Time: Fridays 10 AM to 12 PM
Location:
Professors
sfchang_AT_ee.columbia.edu, 212-854-6894
Office hours:
julia_AT_cs.columbia.edu, 212-939-7004
Office hours: TBA
Teaching Assistant
Rose Sloan
rsloan_AT_columbia.edu
Office hours:
Students who would like to be considered for registration for this course must attend the first lecture.
The instructors will approve registration for a selected group of students after reviewing the first class attendance and reviewing essay responses that will be written on the first day of class.
Announcements | Academic Integrity | Description
Readings | Resources | Requirements | Syllabus
This course is designed for participants in the NSF IGERT program "From Data to Solutions". Students in the seminar may be IGERT Trainees, IGERT affiliates, or other students having the permission of one of the instructors. The course will consist of a series of presentations by faculty and staff at Columbia and CUNY who will describe interesting problems involving very large amounts of data (text, audio, image, video) that require interdisciplinary collaboration with faculty and students in Computer Science, Electrical Engineering, Statistics, Psychology, Biomedical Informatics, Business and Journalism. Students taking the course will complete short reading assignments for each class, turn in 1.5-2 page reports on each of the presentations, and prepare a final longer report on one of the problems presented as a final project. Actual experimental implementations will be welcome, but not mandatory. Some proposed projects may be selected and invited to continue in the following semester or summer under the supervision of the instructors or other participating faculty or researchers from industry. There are no prerequisites for the course and no exams; students will be selected for the class based upon a questionnaire to be administered the first day of class. Note that students who are members of the IGERT: From Data to Solutions project (Trainees and Affiliates) will have preference in enrollment. This is a required course for IGERT Trainees.
Students will be expected to complete all reading assignments before the class. Students will also prepare questions for the speaker before each talk based on their readings. After the talk, each student will prepare a 1.5-2 page report, which must be submitted in CourseWorks before the following class. In the weekly report, we ask you to briefly summarize the talk and discussion, and outline an approach to one of the interdisciplinary problems described in the presentations.
There will be no midterm or final exam. Grades will be based on class participation, weekly reports, and final report.
A guide to weekly reporting can be found here.
An example can be found here.
Information on project proposals, final project reports and presentations can be found here, here and here.
A list of projects from spring 2016 can be found here.
Class participation: 20%
Weekly Reports 40%
Final Report 40%
*Absence policy: An unexcused absence will give you a zero for participation for that day. An excused absence will have no participation penalty.
Absences must be cleared with the professors in advance of the class being missed. Weekly reports are required even if you miss a class.
Copying or paraphrasing someone's work (code included), or permitting your own work to be copied or paraphrased, even if only in part, is not allowed, and will result in an automatic grade of 0 for the entire assignment or exam in which the copying or paraphrasing was done. Your grade should reflect your own work. If you believe you are going to have trouble completing an assignment, please talk to the instructor or TA in advance of the due date.
Required readings are available online from links in the syllabus below.
Excellent reports from Spring 2016:
_ Jie Yuan
|
Week |
Topic |
Reading |
Presenter |
|
Week 1 (1/19) |
Course
Introduction and Essay Assignment |
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Week 2 (1/26) |
TBA |
|
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Week 3 (2/2) |
Privacy in a Data-Driven World |
|
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Week 4 (2/9) |
The Neural Signatures of Social Relations |
|
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Week 5 (2/16) |
Using Unstructured and Social Media Data for Business Decisions |
|
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Week 6 (2/23) |
Large-scale Multimedia Content Understanding and Retrieval |
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Week 7 (3/2) |
Robust Processing of Speech in Human Auditory Cortex. |
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Week 8 (3/9) |
Detecting Algorithmic Prose in Pulp Fiction |
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Week 9 (3/23) |
Computational
Models of Understanding Language in Social Context |
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Week 10 (3/30) |
Asian
Americans in U. S. Media |
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Week 11 (4/6) |
TBA |
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Week 12 (4/13) |
Collective Intelligence and Iterative Design |
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Week 13 (4/20) |
Social Media: Identifying and Addressing Bias and Discrimination |
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Week 14 (4/27) |
Cross-cultural Deception Detection from Speech |
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