I get out of bed for two reasons.

One, small-scale family farmers
need more food.

It's crazy that in 2019
farmers that feed us are hungry.

And two, science needs to be
more diverse and inclusive.

If we're going to solve
the toughest challenges on the planet,

like food insecurity for the millions
living in extreme poverty,

it's going to take all of us.

I want to use the latest technology

with the most diverse
and inclusive teams on the planet

to help farmers have more food.

I'm a computational biologist.

I know -- what is that
and how is it going to help end hunger?

Basically, I like computers and biology

and somehow,
putting that together is a job.

(Laughter)

I don't have a story

of wanting to be a biologist
from a young age.

The truth is, I played
basketball in college.

And part of my financial aid package
was I needed a work-study job.

So one random day,

I wandered to the nearest building
to my dorm room.

And it just so happens
it was the biology building.

I went inside and looked at the job board.

Yes, this is pre-the internet.

And I saw a 3x5 card

advertizing a job
to work in the herbarium.

I quickly took down the number,

because it said "flexible hours,"

and I needed that to work around
my basketball schedule.

I ran to the library
to figure out what an herbarium was.

(Laughter)

And it turns out

an herbarium is where they store
dead, dried plants.

I was lucky to land the job.

So my first scientific job

was gluing dead plants onto paper
for hours on end.

(Laughter)

It's so glamorous.

This is how I became
a computational biologist.

During that time,

genomics and computing were coming of age.

And I went on to do my masters

combining biology and computers.

During that time,

I worked at Los Alamos National Lab

in the theoretical biology
and biophysics group.

And it was there I had my first encounter
with the supercomputer,

and my mind was blown.

With the power of supercomputing,

which is basically thousands
of connected PCs on steroids,

we were able to uncover the complexities
of influenza and hepatitis C.

And it was during this time
that I saw the power

of using computers
and biology combined, for humanity.

And I wanted this to be my career path.

So, since 1999,

I've spent the majority
of my scientific career

in very high-tech labs,

surrounded by really expensive equipment.

So many ask me

how and why do I work
for farmers in Africa.

Well, because of my computing skills,

in 2013, a team of East African scientists

asked me to join the team
in the plight to save cassava.

Cassava is a plant whose leaves and roots
feed 800 million people globally.

And 500 million in East Africa.

So that's nearly a billion people

relying on this plant
for their daily calories.

If a small-scale family farmer
has enough cassava,

she can feed her family

and she can sell it at the market
for important things like school fees,

medical expenses and savings.

But cassava is under attack in Africa.

Whiteflies and viruses
are devastating cassava.

Whiteflies are tiny insects

that feed on the leaves
of over 600 plants.

They are bad news.

There are many species;

they become pesticide resistant;

and they transmit hundreds
of plant viruses

that cause cassava brown streak disease

and cassava mosaic disease.

This completely kills the plant.

And if there's no cassava,

there's no food or income
for millions of people.

It took me one trip to Tanzania

to realize that these women
need some help.

These amazing, strong,
small-scale family farmers,

the majority women,

are doing it rough.

They don't have enough food
to feed their families,

and it's a real crisis.

What happens is

they go out and plant fields of cassava
when the rains come.

Nine months later,

there's nothing, because of these
pests and pathogens.

And I thought to myself,

how in the world can farmers be hungry?

So I decided to spend
some time on the ground

with the farmers and the scientists

to see if I had any skills
that could be helpful.

The situation on the ground is shocking.

The whiteflies have destroyed the leaves
that are eaten for protein,

and the viruses have destroyed the roots
that are eaten for starch.

An entire growing season will pass,

and the farmer will lose
an entire year of income and food,

and the family will suffer
a long hunger season.

This is completely preventable.

If the farmer knew

what variety of cassava
to plant in her field,

that was resistant
to those viruses and pathogens,

they would have more food.

We have all the technology we need,

but the knowledge and the resources

are not equally distributed
around the globe.

So what I mean specifically is,

the older genomic technologies

that have been required
to uncover the complexities

in these pests and pathogens --

these technologies were not made
for sub-Saharan Africa.

They cost upwards of a million dollars;

they require constant power

and specialized human capacity.

These machines are few
and far between on the continent,

which is leaving many scientists
battling on the front lines no choice

but to send the samples overseas.

And when you send the samples overseas,

samples degrade, it costs a lot of money,

and trying to get the data back
over weak internet

is nearly impossible.

So sometimes it can take six months
to get the results back to the farmer.

And by then, it's too late.

The crop is already gone,

which results in further poverty
and more hunger.

We knew we could fix this.

In 2017,

we had heard of this handheld,
portable DNA sequencer

called an Oxford Nanopore MinION.

This was being used
in West Africa to fight Ebola.

So we thought:

Why can't we use this
in East Africa to help farmers?

So, what we did was we set out to do that.

At the time, the technology was very new,

and many doubted we could
replicate this on the farm.

When we set out to do this,

one of our "collaborators" in the UK

told us that we would never
get that to work in East Africa,

let alone on the farm.

So we accepted the challenge.

This person even went so far as to bet us
two of the best bottles of champagne

that we would never get that to work.

Two words:

pay up.

(Laughter)

(Applause)

Pay up, because we did it.

We took the entire high-tech molecular lab

to the farmers of Tanzania,
Kenya and Uganda,

and we called it Tree Lab.

So what did we do?

Well, first of all,
we gave ourselves a team name --

it's called the Cassava Virus
Action Project.

We made a website,

we gathered support from the genomics
and computing communities,

and away we went to the farmers.

Everything that we need for our Tree Lab

is being carried by the team here.

All of the molecular and computational
requirements needed

to diagnose sick plants is there.

And it's actually all
on this stage here as well.

We figured if we could get the data
closer to the problem,

and closer to the farmer,

the quicker we could tell her
what was wrong with her plant.

And not only tell her what was wrong --

give her the solution.

And the solution is,

burn the field and plant varieties

that are resistant to the pests
and pathogens she has in her field.

So the first thing that we did
was we had to do a DNA extraction.

And we used this machine here.

It's called a PDQeX,

which stands for
"Pretty Damn Quick Extraction."

(Laughter)

I know.

My friend Joe is really cool.

One of the biggest challenges
in doing a DNA extraction

is it usually requires
very expensive equipment,

and takes hours.

But with this machine,

we've been able to do it in 20 minutes,

at a fraction of the cost.

And this runs off of a motorcycle battery.

From there, we take the DNA extraction
and prepare it into a library,

getting it ready to load on

to this portable, handheld
genomic sequencer,

which is here,

and then we plug this
into a minisupercomputer,

which is called a MinIT.

And both of these things are plugged
into a portable battery pack.

So we were able to eliminate

the requirements
of main power and internet,

which are two very limiting factors
on a small-scale family farm.

Analyzing the data quickly
can also be a problem.

But this is where me being
a computational biologist came in handy.

All that gluing of dead plants,

and all that measuring,

and all that computing

finally came in handy
in a real-world, real-time way.

I was able to make customized databases

and we were able to give the farmers
results in three hours

versus six months.

(Applause)

The farmers were overjoyed.

So how do we know
that we're having impact?

Nine moths after our Tree Lab,

Asha went from having
zero tons per hectare

to 40 tons per hectare.

She had enough to feed her family

and she was selling it at the market,

and she's now building a house
for her family.

Yeah, so cool.

(Applause)

So how do we scale Tree Lab?

The thing is,

farmers are scaled already in Africa.

These women work in farmer groups,

so helping Asha actually helped
3,000 people in her village,

because she shared the results
and also the solution.

I remember every single
farmer I've ever met.

Their pain and their joy

is engraved in my memories.

Our science is for them.

Tree Lab is our best attempt
to help them become more food secure.

I never dreamt

that the best science
I would ever do in my life

would be on that blanket in East Africa,

with the highest-tech genomic gadgets.

But our team did dream

that we could give farmers answers
in three hours versus six months,

and then we did it.

Because that's the power
of diversity and inclusion in science.

Thank you.

(Applause)

(Cheers)