🎉 We are thrilled to announce that Prof @AgnieszkaTymula @USydneyEcon was awarded an @arc_gov_au Future Fellowship 🌟 This is an incredible achievement and much deserved recognition of Agnieszka’s outstanding research & contribution to the field Congratulations Agnieszka!

EEA ESEM 2026 in Dublin was great. My field, political economy, wasn't represented by the numbers, but the talks I attended - especially by Vincent Anesi, Adam Brzezinski, Anastasia Burkovskays, and Jan Zapal - were excellent.

We're offering 2 lecturer roles (assistant prof) @USydneyEcon One is full time 3 year full time fixed term position as #macro Lecturer Closes 29 Jul👉🏼bit.ly/macro3yrlecturer Other is for an education focused Lecturer for 12 months Closes 22 July👉🏼bit.ly/1yrfixedlecturer

This is the building of @kse_ua where I teach Game Theory and Micro after yesterday's missile attack on Kyiv. It was during the night on the week-end, so thankfully no students, faculty, or staff is killed. Support KSE and its efforts to teach students and do research during the war foundation.kse.ua/en/donatio….

This is probably the best paper I have read about causal reasoning for quite some time. Really a great weekend read! "Causal Persuasion" (Burkovskaya & Starkov) models how much evidence you need to establish vs. rule out a causal link. The result is stark: To prove X causes Y: 1-2 well-chosen variables often suffice. To prove X does NOT cause Y: you must account for every possible common cause. Arbitrarily many confounders. Practically unfalsifiable. This inverts the Humean intuition: in causal reasoning, positive claims are cheap to sell and negative ones are almost impossible to rebut. Now think about what this means for Virtual Cell models. Most perturbation datasets cover a thin slice of the combinatorial space — a few hundred gene knockouts, maybe a few contexts. A model trained on that data can confidently "learn" gene X drives phenotype Y. But if the true structure is X←C→Y , and C was never systematically varied — the model will never see its own confounding. It has no mechanism to distinguish causal signal from correlated noise. The paper formalizes exactly why: the model is a sophisticated receiver that accepts whatever causal story is consistent with the data it's seen. And if the data omits the right confounders, even a "sophisticated" model is manipulable. This is the deepest argument for perturbation diversity. Not just more data, but also more axes of variation. Vary the context. Vary the genetic background. Vary the timing. You're not just collecting samples; you're systematically eliminating alternative causal explanations. This is why we need “scale” the training data with more contexts including cell types, spatial, and temporal variations. Paper: aburkovskaya.com/pdf/causali…

This is one of the best papers I've read in years, highly relevant to our troubled world, where wars of narratives are becoming more dangerous than bombs and bullets. Glad to see some of my old algorithms utilized in the service of persuasion. @burkaru. @eliasbareinboim

I took a UCLA class on causal inference taught by @yudapearl more than 10 years ago. Recently together with my co-author Egor we applied causal DAGs to persuasion. I believe it is worth a read: causality.pdf share.google/XFwcoxZMdlHmiEl…

School of Economics at USYD @USydneyEcon is on the market for a new Head of School. The deadline to apply is February 4. Position: timeshighereducation.com/uni…

Сохранил это и другие сегодняшние видео. Буду смотреть их каждый раз, когда очередная сволочь начнёт рассказывать, что народ у нас – генетические рабы, которые всегда поддерживают власть, и поэтому заслуживают всех санкций. После всего, что произошло, любые разговоры о коллективной ответственности должны прекращаться даже не начинаясь

Какая потрясающая фотография Как много она символизирует Опять реву

«Решается важный цивилизационный вопрос: тела убитых мы хороним или все-таки едим» Е. Шульман

Всех не переубивают. Россия будет свободной

SoE talk is underway with Andrew Wait @AndrewWait2006 and Anastasia @burkaru #USYDOpenDay #Economics #FASS