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Very happy to be here in Brooklyn
this morning with you, Ian. Ian,

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you're a partner at BCG
X. But more importantly,

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you are a compulsive computational person.

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You are one of the deep research
background person we have in

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BCG X. You've done a PhD, in
particular, physics at Oxford,

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then you did a postdoc in Riyad,

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then you joined the Harvard Med School
to do some research on proteins,

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and then you joined Anaconda
in the end. In the first place,

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why did you choose to do so much
research in your curriculum?

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Yeah, thanks Silvain. So
from a very young age,

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probably from about
seven or eight years old,

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I loved math. I loved numbers
and I also loved computers.

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I was fascinated with computers
and electronics and through high

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school and then into university and
an engineering degree at university,

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the amazing intersection of computing,

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the early days of the public internet,

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science and mathematics gave me
great opportunities to see how

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many exciting things there were
to learn about in the universe.

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And out of your years of
research, Ian, any discovery,

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insight, breakthrough experience
you'd like to share with us?

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Having done an engineering degree gave
me the opportunity to appreciate the

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value that comes from actually having
a pragmatic approach to producing

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something that is usable and
comprehensible by other people.

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And so that's a bridge that often is
missing between a lot of scientific work

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to have it be applicable.

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So what I would say is
that the biggest aha!

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for me has been in the space
of how do you take the world of

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computing and data and do something
that can really be impactful,

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impactful in the world? When I
went to Harvard Medical School,

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I had no significant background
in structural biology and protein

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science. However,

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there was an appreciation that applying
high-performance computing and data and

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analytical techniques could improve
the ability of doing protein structure

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discovery, which the last several years,

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we've seen how important it is to
understand proteins with coronavirus.

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And I was part of a leading wave of
applying high-performance computing to

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getting much higher-quality models
produced for real protein structures that

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were a biological interest.

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And in your day-to-day life, this deep
scientific background that you have, Ian,

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what difference is this
making for you in BCG X?

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When you're involved
in scientific research,

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you don't have the kind of
support infrastructure around
you that a company like

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BCG can provide to a team,

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so you have to figure out a
lot of the pieces yourself.

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You have to have the experience with the
computing systems and the security and

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the data processing and the software.

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You have to understand the
algorithms and the analysis,

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and you pretty much got to do it all on
your own or you and maybe two or three

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other people.

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And that's a really good fit for BCG
case teams and what we do for our

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clients.

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I think that it also means that
people like myself with a scientific

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background have really a rich pool of

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experience of really sustained
investigation and sustained understanding

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of a domain.

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Whether that domain is something like
in the life sciences or in engineering,

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wherever,

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that depth of experience and then
the extended period of applying that

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experience means we can then bring
that to our clients and then rapidly

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translate that to quick wins
and to high-impact projects
for our clients at BCG.

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Ian, and this has been a
fascinating conversation.

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Thank you for all the sharing.