RESEARCH IN ARCHAEOLOGY
RESEARCH-PREHISTORIC ARCHAEOL
Prerequisites: the instructors permission. Individual research and tutorial in archaeology for advanced graduate students.
- Department: Anthropology
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Instructor:
Zoe Crossland
CULPA: 9 h-index: 17 Info -
Instructor:
Terence N D'Altroy
CULPA: 37 Info - 3-9 points
RESEARCH IN ARCHAEOLOGY
Prerequisites: the instructors permission. Individual research and tutorial in archaeology for advanced graduate students.
- Department: Anthropology
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Instructor:
Severin Fowles
CULPA: 24
Info
- 3-9 points
RESEARCH-MODERN & CONTEMP LIT
Guided reading and research on a topic or in a field chosen by the student in consultation with a member of the faculty.
- Department: Italian
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Instructor:
Elizabeth Leake
Info - 3 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.
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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
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Instructor:
Nadia Abu El-Haj
CULPA: 13
Wikipedia
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Instructor:
Lila Abu-Lughod
CULPA: 17 Wikipedia h-index: 48 Info -
Instructor:
Vanessa L Agard-Jones
CULPA: 3 Info -
Instructor:
Naor H Ben-Yehoyada
CULPA: 5 Info -
Instructor:
Brian Boyd
CULPA: 6
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Instructor:
Terence N D'Altroy
CULPA: 37 Info -
Instructor:
Zoe Crossland
CULPA: 9 h-index: 17 Info -
Instructor:
Hannah Chazin
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Instructor:
Maria Jose de Abreu
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Instructor:
Catherine Fennell
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Instructor:
Severin Fowles
CULPA: 24
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Instructor:
Elizabeth M Green
CULPA: 2 Info -
Instructor:
Lashaya Howie
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Instructor:
Marilyn Ivy
CULPA: 11
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Instructor:
Brian Larkin
CULPA: 16 Info -
Instructor:
Claudio Lomnitz
CULPA: 3 Wikipedia Info -
Instructor:
Mahmood Mamdani
CULPA: 21
Wikipedia
h-index: 57
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Instructor:
Ellen Marakowitz
CULPA: 1 Info -
Instructor:
Rosalind Morris
CULPA: 20 Wikipedia Info -
Instructor:
John Pemberton
CULPA: 15
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Instructor:
Elizabeth Povinelli
CULPA: 14
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Instructor:
Lesley Sharp
CULPA: 22 Info -
Instructor:
Audra Simpson
CULPA: 5
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Instructor:
Paige West
CULPA: 41
h-index: 23
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Instructor:
Kaya N Williams
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Instructor:
Nicholas Glastonbury
Info - 3-9 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.
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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
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Instructor:
Brian Boyd
CULPA: 6
Info
- 3-9 points
WORKSHOP IN SCRIPT REVISION
- Department: Film
- F 10 a.m.-1 p.m.
- M 6 p.m.-9 p.m.
- R 10 a.m.-1 p.m.
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Instructor:
David B Schwab
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Instructor:
Rafael L Pedreira
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Instructor:
Christina Lazaridi
Info - 0 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
- M 2:20 p.m.-5:35 p.m.
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Instructor:
Natascha Hey
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.
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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
- M 2 p.m.-5 p.m.
- F 9:30 a.m.-12:30 p.m.
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Instructor:
Benjamin Robbins
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Instructor:
Matthew R Fennell
Info - 0 points
SOCIAL NETWORKS
- Department: Sociology
- T 4:10 p.m.-6 p.m.
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Instructor:
Peter Bearman
CULPA: 19
Wikipedia
h-index: 54
Info
- 3 points
COMPUTING FOR BUSINESS RESRCH
- Department: Decision, Risk and Operations
- W 9 a.m.-12:15 p.m.
- W 2:20 p.m.-5:35 p.m.
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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.
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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 8 a.m.-10:50 a.m.
- 3 points
EPIDEMIOLOGY & SURVEILLANCE
- Department: Dental and Oral Surgery
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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
- W 9:30 a.m.-12:30 p.m.
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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
- T 9 a.m.-12:15 p.m.
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Instructor:
Hongseok Namkoong
h-index: 11 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
- T 6 p.m.-9 p.m.
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Instructor:
Tianyi Peng
Info - 3 points
Master's Essay in Biostatistics: Patient
MASTER'S ESSAY-PATIENT OR
This seminar-style course will lead students through the process of writing a Master's Essay in the form of an NIH-style grant application (required for the MS/POR degree track). The essay is undertaken during the fall semester of the second year of study. At the end of the fall term, each student submits a written research proposal following NIH guidelines for either an R01 or K (career development) award. The emphasis in this course is on the quality of the proposed research. The following February, students make an oral presentation to the POR Advisory Board, summarizing the research proposal. Final grades are awarded after the presentations in February.
- Department: Biostatistics
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Instructor:
Qixuan Chen
h-index: 27 Info - 0 points
S TRANSITIONAL JUSTICE
This is a Law School course. For more detailed course information, please go to the Law School Curriculum Guide at: http://www.law.columbia.edu/courses/search
- Department: Law
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Instructor:
Graeme Simpson
Info - 2 points
RESEARCH SEMINAR IN COGNITION
Weekly seminar of presentations and discussion of current topics in cognition.
- Department: Psychology
- T 1 p.m.-3 p.m.
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Instructor:
Lila Davachi
CULPA: 1 h-index: 59 Info - 3 points
TOPICS IN MORAL PHILOSOPHY
Prerequisites: the instructor's permission. At least one foundational course in moral philosophy is recommended as background for this course. In this seminar we will take up several questions about moral understanding and insight. Questions we will consider include: Can trusting moral testimony ever be rational or right? Are the reasons to be cautions about relying on moral testimony moral reasons or epistemic reasons (or both)? What assumptions about moral knowledge do critics and defenders of moral testimony make? How does moral knowledge differ, if it does, from moral understanding? Is there such a thing as moral expertise? Is there any reason to think that moral expertise is more problematic than other kinds of expertise? Can emotions inform us about value? Under what conditions, if any, can emotions contribute to our understanding of value? Under what conditions are emotions impediments to moral knowledge or understanding? Can fictions help us gain moral insight? Can pictures ever be legitimate tools of moral persuasion?
- Department: Philosophy
- W 4:10 p.m.-6 p.m.
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Instructor:
Axel Honneth
CULPA: 2 Wikipedia Info - 3 points
Statistical Practices and Research for I
Stat Prac & Res for Int S
In this course, students will apply the concepts and methods introduced in Statistical Practices and Research for Interdisciplinary Science (SPRIS) I to a real research setting. Each student will be paired with a Biostatistics faculty member. The student will participate in one of the mentor’s collaborative projects to learn how to be an effective member of an interdisciplinary team. The relationship will mimic that between a medical resident and an attending physician.
The SPRIS II experience will vary depending on the assigned faculty member, but all students will gain exposure to preparing collaborative grant applications, designing research studies, analyzing real data, interpreting and presenting results, and writing manuscripts. Mentors will help to develop the student’s data intuition skills, ability to ask good research questions, and leadership qualities. Where necessary, students may replicate projects already completed by the faculty mentor to gain experience.
- Department: Biostatistics
- M 2 p.m.-3:30 p.m.
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Instructor:
Arthur Jeff Goldsmith
Info - 1.5 points
Tutorial in Biostatistics
TUTORIALS IN BIOSTATISTIC
For appropriately qualified students wishing to enrich their programs by undertaking literature reviews, special studies, or small group instruction in topics not covered in formal courses.
- Department: Biostatistics
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Instructor:
Ying Wei
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Instructor:
Shing M Lee
Info - 0-6 points
Master's Thesis in BME
This is a Pass/Fail zero credit course, “BME Master's Thesis” for MS students who are in the process of doing a thesis (BMEN E9100). It would be registered for before/during the final semester, the semester when the student will be defending the thesis. It must be approved by the faculty mentor.
- Department: Biomedical Engineering
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Instructor:
Treena L Arinzeh
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Instructor:
Elham Azizi
h-index: 10 Info -
Instructor:
Ke Cheng
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Instructor:
Santiago Correa
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Instructor:
Tal Danino
Wikipedia h-index: 18 Info -
Instructor:
X. Edward Guo
CULPA: 2 h-index: 70 Info -
Instructor:
Henry Hess
CULPA: 1 h-index: 45 Info -
Instructor:
Clark T Hung
CULPA: 5 h-index: 65 Info -
Instructor:
Lance Kam
CULPA: 7
h-index: 38
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Instructor:
Elisa Konofagou
Wikipedia h-index: 71 Info -
Instructor:
Andrew Laine
Wikipedia h-index: 43 Info -
Instructor:
Kam W Leong
h-index: 126 Info -
Instructor:
Helen Lu
CULPA: 1 h-index: 54 Info -
Instructor:
Jose McFaline-Figueroa
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Instructor:
Grace McIlvain
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Instructor:
Barclay Morrison
CULPA: 9 h-index: 42 Info -
Instructor:
Nandan L Nerurkar
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Instructor:
Elizabeth Olson
h-index: 28 Info -
Instructor:
Nuttida Rungratsameetaweemana
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Instructor:
Paul Sajda
CULPA: 3 h-index: 47 Info -
Instructor:
Samuel Sia
CULPA: 1 h-index: 39 Info -
Instructor:
John T Vaughan
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Instructor:
Gordana Vunjak-Novakovic
Wikipedia h-index: 132 Info -
Instructor:
Qi Wang
h-index: 24 Info -
Instructor:
Megan Heenan
Info - 0 points
Sustainable Development Seminar I
This course is restricted to PhD in Sustainable Development.
- Department: PHD-SUSTAINABLE DEVELOPMENT
- M 3:10 p.m.-5 p.m.
- F 10 a.m.-11:30 a.m.
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Instructor:
Douglas V Almond
Info - 1.5 points
PRERESEARCH SEMINARS I
You may be asked to serve as research subjects in studies under direction of the faculty while enrolled in this course. Participation in voluntary.
- Department: Chemistry
- F 9:30 a.m.-11 a.m.
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Instructor:
Tomislav Rovis
Info - 1 points
SEMINARS IN CMBS I
- Department: Cellular, Molecular, and Biophysical Studies
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Instructor:
Rebecca Haeusler
Info - 1 points
SEM-THEORETICAL STATISTIC
Departmental colloquium in statistics.
- Department: Statistics
- M 4:10 p.m.-5:25 p.m.
- 3 points