Resources

Here's a collection of resources and sites that I think are cool. These sites, books, and organizations have played no small part in shaping my scientific thinking over the years. These span computer science, physics, biology, and neuroscience, and are listed approximately in chronological order of when I came across them. The first few are things that I first encountered as a middle/high schooler, and some of the last few are things I'm currently still working through!

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  The Game of Life

  John Conway

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  Conway’s “Game of Life” is the most well-known example of “cellular automata”, where a regular grid of cells each occupy a certain “state” (in this case, a”alive” or “dead”) and transition between them according to a predetermined ruleset. In the Game of Life, a cell’s state is governed by the states of itself and its eight neighbors. Despite the simplicity and deterministic nature of the ruleset, Conway’s Game of Life can yield infinitely complex patterns and machines (it is Turing complete). It’s a far cry from what real “life” looks like, but highlights how incrdible complexity can emerge from simple building blocks.

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  Complex Systems Institute

  Unversity of Vermont

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  The Complex Systems Institute at the University of Vermont is home to an interdisciplinary collection of researchers studying a wide variety of problems in complex systems, from sociology to evolution. The Institute is close to my heart: having grown up in Vermont, I have heard many presentations from members of the Institute at various events and workshops. and also worked with Dr. Joshua Bongard during my senior year of high school. The institute’s proximity as I was growing up has undoubtedly influenced my research interests today.

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  Growing Neural Cellular Automata

  Mordvintsev et al.

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  Conway’s Game of Life is just the simplest out of many automata models of growth and development. This paper/demo, built by a team at Google and Dr. Michael Levin, is a personal favorite: it mimics regenerative processes by applying cleverly defined, neural network-based update rules to reliably produce a pattern, even upon perturbation. Those who are further interested in cellular automata should also check out Lenia, a cellular automata that is continuous rather than being discretized into individual cells.

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  iGEM

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  iGEM (International Genetically Engineered Machine) is an organization that aims to cultivate a vibrant community of synthetic biology researchers. They host an annual competition for high school and collegiate teams to conduct synthetic biology projects that address everyday issues facing the world. It’s a unique opportunity for undergraduates to take charge of their own project and to collaborate with fellow students. My own experience on Yale’s iGEM team helped me grow immensely as an independent researcher, from learning to troubleshoot experiments to dealing with failure.

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  What is Biophysics?

  Biophysical Society

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  Traditionally, “biophysics” has referred to molecular and cellular topics such as structural biology, crystallography, microscopy, and enzyme kinetics. However, today, the term applies more broadly to any application of physics to living systems, from neural network theory to self-assembling systems and active matter. Institutions sometimes separate these topics into different departments: often times, physics departments are home to topics in this broader definition while biology departments are home to the more traditional topics. Only a small number of institutions have biophysics programs that span all of these areas.

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  Nonlinear Dynamics and Chaos

  Steven Strogatz

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  I’ve been working through this introductory textbook in order to fill in some gaps in my knowledge in the field of dynamical systems. The approach offers an incredible amount of insight into a wide variety of natural and artifical systems, making it an appealing method to draw conclusions and find commonalities that span scales and systems. There is also a YouTube playlist containing recordings of Strogatz’s own lectures from his “Nonlinear Dynamics and Chaos” class at Cornell.

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  The Self-Assembling Brain

  Peter Robin Hiesinger

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  This book fills in the gaps between the seemingly disparate studies of development, evolution, neuroscience, and AI. I’ve often wondered whether trying to combine all of these in my own research would be too daunting of a task; Dr. Hiesinger, a professor at Freie Universität Berlin, effectively brings all of these topics together. Reading this book has allowed me to contextualize my own questions in the history of the field and in current research.