy
- M 7:10 p.m.-9 p.m.
-
Instructor:
Poranee Kingpetcharat
Info - 1.5 points
Porous Bodies
POROUS BODIES
How are bodies in the world? How is the world in bodies? Building from these deceptively simple questions, ours will be an interdisciplinary reading seminar on how bodies (mostly human, but sometimes nonhuman) are made and remade in and through their environments and via their relationships to the material world. Privileging porosity as a rubric, we consider the ever-permeable boundaries between bodies and the other beings (be they viral, chemical, microbial or otherwise) with which they become entangled. Alongside the monographs under study, we will tackle article-length engagements with theories of new feminist/queer materialisms, decolonial and critical science studies. Further, a key aim of this course is to provide students the opportunity to hone some of the most important skills we have in our toolbox as academics, relative to our teaching, our public voice/s as critics, and to our own research.
- Department: Anthropology
- R 12:10 p.m.-2 p.m.
-
Instructor:
Vanessa L Agard-Jones
CULPA: 3 Info - 3 points
LEVEL II FIELDWORK A
LEVEL II FIELDWRK A
- Department: Rehabilitation Medicine (RMED)
-
Instructor:
Phyllis R Simon
Info - 0 points
Data Collection for Evaluation, Policy,
MIA and MPA Policy Skills II Core. Pre-req: Quant I (SIPA IA6500). Priority Registration: MIA and MPA.
Research is an important part of the policy process: it can inform the development of programs and policies so they are responsive to community needs, reveal the impacts of these programs and policies, and help us better understand populations or social phenomena. This half-semester course serves as an introduction to how to ethically collect data for smaller research projects, with an in-depth look at focus groups and surveys as data collection tools. We will also learn about issues related to measurement and sampling. Students will create their own focus group protocol and short survey instrument designed to answer a research question of interest to them.
- Department: Data Science for Policy
- T 5:10 p.m.-7 p.m.
-
Instructor:
Rachel Swaner
Info - 1.5 points
North Korea: State, Society, Diplomacy,
North Korea: State & Stra
This seminar offers an in-depth, interdisciplinary examination of North Korea’s political system, society, foreign policy, and security strategy. Students will critically assess how outside powers influenced Korea’s division, the internal dynamics that shaped the Kim regime’s rise, and how state institutions continue to evolve. Drawing from political science, history, firsthand accounts, and policy documents, the course equips students to challenge common misperceptions and engage analytically with key questions surrounding North Korea’s economy, propaganda, human rights, gender dynamics, and nuclear posture.
- Department: International and Public Affairs
- T 3:10 p.m.-5 p.m.
-
Instructor:
Jonathan Corrado
Info - 3 points
R For Public Policy
MIA and MPA Policy Skills II Core. Priority Registration: MIA and MPA.
This 7-week mini-course leads the students into the R world, helps them master the basics, and establishes a platform for future self-study. The course offers students basic programming knowledge and effective data analysis skills in R in the context of public policy-making and policy evaluation. Students will learn how to install R and RStudio, understand and use R data objects, and become familiar with base R and several statistical and graphing packages. The course will also emphasize use cases for R in public policy domains, focusing on cleaning, exploring, and analyzing data.
- Department: Data Science for Policy
- W 5:10 p.m.-7 p.m.
-
Instructor:
Mike Q Zhu
Info - 1.5 points
ALGEBRAIC NUMBER THEORY
Local and global fields, group cohomology, local class field theory, global class field theory and applications.
- Department: Mathematics
- TR 11:40 a.m.-12:55 p.m.
-
Instructor:
Michael Harris
CULPA: 6 Wikipedia Info - 4.5 points
Introduction to Infographics and Data Vi
Intro to Data Visualizati
MIA and MPA Policy Skills II Core. Priority Registration: MIA and MPA.
This course introduces students to the principles and practices of data visualization as a powerful tool for interpreting and communicating complex information. As large datasets become increasingly available across sectors, the ability to transform raw data into clear, compelling visuals is essential for insight and decision-making.
Students will learn to select appropriate visualization types, apply design techniques that balance form and function, and tell analytic stories with clarity and impact. Through hands-on assignments and guided case studies, the course builds practical skills in visualizing data to uncover patterns, reveal trends, and engage diverse audiences.
- Department: Data Science for Policy
- W 7:10 p.m.-9 p.m.
-
Instructor:
Douglas Williamson
Info - 1.5 points
Assessment and Evaluation
- Department: Rehabilitation Medicine (RMED)
-
Instructor:
Cristin Holland
Info - 1 points
Artificial Intelligence in Public Policy
Artificial Intel in Publi
MIA and MPA Policy Skills II Core. Pre-req: Computing in Context (DSPC IA6000). Priority Registration: MIA and MPA.
This course introduces students to the fundamentals of Artificial Intelligence (AI), its applications in public policy, and its implications for the future of governance. Students will gain a foundational understanding of AI, including the mathematical and programming principles behind common machine learning algorithms used for prediction, classification, and clustering. The course explores the practical applications of AI across various sectors, including business, non-profits, and government, highlighting its transformative potential. In the final segment, students will apply their knowledge to design AI solutions for public policy challenges. Through a "Concept to Implementation" process, student groups will identify problems, navigate data and algorithmic considerations, and propose actionable AI-driven solutions.
- Department: Data Science for Policy
- F 10 a.m.-5 p.m.
-
Instructor:
Sameer R Maskey
Info - 1.5 points
OTHER FRONTIERS IN STAGE MANAGEMENT
OTHER FRONTIERS: INTL
TBD
- Department: Theatre Arts
- W 9:30 a.m.-12:20 p.m.
-
Instructor:
Fredric Hanson
Info - 1.5 points
DEI and Professional Skills
- Department: Rehabilitation Medicine (RMED)
-
Instructor:
Razan Hamed
h-index: 8 Info - 1 points
Building AI Tools with Large Language Mo
MIA and MPA Policy Skills II Core. Priority Registration: MIA and MPA.
In the past two years, Large Language Models (LLMs) built using transformer frameworks have emerged as the fastest-growing area of research and investment in AI/machine learning. Recent releases of chatbots such as ChatGPT (OpenAI), Bing (Microsoft), and Bard (Google) quickly reached hundreds of millions of users and have become the face of artificial intelligence for consumers. There has also been an explosion in the number of applications that depend on LLMs for a variety of more specialized tasks. Recent models have shown impressive performance on both canonical machine learning tasks and for everyday use, yet are in many ways poorly understood and, in some cases, exhibit unexpected and potentially harmful behavior.
Policymakers, analysts, and non-profit and industry leaders need an understanding of these models to take advantage of the opportunities they present and to mitigate potential harms. This course provides an overview of Large Language Models and gives students hands-on experience with various ways of interacting with LLMs. Students will learn to interpret model evaluation metrics, and we will discuss safety and ethics in applied contexts.
- Department: Data Science for Policy
- W 5:10 p.m.-7 p.m.
-
Instructor:
Mike Q Zhu
Info - 1.5 points
THE LONG HISTORY OF ARCH TECHNOLOGY
LONG HIST OF ARCH TECHNOL
- Department: Architecture, Planning and Preservation
- T 11 a.m.-1 p.m.
-
Instructor:
Lucia Allais
Info - 3 points
Data Analysis for Inclusive Policy
Data Analysis-Inclusive P
MIA and MPA Policy Skills II Core. Pre-req: Quant I (SIPA IA6500)
.
Priority Registration: MIA and MPA.
Data is not neutral. How it is collected, categorized, and analyzed is shaped by historical, political, economic, and social forces, often reinforcing existing injustices. While policy professionals are trained in quantitative methods, there is comparatively less focus on interrogating how data itself is produced, how existing frameworks exclude certain populations, and how data can be used to either reinforce or challenge inequities.
This course introduces students to inclusive and decolonial approaches to working with data for policy research and advocacy, emphasizing critical engagement with its lifecycle—from collection to analysis to dissemination. Students will examine how statistical tools, methods, and available data can be utilized to either reinforce or dismantle barriers to opportunity and address structural injustices. Through weekly discussions, hands-on coding exercises, and a research or advocacy project sketch, students will examine a range of data sources and methodologies while developing strategies for ethical, community-centered data practices.
- Department: Data Science for Policy
- M 1:10 p.m.-3 p.m.
-
Instructor:
Harold B Stolper
Info - 1.5 points
Ex. Legal Practice
- Department: Law
-
Instructor:
Gerald Lebovits
h-index: 10 Info -
Instructor:
Mark Nielsen
Info - 2-3 points
TOPICS DATA-DRIVEN ANAL & COMP
Advanced Deep Learning
Selected advanced topics in data-driven analysis and computation. Content varies from year to year, and different topics rotate through the course numbers 6690 to 6699.
- Department: Electrical Engineering
- W 10:10 a.m.-12:40 p.m.
-
Instructor:
Zoran Kostic
CULPA: 1 h-index: 24 Info - 3 points
TOPICS DATA-DRIVEN ANAL & COMP
Deep Learning on the Edge
Selected advanced topics in data-driven analysis and computation. Content varies from year to year, and different topics rotate through the course numbers 6690 to 6699.
- Department: Electrical Engineering
- W 1:10 p.m.-3:40 p.m.
-
Instructor:
Zoran Kostic
CULPA: 1 h-index: 24 Info - 3 points
TOPICS DATA-DRIVEN ANAL & COMP
TPC: MATHEMATICS OF DEEP LEARN
Selected advanced topics in data-driven analysis and computation. Content varies from year to year, and different topics rotate through the course numbers 6690 to 6699.
- Department: Electrical Engineering
- M 4:10 p.m.-6:40 p.m.
-
Instructor:
Predrag R Jelenkovic
CULPA: 1 h-index: 35 Info - 3 points
MAGMATISM & VOLCANISM
Prerequisites: One year each of Chemistry, Physics, Calculus and Earth Sciences Overview This course explores the origin of magmas and their subsequent movements; their ascent, stalling and eruption; their transport of heat and mass through the earth; their formation of crust and creation of volcanoes. The course will explore magmatism itself - its chemical and physical underpinnings - and also develop magmatic tools used to understand other earth processes. Topics will be focused around Grand Questions. Example questions include: What do magmas tell us about the thermal structure of the earth? Why do magmas store and stall where they do? What drives the largest eruptions on Earth? Does continental extension drive melting or melting drive extension? Questions will evolve to reflect the state of the field and student interest. The course is designed to serve as an accessible breadth course for Earth Science graduate students in any discipline.
- Department: Earth and Environmental Sciences
- MW 10:10 a.m.-11:25 a.m.
-
Instructor:
Terry A Plank
CULPA: 6
Wikipedia
Info
- 3 points
RE FINANCE & DEVELOPMENT
- Department: Architecture, Planning and Preservation
- T 5 p.m.-7 p.m.
- 3 points
INVESTIGATIVE TECHNIQUES
- Department: Architecture, Planning and Preservation
- T 1 p.m.-3:30 p.m.
-
Instructor:
Amanda Trienens
Info - 3 points
Advanced Spoken Language Processing
ADV SPOKEN LANG PROC
Applications of spoken language processing, including text-to-speech and dialogue systems. Analysis of speech and text, including entrainment, empathy, personality, emotion, humor, sarcasm, deception, trust, radicalization, and charisma.
- Department: Computer Science
- T 4:10 p.m.-6 p.m.
- None None-None
-
Instructor:
Julia Hirschberg
CULPA: 8
h-index: 77
Info
- 3 points
THEATRE MANAGEMENT & ADMINISTRATION II
THEA MGMT & ADMIN II
- Department: Theatre Arts
- F 3 p.m.-6 p.m.
-
Instructor:
Steven E Chaikelson
CULPA: 5
Info
- 3 points
THEATRE MANAGEMENT & ADMINISTRATION II
UNION AND CONTRACTS
- Department: Theatre Arts
- F 10:30 a.m.-1:15 p.m.
-
Instructor:
Laura B Mackinnon
Info - 3 points
ARCHITECTURAL FINISHES
- Department: Architecture, Planning and Preservation
- F 11 a.m.-1 p.m.
-
Instructor:
Mary Jablonski
Info - 3 points
The Chinese Avant-Garde: A Political His
CHINESE AVANT-GARDE
This course examines the rise and demise of the Chinese Revolution from the unique angles provided by avant-garde writers, artists, designers, graphic novelists, filmmakers, playwrights, and theatre directors in modern China.
- Department: East Asian Languages and Cultures
- R 4:10 p.m.-6 p.m.
-
Instructor:
Lydia Liu
CULPA: 2 Info - 4 points
STOCHASTIC MODELING II
Continuation of IEOR E6711, covering further topics in stochastic modeling in the context of queueing, reliability, manufacturing, insurance risk, financial engineering, and other engineering applications. Topics from among generalized semi-Markov processes; processes with a non-discrete state space; point processes; stochastic comparisons; martingales; introduction to stochastic calculus.
- Department: Industrial Engineering and Operations Research
- TR 2:40 p.m.-3:55 p.m.
-
Instructor:
David D Yao
CULPA: 5
Info
- 4.5 points
RISK & INVESTMENT MANAGEMENT
RISK & INVESTMENT MGMT
- Department: Architecture, Planning and Preservation
- T 11 a.m.-1 p.m.
-
Instructor:
Ryan J Severino
Info - 1.5 points
EXPERIMENTAL PRESERVATION
- Department: Architecture, Planning and Preservation
- W 11 a.m.-1 p.m.
-
Instructor:
Jorge Otero-Pailos
Wikipedia h-index: 12 Info - 3 points
Mural Art and the Ancient Americas
Mural Art & Ancient Ameri
Most simply defined, a "mural" is an artwork made directly on a wall. Its meaning can extend as well to wall-scaled works. A modern sense of the word often evokes the idea of a public or community-facing work at large scale, often made by a collective. That modern image does not often hold for premodern settings, but what is enduring in deep historical study is the fact of mural art as both social and spatial practice. This graduate lecture course is an exploration of the diversity of mural art made in cities and centers in parts of what is now Latin America during the long autonomous era—from about 2000 BC until the European invasions of the 1520s and 30s. Lectures will present case studies of wall painting, relief sculpture, and occasionally textiles that covered the facades and interiors of public monuments, temples, courtyards, and palaces at sites in Mexico, Peru, Guatemala, and Colombia. A secondary throughline of this course will be how images and traditions of Pre-Columbian mural art have been brought into twentieth- and twenty-first-century muralisms and community practices, both in and beyond Latin America. The course's final assignment allows three options: a research paper, a digital project, or an interpretive project designed to be public-facing. While some background in this field is helpful, there are no formal prerequisites for enrollment.
Enrollment is capped at 25. Advanced undergraduate enrollment considered upon petition.
- Department: Art History and Archaeology
- R 4:10 p.m.-6 p.m.
-
Instructor:
Lisa Trever
CULPA: 2 Info - 3 points
COMPARATIVE HERITAGE MGT
- Department: Architecture, Planning and Preservation
- TR 9 a.m.-11 a.m.
- 3 points
BAYESIAN MOD MACHINE LEARNING
Basic statistics and machine learning strongly recommended. Bayesian approaches to machine learning. Topics include mixed-membership models, latent factor models, Bayesian nonparametric methods, probit classification, hidden Markov models, Gaussian mixture models, model learning with mean-field variational inference, scalable inference for Big Data. Applications include image processing, topic modeling, collaborative filtering and recommendation systems.
- Department: Electrical Engineering
- W 4:10 p.m.-6:40 p.m.
-
Instructor:
John W Paisley
CULPA: 1 Info - 3 points
RACE & REPRESENTATION IN CRIMNAL JUSTICE
- Department: Social Work
- M 6:20 p.m.-8:10 p.m.
-
Instructor:
Kimberly D Westcott
Info - 3 points
RE PRIVATE EQUITY
- Department: Architecture, Planning and Preservation
- R 2 p.m.-4 p.m.
-
Instructor:
Jiho Lee
Info - 1.5 points
FORENSIC SOCIAL WORK
This course introduces students to the field of social work and the law – specifically the practice of social work in legal settings. Students will develop competency in forensic social work practice - working knowledge as a practitioner in an interdisciplinary setting representing clients entangled in legal systems including criminal, civil, family and immigration. Students will deconstruct the complexities of the criminal legal systems and further develop awareness in addressing clients’ concerns related to their criminal justice history – pre-arrest, arrest, disposition and re-entry. Similarly, students will gain insight into the filing of Article X petitions in family court and the pathway of a child protection case. This course complements field placements in legal/forensic settings, law minors and students interested in social work and law rooted in rights-based advocacy. This course is premised on a basic understanding of how the legacy of slavery led to mass criminalization and incarceration. Black Lives Matter.
- Department: Social Work
- T 2 p.m.-3:50 p.m.
- R 6:20 p.m.-8:10 p.m.
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Instructor:
Jenny G Crawford
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Instructor:
Rachelle Williams
Info - 3 points
RESTORATIVE JUSTICE THEORY AND PRACTICE
The course will focus on understanding the theory and varied practices of restorative justice (RJ) and transformative justice (TJ), and how they are being used as alternatives to retributive and punitive responses to social problems and individual, community and institutional harm. Students will learn – through modeling and practice – how to facilitate a restorative circle which can serve as the foundation for continued use of restorative practices in social work. The class will provide an understanding of the values and principles of RJ and R, and the most-commonly used RJ models and where they are being used. It will support students in understanding their own relationship to conflict and teach students how to facilitate restorative processes using peacemaking circles. Issues of power, privilege, oppression and identity will be substantial themes throughout the course, both in understanding the need for RJ and TJ, how RJ/TJ can address them, and the ways in which these issues arise in facilitation and the RJ/TJ movement. In addition to understanding RJ, the course will also provide students with a critical analysis of other theories and practices of conflict resolution including mediation, truth and reconciliation, and transitional justice, and how all of these relate to addressing individual, communal and institutional harm. Finally, the course will discuss how social workers can use restorative justice in a variety of settings.
- Department: Social Work
- T 6:20 p.m.-8:10 p.m.
- T 8:30 p.m.-10:20 p.m.
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Instructor:
Sethu L Nair
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Instructor:
Vivianne Guevara
Info - 3 points
Health Promotion: Theory, Research, and
HLTH PRMTION: THRY, RSRCH
Understanding why people behave the way they do, what makes them change their behavior, and how these factors relate to health status and quality of life is critically important for public health professionals. The evidence for the role of individual behavior in all the major health problems throughout the world is indisputable. Equally indisputable is the complex array of factors that combine to produce behavior and deter behavior change. The purpose of this course is to build upon the material presented in the Core in order for students to be able to use individual, interpersonal, organizational and community level public health theories to explain and change health behavior.
- Department: Sociomedical Sciences
- R 8:30 a.m.-11:20 a.m.
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Instructor:
Jane Bogart
Info - 3 points