Spring 2019: Security and Fairness of Deep Learning (18-739)


Professor: Anupam Datta
Office: B23 221, CMU @Silicon Valley
Office Hours:
@PGH Thursdays 12-1pm PCT, on Google Hangout (details on Piazza, TBA).
@SV Thursdays 12-1pm PCT, in B23 221

Teaching Assistant: Klas Leino
Office Hours:
@PGH Mondays 3-4pm EST, in GHC 7004
@SV Mondays 1-2pm PCT, on Google Hangout (details on Piazza, TBA)
Teaching Assistant: Caleb Lu(Andrew ID: kaijil)
Office Hours:
@PGH Wednesdays 12:00-1:00pm EST, in CIC 2131G
@SV Wednesdays 10:00am-11am PCT, on Google Hangout (details on Piazza, TBA)

Course Information

Location: HH1107, CMU @Pittsburgh
Lectures: Tuesday and Thursday, 1:30pm - 2:50pm Eastern

Location: B23 211, CMU @Silicon Valley
Lectures: Tuesday and Thursday, 10:30am - 11:50am Pacific

Course Description

This course will provide an introduction to deep learning methods with emphasis on understanding and improving their security, privacy, and fairness properties. The course will cover basics of machine learning and introduce popular deep learning methods. It will delve into applications of deep learning methods in security, their susceptibility to adversarial manipulation, and techniques for making deep learning robust to adversarial manipulation. It will cover state-of-the-art methods for explaining black-box deep learning models to enhance their transparency. It will also examine methods for deep learning that are designed to respect individual privacy and fairness. Students will do homework assignments and critique weekly readings. Prior knowledge of machine learning, deep learning, and security concepts are useful but not required.



  • Piazza for questions and discussions related to the class: Please mail TA (andrew id:kleino) if you have any issues
  • Canvas for coursework submission, grades, and ppt versions of the lecture notes


Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. Deep Learning. MIT press, 2016.


  • 5 Homeworks 90%
  • Class Participation 10%

Total of 8 late days can be used throughout the semester. No more than 3 late days may be used on a single assignment.


About wellness

Take care of yourself. Do your best to maintain a healthy lifestyle this semester by eating well, exercising, avoiding drugs and alcohol, getting enough sleep and taking some time to relax. This will help you achieve your goals and cope with stress.

All of us benefit from support during times of struggle. You are not alone. There are many helpful resources available on campus and an important part of the college experience is learning how to ask for help. Asking for support sooner rather than later is often helpful.

If you or anyone you know experiences any academic stress, difficult life events, or feelings like anxiety or depression, we strongly encourage you to seek support. Consider reaching out to a friend, faculty or family member you trust for help getting connected to the support that can help.

If you or someone you know is feeling suicidal or in danger of self-harm, call someone immediately, day or night:

If the situation is life threatening, call the police:

  • On campus: Dial CMU Police at 412-268-2323
  • Off campus: Dial 911

If you have questions about this or your coursework, please let us know.