Dean Sastry: Good afternoon, everybody.
Welcome distinguished guests, faculty, students,
friends, to this very special event -- the
sixth annual Ernest S. Kuh Distinguished Lecture.
Each year the Kuh lecture brings an outstanding
leader in technology and engineering to our
campus. Actually, starting this year, some
years we'll have two of these lectures in
a year.
Intel co-founder Andy Grove presented the
first lecture, followed by a series of eminent
leaders in engineering.
I'm delighted that we are continuing that
tradition of excellence today with our 2017
Kuh lecturer, Zexiang Li.
I'll return to tell you more about him, but
let me just tell you about the series.
The series was endowed through the generosity
of Ernie and Bettine Kuh, who have been truly
exceptional citizens of our College of Engineering
community.
A professor of EECS and a trailblazer in the
design of integrated circuits and systems,
Ernie was a former dean of our college and
a national leader in engineering education.
I am so pleased that Bettine and members of
the Kuh family, right here in the front row,
are here with us today.
Bettine, this is a wonderful annual lecture.
It's a lasting addition to Ernie's remarkable
legacy at Berkeley.
Now I'd like to invite Ted Kuh, Ernie's son,
to say a few words.
[Applause]
Ted Kuh: Thank you, Shankar. Good afternoon,
and welcome to all.
I just wanted to say a few words about my
late father and why my parents decided to
establish this distinguished lecture series.
My father was born in Beijing, and he grew
up in Shanghai, where he lived until he was
19. He came to the United States to attend
the University of Michigan to study electrical
engineering, at a time when the United States
was very welcoming of immigrants.
He then finished his graduate degree studies
at MIT, where he received his masters, and
his Ph.D. at Stanford before going to work
at Bell Laboratories.
He had a wonderful opportunity to come to
Berkeley to join the faculty here in the EECS
department, and he became part of the Cal
and Berkeley Engineering community for almost
60 years.
He enjoyed every aspect of his life here at
Berkeley, including of course the research
that he conducted in integrated circuits,
computer-aided design, working with other
distinguished faculty both here and elsewhere
in the U.S. and abroad, working with industry
leaders, and leading the department as chairman
and then the college as dean of the engineering
school.
But what he really enjoyed most was teaching
and mentoring students.
In fact, he taught about 4,000 undergraduate
students during his career, and 40 Ph.D. students,
many of whom became leaders in both academia
and industry.
In 2011, my parents decided to establish this
distinguished lecture series, really for the
benefit of the Cal community, for all that
they had received in terms of their life and
the richness within the University of California,
Berkeley, community.
But they really established it for the students.
For the students to learn from leaders, and
gain interesting and insightful perspective
and insights from leaders who talk about their
career and their endeavors.
So I would just like to quote a very famous
tennis player (which by the way was my father's
favorite sport), Arthur Ashe, who was a
world champion, but he was also an innovator,
a philosopher and a leader.
And one of his many quotes is about life,
and is something that my father lived every
day of his career.
And it says, "From what we get, we can make
a living. What we give, however, we make a
life."
My brother and I would just like to acknowledge
my mother, and we would also like to thank
the College of Engineering and Dean Sastry
for his leadership here at the school.
And I'll turn it over to Shankar to formally
introduce Dr. Li, which we are so pleased
and excited to have here. Thank you.
[Applause]
Dean Sastry: Thank you, Ted.
We are also delighted to welcome members of
our Dean's Society today. We just want to
say, your support of the college, along with
that of the Kuh family, is critical to continuing
the mission of the college, which is educating
leaders, creating knowledge, and serving society.
It's never been more important, and believe
me, we are incredibly grateful to this community
that Ted alluded to, which is helping us through
these challenging budget times.
Now, back to the lecture. This year's Kuh
lecture is co-sponsored by the Engineering
Student Council. Engineering Student Council
is the umbrella that actually oversees and
coordinates over 50 student groups, and so
it's basically THE group.
The president is, he was here, where are you?
There he is, in the back there. He's usually
in a tie and suit, but he's wearing the Berkeley
Engineering shirt.
They're sponsoring it as one of the key events
for this year's E-Week. E-Week is this week.
This is one of the big events out here, so
our thanks go to the Engineering Student Council
for having really embraced the Kuh Lecture
as part of the E-Week activities.
I also want to acknowledge and thank members
of the UAV club at Berkeley -- there they
are, that's their logo -- UAVs@Berkeley -- who
have helped with the preparations for this
lecture, and I think are also using some of
Zexiang's drones, the Phantom in particular,
down there.
Thank you all for your help, thank student
council, and UAVs@Berkeley.
Congratulations to the student groups.
[Applause]
There can be no doubt that innovation depends
on a smart, diverse and technically proficient
workforce.
How we educate that workforce, and in particular
engineers, has changed substantially from
my time as a student.
Our challenge now is to teach engineering
students how to work in interdisciplinary
teams, to iterate designs rapidly, to manufacture
sustainability, and to combine art and engineering,
and how to address global markets.
This challenge to reshape engineering education
was at the center of the discussions Paul
Jacobs, our advisory board chair, and I had
that lead to the creation of the Jacobs Institute
for Design Innovation, which just opened a
year and a half ago.
Few people have done more to help that challenge
than our Kuh lecturer, Berkeley alumnus Zexiang
Li, who I'm delighted to add, has also recently
joined the board of the Jacobs Institute.
Zexiang received his B.S. degree in electrical
engineering and economics from Carnegie Mellon
University, and his M.A. degree in mathematics
and Ph.D. degree in electrical engineering
and computer science from Berkeley.
He worked as a research scientist in the AI
Lab at MIT and as an assistant professor in
the robotics and manufacturing lab at the
Courant Institute at NYU.
He has received the National Natural Science
Award from China, the University Scholar award
from Carnegie Mellon Institute, the E.I. Jury
Award from Berkeley, and several research
initiation awards from the National Science
Foundation, to name a few of his honors.
He joined the faculty of HKUST, Hong Kong
University of Science and Technology, in 1992,
and he co-founded the automation technology
center and the robotics institute.
Before I tell you the second half of his life,
I should say that in the discussions that
Ernie had around putting together the lecture
series, he said he wanted to see people who
came who were uncompromisingly strong academics,
but also had a taste for business and the
management of technology, innovation and entrepreneurship.
This really stuck in my mind as we started
thinking about people; we consult pretty extensively
with the Kuh family as we come up with a slate
of candidates to do this.
And so, I must say that Zexiang has a remarkable
record of success as an entrepreneur.
He'll tell you how this happened from this
uncompromising commitment to academia first.
But he has now co-founded several companies.
One called Googol Technology -- Googol spelled
the "correct" way: G - O - O - G - O - L,
Googol Technology, that's the correct spelling
of 10 to the power of 100 -- which is a leading
motion-control company, a seller of robotics
solutions, in China;
Clear Water Venture Capital -- that's where
HKUST is located;
the Hong Kong X-Technology startup platform.
And I'll save the best for the last: DJI,
which is the world's largest manufacturer
of drones.
I think they sell more than, I don't think
they tell us publicly, but at least 2 million
drones a year. And the next in the business
is a few orders of magnitude less.
We are proud to claim Zexiang as one of our
own, to be the Kuh lecturer this year, and
honored to have him back at his alma mater.
Please welcome Zexiang Li.
[Applause]
Zexiang Li: Thanks, Shankar, for the introduction.
It is indeed a great pleasure to come back
and see so many familiar faces.
Shankar was my adviser, and also saw Phillip
[?}, who signed my course approval sheet when
I first landed in Berkeley. And also Prof.
Gene Wong, who was the head of the department.
And of course, lots of things, to me, my assistants,
the committee members, and the many teachers
here.
I think today I'd like to share with you lots
of the things that I was able to do were a
credit to the people in the audience, and
also from Berkeley in many, many different
ways.
I also hope that something that I'm doing
could be of some help to youngsters and the
young students of the next generation.
I think I happen to have a picture with Prof.
Ernie Kuh that was the 10th anniversary of
the Jury award, I think organized by Prof.
Gene Wong.
Ernie was there, a young Prof. Shankar Sastry
there, and Jitendra, so they all see this.
Even though I was in the systems group and
Ernie was in the microelectronics group, my
roommate was a student of Ernie's, so I heard
all the gossip of Ernie's research group.
He was also later the adviser to the department
of HKUST and also the school for engineering.
In fact, our new dean was also a Ph.D. student
from Ernie.
So you see the interaction and the connections
from Berkeley with things that I do even later,
after I graduate.
I'd like to probably share a couple of my
own experiences in connecting what I learned
in college, in graduate school, and also what
I'm able to do later on in my career.
And of course there are also struggles and
positives, and also some regrets which I'd
also like to share with you. This is a short
outline of what I'd like to highlight.
My brief review of my own education journey.
I grew up during the Cultural Revolution.
So I had basically no formal schooling until
the end of the Cultural Revolution, that was
1977, 1976.
But I was very good at memorizing things and
also taking tests.
I was fortunate to get into college, then
also come to CMU for my undergraduate study,
and after that come back to Berkeley for my
masters and Ph.D.
After a couple of years at MIT and NYU I went
back to Hong Kong and working at HKUST since
then.
I think this has been more than 38 years.
And of course I still see audience who graduate
from here 45, right? So somewhere in between.
So I'd like to highlight a few spots that
I still remember and that had impact on myself.
For my undergraduate study, I mentioned that
first exposure to more than education, but
still somewhat traditional. I'm good at taking
tests, getting good grades, but very newly
experienced at all on hands-on stuff.
Later on I got into robotics. My reason was
I took a course around 1982, but could not
understand a single thing, because I'd never
seen an industrial robot. Also I was just,
memorizing something didn't help.
Fortunately, a year later I spent a summer
internship at CMU with Marc Raibert, like
the robots. So that gave me a little bit of
help.
Over all, for my four years, I didn't find
a problem that I really wanted to work on.
That even attracted me for two years at Berkeley.
I first worked on geometric control with Shankar,
and because of a seminar by Isdori and by
Wonham, I learned some geometry.
But still I didn't really have a feel for
the problem. Other people do, but I don't.
Then Shankar wanted to start a robotics program
here in Berkeley, so asked me to help organize
a graduate seminar in robotics.
I invited a couple of people, and got interested
in multifinger hands, because I have a pair
of hands so I could see the complex relation
of the hands and how to manipulate.
To have an experimental setup is very expensive
at that time. So I have a fellow graduate
student by the name of Brad Paden. He said,
"If you don't have an experimental setup,
perhaps you can prove it."
So I learned that perhaps there is an alternative
approach besides an experimental approach,
which is just like theoretical physics vs.
experimental physics.
So then, jumping into it, I tried to learn
the tool, and thanks to the richness of resources
from Berkeley. Outside the EECS department,
there are so much in addition to that, tools
available, and I took lots of math courses.
Those probably students there, they will still
recognize those are the numbers. And they
also have wonderful graduate students over
there, and also wonderful professors. You
can walk into their door and ask questions
any time.
This I think I truly benefited from -- interactions
with fellow students, with the professors
there.
And of course I still remember that was when
Gene was the department head.
That department was organized into two major
parts: CS (but of course CS was still a small
portion) and the majority was system and microelectronics.
Those are professors that I know.
And of course system and CS had a tremendous
impact academically. But around that time
it was really the age of microelectronics.
There were both impacts academic and industry-wise.
And there were also lots of my fellow students
from microelectronics, after Ph.D., they went
on to form ventures, their own business that
I call the Ph.D.-driven startups.
I had two to three years short stay at MIT
Leg Lab under Marc Raibert was my adviser,
both at CMU and later at MIT.
After many years of being a professor at MIT,
he quit and founded Boston Dynamics. I asked
him why and he said, as an engineer, you really
need to push from basic research, applied
research to business. Even though to the day,
he still did not sell a single one, just one
robot.
I talked to him, but he had no regret that
he took the way, and the company we all know
was bought by Google, and Google probably
wants to get rid of him.
And of course Jack Schwartz used to be a mathematician,
and I know from his heart he wants to do something
real, so he established the Robotics Lab.
And also I had interaction with James Demmel,
who are back to Berkeley, and also Paul Wright,
learned a few real problems on computer-aided
inspection and also manufacturing.
So then I went back to HKUST, and these are
some of the pictures of the university -- very
beautiful.
So began to learn how to use theoretical tool
and also experimental tool. So I established
the test bed and the hand and also five-axis
machine.
And actually that project was approved by
Prof. Gene Wong -- he may not remember.
Then for my later Ph.D. students, I immediately
ask them, "You have to learn the math and
also do the experiments and use both approaches
to try to solve this problem."
After a couple of years, I think I kind of
know how research and also experiments work,
until I finally utilize the controller I built
for the hand for my first startup.
That is the first part of my story. The second
part, I still want to recall a few of the
important elements that I learned in Berkeley
that benefit for a long time many of the things
I do. That is geometric robotics.
I know that here, the robotics program is
getting much, much bigger and also much more
interesting, but I think the tools are still
more or less important.
For us, and also for people from Berkeley,
we benefit from the rich mathematical environment
and also the theoretical approach.
We use not just the traditional mathematical
tools, the Euclidean geometry, for example.
Those are the people who contribute to the
development of the tools.
Today we know that if we have a space that’s
modeled by Euclidean space, then you can use
calculus to analyze properties of your system
and those spaces.
Because all the engineering problems, through
approximation, or [??], eventually become
a function on Euclidean space. This we all
know so well.
But when robotics and many other things come
up, the underlying space is no longer flat.
So we need new tools to see and visualize
those spaces.
The masters who built the tools for non-flat
space -- Gauss, Riemann, Sophus Lie, Klein,
and Hermann Weyl. And here in Berkeley, we
see so much influence of Prof. Chern and Jerry
Marsden.
Here the engineering and the math are closely
connected; Jerry serves as the bridge, and
also a number of other professors, between
math and engineering.
And all this, Math 214 and 240, I just looked
at last night, they are still the same numbers.
And of course the use of mathematical tools
in the old days to analyze mechanisms, analyze
the problems of robotics.
If you use the traditional mathematical tools,
those are called screw theory, which I call
the classical mathematics for robotics, and
those are the developers.
And for me, I am so fortunate I'm able to
learn the modern tools. And that was introduced
in earlier days by Roger Brockett from Harvard.
Shankar brought me the Ph.D. thesis by Montana,
and also so forth.
The groups from East Coast and West Coast
not only collaborate but also compete in very
friendly manner.
Here, Shankar and many of the students, we
apply and we develop the tools to robotics,
to 3-D vision, and also to many other interesting
things.
All those I believe are in those courses.
If you take EE125, 192 and also, you will
see.
It took me a long time to see these problems.
I think the problems are really, really important.
The tools come next to it, and you have also
AI, machine learning, but the problems are
still the first-order issue.
I'd like to quickly go through some of the
problems that those tools are extremely useful.
How do you describe rigid body motion, using
those mathematical tools -- kinematics, trajectory.
I think when you take the course you are going
to see, those are fundamental for drones,
for robots, for mobile robots.
And also for interconnected rigid bodies,
such as industrial manipulators, or manipulators
under constraints. You need the right tools
for you to visualize the kinematics, the inverse,
the Jacobian, all those.
They're also for multifinger hands, which
was my favorite subject for many, many years
-- all those grasping force model, optimization,
contact modeling.
Also for parallel mechanisms, manipulators
like all those for high-speed [??] place,
and they are for variety of problems.
And they're also for biomechanical systems,
like the shoulder joint, the eyeball joint,
and all those. How do you model them, how
do you analyze them, planning control synthesis.
And also for machine design, some critical
components underlying vehicles, five-axis
machines, how do you model those extremely
important components.
And they're also for nonholonomic motion planning.
When we worked on this problem, we didn't
know today, autonomous driving has become
such a big popular subject.
Around that time, we just wanted to understand
a few things: how do you manipulate in air,
how do you understand a falling cat, how do
you understand parallel parking. Many, many
years later the theory, the formulation all
become a real practice.
Also for places I come from, probably 80%
of the world's smartphones are manufactured
there. For such high-precision gadgets, how
do you specify the tolerance, control the
tolerance, and also do inspection using automated
setups. So again they are in the same setup.
And also for workpiece localization to automate
industry production line. This today we call
Industry 4.0. So those are the issues.
And also, today you need movable arms to work
together. How do you model such kinds of systems?
And those are also problems of importance.
This is a setup where the motors for the drones
are assembled. There are lots of calibration
issues and testing issues, and using 3-D sensing,
workplace modeling, offline programming.
So I think I give you, some of the students,
if you are going to take these robotics or
related courses, those are the building blocks
for a variety of technology or robotics applications.
If you have those mathematical tools, you
will see much more clearly the fundamentals
of those problems.
I then move on to the next part.
In Hong Kong, when I joined the university,
it used to be labor-based manufacturing. There
was no need for automation, for robotics.
How do we move out from the laboratory to
build a new industry? Because we cannot wait
for something to happen. I think the best
thing is to create this industry.
One of the motion controller cards that we
built was accidentally utilized to save a
production line in China.
From that experience, we tried to ask a question:
How do we use the technology to benefit the
ordinary manufacturers? The best way is to
start up a company.
Around that time there were no policies at
all governing how do you move the IP technology
from laboratory to factory, to spin off.
We were so fortunate that Gene Wong, again,
was the VP R&D at HKUST, and Prof Pincot [?], also
used to be a professor from this department,
was the dean of engineering.
They helped to define the policy at HKUST
for technology transfer.
Today I go to many universities and places,
and no place has a policy that is so supportive
to these efforts as the policy we have in
HKUST.
Perhaps Prof. Gene Wong can tell us lots more
how he did it.
The second thing is we need a place for interacting
with the manufacturing industry in China.
HKUST, under the leadership of our first president,
Woo Chia-wei, with the Shenzen government,
established an incubation facility in Shenzen
to allow our students and faculty to work
there with the massive manufacturing industry.
Those are the elements that I needed to put
everything together into something that happens.
Today, Googol Tech is the largest motion-control
company in China. We help to build a manufacturing
equipment machinery industry in Shenzen and
across China.
Those are some of the products that we manufacture.
It's being utilized in more than 60 different
sectors, and especially as the country moves
to Industry 4.0, this provides the foundation
for it.
Through this example, I said I learned a lot:
Not just how to run a business, but how do
we prepare our students so they become very
competitive in this innovative process.
I was fortunate to teach a course -- a robot
design course. This course takes place over
a period of eight months.
The students are grouped together from different
disciplines: mechanical, electrical, computer
science, or even math department.
They work intensively together to design,
build, and also iterate faster for several
robots, to engage in the competition.
They learn all the things that a system designer
needs: project management, time management,
system, hardware, software, electronic design.
In order for them to speed up the process,
I bring the students to Shenzen, where they
can buy the components, they can make the
PCB, they can do the metal machining much,
much faster than if they do it here at the
university -- five or ten times faster.
This way allowed them to not just win the
competition, but also to understand the manufacturing
ecosystem in Shenzen.
From that project, a number of students emerged
to be entrepreneurs.
Before that, they would probably go to work
for finance, go to work for big companies,
multinational companies, and since then the
picture has been more or less changed.
Those are the students who continue on to
found their companies, including Wang Mingyu,
a kind of electrical outboards company, Wang
Tao, DJI, and also industrial robot company.
Here, a little bit sidetrack. Wang Tao asked
to do a final year project in drones, because
he loves helicopters, and to fly a helicopter
was difficult.
He said he wanted to make that process easy,
to build an autopilot.
I said, you are crazy, because in order to
do this, you need probably big lab, big budget.
Those are the people who are able to do it:
Takeo Kanade from CMU, and my professor in
Berkeley, and Vijay Kumar from UPenn. They
have big labs to do this.
I said you have only 3,000 Hong Kong dollars,
this is only $500 US; this is not possible.
But anyway, he kept on doing. After the course,
he built a very ugly autopilot for the drones.
Then he continued his masters study with me,
but just to get a little bit of stipend so
that he can continue his effort.
He set up a company called DJI, hoping to
sell a few autopilots to the hobbyists out
there.
Then the quadcopter arrives, then he switched
to quadcopter, and eventually the Phantom
that you see over there.
There was a little story behind the Phantom.
We found out lots of the autopilots were used
by DIY, who use a GoPro camera and DJI autopilots
to do aerial photography.
Then we went to Silicon Valley to talk to
GoPro, made a proposal to see if we can collaborate
with them.
GoPro finally said, "OK, fine. I love your
stuff, let's do it, and here is a proposal:
you get 30% of the profit, I get 70%," for
design, manufacture, everything; he does the
marketing.
Around that time, that was the normal. If
you look at how Apple distributes, Foxconn
being the manufacturer for Apple, only gets
2% of the profit. Giving you 30% was pretty
generous.
Then we were a little, are we going to stick
with the status quo, or are we going to do
something different?
I was fortunate to find a Berkeley alumna
who happened to have a company providing the
chipset to GoPro, but he could only give us
a low-quality chipset.
So I got other students together, and they
built the camera in three months. They learned
quickly how to design and build something
new, and then the Phantom was the story.
Today, DJI is a much bigger operation than
GoPro.
And the Phantom received the Top 3 Gadgets
of the Year from Time magazine, and also they
inspired number 2. We beat Apple in both places.
That is the story -- highly recognized as
the first high-tech product from China, which
a few years back was only recognized as a
copycat. It's changed the history of the tech
industry in China.
I'll show you a video -- not just for taking
pictures, but also applications, changing
many other industries.
[Video soundtrack] When DJIl launched the
Phantom, we changed the world.
With every generation since, we've made flying
easier, more reliable, and smarter.
Now, we are bringing this expertise to the
world of agriculture with the DJI Agras MG-1,
the first agricultural aerial platform designed
for ultimate effectiveness, industry-level
reliability and precision spraying.
One single Agras MG-1 can carry 10 kilograms
of fluid and cover and cover 10,000 square
meters on a single charge -- 40 to 60 times
faster than manual spraying.
The Agras MG-1 is dust-proof and corrosion-proof.
It's also water-resistant, so at the end of
a spray it can be rinsed clean.
Its extreme reliability is possible through
a specially designed internal cooling system.
Air enters from the front, and mist, dust
and large particles are filtered out before
reaching the motors, where heat is then dissipated
into the surrounding air.
Industry-standard ceramic nozzles come pre-installed,
and can be swapped out if necessary.
Spray quality is further enhanced with a downward-facing
radar that keeps the Agras MG-1 at exactly
the right height above the crops.
Using the Agras MG-1, modern farms can spray
faster, more accurately, and more efficiently,
bringing the DJI powered aerial revolution
to agriculture.
With the Agras MG-1, we are building the world
of tomorrow.
[End of video]
Zexiang Li: So the picture that you saw, in
the old ways, each year in China, about 20,000
farmers die from poisoning.
Now with the drones, you no longer have that
problem. And the efficiency improves by more
than 100 times.
DJI set up the example, and the first impact
was in my own lab. Now my students all group
together, try to find a problem and then work
on a problem.
The second project was a group of students
who wanted to design and build industrial
robots.
It took us a few years to understand the right
market, the right product.
Because before we started, there were already
big players in the industry, like ABB, KUKA,
Yaskawa, FANUC.
How can a 3- or 5-student team get into this
industry and compete with such bigger players?
Then we saw another industry which is called
C3: manufacturer for your smartphone, computers
and consumer products.
This industry is four times bigger than the
automotive industry, and there are no industrial
robots that are capable of solving the problem:
the precision and all those.
Foxconn employs more than a million workers
just to assemble and test the handsets.
So we are hoping to revolutionize this industry
using a new generation of robots.
This is another project team, following the
same path line: three, four students together
taking the competition project, and then final
year project they decide to build electrical
outboards for surface vehicles.
After a number of trials, they finally get
a product that match the market requirement,
and it is on the way to open out.
Those are the experiences that I had with
some of my students and post-docs.
We were fortunate enough to be able to be
next to Shenzen and Dongguan, which has a
nickname, being the Hollywood of Makers.
In the sense that you get all the suppliers
of components, all the country manufacturers,
big and small.
So you can do the design, do the prototyping,
do the scale-up just next door, at a speed
that is probably 5 to 10 times faster than
if you are doing it here.
So that is important.
We also learned that this kind of resource,
the experience that we went through, could
be beneficial to other students, not just
from Hong Kong: from China, from U.S. and
also elsewhere.
So we decided to set up a robotic incubation
facility in the heart of this region.
Any student teams, if they are interested
to pursue their idea further, they can come
to us.
We provide them some of the components, the
supply chain and also the needed funding so
that they can propagate their ideas to a final
product.
Over the last year and a half, we have taken
around 25 project teams.
Some students come in with no idea what they
are going to do, but in a year and a half,
you just are so amazed how much they're able
to progress, using mentorships, and support
of the facility over there.
Those are the different types of startup groups,
some one people, some two. In a year and a
half, they probably develop to 10, 20, 30
students.
From those lessons, I learned a lot. Now,
with all the lessons learned, come back to
see how do we redesign our curriculum for
students. This is my own challenge.
Here is a pipeline. You spend four years as
college students, probably two years masters,
Ph.D. multiple number of years, then probably
either go to work as a faculty or go to work
in a bigger company to gain some experience.
For Marc Raibert, I counted from his undergraduate
years to his first startup. It took him 23
years. For myself, it took me 21 years -- a
long journey.
And for Wang Tao, it took him six years. And
also the many student groups.
So a fundamental question is can we redefine
or redesign our engineering curriculum so
students are prepared to launch their first
tech-based startup right after graduation?
Of course, we have seen people who are capable
of doing this. Perhaps Steve Jobs, his university
did not have the right kind of program, otherwise
he probably could have stayed.
Those are examples, but I don't think at around
their time, such a program existed.
I was pretty impressed by the guy, Joi Ito,
MIT Media Lab director.
A couple years ago he made a trip to Shenzen.
He went to visit Foxconn, DJI, Huawei, and
those bigger hardware startups. He came back,
and he completely changed his principles.
He said before, Media Lab had a motto, which
is "Demo or die," in comparison with "Publish
or perish."
They have big companies, if you prove a demo,
then big companies will take it over, convert
it into product.
He found that efficiency is very low; many
things simply stayed in the lab.
The idea is that with advances in hardware
-- Moore's Law, Internet -- and the hardware,
software manufacturing tools today available,
and also customers moving from government,
defense, military to consumer, the whole picture
has been changed.
It is possible that a small group of students
could be able to move from what they are doing
in the laboratory, small hobby projects, into
product: Deploy or die.
In order to do that, you have to understand,
learn how to learn.
Also the mindset, he said, campus over maps.
In old days, you build, spend lots of time
and effort to build a map.
But nowadays, if you have a problem, you know
the objective. You just bring your smartphone
and it gives you the direction, will navigate
to your final destiny.
So a lot of things have been changed.
That is now the Lean Startup cycle, and if
you take any of the business courses here,
they will teach you how important.
You have to iterate fast, before your resources
run out.
As Shankar just mentioned, the founding principle
of the Jacobs Institute is in order for you
to do that, we have to prepare our students
to learn how to work in multidisciplinary
teams, how to iterate designs rapidly, how
to manufacture sustainably, and also combine
art with engineering, and also address global
market needs.
This is the famous Krebs Circle of Creativity:
You combine art, science, design, engineering.
But how do you combine? You have to have a
purpose. The purpose is entrepreneurship.
And the vehicle to do that are the projects
that allow you to move on, even just to understand
the scientific principles.
There are lots of efforts, examples, moving
in that direction, including our Jacobs Institute,
and also the Olin College model, which I went
to look at. Of the 24 courses you take, 20
of them are project-based.
Also I'm working with Guangdong University
of Technology to set up a robotics school
with this objective in mind.
We take students from design, mechanical,
electrical, computer science and math together.
And then across, in addition to the traditional
curriculum, which also we changed so much.
And also we introduced eight comprehensive
projects, so they work together on something
very specific.
After that they have something similar to
what Frank Wong and those kids are doing.
Those are some of the photos; I will not say
too much.
I'd finally like to conclude. No better than
the fundamental principles behind the founding
of the Jacobs Institute. This is what we tried
to get into.
From my own experiment, from my own experience,
we have first, have a problem, have a purpose.
Then form multidisciplinary, or even multi-culture
teams to work on those specific projects.
But don't stop at the projects, don't stop
with a degree. You move on from design to
deployment. That is my final lesson. Thank
you.
[Applause]
Dean Sastry: We'd like to take some questions
from the audience, and as always we give preference
to students.
A small price to pay: Tell us your name, major,
all that.
Audience question: Hi, my name is Bronston,
I'm a first-year EECS major, and my question
for you, professor, is what did you find to
be the most difficult thing in starting Googol
Technologies, as well as DJI, in terms of
the startup process itself?
Zexiang Li: I think as I have gone through,
it's the team. Because DJI took several, had
to be rebuilt a number of times, because he
didn't in the beginning have the right team
to start with.
The course, the curriculum now we are designing,
and also with Jacobs Institute, are just the
right kind of opportunity for you to build
your team in the very beginning through your
course project.
Audience question: Hi, I'm Griff (wow, that's
loud), I'm a third-year EECS major, and I
wanted to ask you what advice do you have
for people who maybe don't have a lot of experience
in that region -- southeast China, East Asia
in general -- but are interested in tech in
that region?
Zexiang Li: Now we have a team to help people
from outside Hong Kong, China, to do this.
Actually, we are working with IEEE robotics
and automation society to run a boot camp
in the summer.
Also I'm talking with the Jacobs Institute
to perhaps set up joint courses, so that our
students from China, Hong Kong, and the students
from Berkeley can have opportunities to work
together in a joint course and also explore
in both areas.
We had that last semester with National Seoul
University and also Tsinghua University with
more than 60 students.
Dean Sastry: Zexiang, this has been a fascinating
afternoon with you, as we knew it would be.
On behalf of the college, we'd like to present
you -- and this is the president of the Engineering
Student Council presenting it to you -- with
a small remembrance of today's event.
It recognizes our deep appreciation for your
commitment to engineering education. Many
thanks to you.
[Applause]
Thank you also to our co-sponsors, the Berkeley
Engineering Student Council and especially
to Ernie and Bettine Kuh for making this outstanding
forum possible.
Thank you all for being with us today, and
Go Bears!
[Applause]
