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.
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.