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In this #DataTalk, we had a chance to talk with Emma Yang on ways to get more girls involved in data science. Please support her work on the Timeless App to help Alzheimer’s patients by donating money to her IndieGoGo campaign here.
This data science video and podcast series is part of Experian’s effort to help people understand how data-powered decisions can help organizations develop innovative solutions and drive more business To suggest future data science topics or guests, please contact Mike Delgado.
Here is a full transcript of the interview:
Mike Delgado: Hello, and welcome to Experian’s Weekly Data talk, the show where we feature some of the smartest people working in data science today. Today, we’re talking with Emma Yang. Emma is 13 years old. She’s passionate about mathematics, computer science and technology innovation. She started coding when she was 6 years old. She developed the Timeless app, which we’ll talk about in a little bit, which was to help Alzheimer’s patients. Her app ended up winning the Technovation Challenge, where she competed against 400 teams from more than 60 countries.
She’s won numerous STEM awards. And she’s been named one of New York’s Top Ten under 20 Young Innovators to Watch. She speaks English, Mandarin and Cantonese and is learning French and Latin. And aside from all that, she also loves playing the piano and the cello and has performed at Carnegie Hall twice. Emma, thank you so much for being our guest today.
Emma Yang: Thank you.
Mike Delgado: So I thought it’d be great, Emma, if you can share a little bit about how data science has impacted you. Starting off at age 6, can you take us through your journey?
Emma Yang: I started coding when I was 6 years old. But I really got started in data science when I met Dr. Stephen Wolfram, the CEO of Wolfram Research, when I was 12 years old. I actually went to a New York Maker Fair, and he was doing a talk there. That’s when I got started with the Wolfram language that he made. And I started the Wolfram’s mentorship program, which actually helps middle school to high school kids get started in coding. One of the first projects I did was taking NYC open data on collision data, traffic, and analyzing that with basic data science. From there, I got some image recognition, learning neural networks and even deeper data science. That’s how I got started.
Mike Delgado: Were you working with the MIT Scratch program originally?
Emma Yang: Yeah. When I was just starting, when I was really young, I did Scratch. And then I did App Inventor, which is a very similar thing but for Android apps. And then I progressed to Java and then HTML. And now I mainly do Swift. But yeah. I have a really broad interest in coding.
Mike Delgado: That’s awesome. So tell us about your very first adventure developing an app.
Emma Yang: I started an MIT App Inventor because I was living in Hong Kong when I was younger. When I was there, I think I went to this class that was designed for kids to get started. And we did basic things like games. And then later, I found Technovation Challenge, which is a girls’ entrepreneurship challenge. Basically, you get to develop a mobile app, develop a business plan for it, and then go through a competition where you pitch your app. That’s where I got started. I created an app called Concussion Checker. It’s basically an app that helps put a test into your mobile phone so you can test for a concussion easily. That’s how I got started developing apps. And I went from there … How can I use technology to impact people I may not know, but I know that my app will benefit them even if they’re here or around the world?
Mike Delgado: Yeah. No doubt. It’s just beautiful to see how you’ve been leveraging data to help improve our world with both the concussion checker, as well as the app that you worked on called Timeless, which won numerous awards. Definitely puts you in the spotlight, got you working with neurosurgeons and neuroscientists. Can you talk a little bit about … Because this is maybe the first time where you’re actually having to develop a business plan around an app. Can you talk about that whole process for you? Because that must’ve been new to actually incorporate the data science and the business.
Emma Yang: Yeah, definitely. Because this is the first time I’ve really developed a full-blown app and then thought about actually putting it out there. I’m really lucky to have met some of the people along the way who have been supporting me. My parents have been helping me with the business plan aspect. So it’s really like a learning process for me as well as a process of getting this out there and making sure that it can help people, real patients around the world.
Mike Delgado: I was also reading … When I looked up your name on Google, I found tons of articles about you and different bios. And I also saw somewhere that you were involved in a girls coding camp or helping young girls with coding. Can you talk a little bit about how you’re acting as a mentor as well?
Emma Yang: Sure. When I was back last year, when I was in eighth grade in middle school, I started a coding club at my school. Basically, we ran after school and I would teach these middle school students, mainly fifth- to seventh-graders, about MIT App Inventor. I encouraged them to actually look at things, materials in Technovation … They have a really awesome curriculum. And to see what you can do with apps. What can you do to help your community? That’s something I hope to be able to foster in girls my age. How can you empower yourself with technology to help people in your community?
Mike Delgado: I think a big part of it also is not only what you’re doing to inspire girls to pursue STEM education and data science, but also getting the parents involved. Can you talk a little bit about where you see the parents’ role in helping their children? Because a lot of the things you’re talking about, Emma … I don’t have a background in data science. So if my daughter said, “Dad, I want to start doing coding,” I would probably be like, “I don’t even know where to begin.” So talk to the parents who are listening who maybe feel like me … like, “I’m not equipped to even help my child learn about data science.” What would be your advice for parents who are trying to encourage their children in a field they don’t know anything about?
Emma Yang: I think that what’s great about coding education nowadays. There are so many resources out there. And in my experience, for me, I was put in front of the computer with MIT Scratch as kind of “let you loose and see what you can do with it.” That’s where I got started. So I think putting them in front of those resources and finding them that starting point is really important because after you have that starting point, you just go crazy with it.
Mike Delgado: Would you recommend that parents look for certain websites to begin helping their children or certain books to buy? What would be some resources parents could go to?
Emma Yang: I think MIT Scratch and MIT App Inventor are great places to start because it’s not as daunting. It’s not like typing in code. It’s drag-and-drop interfaces. It’s animation and games. So it’s really … And that speaks to younger kids more. That’s why I got motivated, because I saw you can do these blocks and you can do so many things with it. Those are two really great places to start.
Mike Delgado: One thing I’m really impressed by about the MIT Scratch program is that it is very fun, it can be very intuitive for children and also teaches children the logic of how programming works. So even though you’re not necessarily hand coding things, they’re using blocks and beginning to understand how code works.
Emma Yang: Yeah. Exactly.
Mike Delgado: So moving on from Scratch and then getting more excited in thinking about how I can use data to help others, tell us about this Timeless app. Tell us about this journey that you went on to develop Timeless.
Emma Yang: Sure. My inspiration came from my personal experience with my grandmother, who has Alzheimer’s. I saw, personally, how it can impact our family … Not only her as a patient, but also her friends and family not being able to communicate with her as well. Around when I started developing this, I actually had just finished going through the process of going to Technovation and doing Concussion Checker. That’s really what inspired me — my personal experiences, but also my motivation, my knowledge that what I develop, the apps I develop, can really help people and can speak to people. So I started from there. Timeless is an app that uses artificial intelligence, facial recognition technology to help Alzheimer’s patients and their families and friends stay connected while coping with the disease.
The main thing is repetition of information and accessibility. You have places where friends and family can send updates, where they send photos. And each of those photos is tagged by AI so the patient doesn’t have to ask every time or wonder who this is in the photo; it just recognizes it for them. And then you have places where you can take a picture live of either that person or a physical photo that you have and see who that is. And you have places where you can find an agenda of the day. The main thing is making sure the information’s in front of them all the time and it’s really accessible. Using mobile phones, you can always access your mobile phone, you can look at it, and you can remind the patient.
That’s been proved to help with the decline and make sure that slows down. That’s where I’m at with the app. I’ve just launched an Indiegogo campaign that’s helping to raise funds for me because I’m a high school student. I can only work on this for so much time. Getting people to help me, which I’m currently doing, is really what the funding is going into.
Mike Delgado: That’s beautiful. We’ll make sure to put a link to the Indiegogo campaign on the URL that I’ll put on the screen in just a bit, which is ex.pn/Emmayang. Those who are listening to the podcast or watching the video can go over to learn more about how you can support Emma in this process. Because I think it’s beautiful, what you’re doing, Emma, to help patients who are suffering from this debilitating disease. It’s a beautiful way to use AI to help with recognition, to help them remember things.
Emma, you have this amazing background with the data sciences. When you’re coming to help to solve or trying to figure out ways to solve this problem, take us through … There is the neuroscience aspect that maybe you weren’t familiar with. How did you connect those dots to bring data science and neuroscience together?
Emma Yang: The way I got started with mapping out what I want to put in the app is asking myself what I wanted to do right now with my grandmother. And right now, we have a whiteboard in her living room where we write down the date, my dad’s phone number, her address, and all this important information so she can look over and see that info. And then also, we send her these photos through her iPad so she can look at those with her caregiver. But then if you want to automate that and put it into an app, how do you do that?
I’ve been seeing a lot of things popping up about facial recognition and AI that’s developing really quickly. So I’ve found that bridge where you can use AI to be that caregiver and show them who that is so you can do it quickly, and you can do it on your own, and it’s even more accessible on your mobile phone.
Mike Delgado: That’s wonderful. And what I think is also beautiful about your project is it’s been definitely coming from your heart. It’s coming from your family, things you’re trying to solve. The fact this is a personal project for you just gives you more drive to make it as good as possible.
Emma Yang: Yeah. Really knowing that this can help people like my grandmother, not only her, but families who are struggling like us, is something that’s really motivating for me.
Mike Delgado: Congrats and wonderful to hear the progress on the app. And we’ll definitely be linking to the Indiegogo projects to help you get more funding to support you in there. So right now, you’re 13 years old?
Emma Yang: I’m 14 now.
Mike Delgado: You’re 14 now. And you’re in high school. Where do you see yourself going after high school? Because you can do anything you want to. So where do you think you’re headed?
Emma Yang: In college I definitely want to study something like interaction between computer science, AI and health because that’s the field that’s really developing so quickly right now. And I’ve taken a dip into it. But I really want to study and immerse myself in that field in the future. Right now, I’m also doing projects that use AI to detect lung cancer with the Wolfram’s Mentorship Program. That’s really what I want to go into and really understand where that comes from.
Mike Delgado: What are some of the things that excite you about the future of AI and health, seeing where we’re at now, the data points that we have now and where things are headed?
Emma Yang: I’m really excited to see how much AI is working its way into our daily lives. You have the detection of lung cancer that’s coming out and all these different things with AI. I’m hoping that if you use computer science to make things more efficient, faster, how many more people can benefit? That’s really what’s exciting for me.
Mike Delgado: That’s beautiful. Very cool you’re looking to use data and health and leverage data for the good of all mankind. Helping with the medical field is gonna be huge. It’s really cool you’re taking that path. Are there other types of classes you think you are gonna take in the future to help you progress?
Emma Yang: Yeah. Finance is definitely a field that’s growing a lot in data science as well. That’s something interesting I probably want to pursue in the future as well. And things like that … There are so many fields now that AI is working with, even liberal arts. You can see so many different applications now. I think I have a lot of choices in the future.
Mike Delgado: I was also reading in your bio that aside from the mathematics side and the arts side that you have with playing piano and cello, you’re also a writer.
Emma Yang: Mm-hmm (affirmative).
Mike Delgado: Where do you see AI going with literature and writing and helping people become better writers?
Emma Yang: I think that things coming out right now like Grammarly to help people improve their writing … There are so many places even with text analysis that AI is coming out with. I was at the Wolfram Summer Camp this summer, and there was a girl who used AI to match your Twitter with which Shakespeare play we’re doing.
Mike Delgado: That’s cool.
Emma Yang: There are so many advances coming that AI can be applied to that I think the field is open for that.
Mike Delgado: That’s wonderful. Now, Emma, it’s funny … We see all these headlines in the news about rogue robots taking over the world, the problems of AI maybe decreasing employment. I’m curious about … I mean, you have a very optimistic view, especially in the health area, which is totally true. But I’m curious about … There seem to be almost these two sides. Either you believe AI is gonna be hurting human employment or it’s gonna be boosting human employment. Where do you fall? Not that you have to fall on either side. But where do you see things headed with AI?
Emma Yang: I think that AI, if we look more into it, and we research it more, we can find places that it can help people even more. But as the field progresses with any sort of innovation about how we work and how we live, it’s important that we take care of the people who are gonna be falling into that gap where they’re put out of jobs. Because there are so many different ways to learn coding nowadays with computer science, it’s really important that we boost those because anyone can learn how to code and anyone can get into computer science. And we can help to bridge that gap for people.
Mike Delgado: What’s your advice for people, especially your peers, who are interested in data science. They’re listening to you, and they’re saying, “Wow, I would love to start learning this, but I don’t feel like I have a very strong math background.” What would be your advice for those students?
Emma Yang: I think the best advice is to get started. Because when I started with computer science, data science, when I was around 12 years old, I came in with “I can code, but not really data science code, and I have minimal math.” And even now with high school math, you can’t really go all the way. It’s really important to get started because there are so many tools that can really help you with that and that automate so many of the things I think anyone can get their hands on. Go searching around on Google, and don’t be afraid of all that stuff out there because there’s a lot of people out there and a lot of resources out there that can help you narrow that down and find your niche and find where you really want to stand.
Mike Delgado: Mm-hmm (affirmative). And then going back to the parents, because I do think parents obviously play a big role in encouraging their children … What advice do you have for parents who are trying to nurture that desire for data science for their kids? Because we look at the future and we see we’re moving into this new age of AI and machine learning, and certain jobs will probably go away even with the littlest things like … Well, not little … But things like economist driving. There’s certain areas where certain jobs may not be around anymore. And parents want to encourage their children to seek fields where they’ll find employment and find pleasure.
What’s your advice for parents to help them train their children and be prepared for the future?
Emma Yang: The biggest thing is connecting it with the real world, connecting with computer science, things that speak to people. Because people are always like, “Oh, this is computer science and math. I’m not dealing with this. I’m gonna leave it be.” But because there are so many connections you can make with all sorts of fields, liberal arts or science, it’s a lot easier to get kids into coding because it doesn’t have to be complicated math in coding. It can be something as simple as detecting text and looking at improving your writing and things like that. Bridging that gap between computer science and the things around me, my world, my surroundings, is something really important that you can bridge.
Mike Delgado: Emma, we just got a question here on Facebook from Alex, who says, “Emma, do you have a favorite source when reading about the progression of AI? A professor, blog, books that you’re reading?”
Emma Yang: I keep going back to Wolfram. But Dr. Wolfram’s blog is really awesome. He writes really great things. He just posted something about computational essays, which is using code to prove something or explain something. That’s one of the examples of the bridge between liberal arts and computer science. That’s really all of the places where I get my ideas and get my inspiration from. You should definitely check that out.
Mike Delgado: That’s awesome. We’ll make sure to provide a link in the blog post, which we’ll put up in just a bit, so everyone can learn more about that. So at the end of every broadcast, Emma, we always ask a series of questions to all our guests just to get to know them a little bit better. And the first one is, what is your favorite programming language and why?
Emma Yang: My favorite programming language would be A, Wolfram language, and B, Swift. Because Wolfram language, especially because they’re expanding it right now, they have so many applications in so many ways. And then Swift because I’ve been mainly using that for iOS programming. And it’s so different, but it’s so much simpler. It’s really elegant to see that.
Mike Delgado: Where did you learn those languages?
Emma Yang: Wolfram language I learned from the Mentorships program that I got involved in when I was around 12. And then for Swift, I went to a class, the Flatiron School for high school students. And there I learned iOS development. That’s where I got started with that.
Mike Delgado: For those girls who are watching and are interested in learning a programming language, what language would you encourage them to start with?
Emma Yang: A popular one to start with now is Python because it’s so much simpler. But I think you can start with … Once you do the more basic, you can build up to whatever you find because you can do almost everything and anything right now. If you start somewhere and even go to Java or Swift, there’s something you can do with that. You can really start from anywhere.
Mike Delgado: Awesome. Second question. What advice do you have for girls or people in general who are interested in beginning in data science?
Emma Yang: Find the place you want to be, but also to be broad in your interests and broad in your knowledge because there’s no one discipline that’s gonna stay the same forever, especially in computer science, because every year we have new advances. Find something you’re really good at, but also have a broad spectrum of interest. Not only in health, but also in the math side and finance. Knowing where you stand but also where you have interests is important.
Mike Delgado: Beautiful. You have been working in different projects on different teams. I’m curious what advice you’d have for leaders who are looking to hire data scientists. If you were put in a position, which I’m sure you will be, to hire a data scientist in the future, what qualities would you be looking for from that person?
Emma Yang: A willingness to learn and a willingness to take risks because now there are so many different things you have to learn. If you’re an expert in one place, you’re gonna have some other place you’re not gonna be very sure at. Being able to take that leap and cross that line and learn about something you’re not very familiar with or explore. That is a really important characteristic to have.
Mike Delgado: So being curious, being driven, are all key characteristics for you?
Emma Yang: Right. Yes.
Mike Delgado: Awesome. And then another question would be about where people can learn more about the work you’re doing, the research you’re doing and how they can help you along that process.
Emma Yang: I’m on Twitter at Emmayang78. You can also check out my website. It’s Emmayang.com. And Timeless’ website, which is Timeless.care.
Mike Delgado: Wonderful. And for those who are listening to the podcast … If you’d like to get a full transcription of today’s episode, you can go to ex.pn/emmayang. That’ll provide you with the full transcript, as well as links to all of the things Emma has mentioned today. For those who are watching the video here on either Facebook Live or YouTube Live, we’ll make sure to put those links in the About section or in the comments of the video.
So now, just two quick final questions I love to ask when I’m getting to know somebody. Emma, what spirit animal would you be?
Emma Yang: I really love cats. I love them. I think I would want to be a cat.
Mike Delgado: Nice. And then the next one is, favorite dessert?
Emma Yang: I’m really into Japanese desserts now, especially green tea stuff. So that’s my favorite dessert. Everything that’s green tea.
Mike Delgado: Like green tea mochi?
Emma Yang: Yeah. Definitely.
Mike Delgado: That’s awesome. You’re on Twitter, but are there any other social apps you like using for social media?
Emma Yang: I’m also on Instagram. I’m not completely on social media, but I use Instagram as well.
Mike Delgado: Okay. And then the last one is … One of your favorite musical artists you like to listen to.
Emma Yang: I really like 21 Pilots. And also, I’ve recently gotten into Troy Sivan’s stuff as well.
Mike Delgado: Beautiful. Well, Emma, thank you so much for being our guest on Data Talk today. For those who are watching, we have data talk happening every single week where we talk with data science professionals, movers and shakers. Emma Yang is definitely one to watch. Keep your eye on her. And to learn more about everything she’s doing, check out ex.pn/emmayang.
Emma, thank you again for sharing your insights with us. Thank you for all your work encouraging young girls to pursue data science. Just thank you for all the work that you’re doing.
Emma Yang: Thank you.
Mike Delgado: And for those who are watching, we’ll be back next week. To learn more, you can always go to ex.pn/datatalk or just do a Google search for data talk and you’ll find the Experian blog. Take care.
A 9th grader, 13 year old Emma is passionate about Artificial intelligence, Machine Learning, Robotics, Science, Computer Science, and Technology Innovation. In 2015, Emma won first place in the US and second place globally in Technovation Challenge, a global technology entrepreneurship competition for girls, out of 400 teams from more than 60 countries. Emma believes that technology can be used to help solve problems and make the world a better place. She is a strong advocate for STEM and would like to encourage all girls to explore their interests in science and technology. In 2016, Emma was named one of New York’s 10 Under 20 Young Innovators to Watch and Crain’s New York’s 20 Under 20 2016. Most recently, Emma was selected as one of the 100 Faces of Impact globally.
Emma excels academically and is a Davidson Young Scholar, a member of Johns Hopkins University Julian C. Stanley Study of Exceptional Talent (SET), and Wolfram Research’s youngest and first ever middle school mentee of the Wolfram Mentorship Program. Emma was the youngest participant of the White House’s Opportunity Project, representing Wolfram Research in bringing the power of the Wolfram Language to solve problems using Open Data.
Emma was awarded the U.S. Space and Rocket Center Space Camp Scholarship, Stony Brook International Piano Festival Scholarship, and the Michael Perelstein Memorial Discover Your Passion Scholarship for her outstanding achievement in Music and STEM. In the fall of 2016, Emma was selected as one of 500 exceptional students globally to participate in the Junior Academy of the New York Academy of Sciences solving the world’s greatest challenges. Emma is also a member of the school Robotics team who will be participating in the FIRST Robotics Competition. In 2017, Emma’s project won the Best of Fair award at the New York State Science and Engineering Fair. Follow Emma Yang on Twitter.
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