Manoj Leelanivas, COO, Juniper Networks

Guiding a New Generation of Talent

Be BoldLeadership Voices Manoj Leelanivas
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This is episode four of the Be Bold podcast with Juniper Networks COO Manoj Leelanivas. In this episode, he interviews Sunil Kumar, Provost and SVP of Johns Hopkins University. This podcast interview focuses on Sunil Kumar's career and experiences as an educator.

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You’ll learn

  • The journey that led Sunil to John Hopkins University

  • How students have evolved 

Who is this for?

Business Leaders Network Professionals


Manoj Leelanivas Headshot
Manoj Leelanivas
COO, Juniper Networks

Guest speakers

Sunil Kumar
Provost & SVP, John Hopkins University


0:00 in terms of not just how prepared they are but simply the breadth so our the

0:06 diversity in our classes especially undergraduate classes is substantially higher than it was 20

0:13 years ago when I started teaching for example Hopkins last year was almost 50 50 in Engineering in between men and

0:21 women so it was I think 49.4 percent women and so so this is an example which was

0:29 is quite different from when I was and it's a change for the better

0:34 [Music] hello everyone and welcome to another

0:42 episode of the b-ball podcast remember to like And subscribe to our

0:48 podcast on Spotify Apple music and other major platforms

0:53 in this episode Our Guest is Sunil Kumar currently Provost and Senior vice president for academic Affairs at John

1:00 Hopkins University and in July he will become the next president of Tufts University

1:07 Sunil has a very distinguished academic career starting with Stanford University as a professor in The Graduate School of

1:15 Business after spending about a dozen years there he was named the dean of the University

1:21 of Chicago Booth School of Business most recently in 2016 he became the

1:27 Provost and Senior vice president at John Hopkins Sunil really loves what he does

1:35 during his recent appointment to become the next president of Tufts he said I never lost that kind of awe and wonder

1:43 about the academic Enterprise and I'm happiest in it

1:49 in today's conversation we will learn about sunil's Journey from his early days in India to eventually making his

1:56 way to the United States where he received a PhD in electrical engineering at the University of Illinois ravana

2:02 champion he'll also ask about his work with today's young people and how he can

2:08 how we all can Inspire more of them to pursue career in stem fields

2:15 hi Sunil it's an absolute pleasure to have you join us today you and I went to school together and

2:22 have known each of the four 30 plus years I still remember both of us starting on

2:28 the semester project two weeks before it's due in our final year if I remember it correctly not our

2:35 brightest moment eh but from what I can tell you have not done too shovel in your career Sunil neither have you and

2:43 uh for the congratulations on your position at Juniper and thank you for

2:49 inviting me and funnily enough that project if you remember was uh trying to

2:55 do make the PC act as a kind of dynamic

3:01 controller in the Dos days it was impossible to do multitasking and we

3:06 managed to get our PC to do it us and it and funnily enough I've stayed in

3:12 control theory and controls the rest of my life that is I still work on problems similar

3:18 to the one we did in our final project it's delightful to hear that I'm gonna you know pick up on that a little bit

3:25 later from now but let's just get the audience to kind of familiarize with you and your academic Journey you know what

3:32 kept you motivated to continue a trajectory and eventually earn a PhD

3:38 right I think that would be great for the audience to hear that so let's just start there yeah so

3:44 um so for me uh I didn't have a particular view that I would get a PhD I

3:51 actually had a very good job coming out of the National Institute of Technology that you and I went to uh I was I had a

3:59 job with the tatas in Pune and which is a large Indian conglomerate and and I I

4:08 didn't want to do that job because they said I had to start as a night shift

4:13 supervisor at a truck manufacturing plant and I didn't want to be night shift

4:18 supervisor and and so I wrote The Graduate exam and and got into the

4:26 Indian Institute of science and uh and um and and that's where I realized

4:34 um I understood for the first time what high-end academic research looks like

4:39 and realized that's what I wanted to do so so the year my two years at iic were

4:45 the ones that kind of transformed my aspiration yeah it's great to hear that if I remember

4:51 correctly in your school days itself you were a ham Enthusiast you were into things which were engineering oriented

4:58 and then you went to ISC you know you mentioned you know your

5:04 uh your career in iic in in actually spending time there as well as

5:09 eventually you know graduating with a computer science and automation degree in ISC if I'm not mistaken

5:16 all through this like you know what drove your interest and passion about Engineering in engineering right from

5:22 the start yeah so I I you know the the basic hubris if you will of engineering is

5:29 that that will simply fix it uh that we

5:34 Engineers would simply find solutions to problems and that is always appeal to me

5:42 um I'm not particularly handy with my hands so even when I was a ham radio

5:48 Enthusiast somebody else would build my equipment for me I I didn't build them myself and uh and so but it that's why

5:56 when I realized that I could use math to find solutions to problems that was

6:02 the kind of uh point where I realized finally I have something which I'm both good at and like otherwise things I

6:09 liked I was not necessarily good at and things I was good at I didn't necessarily like so this was the one thing that check both boxes

6:17 great we talked about math you know one of the things India is especially known

6:23 for is it's producing so much talent specializing in stem computer science and engineering as an educator yourself

6:30 and an academic leader now what can the world and specifically the United States

6:35 of America learn from India about inspiring young people to pursue careers in stem

6:40 yeah so I think one of the things that's uh really

6:46 um great about Indian Society is at the in the family you know studying is

6:52 emphasized and and and stem

6:58 is emphasized in as much as the government had invested in very high-end

7:05 institutes like the ones we went to in the stem fields which was seen as necessary for the country's progress and

7:12 indeed has contributed to the country's progress and so uh so I think a

7:17 combination of commitment by local and federal governments to education and and

7:25 investment in it combined with a kind of culture shift or

7:31 at least a a a a an emphasis on education in general so I don't

7:37 particularly see stem as somehow Superior or diff better than

7:43 social sciences or the humanities but education in general I think is uh you

7:50 know is a lesson that is worth learning I think makes a lot of sense I think it's

7:55 emphasized to the Grassroots level much more than in the US and that's something which we can actually learn in this

8:01 country also let's fast forward a little bit right you know you come come over to the United States in the 90s you join

8:07 your doctoral program at up in a champagne you receive a PhD and eventually you start a teaching position

8:14 at Graduate School of Business and right in the heart of Silicon Valley if I'm not really stable

8:20 so you could have easily joined a leading technology company in those days you know what kept you in Academia what

8:27 is the burning passion and desire that kept you in Academia so uh well I I'd say it's three things

8:33 first and foremost um uh you know I you get you get the

8:41 freedom to follow your nose in Academia in a way that it's very hard

8:47 to duplicate elsewhere it would be very efficient for Juniper as a company if

8:52 everybody wanted to do their own thing um universities are not designed for efficiency so the you know people do

8:59 their own thing and that's seen as a and for me that is extremely appealing the second is and I think this is the

9:06 part that appears to be the most about a university is that almost nobody else is like you

9:12 almost nobody else is working on a problem similar to what you're working on

9:17 um there are team-based uh you know projects of course especially in the Sciences large teams and they're

9:23 essential for making progress on those problems but their members of the team bring very different skills to the team

9:30 and so on so this kind of having people who are very different from you doing very cool things that are

9:37 very different from what you're doing is another very appealing feature of Academia and so those two things so

9:45 um yeah makes a lot of sense you know the breadth the diversity and it's not like

9:52 a homogeneity in like in one particular area so that that is very appealing in the Academia but I'm going to kind of

9:58 drill down a little bit more here right because for most folks in Academia being a professor an associate Dean at

10:04 Stanford is kind of the Pinnacle of their carriers right now kind of wow this is this is the achievement I want it to be you did not stop there next

10:12 thing I know you're a Dean at school you know Chicago School boot School of Business

10:17 what made you pursue a different Journey you know going into this administrative world something broader than actually

10:22 just teaching yeah so you know as an academic I was doing okay uh you know I my work was

10:30 getting published my students were getting very good jobs uh I was editing it you know a journal

10:37 top journal in my field so I could have kept doing what I was doing uh but but

10:43 it was clear that um and this again like most things in my life

10:48 happened partly by Serendipity I happened to serve on a committee at Stanford

10:54 which looked at the MBA Core Curriculum and proposed some radical changes some of which have even stuck

11:01 and uh and um and while in that process I realized that I was actually

11:08 good at helping people who were way better than me get even better

11:15 um and so that's what drove me to this that I could have a much greater impact

11:20 on institutions and by making people who were significantly

11:25 more talented than me uh be even better at whatever it is that

11:31 they wanted to do so I see myself as a as a taxi driver almost uh I don't necessarily want to tell

11:38 people where to go but I do want to help them get there and so for me therefore the academic

11:45 Administration leadership is something that appeals to them yeah so that's what made them made me

11:52 take that opportunity and of course great school and great opportunity

11:58 relatively early in my career so that was the other kicker okay

12:03 I totally get the appeal of the force multiplier right because you're not just doing one thing based on your 24 7

12:10 you're able to influence a broader set of people to move in a direction which is good for the you know institutional

12:16 as well as the country so I do get the appeal completely makes a lot of sense

12:21 specifically let's just jump into teaching and kids you know kids to students in general

12:27 it all starts with you know who you're teaching at the end of the day right as you progress in your career work with

12:32 students all along the way what has struck you about how students have evolved over a period of time a student

12:39 in the early 2000s is probably very different from a student today uh has you know academic institutions

12:46 really evolved to better cultivate talent in this changing you know Dynamics

12:51 um and has your own approach to teaching changed over the years teaching or Administration in General changed over

12:57 the years yeah I um I'll answer that in two parts

13:04 um I think the institutions have changed um in many respects and and have changed

13:11 Less in other respects so uh we have changed a great deal

13:18 um in who we teach uh in terms of not just how prepared they are or but simply

13:26 the breadth so our the diversity in our classes especially undergraduate classes

13:31 is substantially higher than it was 20 years ago when I started teaching for example Hopkins last year was almost 50

13:38 50 in Engineering in between men and women so it was I think 49.4 women

13:46 and so so this is an example which was is quite different from when I was and

13:52 it's a change for the better the other way in which especially the so-called need blind or the institutions that need

13:59 meet full Financial need do is they've improve the economic diversity of

14:07 uh the classes significantly as well so our student bodies have evolved uh and

14:13 they've evolved by becoming just more interesting for me as a professor they come from much more different backgrounds they bring much more

14:20 different perspectives so in many many ways they're just it just feels better uh as a student body the professor yet

14:28 evolved slower it has changed less so but it is changing it is getting better

14:34 what has not changed as much is what we teach and some of it shouldn't change I don't

14:41 think uh you know thermodynamics is completely different because the students are different

14:47 but I think we over emphasize uh a lot of information transfer which in today's

14:55 world is perhaps less important than teaching people to think critically

15:00 do analysis to synthesize create

15:05 to dream and I think that's the part that in a curricular getting better at

15:11 it but it's the change is slow and if you ask me as a professor

15:16 um you know if I taught a class today versus my first year as

15:22 a assistant professor at Stanford my first year I would be worried about

15:29 um making sure that you know

15:36 everybody learned the stuff I had to teach them that they could do is a problem set

15:42 um today I'd be more worried about whether I have taught them to learn all the things that will change in my field the

15:49 stuff I taught you know 25 years ago a lot of it has changed completely you

15:56 you wouldn't be doing those things the way I used to teach you should do them right so

16:03 yeah what I'm you know if I synthesize what you say it said just now I think the most important thing is you know

16:09 really teaching the young minds to think and evolve as

16:15 as things around them evolve right the ability to think and shape rather than like think you know focus on a

16:21 particular thing the ability to think and create a frame and improve upon what they're doing uh is very well said

16:28 especially in this current changing environment where almost everything is changing from geopolitical stuff to you

16:34 know you know everything else so it's very good to hear that actually I also wanted

16:40 to touch a point right since you were very clear about what you wanted to do

16:45 when you wanted to start when you started teaching and then over a period of time you said okay things have

16:50 changed the goal post has changed a little bit in terms of what I need to emphasize were there any mentors you had

16:56 in your career who kind of really helped you you know sharing some you know inside

17:03 support say like you know maybe you can share some insights about special mentors you had along the way and have you know has there been some of

17:11 these mentors along the way and can you share some of the sage advice you've got from those yeah I I've had several

17:18 um you know I've been very lucky to have several very good mentors uh the person who stands out is a guy

17:26 called Mike Harrison at Stanford who was my senior colleague for almost 15 years

17:32 and and if you think about what's the hardest thing for a person to pick up on

17:37 their own it is uh the ability to place their work

17:44 in the context of others and to figure out what it is that they are capable of doing

17:49 because you do something like I'll think of our final project right we told our

17:54 advisor that we'd get this to work and we got it to work everybody was happy I think we got good

18:00 grades I'm not I can't remember my grade from that project uh but

18:06 we didn't ask ourselves why did we stop here what else could we have done

18:15 um and so this kind of getting calibrated on aspiration and to kind of

18:21 learn to push to say this is not where we stop we got to do more that you

18:27 learned from a mentor and especially in Academia where since you have so much Freedom you

18:35 can stop on a project whenever you want and say this is as far as I'm willing to go

18:40 because I can get three quarters of the credit for two-thirds of the work and yet you if you haven't fully

18:47 understood what you did in some sense you're not being true to your academic roots and so then you're going to spend

18:54 the remaining two one third of the time to just understand the remaining one quarter of the problem that you didn't

19:00 understand when it began but it's worth it and that's something that a mentor needs to teach you by both by example

19:07 but also pointing out what other people are doing and so this notion of when not to stop

19:13 and how to decide what to Aspire for is what I think I picked up the most from my mentors

19:19 very well said you know it really is about broadening The Horizon right you're not stopping at any point you're

19:25 the ability to look at you know something beyond that and you know kind of aspire to you know even goals you

19:31 wouldn't have thought of otherwise totally makes sense flipping into a mentee mentor role and you as a mentor

19:38 right you know I'm sure you've had honored to be a mentor to many students many aspiring students like you said the

19:44 word is aspiring uh what are some of the common questions you know you typically get from students and how do you help

19:50 them along the way yeah so some are tactical um they for example very common question

19:57 is writing is hard because in our world eventually you have to communicate what you've done in a written in a written

20:04 way even if it's just a conference proceeding so communication by writing is hard is a very common thing and there

20:11 the advice you give is simply you know like my favorite cliche is uh the key to

20:18 writing is writing which is uh you just keep writing it and

20:23 keep getting told that well you can do better and you revise the draft and you start over

20:29 and sumathi my wife is fought she laughs every time I write something because she

20:35 says so when are you going to throw it out and start over because you know you know that the first

20:42 draft you can do better than your first draft so you toss it and start over and and so

20:48 um so that's something so tactically you teach them that look it's the iteration

20:54 is fine making mistakes is fine the fact that it doesn't work is actually a good thing in research it means you've

20:59 stumbled onto something otherwise it's pedestrian if everything worked and what you set out to do you did

21:05 a work that it's pedestrian so if it doesn't work that's actually a good thing it means it's the problems more

21:11 interesting than you thought it was and uh and so those things I teach but the

21:18 one that I struggle with and this is the hardest thing for a mentor to do

21:23 is to not tell them to tell them look if you just did these

21:30 six steps you'll get a thesis and you'll be out of here and you can tell them that and in fact they will probably

21:36 finish a year earlier but you wouldn't have served them well you have to let them stumble around a

21:43 little and keep your mouth shut while they're doing it uh so that they they

21:48 just get better at it and it's not cruelty on my part it's because I don't want my intellect to limit their

21:55 achievement by stumbling around they may stumble onto something that I haven't seen in the problem at all

22:01 right and so you don't wanna you don't want that to not happen so that's that's uh that's the hard part of it

22:10 um it's it's funny you said that because when my personal experience too I think you know I always see it as a two-way

22:15 street you know because I learn a lot from my mentees so it's a totally

22:20 two-way street so there are some aspects of that you just touched now

22:25 um let me just take the conversation to a different area

22:31 um you know I just read the story about your appointment for the being the next president of Tufts University there's a

22:38 there's a topic which talks about you know seeing the big picture as part of your research in operations

22:45 management you built mathematical models of systems you know that guarantee the

22:50 best solution you know or the almost best solution to many problems and I know you started off in you know

22:56 champagne and then in Stanford can you tell me a little bit about your work and how you've applied that in your

23:02 career these mathematical models and systems and how they guarantee the

23:07 solutions you're looking for yeah so um the the problems I work on tend to be

23:15 systems that intersect people and and automated systems in some sense from the

23:23 perspective of trying to find the best answer to something and so a the current problem I'm working

23:30 on is worth talking about which is asking the following question suppose uh

23:36 a city were to provide a uber like app for all the taxi cabs

23:43 how did price and manage the cabs different than Uber would

23:49 and first of all why would it be different because the city doesn't care about maximizing profit it cares about

23:55 maximizing access so suppose you were interested in maximizing access to cabs how would

24:01 things be different so that becomes very quickly a hairy

24:07 problem because you know just figuring out what

24:12 the pricing involves for example realizing that each taxi is driven by a

24:18 driver who's trying to maximize her return on her medallion

24:23 so she is not interested necessarily in Access she's interested in maximizing

24:29 her return and yet the city has to manage it in such a way that access is maximized and so this becomes so you

24:37 gotta it's big becomes very hairy and complex very fast and so you got to cut

24:42 through the details and ask what is important in this problem and what's not and so that is the and in second is you

24:50 have to ask yourself I clearly can't find the very best answer here what's the closest I can get to best and how

24:57 can I guarantee that I'm close enough to the best answer so so the second one is about

25:02 approximating the solution the first one is modeling which is figuring out what goes into the math and what just gets

25:09 left out so for example my current paper which is as yet still under review

25:16 argues that it actually matters a great deal how you relocate the empty cabs and

25:21 how you incentivize drivers to relocate their empty caps it matters more than people have given it credit for and so

25:29 so that's something where it's gotten partly by a fudge but partly thinking of the big picture and arguing okay so the

25:37 empty caps matter more than we are giving it credit for in some sense so it's it's fun

25:44 yeah I think the way you explain it it became a lot more fun because then when I look at you know mathematical modeling

25:50 you know it wasn't exactly fun when I first thought about it but I think the way you explain it you made it very lucid very easy to understand for you

25:57 know folks so thank you for doing that Sunil okay a completely different area and an area

26:03 which is very near and dear to me as well as you know most people around Silicon Valley most leaders

26:09 um what what do you think our industry you know especially Silicon Valley can learn from universities as it relates to

26:15 diversity efforts you know how can we embolden more people from DuBois background you know to pursue carriers

26:22 in fields like computer science yeah so uh you know this is uh I it's a

26:28 it's given that you know half our graduating students here will be uh

26:35 women in engineering at Hopkins I will um you know this is a is something that I

26:43 care deeply about and it's not just women but of course underrepresented groups uh Health students you know

26:50 students from who have greater economic need Etc and

26:56 the key there is how do you evaluate talent so one question that the valley in

27:03 particular but Employers in general can ask themselves is the following which is why did Hopkins admit this kid

27:11 and or whichever institution it was I admit this kid uh and in particular one of the things

27:20 as a consequence of the pandemic but something that we are probably going to keep for at least forcible future at

27:27 Hopkins is making the SATs optional so many of our files come in without the

27:34 SATs and so what we do is to holistically review the file look at all

27:40 aspects of the file look at given the opportunities this kid had

27:45 how have they achieved against those opportunities rather than looking at some absolute standard

27:51 and and so the way I characterize those is there are two ways to assess Talent

27:57 one is minimize downside risk so you're hiring a coder make them code if they

28:02 can already code the downside risk is low Ohio

28:07 right and the better they can code faster they can code the more likely you give them a job your downside risk is

28:14 minimized we could do the same thing we could make basically give them the first year exams and say whoever did well on

28:21 the exams is the only people will admit into the first year because we know they won't

28:26 fail the exams they've already passed them but that's not the point of college education right so so what you have to

28:35 do is to actually ask the other question ignore the downside

28:40 what's the upside here and if you manage to the downside you

28:46 will need a homogenous bunch of people because that is in fact if you did the mathematical modeling if you want to

28:52 minimize downside you want to minimize variance which means you're going to actually get

28:57 people who look like each other at least on you know in terms of what they can do and in many cases that

29:03 translates to they look like each other and who they are and that's not a great thing I think

29:10 whereas if you say I want to maximize upside then you want to have high variance

29:16 you want to have people who look don't look like who you would hide hire the court

29:21 for example and then so so the key thing is to figuring out how to assess Talent

29:26 and how to assess Talent whether we upside potential and in a in a time when

29:33 uh you know how can we have a one hour or 30 minute conversation without saying chat GPT so

29:39 I'm going to say it now and so um when there are assistants automated

29:47 assistance for coding and more routinized tasks you have to ask the things that are

29:54 harder to recognize like thinking critical thinking synthesis design

30:00 and so so those are I think that's really what

30:05 um would be of value I think to most employers and particularly to the valley

30:11 right so I think it caught me thinking in many ways I think especially the parallels you're drawn in from you know

30:17 the mathematical modeling too how you look at Talent right and the second part is you know

30:23 we tend to pigeonhole ourselves if you look at the downside risk and the upside

30:28 is not something which um I think Industries in general you know technology technology folks General

30:35 hasn't done enough uh I think you bring up a very good point there and also

30:40 there is parallels to in a fixed mindset with the growth mindset too here right you know you're looking at downside

30:46 downside risk you're getting to more of a fixed mindset which is not good for expanding your horizon so and the upside

30:53 growth growth mindset very similar so I really get that point I think some

30:58 something is good Sage advice for all of us in the in the valley and the it and Industry in general

31:04 so it's and the other thing is uh you know you'd be surprised if you looked at mid-carrier people from carriers outside

31:11 uh lots of talented people who are far from Tech who potentially could be

31:16 useful in things so as we close out the conversation you know you're taking on a new challenge as

31:23 the president of Tufts University how do you prepare for a job like that and what are you looking forward most

31:28 part of this journey well um the thing I'm looking for most is uh to

31:36 learn about an institution that I'm getting familiar with but not as familiar as I am with other institutions

31:42 so the learning part is always very kind of rewarding for me and to serving that

31:49 institution like I said there are lots of very talented people at Tufts who I hope I can help them achieve more uh

31:58 through whatever little I can do so that's that's really what I'm looking forward to so

32:04 it's uh it's delightful to be with you Sunil thank you for spending the time with us

32:09 um happy to have you back anytime thank you well thanks for the opportunity I'm very grateful thank you

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