Dr. Deborah Berebichez is a Chief Data Scientist, who made history as the first Mexican woman to graduate from Stanford University with a Ph.D. in Physics. Deborah has been the co-host of Discovery Channel’s “Outrageous Acts of Science” for the past eleven seasons, where she uses her physics background to explain the science behind extraordinary engineering feats.
Deborah has been featured by many media outlets worldwide, including in Forbes, Wired, The New York Times, US & World News Report, and on The Travel Chanel, CNN, FOX, MSNBC, Univision, NatGeo, and many more.
Deborah’s work in science education and outreach has been widely recognized by The Wall Street Journal, Oprah, TED, and by organizations like the American Association for the Advancement of Science (AAAS) where she was named the IF/THEN Ambassador for inspiring and empowering young women to learn science and to improve the state of STEM education in the world.
Deborah completed two postdoctoral fellowships at Columbia University’s Applied Math and Physics Department and at NYU’s Courant Institute for Mathematical Sciences.
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Deborah Berebichez: Data Is Everything. STEM Is The Future. Virtually Speaking Episode #44
Joining us is Dr. Deborah Berebichez, a Chief Data Scientist who made history as the first Mexican woman to ever graduate from Stanford University with a PhD in Physics. Debbie has been the co-host of Discovery Channel’s Outrageous Acts of Science for the past decade-plus where she uses her physics background to explain the science behind extraordinary engineering feats. Deborah has been featured by many media outlets worldwide, including Forbes, Wired, The New York Times, US & World News Report and on the Travel Channel, Nova, CNN, Fox, MSNBC, Univision and many more.
Deborah completed two postdoctoral fellowships at Columbia University’s Applied Math and Physics Department and NYU Courant Institute for Mathematical Sciences. Deborah’s work in science education and outreach has been widely recognized by the Wall Street Journal, Oprah, TED and by organizations the American Association for the Advancement of Science. She was named the IF/THEN Ambassador for inspiring and empowering young women to learn science and to improve the state of STEM Education in the world. Please join me now with the incomparable Dr. Deborah Berebichez.
Dr. Deborah Berebichez, thank you for joining me on the show. How are you doing?
Chris, it’s lovely to be here. I’m doing great. I’m packing for a trip to Finland. I’m moving with my husband and my two kids for at least 4 to 5 months and we will see what the future holds.
You have a spacey background. Is that the kids’ room that we are in because of all the packing?
We are. My husband and I are Physicists. We love space so our kids are well versed in space. Our daughter comes up with theories of why we can’t live in some and the next day, she comes up with a different theory of why we can. They were able to produce oxygen on Mars, by the way, so that was pretty cool.
In a controlled environment?
Yes.Data science is the sexiest job of the 21st century. Click To Tweet
That was the first time that’s ever happened?
I would imagine that if you are moving to Finland, you are probably going there for some science or technology-related endeavors?
Yes. What happened was that in the middle of the pandemic, my husband was being strict about not traveling. He was in the super strict end of the spectrum of people that we knew. Even leaving New York for a weekend was out of the question. I was daydreaming and one day my friend, Ola, who I met in New York, who was from Finland, posted on Facebook that the Helsinki Business Hub had created a program called the 90 Day Finn, which was inviting high tech talent from all over the world. Finland needs a lot of young tech talent. I decided to apply as a joke. Fast forward 3, 4 months later, we were selected out of 5,000 people and we are going as a whole family. My job there will be helping high-tech companies and people in the job market bridge the skills that they need in data science or STEM so that they can hire the right data scientists with the right skills and progress. They want to recreate Silicon Valley.
You are the perfect person to do that. You have been such a huge advocate for STEM, young people and women in STEM. Famously, you have an incredible story that I want you to tell. I’m going to get to the punch line, which is that you became the first Mexican woman to get a Physics PhD at Stanford. Is that correct?
I’m sure there has been a lot of other great Mexican women who have done the same and you were a trailblazer. Tell us a little bit about that story because it’s a big part of what you believe in, what drives you and where you come from, it’s important for everybody to know. You grew up in Mexico.
I grew up in a conservative community where women who expressed a desire to learn Math and Physics were discouraged from doing so because girls should study something more feminine. From a young age, I was extremely inquisitive and curious. I would ask questions about everything around me in nature. My father, who was a Civil Engineer, was fond of talking with me about the stars, bridges and how things were built.
When I reached high school, I remember at the time, all my friends said that I was crazy when I told him that I wanted to study Physics. Even the counselors in school said to me, “No. To study Physics, you have to be a genius.” I knew I wasn’t. They also said, “Plus, as a woman, it’s impossible. The jobs are long hours. You won’t be able to combine it with a family.” It got me scared that I became insecure about my Math abilities.
I started to read stories about obscure physicists like Tycho Brahe. He was a Danish Astronomer of the sixteenth century, who was a nobleman. There’s this legend that he lost his real nose in a duel. His copper nose, which was the replacement they gave him at the time, sits in a museum in Prague. I became fascinated by his story and I said, “I will be like Tycho Brahe.” My son is called Tycho because of that. I said, “Maybe I will end up being like him. Nobody will like me and I will be anti-social but at least I have my meticulous science calculations to keep me company.” These were my role models. I couldn’t express that to people because I would be discouraged.
When it came time to pick a subject to study in college, I picked Philosophy because I was so afraid of Math and people were telling me Philosophy is the same. You ask questions about why and the universe. It wasn’t the same even though I enjoyed Philosophy. Two years in, I decided to apply behind everyone’s back to schools in the US to transfer and study Physics because the voice inside me clamored that I had to learn more Math and Physics was not going to go away.
I applied to schools. Universities in the US cost eight times what we were paying for a private university in Mexico. My parents couldn’t have afforded a regular university without financial aid, which is not given to international students. I was lucky to get a full scholarship from Brandeis University in Massachusetts that was awarded to me for two years as a transfer student. I flew to Massachusetts and I arrived in the middle of the winter as a transfer student.
I was passionate about Physics. In my first semester, I had the courage to take my first almost no Math intro to Astronomy class. In that class, I sat way in the back and I befriended the teaching assistant who was a grad student by the name of Rupesh from India. Rupesh and I became friends and I would ask him all kinds of questions about quantum mechanics, special relativity, and Einstein. It was an incredible adventure. One day I told her, “Rupesh, I don’t want to die without trying to do Physics.” Rupesh said, “I will call my advisor,” who was the Head of the Physics Department at the time, Dr. Wardle.
He called me into his office and Rupesh said, “There’s a problem. We have this girl who wants to do the Physics major but she only has two years left.” The full major takes four years regularly. Dr. Wardle said, “We know somebody who’s done this. His name is Ed Witten.” For those in your audience that know him, you’ll realize what a crazy idea this sounded because Ed Witten is the Father of String Theory, which is the most popular physics theory now and he’s a genius. He’s a professor at Princeton and he had switched many years before me at Brandeis from History to Physics.
They said, “He was able to do it, we know what to do with you.” He handed me a book called Div, Grad, and Curl which was Vector Calculus in Three Dimensions. I didn’t even know Basic Algebra and he said, “If by the end of the summer, in two months, you master this material, we will let you skip through the first two years of the Physics major so you can finish your BA in only two years.” I will finish the story by saying that Rupesh was my first mentor and I loved all this because he decided to devote his entire summer to mentor me and tutoring me. I always wanted to pay him for all that he did for me because thanks to him, my mission in life was born.
He told me that when he was growing up in Darjeeling, like the tea, in India, there was an old man who used to climb up to his town and teach him and his sisters’ tabla, the musical instrument, Math and English. Whenever the family wanted to compensate this old man, he said, “The only way you could ever pay me back is if you do this with someone else in the world.” That’s what Rupesh did with me. I was a pay-forward engine where he said, “Your mission in life now is to help and inspire other women or minorities who, like yourself, feel attracted to STEM but for some reason feel that they cannot achieve their dreams.
You ended up at Stanford somehow after that.
Years later in complete disbelief and it’s an incredible story, I was in Mexico pursuing my Master’s and I was again being told by everyone, “Let’s see if we can get you married and stay in regular society.” I was thirsty to know more about the world, Physics and nature and I said, “I have to leave this environment.” I applied for a PhD. I went to my advisor in Mexico and I said, “I learned that there’s this man, this physicist called Steve Chu at Stanford and I like his research because he’s manipulating DNA with lasers.”
His jaw dropped. He said, “Steve Chu?” I said, “Yes. Why?” He said, “Do you realize that he won the Nobel Prize a few months ago?” I didn’t know. He was later the Secretary of Energy during Obama’s administration. Had I known, I probably would have been shyer. I wrote him an email directly and I said, “I love your work. I have a scholarship from the Mexican government. Can I come and work directly with you?” He said, “Yes.”
You had another incredible mentor and you went through to PhD Physicist,
I ended up switching because working with Steve in the lab was not exactly what I wanted to do. I ended up becoming a Theoretical Physicist. All I needed was a computer and thinking formulas and Math. I ended up working with another Nobel Prize winner, Bob Laughlin. That’s what you get when you go to places like that. Bob and I remained friends and he’s a great mentor.
That was your third mentor. Mentorship is important.
It’s hugely important in my life.
Also, in people’s lives who want to succeed. Doing it alone is often impossible, especially if you are in a sector of society where they don’t believe that you should be pursuing this.
Something that comes to mind is when I was studying Physics at Stanford, I recall that we spent maybe 2 or 3 all-nighters per week doing homework. This was a traditional thing. I consider the people in that group my friends. We don’t like to go out or anything but they were my friends. I attended the American Physical Society meeting and I was with my Mexican professors walking in the hallway. There are thousands of physicists in a large conference and I said, “Here come my friends,” because they had the badge that said Stanford Physics. I was saying hi in a friendly way and they passed me by as if they didn’t know me. I said to my professor from Mexico, “I promise you, these are my friends.” He said, “I believe you. They are maybe shy or whatever it is but don’t take it personally.” It was hard for those six years to be in an environment where people like me, came to Physics later, not the Math wizard growing up that had won Math Olympiads, who are female because we were only two women in my whole graduate class of 34 people, I felt that bias and I lived with it. It takes more courage to pursue those fields.
You are such an inspiration to so many people. I know you talk a lot about it. You are a huge advocate for STEM and for everyone to be able to succeed in it because everyone should be able to succeed in it. I am excited to talk about what’s happening in the world we live in right now. I have known you for years and it’s almost I keep hearing more and more now than ever the words, algorithms, data and big data. Therefore, you, a data scientist sounds like to me, if I’m not mistaken, that data science is more prevalent, more important, needed and will be a part of the future than ever. This is probably an exciting time for people like you and for you to look at the future of what’s happening. Tell us if I’m right and tell us what’s going on.
A few years ago, Harvard Business Review came up with a sentence that said, “Data science is the sexiest job of the 21st Century.” I’m not sure I agree with that but it did signal an incredible boom in the demand for people with analytical and computational skills to make use and make sense of all this large amount of data that we are collecting as the human species. The amount of data that we saw in physics in the ‘70s or even now like the Square Kilometre Array, the Large Hadron Collider, the particle physics experiments are so vast. I had the culture from Physics of how to use computing to choose and classify things.
It was easy for me to translate those skills and those concepts into the world of data science when I pivoted and I became a data scientist. As a Chief Data Scientist at Metis, we’ve got hundreds of people of all ages and all backgrounds taking our bootcamp to transition to become full-time data scientists. We are not even seeing a tapering of the demand. More and more companies are even being valued. The valuation of companies is sometimes based on data that they have.We are in an era of iteration, agile invention, and innovation where things can get created quickly. Click To Tweet
I heard about that. It’s something having to do with Vegas. The casinos were having some issues. There was one major conglomerate that was having an issue with maybe going into bankruptcy and they realized upon analyzing what they had, the data they had was what saved the company. I have heard and I know that this is the future. It sounds like companies are going to be hiring data scientists. It sounds like data is the key to survival, this the key to understanding your customers. Tell us a little bit about how that works. A lot of people don’t even know that data applies to them but it does.
I want to interject and say that during the pandemic, we are seeing the numbers slowdown of hiring data scientists because of a key issue. A lot of companies were hiring data scientists to speculate on things and to not directly related to the profitability of the company. It’s like, “Let’s see if we can figure out a new demographic or if we change AB Testing. If we do this differently, what would be the results?” Now we are seeing that the hiring is more with data scientists that are directly related to an at-scale algorithm to something that is already profitable, part of the business and is at a somewhat large scale.
I teach and talk about data literacy, for example, which is to say that data is not some complicated formula or algorithms that are on a blackboard in a university. It’s not that. Data is everything that surrounds us. I teach it to middle school and high school students as well. Every app we use, whether it’s Facebook or a healthcare app to monitor your health, your weight, all of that is data. These are facts or factoids about you and everyone that surrounds you.
We have come to a tipping point where machines like our computers, Amazon or Netflix, know more about us than our spouses, for example. They were able to predict products that we are going to want to buy in the future by analyzing our data and aggregate it with everybody else’s data and preferences. You see data is immersed in every process from the janitor at the airports. I don’t know if you have seen but when you go to the restroom, there are three little faces, green, yellow and a red frowny face. You can click on one to comment on the state of the restroom.
Before, they would clean every now and then it was all manual. Now, they get in their watches a signal saying, “Too many people are clicking on the yellow or red button.” The data is influencing the timeline for that. I can give you tons of examples of entire companies that have to change their business model like Rolls Royce who used to build motors for cars is also in the business of building air turbines for airplanes.
Instead of being a hardware company that sells you this expensive turbine that can fail in twenty years, they are becoming a software management company because what they do is you have the turbine but they have embedded microsensors in them. IBM was able to do it in nanoscale to write a little sensor that’s 100th of the size of one strand of hair. They embed these tiny microsensors that continuously send signals to a program wirelessly giving information about the state of the turbine. It’s predictive maintenance so you will know beforehand when this is likely to break or stop working.
There are different companies with different risks. We are in an era of iteration, agile invention and innovation where things can get created quickly. Concepts can get tested by companies and they can be put on the market or not. I have to add that this is why the whole emerging field of data ethics is so important. I teach about this as well. The way that we all build our algorithms is generally biased in one way or another.
For example, if I work in finance in a bank, instead of having people manually inspecting everybody’s credit score and their situation to give a mortgage, I want to outsource it to an algorithm. I have a machine doing that and it saves me a lot of costs. What happens is that I’m going to set the rules for that algorithm to classify someone as meriting a mortgage or not. It’s easily shown that there are many biases. For example, if you feed it with historical data that traditionally has African Americans not getting mortgages, the algorithm is more prone to not giving a mortgage to an African American person simply by looking at ZIP code and this and that. We have to be careful about engineering a future with the data we have that serves and mimics our entire diverse communities and that’s a big thing.
I have heard that being talked with several other thought leaders, speakers and experts that I know. It’s awesome to know that the biases that we have lived with are going to be written out of it and obsolete hopefully. The data that we are analyzing is based on a human being and his track record or her track record with payments or credit and also the amazing ability for algorithms, AI and data to predict what somebody is likely to be able to do or will do with decision making or with success. To me, that’s mind-blowing. How does this data work? What is it that it can predict? How does it do it?
I’m Amazon, let’s say. I collect data from hundreds of thousands and millions of customers. I have Chris’s data. He likes sports, books and watches romantic movies on Amazon Prime. He had twins because I see his purchase habits. He bought a lot of diapers last month. The kids must be around the age of two so now I’m going to try to recommend that he buys potty because potty training is starting and whatnot. What Amazon does is he takes people like Chris and you are what’s called a vector. You have all your likes, dislikes and interests. You have clicked away and you have moved away from stuff they have shown you.
They do this in two ways. It’s either they take the object that you like or that you bought, such as a romantic movie and they have a database that says, “Everybody else who likes romantic movies, what else do they like?” They are going into everybody’s vector and a computer can do this quickly. They look at John Smith. He is a little bit Chris, around the same age range, similar ZIP code, he had kids and he bought a humidifier for his kids’ room so then let’s recommend Chris a humidifier. They will recommend the object that thousands of other what’s called proxies or Chris-like substitutes are buying. That’s one way in which they recommend.
The other way in which they recommend because they do the hybrid method, another thing to do is to look at the person. Instead of seeing what objects you buy, it says, “You like The Cure and David Bowie.” Those are things that I like. You like that kind of music and so what kind of person are you? I look at another person that also likes that and invent a new category. What I’m saying is, beforehand, if you like romantic comedies, I will recommend different objects.
I’m going to get into a completely different category and I’m going to predict that because you like that type of music, my model will say that people who were born around that time or trending towards that are highly likely to seek somebody to help with your estate, write your will or something at a certain year or window. I’m going to send you those experts. It’s a completely different category. It’s not a product that you can buy but it’s a recommendation based on the likelihood because of your behavior and not as objects that you have bought. It’s making guesses but they were pretty accurate guesses because you have a lot of people purchasing these vast networks of data.
It sounds like a lot of it is advertising and marketing. What do you say to people who say, “This is awful? The marketers are the devil. I don’t want my information out there.” Isn’t the truth that with technology, we have built it to help us? Most of the originations of the people creating that technology were like, “We are going to help people do something better or make something easier for them.” Isn’t this a good thing?
I have said this a million times even on this show. I’m on Instagram looking occasionally at the feed and the ads that are shown to me on Instagram are the best ads ever. I have bought so many incredible products, from shoes to technology or a great toy for my kids that has changed my life. I’m like, “I’m so glad I bought that.” It’s usually something I have never seen before. It’s usually something unique and something I would have liked. I have never seen advertising done as well as they do on Instagram. I appreciate it because it’s turning me on to great products that I am interested in.
You are one of the lucky ones. By chance, if I google a program for women entrepreneurs but it was for one piece of research that I was doing, then the rest of the week, I will get ads for women entrepreneurs. I hear what you were saying. There’s a whole spectrum. Especially Millennials and younger, people are willing and open to give up their privacy for some comfort and use the apps and data insights give us. Whereas for older generations, we are a little bit wearier of having all our details out there.
There are these spectra and people constantly move around. There are certain pieces of data in your life that you say, “Privacy is overrated. Who cares if they see what I do and where I am?” Maybe something happens in that neighborhood and you start to be more careful and now you start caring about logging in Facebook with a location on and tagging yourself in certain areas. It all depends on what the benefits are. That line is a line that’s going to move in the future because companies are being more and more pressured to provide a good added benefit for selling our data.
People are becoming savvier and they were saying, “Look at what happened with Cambridge Analytica or even the Russians interfering in the election.” Data is powerful. It can change it and affect our lives in ways that previously we didn’t know of. Facebook can change our opinions on things that matter to us. With that, people are not easily sharing as much information as they previously were with all these platforms. Unless they see that by sharing something, they are going to earn a huge benefit.
What do you think is the most common area that companies are starting to look into as far as the data? Is it also about what to do next? Is it also about what they are going to do next and what they should do next? Can data help companies figure out their futures?
Companies that want my consulting services come to ask me for 1 of 3 things. The first one is data literacy. They were like, “I want to empower my whole workforce to use the data that we have. I don’t want only a small ten people group in R&D or IT to be the data scientists. I want my HR people to be able to get data and use the data. I want my sales personnel to be able to give a discount when they have the data of the client in front of them. I want to empower everyone. How do we educate everyone about what data is, what data isn’t, how to use it, etc.?”
The second thing that people come to ask for when it comes to data science is deciding on what products and what features to include in a certain product. They will release Product A and they will release a slightly different Product B with maybe one less feature. They collect information from a beta group of testers who will give them the information needed to decide, “What products should we put out? What features are important for this community and these people? What should an upgrade look like?” Thirdly, it’s what you said, a group of companies who are at the forefront of technology like IBM, Xerox PARC, HP, Google, etc. They come in and they say, “We want to predict what the future of work will look like, what the future of education will be, childcare and so on.” By predicting those things, they can design algorithms, platforms, products that will serve the future of mankind.
This is an exciting time for anybody in technology. I’m excited that we get to get the inside information here from an actual data scientist. You are in the middle of an incredible career and now you are going overseas. You are going to be helping establish some more people in technology all over the world, which is another great thing that you are doing. You are giving back, which has been a theme for you for so many years, giving back, fighting for people’s rights and encouraging people to get into STEM and to be excited about science. You are an inspiration. It’s wonderful to catch up with you and this has been fun.Social media can change our opinions in many ways than we could ever expect or imagine. Click To Tweet
Likewise. I always like talking with you and sharing my thoughts on data, mentoring and how important it is. I spoke to one of my mentees. She was a high school girl when I met her from Mexico in New York and she was timid. I noticed when I went to give a talk to her school that she was curious about STEM. I adopted her and mentored her. She won The Technovation Challenge, which is a great tech contest done all over the world now. She won with a group of friends and Google paid them $15,000. They helped her develop the app, which is now on the market. She finished her BA in Computational Science at the University of Pennsylvania. When you see the fruits of that, I sleep a little better.
I know you have been thinking about women and people who are of different diversities and ethnicities. It must be a cool time for you to be alive also to see that everybody’s voice is now coming out, being listened to and championed more. That is a world that we are living in. I don’t think we are going to go backward. We are going to continue to go forwards. This has been awesome. Deborah, thank you so much for joining me. Have a great trip overseas. I’m sure we will stay in touch while you are there. You will be doing some virtual events for American clients, I’m sure, for a few months more. This has been a real pleasure. Thanks so much.
Take care, Chris.