NEW! Podcast show
Manifold.
I started writing this blog in 2004 (it has had millions of visitors!), and by now the content is a bit unwieldy to navigate, even with labels and search. I thought I'd make a list of some of my favorite posts and topics. Please suggest other posts to add to the list!
Pessimism of the Intellect, Optimism of the Will.
Feynman and me,
Memories of Feynman. Labels:
Feynman,
path integrals.
Richard Feynman and the 19 year old me at my Caltech graduation:
Mama said knock you out (learning how to fight).
Many Worlds and quantum mechanics,
a brief guide. Label:
Many Worlds. Note, the usual quantum probabilities
do not emerge naturally in this interpretation. See my papers
On the Origin of Probability in Quantum Mechanics and
The measure problem in no-collapse (many worlds) quantum mechanics.
Cognitive limitations:
statistics ,
higher ed. Label:
bounded rationality,
human capital.
Brainpower and globalization.
Expert predictions in soft subjects are unreliable.
Intellectual honesty.
Frauds! Label:
expert predictions.
We can (crudely)
measure cognitive ability using simple tests. (It is amazing to me that this is a controversial statement.) Randomly sampled
eminent scientists have (very) high IQs, and given the observed stability of adult IQ the causality is clear:
psychometrics works.
The cult of genius? Income, Wealth, and IQ,
One hundred thousand brains.
Bezos on the Big Brains. Label:
psychometrics.
Historically isolated groups of humans cluster genetically according to geographical ancestry. Explained in
pictures ,
words ,
more words.
I am skeptical of all but the weakest claims of
market efficiency. My
talk on the 2008 credit crisis.
Venn diagram for economics.
Careers, advice to geeks:
A tale of two geeks ,
success vs ability. Labels:
careers ,
startups ,
entrepreneurs.
Net worth ,
life satisfaction ,
happiness ,
the gilded age.
What is the likely development path for China in the next decades?
Sustainability of China growth ,
China development: how big is the middle class? ,
Back to the future ,
Shanghai from an Indian perspective.
That curious institution,
Caltech. How did a 16 year old kid from Iowa end up there? (See memories of Feynman above.)
There are
geniuses in the world.
The cult of genius.
My lovely
kids.
Photos.
Autobiographical.
Update:
Credentialism and elite careers ,
Defining merit ,
elitism ,
brainpower
Recent videos (talks on genomics):
https://www.youtube.com/results?search_query=hsu+genomics
Talks (some with slides + video):
Cold Spring Harbor Laboratory
Berkeley Innovative Genomics Institute and OpenAI
Janelia Research Campus (HHMI)
Allen Institute (Seattle) meeting on Genetics of Complex Traits
Review article:
On the genetic architecture of cognitive ability and other quantitative traits (2014)
I work on algorithms for phenotype prediction from genotype, using new methods from high dimensional statistics. My estimate is that prediction of complex traits such as height, cognitive ability, or highly polygenic disease conditions will require data sets of order one million individuals (i.e., to build a model which accounts for most of the genetic variance). Once these models are available, human reproduction (and evolution!) will be revolutionized.
These papers are somewhat technical:
https://arxiv.org/abs/1310.2264
http://arxiv.org/abs/1408.6583
This one is a bit less technical and gives a broader overview:
http://arxiv.org/abs/1408.3421
Cow genomics (an existence proof):
http://infoproc.blogspot.com/2012/08/genomic-prediction-no-bull.html
http://infoproc.blogspot.com/2014/08/its-all-in-gene-cows.html
These are for popular audiences (Nautilus Magazine):
http://nautil.us/issue/18/genius/super_intelligent-humans-are-coming
http://nautil.us/issue/28/2050/dont-worry-smart-machines-will-take-us-with-them
2018: As anticipated, we now have good height predictors thanks to the 500k genome release of UK Biobank data:
Scientists of Stature
Genomic predictors for common disease risk, constructed via machine learning on hundreds of thousands of genotypes. The predictors use anywhere from a few tens (e.g., 20 or 50) to thousands of SNPs to compute the risk PGS (Poly-Genic Score) for conditions such as diabetes, breast cancer, heart attack, and more:
Genomic Prediction of Complex Disease Risk.
The Economist on polygenic risk scores (2019).
Detailed analysis of
genetic architectures of disease risk predictors. Implications for
pleiotropy.
Sibling validation of genomic predictors.
Recent papers from my group:
https://www.genetics.org/content/210/2/477
https://www.nature.com/articles/s41598-019-51258-x
https://www.nature.com/articles/s41598-020-68881-8
https://www.nature.com/articles/s41598-020-69927-7
2021 review article, prepared for the book Genomic Prediction of Complex Traits, Springer Nature series Methods in Molecular Biology: