Over the years of teaching and research, I have gradually standardized the notation that I use for describing the math of recommender systems. This is the notation that I use in my classes, Joe Konstan and I have adopted for our MOOC, and that I use in most of my research papers. (And thanks to Joe for helping revise it to its current form.)

If you haven’t already settled on a notation, perhaps you would consider adopting this one. I also welcome feedback on improving it.

Fabric posters are great. You don’t need a clumsy poster tube, just fold it up and put it in your suitcase.

We use Spoonflower for ours, and there are even instructions. But there are a few details that take some extra work to get right; I hope that this will guide you through them.

I have also made a video of the process, which you can view on YouTube.

The very short version, so you have an idea of where we’re going:

As you’re hopefully well aware if you follow my Twitter, the end of this month will bring the first Conference on Fairness, Accountability, and Transparency (FAT*). It’s been an honor to be involved in some of the planning for this conference series; it is also a great honor to have two papers in the first edition. Algorithmic fairness is the main focus of my research agenda for the next several years.

Last year, I wrote up the software and hardware tools I use. I am still using a lot of that stack, so I thought this year I would just highlight the changes:

2017 is almost over! What’s happened?

Quite a few things. Surviving the year feels like an accomplishment, for a bunch of reasons. And I have by no means experienced the worst of it.

But in the spirit of last year, here’s a rundown of 2017’s win list:

• Had 2 papers (one full, one short) accepted & published at FLAIRS. I believe this is the first time that I have succeeded in publishing papers with all necessary reproducer scripts in a usable package.

• Reviewed a lot of papers again. Cut back slightly on that this year, and will be cutting back some more for 2018.

• Adopted two rabbits, Nyssa and Adric, from the Idaho Humane Society. They have been an incredible amount of fun to have around.

• Built a platform bed frame, and then learned it was a terrible idea. Learned how to work with pocket-hole screws, though.

• Served on the Ph.D committee of Felix Sommer, who successfully defended in October.

• Submitted a full and a short paper to RecSys, both of which were rejected.

• Took a 2-week trip through Belgium and the Netherlands, meeting with colleagues and giving talks on recommender ethics and my overall research.

• Traveled back to the Midwest with Jennifer to see our families in the summer.

• Organized the first workshop on fair recommendation.

• Accepted an invitation to join the inaugural steering committee of the Conference on Fairness, Accountability, and Transparency (FAT*).

• Secured a venue, organizing committee, and other preparatory things to announce RecSys 2018 in Vancouver, BC; co-chairing that is the major service responsibility from last year’s list.

• Attended my first meeting as a member of the RecSys Steering Committee.

• Published the first collaborative work with Sole Pera & the PIReTs, first as a poster at RecSys and then as a full paper to appear in FAT*. These are also the first publications to come out of my new research agenda on algorithmic fairness in recommender systems.

• Wrote a position paper on fairness and privacy with another colleague, Hoda Mehrpouyan, and her student that has been accepted for FAT*.

• Published a position paper on evaluating recommender systems for children at KidRec.

• Finished rebuilding the Recommender Systems MOOC.

• Created a new graduate-level Introduction to Data Science class. Its first offering was rough, but I’ve learned a lot about how to make it work better next time.

• Participated in the Dagstuhl Perspectives workshop on performance prediction for IR, NLP, and recommender systems.

• Submitted 2 NSF grants as PI (including a credible attempt at CAREER), 1 NSF grant as a major collaborator, another as a minor collaborator, 2 private-sector grants (1 as lead, 1 as co-PI), and an internal proposal.

• Won the first competitive research funding for PIReT research, an internal seed grant from the College of Education. Katherine Wright in education led the proposal, and it will fund a collaboration with her, Sole Pera, and myself.

• Arranged 4 research seminars for our department & Ph.D program.