XY Han

@andrewgwils I wonder if this is how the "only 15 papers their whole career" old guard (from math/physics/etc) felt when folks started publishing more regularly in the 90's...

There's a new generation of empirical deep learning researchers, hacking away at whatever seems trendy, blowing with the wind... no accumulation of real understanding, or foundations. No real passion or depth, just light amusement and career advancement. I'm hoping it's a phase.

If you want PhD, sleep. If you want idea, sleep. If you want offer, sleep. If you want paper, sleep. If you want reward, sleep. If you want breakthrough, sleep. If you want collaborator, sleep. Please sleep well.

scaling law? sleeping law!🛏️😴

what if everything is just chaos

It's time we protect society from linguists. The linguistics industry is trying to foist alleged benefits of researching language on us. Language has only three use-cases: 1. Fraud 2. Plagiarism 3. Cognitive off-loading Which of these are linguist promoting?

> needs detergent > same-day delivery costs extra > prepares uber to target > realizes same-day fee < uber fee > orders delivery > is this... economics?

Yes.

Belated professional update 🔊 I’ve been promoted to Associate Professor with tenure at @JohnsHopkins @JHUBME. I’m incredibly thankful to my mentors over the past two decades, to my past and current collaborators (and friends!), and immensely proud of my students!

@Jere_je_je @JohnsHopkins @JHUBME Congrats!

Haven’t owned a desktop since 2012 (when I switched to laptops for colleges). In my mind, this is still how you turn them on.

My first AI assistants:

@miniapeur Model Theory

What is your least favourite topic in mathematics?

@miniapeur lol image if that ends up in the system prompt "If user is an idiot, DO NOT put that in the chain-of-thought."

@XYHan_ AI won’t judge me (I think?) for being stupid.

The difference between AI and human collaborators is that the AI will tolerate my repetitive, aggressive, and obsessive compulsive badgering in a way that I can't do with real people without irreparably damaging the social relationship.

The correct answer was "over $4.5B"

Not to brag but Claude thinks my questions are sharp and get to the heart of the topic

Booth MBA students 🔔 The CAAI Fellows Program is open for Spring 2026. Receive up to $1,000 to pursue AI initiatives, attend events, connect with alumni, and grow in Booth’s AI community. Apply by March 29. chicagobooth.edu/research/cente…

Reaching scientific goals: expectation vs. reality, v/Florian Aigner.

AI is getting great at math, but how good is it at solving real research problems in areas outside of those covered by Erdős problems? Towards gauging this, I have started putting together a list of unsolved research problems in mathematical statistics and machine learning, sourced from recent papers in a leading statistics journal, the Annals of Statistics (with some bonus COLT open problems: solveall.org. Currently >100 problems. In my view, much of the value of AI for researchers in the mathematical sciences stems from helping with their own research problems. These are problems without known solutions. There are many math benchmarks, but few with the following properties: (1) of a realistic research-level, so that solving them can potentially lead to a publication in a top journal (problems discussed in papers already, not contest math, not Millenium problems, not problems created for a benchmark, not problems that have a known solution); I'd say Erdős problems are the best example of this. (2) cover problems outside of the usual focus (combinatorics, number theory, ... ) of Erdős problems. Especially under-represented are domains of applied math, along with statistics, operations research, etc. I'm interested in statistics and ML, so that's where I started, but this could grow over time. Hope this can grow into something useful to the community! Happy to hear your thoughts...