My academic work lies broadly in theoretical and computational biophysics, primarily focused on understanding
proteins from a dynamical and mechanistic perspective.
In layman's terms, I use computers to watch how molecules in your body (proteins) jiggle around (dynamics)
and try to learn interesting things (mechanisms) from the seemingly random
movement.
You can read more about this below or in my blog (where I
also discuss general scientific topics I find interesting).
Previously, I was in the Markland group investigating various
methods of simulating infrared spectra for condensed-phase systems (mostly water).
Before that, I worked in the Chen lab synthesizing optochemical probes
for studying zebrafish development and at Genentech.
If you'd like to get in touch, please send an email to
scguo [at] uchicago.edu.
For a more traditional synopsis of my professional experiences, you can check out my LinkedIn.
Research
Motivation
As a mentioned above, my research work tries to answer the general problem of understanding protein dynamics in
all its forms, especially to elucidate mechanisms and compute kinetics.
Of course, the real question is why do we care about protein dynamics and mechanisms at all?
Broadly speaking, traditional methods of looking at proteins (such as x-ray crystallography) can only yield
static snapshots.
Yet we can't fully understand their activity from these snapshots, just as we can't ascertain the plot of a
movie from stills alone.
To answer questions about enzymes—proteins which speed up essential reactions in your body such as metabolism—we
need to understand how the target molecule binds or unbinds to the protein and how its complex machinery
activates to catalyze the reaction of interest, all of which is necessarily a dynamic process.
On a more practical note, we hope that a deeper understanding of protein dynamics and mechanisms will allow us
to more precisely design therapeutics that do what we want.
For example, to design fast- or slow-acting therapeutic formulations of insulin, we need to know how insulin
activates from its injected formulation on short and long time-scales.
Computational methods, including machine learning, to extract kinetic and mechanistic information for
chemical
reactions from simulation data.
(How to get the most interesting things out of your [super]computer most efficiently.)
John Strahan, Spencer Guo, Chatipat Lorpaiboon, Aaron Dinner, Jonathan Weare.
(arXiv, code)
Writing
Food
I love all things food and cooking, whether it be American staples such as mashed potatoes, a classic French
bœuf bourguignon, or Shanghainese specialities ranging from drunken hairy crab to shengjianbao.
I'm a huge fan of The Food Lab, headed by the inimitable
J. Kenji López-Alt, which I credit to giving me a knowledge of the scientific principles which underlie cooking.
I maintain an occasional food blog on this website! There I discuss anything
which I find interesting and is tangentially related to food.
This writing grew out of a previous effort to document my food experiences.
Miscellaneous
Update (Dec. 2023)! Some of my favorite things from 2023. (You can find
previous years' lists here and here.)
Media
Two of my performances with the Stanford Collaborative Orchestra:
