Readings

Last semester was full of travel but short on time. Despite having more time to read, I end up reading less. Maybe I can just blame the election. This semester is not going that great either, reading-wise.

Measuring the World (Daniel Kehlmann). This was apparently a bestseller in German-speaking countries. It’s about Gauss meeting von Humboldt, but mostly about von Humboldt. Gauss comes off as pretty cranky, but von Humboldt’s adventures have an air of the fantastical about them. I’m not sure why it was so popular in Germany, but I think those who like science and history would enjoy it.

The Fifth Season (N.K. Jemisin). Won the Hugo award, wide-ranging, multiple perspectives. A world in which seismic activity crushes civilizations regularly. Engenders a kind of cruelty and fend-for-oneselfness that seems raw but desperate. Really a great book, can’t wait to read the next.

The Social Construction of What? (Ian Hacking). A book that is not really about the “science wars” but is couched in there nonetheless. Hacking tries to taxonomize and break down what “social construction” means. I like the approach but as a “book” it kind of meanders to the end, with a chapter on child abuse more or less stapled in. He sets up the first half with a bunch of scalpels with which to dissect cases, but then doesn’t use them as clearly. I think I’m biased because I like reading math books where you get a general theorem and then a bunch of nice corollaries that recover known results or shed new light on something etc.

Too Like The Lightning (Ada Palmer) One of the best sci-fi books I’ve read in terms of Big Ideas and Lots of History. The second book in the series came out and I am going to read it soon. There’s a Crooked Timber seminar on it that I’ll read afterwards because spoilers. It’s a very difficult book to describe to others, but it’s in a very futuristic Earth with a very complex governmental system and perhaps extreme stratification into affinity groups. The latter seems “for the purposes of argument” in terms of the philosophizing. The narrator is remarkably unreliable, and the novel is written in a historical style, addressing the Reader, who sometimes themselves interjects. Read it if you like heady speculative fiction and complex worlds.

My Brilliant Friend (Elena Ferrante) This is the first of the Neapolitan Quartet novels and I found it utterly engaging. I think it’s one of those books which many of my friends who are women have read and almost none of my male friends have read, but that’s just some stupid sexism-in-publishing BS. I’m looking forward to the next three books, although I’ve heard this is the best of them. The thing to me about it is how vividly I could picture the events without Ferrante actually going through and describing the details. It somehow captures the feeling of revisiting a memory. Maybe I’m getting older. Time to start reading Proust?

 

Postdoc at ASU/Harvard on ML and Privacy

A joint postdoc position at Arizona State University and Harvard University in the area of machine learning and privacy is available immediately. The successful candidate will be working with the research groups of Prof. Lalitha Sankar and Prof. Flavio du Pin Calmon.

Specific topics of focus are the interplay of machine learning and privacy with focus on both rigorous information-theoretical results as well as practical design aspects.

The appointment will be for a period of 12 months initially, with a possibility for renewal. We are looking for strong applicants with an excellent theoretical background and a proven capacity for high-quality research in form of a strong publication record. Knowledge of privacy literature is desirable.

Interested applicants should submit a current CV, a 1-page research statement and a list of three references. Candidates should contact us via email at lsankar@asu.edu and/or flavio@seas.harvard.edu.

DIMACS Workshop on Distributed Optimization, Information Processing, and Learning

My colleague Waheed Bajwa, Alejandro Ribeiro, and Alekh Agarwal are organizing a Workshop on Distributed Optimization, Information Processing, and Learning from August 21 to August 23, 2017 at Rutgers DIMACS. The purpose of this workshop is to bring together researchers from the fields of machine learning, signal processing, and optimization for cross-pollination of ideas related to the problems of distributed optimization, information processing, and learning. All in all, we are expecting to have 20 to 26 invited talks from leading researchers working in these areas as well as around 20 contributed posters in the workshop.

Registration is open from now until August 14 — hope to see some of you there!

Register soon for the 2017 North American School of Information Theory

The site for the 2017 North American School of Information Theory is now live and registration will begin next week. The IT Schools have been going strong for the last few years and are a great resource for students, especially new students, to get some exposure to information theory research beyond their own work and what they learned in class. Most schools do not have several people working on information theory. For students at such institutions the school provides a great way to meet other new researchers in the field.