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Sampath Kannan
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Dear friends,

I am delighted to announce that Sampath Kannan will be the next associate director of the Simons Institute. His official appointment...

Think about the last time you faced a problem you couldn’t solve. Say it was something practical, something that originally seemed small — a leaky...

Greetings from Berkeley, where we are deep into a pair of interconnected research programs on Quantum Algorithms, Complexity, and Fault Tolerance and...

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Greetings from the Simons Institute, where we are wrapping up our Spring 2023 research program on Meta-Complexity and an extended reunion of the Satisfiability program. It has been a semester full of scientific discoveries, chances to make new friends and reconnect with old ones.

In his recent Theoretically Speaking public lecture, U.S. International Mathematical Olympiad team coach Po-Shen Loh (Carnegie Mellon) spoke on educational adaptation to generative AI.

The Simons Institute’s Breakthroughs lecture series highlights major research advances in theoretical computer science, as they happen. This spring, Raghu Meka presented joint work with Zander Kelley on one of the most important open problems in additive combinatorics. 

 

The term “mechanism” or “causal mechanism” is used in two possibly conflicting ways in causal inference literature. Sometimes “causal mechanism” is used to refer to the chain of causal relations that is unleashed between some stipulated triggering event (let’s call it X) and some outcome of interest (let’s call it Y). When people use the term in this sense, they mean “a causal process through which the effect of a treatment on an outcome comes about.” One could think of this use of the term as slowing down a movie about the causal process between the moment when X is unleashed and when Y obtains so that we can see more distinct frames capturing ever-finer-grained descriptions of prior events triggering subsequent events as they unfold over time.

| Machine Learning & Data Science

By imbuing enormous vectors with semantic meaning, we can get machines to reason more abstractly — and efficiently — than before. (Quanta Magazine)

The prestigious awards recognize scholars with impressive achievements who also show exceptional promise in fields ranging from the natural sciences to the creative arts.

Theories of sequential decision-making have been around for decades but continue to flourish. The Simons Institute’s Fall 2022 program on Data-Driven Decision Processes provided an excellent overview of recent results in online learning and sequential decision-making.

Dear friends,

I hope all of you are enjoying the arrival of spring. 

| Engineering & Technology

In this episode of Polylogues, Sandy Irani sat down with theoretical computer scientist, Pixar co-founder and FOCS Proceedings cover artist Alvy Ray Smith to discuss his rich and varied career.

In his presentation at the Simons Institute, mathematician and best-selling science communicator Jordan Ellenberg (University of Wisconsin–Madison) emboldened his colleagues to practice the art of writing about science for a broad audience.