CIVIL ENGINEERING RESEARCH
Advanced study in a specialized field under the supervision of a member of the department staff. Before registering, the student must submit an outline of the proposed work for approval of the supervisor and the department chair.
- Department: Civil Engineering and Engineering Mechanics
-
Instructor:
Marianna Maiaru
Info -
Instructor:
Ibrahim Odeh
Info -
Instructor:
Markus Schlaepfer
Info -
Instructor:
Andrew W Smyth
CULPA: 3 Info -
Instructor:
Waiching Sun
CULPA: 1 h-index: 30 Info -
Instructor:
Haim Waisman
CULPA: 3
h-index: 29
Info
-
Instructor:
Huiming Yin
CULPA: 1 h-index: 25 Info -
Instructor:
Zhengbo Zou
Info -
Instructor:
Fredric Bell
Info -
Instructor:
Nicolo Daina
Info - 1-6 points
TV WRITING THESIS WORKSHOP
- Department: Film
- W 6 p.m.-9 p.m.
-
Instructor:
Blair Singer
Info - 0 points
RESEARCH
Before registering, the student must submit an outline of the proposed work for approval by the supervisor and the chair of the Department. Advanced study in a specialized field under the supervision of a member of the department staff. May be repeated for credit.
- Department: Industrial Engineering and Operations Research
-
Instructor:
Anish Agarwal
Info -
Instructor:
Shipra Agrawal
h-index: 24 Info -
Instructor:
Eric Balkanski
h-index: 13 Info -
Instructor:
Daniel Bienstock
h-index: 38 Info -
Instructor:
Agostino Capponi
h-index: 19 Info -
Instructor:
Rachel Cummings
h-index: 16 Info -
Instructor:
Antonius B Dieker
CULPA: 10 h-index: 19 Info -
Instructor:
Christopher J Dolan
CULPA: 4
Info
-
Instructor:
Adam N Elmachtoub
CULPA: 1 h-index: 13 Info -
Instructor:
Yuri Faenza
h-index: 11 Info -
Instructor:
Donald Goldfarb
CULPA: 1 Wikipedia h-index: 55 Info -
Instructor:
Vineet Goyal
h-index: 21 Info -
Instructor:
Ali Hirsa
h-index: 8 Info -
Instructor:
Anran Hu
Info -
Instructor:
Garud Iyengar
CULPA: 6
h-index: 30
Info
-
Instructor:
Hardeep Johar
Info -
Instructor:
Cedric Josz
CULPA: 2 h-index: 13 Info -
Instructor:
Soulaymane Kachani
CULPA: 12 Info -
Instructor:
Yaren Kaya
Info -
Instructor:
Christian Kroer
h-index: 16 Info -
Instructor:
Daniel Lacker
CULPA: 4
h-index: 13
Info
-
Instructor:
Henry Lam
h-index: 17 Info -
Instructor:
Fabrizio Lecci
Info -
Instructor:
Tianyi Lin
Info -
Instructor:
Jay Sethuraman
CULPA: 10 Info -
Instructor:
Karl Sigman
CULPA: 15
Info
-
Instructor:
Clifford Stein
CULPA: 31 Wikipedia h-index: 53 Info -
Instructor:
Wenpin Tang
h-index: 6 Info -
Instructor:
Kaizheng Wang
CULPA: 1 h-index: 8 Info -
Instructor:
David D Yao
CULPA: 5
Info
-
Instructor:
Yi Zhang
CULPA: 2 Info -
Instructor:
Xunyu Zhou
h-index: 54 Info -
Instructor:
Winsor Yang
Info - 1-6 points
CLIN PRACTICE IMPLANT DENTISTRY II
CLIN PRACT IMPL DNTRTY II
- Department: Dental and Oral Surgery
- 0 points
SIGMUND FREUD-THINKNG/THEORZNG
- Department: Psychoanalytic Center
-
Instructor:
W. C Tomlinson
Info - 0 points
RESEARCH IN ARCHAEOLOGY
RESEARCH IN PREHISTORIC ANTHR
Prerequisites: the instructors permission. Individual research and tutorial in archaeology for advanced graduate students.
- Department: Anthropology
-
Instructor:
Brian Boyd
CULPA: 6
Info
-
Instructor:
Zoe Crossland
CULPA: 9 h-index: 17 Info -
Instructor:
Terence N D'Altroy
CULPA: 37 Info - 3-9 points
RESEARCH IN ARCHAEOLOGY
RESEARCH IN PREHISTORIC ARCH
Prerequisites: the instructors permission. Individual research and tutorial in archaeology for advanced graduate students.
- Department: Anthropology
-
Instructor:
Severin Fowles
CULPA: 24
Info
- 3-9 points
RESEARCH IN ARCHAEOLOGY
RESEARCH IN PREHISTORIC ANTHR
Prerequisites: the instructors permission. Individual research and tutorial in archaeology for advanced graduate students.
- Department: Anthropology
-
Instructor:
Hannah Chazin
Info -
Instructor:
Camilla Sturm
CULPA: 2 Info - 3-9 points
Probability for Biostatisticians
Probability: Biostatistic
The biostatistical field is changing with new directions emerging constantly. Doing research in these new directions, which often involve large data and complex designs, requires advanced probability and statistics tools. The purpose of this new course is to collect these important probability methods and present them in a way that is friendly to a biostatistics audience. This course is designed for PhD students in Biostatistics. Its primary objective is to help the students achieve a solid understanding of these probability methods and develop strong analytical skills that are necessary for conducting methodological research in modern biostatistics. At the completion of this course, the students will a) have a working knowledge in Law of Large Numbers, Central Limit Theorems, martingale theory, Brownian motions, weak convergence, empirical process, and Markov chain theory; b) be able to understand the biostatistical literature that involves such methods; c) be able to do proofs that call for such knowledge.
- Department: Biostatistics
- F 1 p.m.-3:50 p.m.
-
Instructor:
Bin Cheng
h-index: 32 Info - 3 points
RESEARCH IN SPECIAL FIELDS
Prerequisites: the instructors permission. Individual research in all divisions of anthropology and in allied fields for advanced graduate students
- Department: Anthropology
-
Instructor:
Naor H Ben-Yehoyada
CULPA: 5 Info -
Instructor:
John Pemberton
CULPA: 15
Wikipedia
Info
-
Instructor:
Lila Abu-Lughod
CULPA: 17 Wikipedia h-index: 48 Info -
Instructor:
Marilyn Ivy
CULPA: 11
Wikipedia
Info
-
Instructor:
Claudio Lomnitz
CULPA: 3 Wikipedia Info -
Instructor:
Elizabeth Povinelli
CULPA: 14
Wikipedia
Info
-
Instructor:
Ellen Marakowitz
CULPA: 1 Info -
Instructor:
Paige West
CULPA: 41
h-index: 23
Info
-
Instructor:
Lesley Sharp
CULPA: 22 Info -
Instructor:
Kaya N Williams
Info -
Instructor:
Brian Larkin
CULPA: 16 Info -
Instructor:
Sheng Long
Info -
Instructor:
David Scott
CULPA: 6
h-index: 72
Info
-
Instructor:
Mahmood Mamdani
CULPA: 21
Wikipedia
h-index: 57
Info
-
Instructor:
Vanessa L Agard-Jones
CULPA: 3 Info -
Instructor:
Maria Jose de Abreu
Info -
Instructor:
Catherine Fennell
Info -
Instructor:
Lashaya Howie
Info -
Instructor:
Nadia Abu El-Haj
CULPA: 13
Wikipedia
Info
-
Instructor:
Elizabeth M Green
CULPA: 2 Info - 3-9 points
(PhD) Advanced Marketing Analytics
(PhD) Advanced Mrkt Analy
Multivariate statistical techniques are important tools of analysis in all fields of management. This course is designed to provide students with a working knowledge of the basic concepts underlying the most important multivariate techniques, an overview of actual applications in various fields and experience in actually using such techniques on a problem of their own choosing. The course addresses both the underlying mathematics and problems of applications. As such, a reasonable level of competence in both statistics and mathematics is needed to take this course.
- Department: Decision, Risk and Operations
- W 2:20 p.m.-5:35 p.m.
-
Instructor:
Kamel Jedidi
Info - 3 points
Theory of Statistical Inference I
THEORY OF STAT INFERENCE
This course offers a general introduction to essential materials in advanced statistical theory for doctoral students in biostatistics. The course is designed to prepare doctoral students in biostatistics for their written theory qualifying exam. Students in this course will learn theory of estimation, confidence sets and hypothesis testing. Specific topics include a quick review of measure-theoretic probability theory, concepts of sufficiency and completeness, unbiased estimation (UMVUE), least squares principle, likelihood estimation, a variety of estimators and their asymptotic properties, confidence sets, the Neyman-Pearson lemma and uniformly most powerful tests. If time permits, the likelihood ratio test, score test and Wald test, and sequential analysis will be covered.
- Department: Biostatistics
- TR 1 p.m.-2:20 p.m.
-
Instructor:
Caleb Miles
h-index: 5 Info - 3 points
MUSEUM ANTHROPOL INTERNSHIP I
An internship arranged through the Museum Anthropology program of 10 hrs/week (for 3 credits) or 20 hrs/week (for 6). Involves meaningful work, requires keeping a journal and writing a paper at the completion of the semester. Not to be taken without permission of the program directors, usually after completing the Museum Anthropology core courses.
- Department: Anthropology
-
Instructor:
Brian Boyd
CULPA: 6
Info
- 3-9 points
WORKSHOP IN SCRIPT REVISION
- Department: Film
- F 10 a.m.-1 p.m.
- T 10 a.m.-1 p.m.
- T 6 p.m.-9 p.m.
-
Instructor:
David B Schwab
Info -
Instructor:
Richard Dresser
Info -
Instructor:
Christina Lazaridi
Info - 0 points
METAETHICS
What is realism and how does it relate to objectivity? In this course, we will consider a range of answers, with special attention to problems of value. We will begin by clarifying the nature of realism about a subject matter and arguments that might support it. We will then look at limitations of realism per se, and the need to supplement it with a distinct notion of objectivity. Next, we will consider arguments that “realist objectivism”, while attractive, is an untenable package. This will lead us to discuss anti-objectivist forms of realism and their deflationary methodological ramifications. Finally, we will look at the prospects for objectivity without realism, particularly in the evaluative case. We will conclude by sketching a neo-pragmatist metaphilosophical outlook.
- Department: Philosophy
- T 6:10 p.m.-8 p.m.
-
Instructor:
Akeel Bilgrami
CULPA: 28 Wikipedia Info - 3 points
MUSEUM ANTHROPOL INTERNSHIP II
An internship arranged through the Museum Anthropology program of 10 hrs/week (for 3 credits) or 20 hrs/week (for 6). Involves meaningful work, requires keeping a journal and writing a paper at the completion of the semester. Not to be taken without permission of the program directors, usually after completing the Museum Anthropology core courses.
- Department: Anthropology
-
Instructor:
Brian Boyd
CULPA: 6
Info
- 3-9 points
Asymptotic Statistics
ASYMPTOTIC STATISTICS
This course will provide a comprehensive introduction to the field of asymptotic statistics. The treatment will be both practical and mathematically rigorous. The course will consist of two parts. The first will be a review of most of the standard topics of limit theory, such as the delta method and central limit theorems, while avoiding many technicalities. The second will present advanced topics such as semiparametric models, counting processes, empirical likelihood, the bootstrap, and empirical processes. These powerful research techniques are becoming increasingly important for the development of biostatistical methods to handle complex data sets. The overall goal of the course is to train students in the use of advanced asymptotic techniques for medical and public health applications. This course is intended for second-year Biostatistics Ph.D. students to provide a review of asymptotic statistics for the Ph.D. qualifying exam, and give them exposure to a variety of advanced topics.
- Department: Biostatistics
- T 1 p.m.-3:50 p.m.
-
Instructor:
Ian McKeague
h-index: 43 Info - 3 points
(PhD) Foundations of Optimizat
The course is designed for entering doctoral students and provides a rigorous introduction to the fundamental theory of optimization. It examines optimization theory in continuous, deterministic settings, including optimization in Euclidean as well as in more general, infinite-dimensional vector spaces. The course emphasizes unifying themes (such as optimality conditions, Lagrange multipliers, convexity, duality) that are common to all of these areas of mathematical optimization. Applications across a range of problem areas serve to illustrate and motivate the theory that is developed. Additionally, review sessions explaining how to solve complex optimization problems using CVX and Python are offered.
- Department: Decision, Risk and Operations
- R 2:20 p.m.-5:35 p.m.
-
Instructor:
Santiago R Balseiro
Info - 3 points
Topics in Statistical Learning and Data
TPCS-STAT LEARN/DATA MINI
The aim of this course is to provide students a systematic training in key topics in modern supervised statistical learning and data mining. For the most part, the focus will remain on a theoretically sound understanding of the methods (learning algorithms) and their applications in complex data analysis, rather than proving technical theorems. Applications of the statistical learning and data mining tools in biomedical and health sciences will be highlighted.
- Department: Biostatistics
- R 1 p.m.-3:50 p.m.
-
Instructor:
Min Qian
h-index: 19 Info - 3 points
TV REVISION
FILM AF 9120 TV Revision
The goal of TV Revision is to bring in a completed pilot and then completely revise it in one semester. Students will initially present their full scripts for feedback in class discussion, then map a plan for rewriting with their instructor. Deadlines throughout the semester will focus on delivery of revised pages.
The work can range from an intensive page 1 rewrite to focus on selected areas in a script. Reading of all scripts in the workshop and participation in class discussion is required.
There is an application process to select students for the class.
- Department: Film
- W 9:30 a.m.-12:30 p.m.
- R 10 a.m.-1 p.m.
-
Instructor:
Courtney M Baron
Info -
Instructor:
Blair Singer
Info - 0 points
COMPUTING FOR BUSINESS RESRCH
- Department: Decision, Risk and Operations
- F 9 a.m.-12:15 p.m.
- F 2:20 p.m.-5:35 p.m.
-
Instructor:
Miguel Morin
Info - 3 points
Advanced Biostatistical Method I
Adv. Biostatistical Metho
This is an advanced course for first-year Ph.D. students in Biostatistics. The aim is to provide a solid foundation of the theory behind linear models and generalized linear models. More emphasis will be placed on concepts and theory with mathematical rigor. Topics covered including linear regression models, logistic regression models, generalized linear regression models and methods for the analysis contingency tables.
- Department: Biostatistics
- M 8:30 a.m.-11:20 a.m.
-
Instructor:
Zhezhen Jin
h-index: 51 Info - 3 points
Fundamentals of Case Narrative Writing f
Fund Case Narrat Writing
This course is designed to increase student knowledge of Psychiatric Nurse Practitioner Case Narrative writing, and DNP competencies. Students will use case narratives as a framework to synthesize knowledge, assessment, and clinical thinking skills. Students will explore Social Justice competency, Competency D3C3 in depth. Students will develop a treatment intervention that identify and challenge biases that contribute to health disparities.
- Department: Nursing
- M 10 a.m.-12:50 p.m.
- 3 points
APPLIED PHYSICS SEMINAR
REACTOR DESIGN
May be repeated for credit. Selected topics in applied physics. Topics and instructors change from year to year.
- Department: Applied Physics and Applied Mathematics
- MW 10:10 a.m.-11:25 a.m.
-
Instructor:
Carlos Paz Soldan
h-index: 28 Info - 3 points
EPIDEMIOLOGY & SURVEILLANCE
- Department: Dental and Oral Surgery
-
Instructor:
Kavita Ahluwalia
h-index: 10 Info - 0 points
Portfolio Film Workshop
This fourteen-week elective, open to Research Arts Screen & TV Writing students, will provide vital directing advisement to Portfolio films. It covers pre-production and director’s prep.
- Department: Film
- T 2 p.m.-5 p.m.
-
Instructor:
Bogdan G Apetri
Info - 0 points
DROM Preseminar Discussion
Students get together to discuss the paper which will be presented at the IEOR-DRO seminar. One group of students (~2 students) presents. A faculty member is present to guide and facilitate the discussion. Students are evaluated on their effort in leading one of the discussions and participating in the other discussions
- Department: Decision, Risk and Operations
-
Instructor:
Daniel J Russo
Info - 0.5 points
Generative AI: Technical and Social
Generative AI: Tech & Soc
This course examines Generative AI technologies through both a technical and social lens. In
the first part of the course, students will develop hands-on experience in the technical workings
of LLMs, including prompt engineering, retrieval augmented generation, fine-tuning, and safety.
In the second part of the course, students will examine the social and ethical implications of
these technologies and examine the impact of these technologies on topics like content
creation, labor markets, and security.
Designed for students interested in advancing AI technology responsibly, this course
encourages critical thinking about AI's broader effects. Participants will gain practical skills and a
deeper understanding of how AI tools can be developed and utilized ethically and effectively in
various sectors.
- Department: Decision, Risk and Operations
- R 2:20 p.m.-5:15 p.m.
- 3 points