It’s not easy, figuring out the fundamental laws of physics. It’s even harder when your chosen methodology is to essentially start from scratch, positing a simple underlying system and a simple set of rules for it, and hope that everything we know about the world somehow pops out. That’s the project being undertaken by Stephen Wolfram and his collaborators, who are working with a kind of discrete system called “hypergraphs.” We talk about what the basic ideas are, why one would choose this particular angle of attack on fundamental physics, and how ideas like quantum mechanics and general relativity might emerge from this simple framework.

Listen at: www.preposterousuniverse.com

Dashun is an Associate Professor and the Founding Director of the Center for Science of Science and Innovation at Northwestern University. 

He works on the Science of Science, turning the scientific method upon ourselves, using amazing new datasets and tools from complexity sciences and artificial intelligence.

His research has been published repeatedly in journals like Nature and Science, and has been featured in virtually all major global media outlets. Dashun is a recipient of multiple awards for his research and teaching, including Young Investigator awards, Poets & Quants Best 40 Under 40 Professors, Junior Scientific Award from the Complex Systems Society, Thinkers50 Radar List, and more. 

In this wide-ranging conversation, we talk about his life, career and his new book The Science of Science.

Listen at: toolazy.buzzsprout.com

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Our planet is experiencing an accelerated process of change associated with a variety of anthropogenic phenomena. The future of this transformation is uncertain, but there is general agreement about its negative unfolding that might threaten our own survival. Furthermore, the pace of the expected changes is likely to be abrupt: catastrophic shifts might be the most likely outcome of this ongoing, apparently slow process. Although different strategies for geo-engineering the planet have been advanced, none seem likely to safely revert the large-scale problems associated to carbon dioxide accumulation or ecosystem degradation. An alternative possibility considered here is inspired in the rapidly growing potential for engineering living systems. It would involve designing synthetic organisms capable of reproducing and expanding to large geographic scales with the goal of achieving a long-term or a transient restoration of ecosystem-level homeostasis. Such a regional or even planetary-scale engineering would have to deal with the complexity of our biosphere. It will require not only a proper design of organisms but also understanding their place within ecological networks and their evolvability. This is a likely future scenario that will require integration of ideas coming from currently weakly connected domains, including synthetic biology, ecological and genome engineering, evolutionary theory, climate science, biogeography and invasion ecology, among others.

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You observe a phenomenon, and come up with an explanation for it. That’s true for scientists, but also for literally every person. (Why won’t my car start? I bet it’s out of gas.) But there are literally an infinite number of possible explanations for every phenomenon we observe. How do we invent ones we think are promising, and then decide between them once invented? Simon DeDeo (in collaboration with Zachary Wojtowicz) has proposed a way to connect explanatory values (“simplicity,” “fitting the data,” etc) to specific mathematical expressions in Bayesian reasoning. We talk about what makes explanations good, and how they can get out of control, leading to conspiracy theories or general crackpottery, from QAnon to flat earthers.

Listen at: www.preposterousuniverse.com

Today on the pod is Marta Sales-Pardo & Roger Guimera.
What a great talk. We could have gone on for hours. Peer review, power-laws, becoming scientists, Bayesian statistics, and much, much more.
Marta and Roger study fundamental problems in all areas of science including natural, social and economic sciences. They have expertise in a broad set of tools from statistical physics, network science, statistics and computer science.
Both were many years at Northwestern before starting a group at URV in Catalonia. They are authors of many classic papers in Network Science, lots of important work, e.g. on community detection. 
We talk about their paper “A Bayesian machine scientist to aid in the solution of challenging scientific problems”

Listen at: toolazy.buzzsprout.com