Madhubanti (Madhu) Mukherjee is currently an engineering leader at Facebook. She’s worked in the San Francisco Bay Area for one and a half decades taking on engineering leadership roles in high-tech startups and large organizations. She has a Ph.D. in Computer Science and Engineering. 

Proteeti Sinha: What made you decide to pursue computer science?

Madhubanti Mukherjee: I should first clarify that my technical specialization is in Computer Science and Engineering – not CS.

A combination of three things got me to tech – I was good at Maths and Physics, enjoyed designing and making stuff (like drawing up building floor plans, building miniature furniture), and I was (and still am) pretty curious in general – with interests in how things work both from the technical as well as sociological perspective.

My first exposure to computers and programming was in middle school – but real access came during undergrad years. I worked on image processing algorithms and tinkered with electronic design automation as side projects. It was such a high to be able to write a few lines of text and be able to accomplish some pretty amazing things – like detecting faces in an image! And it was even more fun to design computers that design computers.

Being in this field let me be part of the accelerated technological revolution in the last two decades and I continue to be excited about the future.

PS: What did you wish you knew before you got into the tech industry?

MM: I wish I knew to focus less on texts and grades and lean on learning by doing.

It took me some time to understand that the most important skill to build is the ability to learn fast and constantly seek out stretch assignments that push you to learn new skills.

Technology has moved at an exponential pace in the past few decades and continues to do so. Also – as your role changes, your non-technical skills need to keep up.

Without constant learning, it’s very easy to become obsolete.


PS: Is there any tech stereotype you’d like to bust?

I was thinking how to best answer this question because my mental model does not really have a tech stereotype.

I’ve worked with a very diverse set of colleagues throughout my career and there’s no way they could fit into a box.

So I guess the stereotype to bust would be that there is a stereotype at all.


PS: An open secret in the tech industry?

MM: The most important skill one can have is self awareness and curiosity.


PS: What is the one thing you think the world needs from the tech industry?

MM: The potential impact through technology is truly boundless – it is possible to impact all of humanity.

As an industry we cannot lose sight of the hard problems that face humanity today – like climate change, broadening inequity, access to affordable healthcare, education – and come together to solve them. And then make sure as we pursue all that, vast swaths of humanity are not left behind.


PS: What role does the tech industry play in social activism? Algorithms and data drive many important decisions. Do you think algorithms can ever be completely unbiased?

MM: My personal take is that the tech industry by itself shouldn’t play a role in social activism.

From my perspective, the industry provides platforms and tools for the world to use them for getting their voices heard, to organize and mobilize others for social change.

Having said that, it’s not so black and white and the industry does have a role to play to establish equity.

The first thing is we need diverse representation in tech – in the industry and in academia to adequately represent what the world looks like. Where machine learning models are used, the models will be only as good as the data – without enough training data that captures the diversity in this world, the results will be biased. This is true not only for recommendation systems in search engines or social platforms, but everywhere learning models are used. Imagine using traffic data from the US to train a self-driven car targeted for Indian markets, or using genetic data from a certain ethnic population to develop prediction models for everyone – it just wouldn’t work.

The second thing is not to lose sight of the long term impact of decisions – sometimes the right decision may not look good for the balance sheet in the short term. So we need to be very thoughtful when picking what we measure and optimize for.


PS: Name a book you think every tech newbie should read!

I was going through my booklist and this is a tough one!

If I were to pick one book, I read recently, it’d be John Carryrou’s exposé on Theranos – “Bad Blood: Secrets and Lies in a Silicon Valley Startup”.

The Theranos saga tells us a lot of the addiction of our world with celebrity and storytelling. It’s a cautionary tale of what may happen when folks are ready to gloss over details in favor of the fear of missing out on a potential next big thing.


PS: What are your views on the gender gap within the tech industry?

I look forward to reading McKinsey and Lean In’s Women in the Workplace report every year.

Quoting from the latest report:

Based on five years of data from 590 companies employing more than 22 million people, two things are clear:

  1. Despite progress at senior levels, women remain significantly underrepresented.
  2. A “broken rung” at the step up to manager is the biggest obstacle that women face on the path to leadership.

 Although this report is centered in the US, I think it does apply to India as well. Top of the funnel is getting better but representation at the highest levels are not going up as much.

So my message to everyone starting out their careers is – be here for the long game. Seek the stretch assignments. Find your personal board of advisors. And fix the broken rung.


PS: Is there a message you would like to share for those in the AFH community who are starting out in tech?

I personally believe this is the industry where the potential impact is enormous.

I’ve been extremely fortunate to have been a part of teams that build computation platforms used to solve a broad range of technological challenges like automation for self-driven cars, fast gene sequencing, gravity wave detection, artificial intelligence and recently, core technology that powers the largest social networks.

Be here for the long haul. Take a seat at the table and then pull in others.

Rapid Fire!

One person, fictional/real and dead/alive that you want to have dinner with

Answer: Leonardo da Vinci and Yuval Noah Harrari.

3 things on your bucket list

Answer: Learn to play the piano well, climb Mt Kilimanjaro and record music.

A fun fact about you!

Answer: “Relaxing” – is my biggest nightmare.

If money and reality weren’t a concern, your alternate career would be?

Answer: Travel blogger and photographer.

Is there a quote or something that you read that completely changed the way you think?

Answer: This is a tough one. I read a lot and every book teaches me something new!

I just finished reading “Being Mortal” by Atul Gawande and this quote stood out from that ““We’ve been wrong about what our job is in medicine. We think our job is to ensure health and survival. But really it is larger than that. It is to enable well-being.”

I think this applies to tech as well.

I am currently reading “Hacking Darwin” by Jamie Metzel and ”The Color of Law” by Richard Rothstein.

Here are a few more quotes that were meaningful to me.

  • You can choose COURAGE or you can choose COMFORT, but you cannot choose BOTH!’ – Brene Brown
  • George Bernard Shaw: “Don’t wait for the right opportunity: create
  • “highly successful people have three things in common: motivation, ability, and opportunity.” ― Adam Grant
Proteeti Final

Interviewed by: Proteeti Sinha
Co-Founder, Aspire For Her