Course Information
MW 3:30-4:20pm, starting 10/17/2018
LWSN B155
Instructor:
Kihong Park
park@cs.purdue.edu
494-7821
office hours by appointment (LWSN 1211)
Course Policy:
Doctoral students are required to take this 1 credit course in their first year. It is intended to introduce research of CS faculty and disseminate issues relevant to conducting research in academia and industry. The latter includes adhering to strict standards of ethics and integrity.
Grading is pass/fail and based on attendance. Students are required to attend all lectures. In cases where attendance is infeasible, prior approval must be requested by contacting the instructor (email to park@cs.purdue.edu) at least a week in advance stating the reason. If an exception is granted, the student will be assigned a paper to read and asked to submit a 2-page report (11pt, single-spaced, pdf) within 10 days of the missed lecture. Missing a lecture without prior approval will result in fail except for health and family emergencies. Missing more than two lectures, even with approval, will require retaking the course.
As part of the graduate program's ethics requirement, students must pass an on-line test administered by the CITI Program. Please wait until after the "Ethics and Integrity" lecture scheduled on 11/26/2018 to take the test. Additional details will be provided then.
Instructions for taking the online test is available at
https://www.cs.purdue.edu/graduate/curriculum/doctoral.html
under "Ethics Training".
Schedule
- 10/17, K. Park, Introduction
- 10/22, D. Comer, Research Careers in Academia and Industry
- 10/24, H. Wang, Mobile Sensing Systems
- 10/29, D. Kihara, Protein 3D Structure Modeling from Low-resolution Image Data (to access the presentation slides, send email to park@cs.purdue.edu)
-
10/31, V. Popescu, How to Write a CS Paper
(pdf)
- 11/05, P. Fonseca, Building Reliable Software Systems
- 11/07, M. Yin, Peeking into the On-Demand Economy: A Computer Science Perspective
- 11/12, A. Kate, Security and Privacy Research at Purdue
- 11/14, J. Honorio, Learning Linear Structural Equation Models in Polynomial Time and Sample Complexity
- 11/19, Y. Xue, Combining Reasoning and Learning for Data Science and Decision Making: Integrating Concepts from AI, Sustainability, and Scientific Discovery
- 11/21, no class
- 11/26, E. Spafford, Ethics and Integrity (video)
- 11/28, C. Peng, AIM: Amplifying Intelligence in Mobile Networks
- 12/03, K. Park, Research Contributions of Computer Science with Wider Impact on the Sciences
- 12/05, B. Ribeiro, Learnable Pooling Layers for Deep Neural Networks