Schedule

Before class: Sign up on EdStem, complete the pre-class survey, create a slide introducing yourself on the class google-slides.

In class:

• How to read a research paper
• Practice reading (don’t read before class!): The PageRank Citation Ranking: Bringing Order to the Web

Before class:

• Review how to read a research paper

In class: practice paper-reading (don’t read before class!)

• Rx: Treating Bugs As Allergies – A Safe Method to Survive Software Failures
• The Dimpled Manifold Model of Adversarial Examples in Machine Learning

Before class: None.

In class:

• Guest: Professor Stuart Shieber
• Discussion about computational linguistics, the dissemination of research, and Professor Shieber’s professional trajectory

Before class: In this class we will discuss and practice how to update your advisor / collaborators on recent progress. Please come to class with a topic in mind – a project (e.g. current or past research project, a hobbie, etc.) that you have worked on but haven’t yet completed. The topic should be reasonably technical (your fellow classmates should only have a partial prior understanding of the topic).

In class: How to communicate about weekly progress with your collaborators

Before class: read

• Saving Science
• The Matthew Matilda Effect in Science

In class:

• Guest: Professor Sheila Jasanoff
• Discussion of the pre-class reading

Before class:

• Read: Multiagent Rollout and Policy Iteration for POMDP with Application to Multi-Robot Repair Problems

In class:

• Guest: Professor Stephanie Gil

Before class: (see John’s post on EdStem)

In class: Discussion with PhD Student-Panel – Thierry Tambe, Jennifer Shum, Samuel Hsia.

Before class: Parts 1 and 3 from How to make the most out of your PhD

In class:

• Discussion with PhD student-panel: Ike Lage, Lillian Pentecost, Zana Bucinca, and Dor Verbin
• Special note: no faculty present

Before class: read

• Smart Enough to Talk With Us? Foundations and Challenges for Dialogue Capable AI Systems. Be sure to especially focus on the last paragraph.
• Embedded EthiCS: Integrating Ethics Broadly Across Computer Science Education, and have a look at Harvard’s Embedded EthiCS website.

In class:

• Guest: Professor Barbara Grosz
• Discussion about Professor Grosz’s professional trajectory and advocay, the myth of the “lone scientist”, Embedded EthiCS.

Before class: Part 2 from How to make the most out of your PhD

In class:

• Discussion with PhD student-panel: Ike Lage, Lillian Pentecost, Daniel Alabi, and Radhika Ghosal
• Special note: no faculty present

Before class: None.

In class: Discussion about,

• What did you learn in your first semester of the PhD that you didn’t expect to learn?
• What was the most rewarding / challenging experience of the first semester?
• What do you expect of yourself, and what are your goals and hopes for the spring semester?

After class: Sign up for 1-on-1 chats with Yaniv.

Before class: read

• The Night Watch

In class:

• Guest: Professor James Mickens
• Discussion about building research skills as a new grad student, mental health, and issues faced by academics from underrepresented backgrounds.

Before class:

• From Harvard’s Report from the Task Force on Managing Student Mental Health, read:
  • Page 18
  • Pick two subsections to read from from pages 19-25 – one that feels possibly related to your experience so far, and one that feels unrelated
• Read pages 1-10 of: Dealing with Social Isolation to Minimize Doctoral Attrition – A Four Stage Framework. (Note: the words competent/incompetent in the article are technical jargon from the learning and cognition literature. As such, you should not interpret them using their colloquial meanings; we instead encourage you to think of these terms more as novice/expert).
• Answer these questions by 8pm the night before.

In class:

• Guest: Danielle Farrell, the Director of Student Services
• Special note: no faculty present
• Discussion of readings, how to support peers, how to create a web of support

Before class:

• Read:
  • Harvard Pulse Survey Executive Summary
  • Constructing Allyship and the Persistence of Inequality
• Answer these questions by 8pm the night before.

In class:

• Guest: Dr. Alexis Stokes, the Associate Chief Diversity and Inclusion Officer

Before class:

• Skim:
  • How NOT to review a paper: The tools and techniques of the adversarial reviewer
  • How to review CS papers
• By 8pm the night before, complete this assignment. The assignment requires you to read and answer questions about 2 of 3 of the following papers, assigned to you in the email (spend around one hour per paper):
  1. Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers
  2. Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  3. Simeon – Secure Federated Machine Learning Through Iterative Filtering

In class:

• Discuss how to critique a research paper.
• Simulate the paper review process.

Before class:

• Read Envisioning Systemic Effects on Persons and Society Throughout Interactive System Design (pay particular attention to sections 5–7)
• Read this interview about the concept of nudging, which will inform our first case study. Pay particular attention to this short video.
• Answer these questions by 8pm the night before.

In class:

• Guest: Dr. Trystan Goetze
• A brief introduction to Embedded EthiCS and to computer ethics generally
• An introduction to value-sensitive design
• A case study on technological nudging
• Start work on a short follow-up assignment applying value-sensitive design to a project of interest to you

After class:

• Answer these questions by midnight tomorrow.

Before class:

• Read:
  • “Appendix: Methods, Ad-hoc Ethics, and the Politics of Sexuality Studies” from Out in the Country: Youth, Media, and Queer Visibility in Rural America
  • Funding Black and Latinx community institutions is the key to vaccine equity
  • How human-centered tech can beat COVID-19 through contact tracing
  • We Need More, Not Fewer, Collaborations With Tech Companies
• Answer these questions by 8pm the night before.

In class:

• Guest: Professor Mary L. Gray

Before class:

• Review the guide about how to read a research paper.
• Spend one hour reading and trying to get as much as you can out of the paper, The Complexity of Gradient Descent: CLS = PPAD ∩ PLS. Note that the paper is far too long to read entirely in one hour; use strategies like those from the paper-reading guide to figure out where to focus your attention and try to get as much value as you can in the hour.
• Answer these questions by 8pm the night before.

In class:

• Guest: Professor Salil Vadhan
• Learn and practice how to read a theoretical CS paper

Before class:

• Watch CASA + PhD Balance: Mental Health in Academia with Fay Lin (first 36min).
• Answer these questions by 8pm the night before.

In class:

• Discussion with PhD student-panel: Daniel Alabi, Radhika Ghosal, Dor Verbin, and Eura Shin
• Special note: no faculty present

Before class: answer these questions by 8pm on the Monday before.

In class:

• Workshop on Self-organization
• Guest: Sadé Abraham

Before class:

• Watch the 3rd talk in this series as an example
• Skim these slides
• Prepare a 10min presentation as per these instructions

In class:

• Practice presenting and public speaking

Before class:

• Watch “The Pursuit of Collective Intelligence” by Professor Radhika Nagpal
• Answer these questions by 8pm the night before.

In class:

• Discussion with PhD student-panel: Lillian Pentecost, Beau Coker, Samuel Hsia
• Special note: no faculty present

Before class: Reflect on your G1 experience so far.

In class: Discussion about,

• What did you learn in your first year of the PhD that you didn’t expect to learn?
• What was the most rewarding / challenging experience of the first year?
• What do you expect of yourself, and what are your goals and hopes for your G2 year?

After class: Sign up for 1-on-1 chats with Yaniv.