 Good morning nerd fam and welcome back to Palo Alto, California. We are at the Women in Data Science Worldwide Annual Conference here with live coverage all day long on theCUBE. My name is Savannah Peterson. Very excited to be joining you all for International Women's Day with a series of absolutely fantastic interviews. Kicking off this morning with Harshita. She is a grad student in machine learning at my favorite university on the planet, the University of Washington. Harshita, welcome. Thank you so much for being here. Thank you for having me here and thank you for the opportunity to be here. It's wonderful. I can tell just sitting next to you, the energy you're radiating. Is it great to be around your peers and all your fellow data scientists today? It's so beautiful, a lot of women, inspiring women. It's so beautiful to be here, lot to learn and still lot to learn. Yeah, there's always a lot to learn. There's a lot to learn. Speaking of learning, you've had quite an impressive academic journey. You're also the first woman in your family to study and take on this challenge here. Tell us about what that was like, the challenges you faced. So it definitely looks scary, but if you see on the other side, there has been a lot of positive things. I'm the first girl in my family and the first person in my family to come to the US and study in the US and especially studying Master of Science in Engineering. So it definitely looks scary, but if you see on the positive side, I have gotten a lot of learning. So I have seen everything from scratch. How do I get here? What do I need to do? Who do I talk to? So I think this only led to a lot of opportunities to question people, to get the right people to answer your questions. So it has been beautiful. I love that and you're obviously clearly optimistic. How did you get the courage to go down this path? So I always wanted to be in the science field and yeah, looking at US. So I always wanted to pursue my Master's in the United States of America and science is so beautiful here and women are being supported here. And yeah, I started my journey in 2021 where I prepared for the GRE exam and then I got cleared and now I'm studying at the University of Washington, Seattle. Oh, I love it. Loving the Husky vibes. How does your family feel? They must be so proud. Yeah, so one thing is my family were always supportive. My parents, my sister and my uncle, they were always supportive of me to study anything and to study anywhere. So that's one thing which was a very huge positive thing in my life. So they are really proud of me. I mean, even a single thing I do, they're very proud of me. I mean, how could they not be? It's very easy to see just sitting here next to you. Do you feel like you're seeing more and more momentum around women in school and data science, given your lens? Yeah, it's clearly so beautiful. You can clearly see at the conference it tells how many beautiful and inspiring women are over here. And even in my university, you can see a lot of good diversity present in the university or anywhere I go, whether it is internship or university or conferences. There are a huge amount of inspiring women in data science. Yes, and I feel lucky. I was telling the crew, actually, I'm a little intimidating coming in here because there's so much brain power and great energy and drive. You're now, it focused on machine learning, but your background was originally in power electronics, also impressive, but I'm curious, what was that career pivot like? What made you change your direction? So before I came to the U.S., like last year, like September 2022, I wanted to pursue my career in power electronics, but there was some unfortunate incident where I could not take my career in power electronics and I had the opportunity to explore. I mean, it again looks scary. Many of the people told me you cannot do machine learning stuff. It's just hyped up, but I thought this is what I like. I explored Python, I explored coding, and then I thought this is what I want to pursue for the next few years or forever. So I just started with coding and then, yeah, and then I was able to pursue internships in the same field. I love that. You know what you're passionate about. Advice for folks at home or young women who might be thinking about data science, go what you're passionate about. I mean, I don't think I've actually ever heard someone talk about Python, which is with as much glee as you just had, and I wish I could puddle that up. You mentioned internships and you've had some impressive internships. Tell us about how you went about getting those internships and where you've had the pleasure of doing some work at. Yeah, so I started applying for internship from, like I was late. I started applying from Jan 2023. So from September, I started learning machine learning and then I was so keen at learning what it is, what is Python, what is data science, and then I started applying for internships and I performed a data science internship at Quadrant Technologies during the summer where I worked on Microsoft Cloud Technologies and during my fall in 2023 from September to December, I got an opportunity to work as a machine learning research engineer at the Robert Bosch Technology. Yeah, so this both was, it was a really good experience. What's the energy like, you know, machine learning and AI is really having a moment right now in terms of the hype curve, we're all waking up and the technology is really getting applied to our everyday lives. What was the energy like on these teams that you got to intern with? I mean, like everyone's so open to learning because there's always, you need to keep up with the technology. So every week there's a new technology. So what I saw in the team during fall at Bosch, everyone reads paper every day. So they want to keep up with the technology and they keep talking to the peers, work on new projects, and I think it's really good to see that everyone in this field are continuously updating themselves and it's beautiful. It is beautiful. I feel like there's a real intersection of industry veterans who've been working in AI and ML for 20, 30 years and fresh excited faces of your generation of students and also people in the workplace and even entrepreneurs that are really getting to get excited and to dig in beyond your impressive academic backgrounds and your fantastic internships and everything else you do. I'm not exactly sure how you sleep. You've also been selected as a delegate for Harvard for a really special project. Can you tell us a little bit more about that? So HPA is a conference held by Harvard University. So every year they select a certain number of delegates from around the world to talk about their community or their interests. So I represented my community of women in technology and I also represented my country, India. So there were a lot of people from various countries, I think more than 40 plus. Wow. Yeah, and they were so inspiring in various field. Like I got to talk about sustainability. I got to talk about climate change, healthcare in different countries and about different countries. So it was really nice experience. How did you find out about this program? I always wanted to go to this program since I'm in the US itself and I could not miss it. So I was waiting for the registration to begin and then I just clicked and applied it. Jumped on it. Wow, I'm sure they were very lucky to have you there. Is there a particular space or application of AI that really gets you personally excited? Healthcare industry. So healthcare industry requires, yeah, AI in healthcare would be a huge, huge change and requirement because it can help save a lot of life. I mean, currently I'm working on a mental health project which is AI based project to provide mental health accessibility to everyone. Wow. So using AI to provide the right amount of, yeah, to provide accessibility to everyone. So that is one solution which we could think of and providing healthcare accessibility to many people using artificial intelligence is very important. We could save a lot of life. So tell us a little bit more about how that works. Tell us about your project. So basically, so most of the mental health problems right now, yeah, everyone faces mental health issues. I do face anxiety myself. So major pain points in this industry are early detection and early detection. So people are facing a huge issue in detecting the symptoms and also going to therapy costs a lot. So our solution, I'm working on the solution where it'll be easily accessible for everyone. And then the app will be there for you every time, anywhere. So yeah, that's what I'm working on right now. An emotional support app, to agree. Yeah, always there for you. Oh, I think that's so important. As someone who's neurodiverse and struggled with a menagerie of mental health challenges over the course of her life. There are moments when there isn't someone who can pick up the phone and having a tool like that, especially accessible when mental health care is extremely disadvantaged and favors the privileged in so many different ways is really powerful. Thank you for working on that. I didn't even know that you were working on that when we sat down and started chatting. That's really powerful. So how can people find out more about that? How can they follow your work? So they can follow me on LinkedIn. I'm currently still working on the project. So I'll soon launch it. So we are a team of four and we are still working on it. And once we launch it, I'll put it on my LinkedIn post. Excellent, okay. We're going to have a lot more LinkedIn fans now, including me after this session. I want to talk also about as if you haven't contributed to enough things. You also work with some NGO activities. You're all about empowering young women in STEM. Tell me more. So as a woman myself and then being the first to come to the US, it was really difficult to actually understand how to come. The awareness is very important. Awareness about, okay, there is something called data science, but there is something called technology. Some of the people don't even know that. So I, internet was a huge friend to me. I kept searching, searching. Even the Harvard conference, I kept searching, is there something I can do? So I think some people do not even have internet, do not have access to all of this. So that's why I wanted to get into this and volunteer with different NGOs to bring this to the people, younger girls and underrepresented communities. So that's why I was actively involved in NGOs. What does it mean for you to be able to talk to young women like you and get them excited about science? You know, it's so beautiful because I think every kid is so excited about science experiments, different colors and liquid turning into gas. So recently I went to this science explorer program. I volunteered at the UW Science Explorer where we went to elementary school nearby in Seattle. And then we showed them how to make a laugh. Yes. They was so excited. You make a little volcano and do the whole thing. Oh my gosh, how cool. And so you get to see that moment when they realized science is magic, except real. Yeah, it was so beautiful to see that. And it's really nice that they're so open to learning what it is, what is science, how to get into that. So I think we need to go to every corner in a triangle, like an inverted triangle, reach every sector of the people and then tell them that, yeah, there is something called science, you can do it. Yeah, absolutely. What a great message. There is something called science, you can do it. Anyone can do it. Hopefully tools and things like AI and ML will help even more people get involved in science. And also see how science applies to everyday lives. To your point, science and healthcare isn't just about medicine. It's also about a variety of different tools that doctors and healthcare providers use, mental health, holistic wellness, all of it. Oh my goodness. So how do you balance all of these hats that you wear? What's your advice for people who are as driven to achieve as you are? So I have three more, two. So one thing, it's risky to not take a risk. I always think it's risky to not take a risk. And second, always say yes. Yes. So if not you, someone else is going to say yes to that. So why not you, just start with an S. And thirdly, so there is this thing which made me feel better whenever I think about any obstacles I'm facing or I'm going through something, I always think about if one door shuts, look for the windows that open. So if one door shuts, look for the other windows that open. So you always have so much more opportunities. So if you lose on something, it doesn't mean the end of the world. You have still so many opportunities right in front of you, say yes. Oh my gosh, great advice for anyone interested in doing anything really. Do you have any advice specifically for women in data science watching this interview, seeing you, getting inspired, maybe thinking about going to UW? What would you tell them right now? So if you're interested in data science, so there are so many things in data science itself. So machine learning, and then nowadays deep learning. So start with Python, and it's really exciting. Even I started at some point, everyone starts at some point. It's not like everyone knows everything. So everyone starts at that point zero. Start now. Start learning Python. Start knowing what this is, what applications you like to solve. And then yeah, start now. Just get started, I love that. There's a sign here outside the D-School at Stanford if you go for a walk today. And it's one of the more photograph signs at Stanford, and it says you are here. And it's just one of those little pins, and it's really start where you are, essentially. And so you're doing that. You're advising everyone to do that so well. Since today is International Women's Day, is there, or are there any women in your life you would like to give a little shout out or say thank you to? My mom and my sister, they have been a huge support to me all the time. So they tolerate me, so it's really nice. I think it would be easy to tolerate for the record. How they support me all the time, so I really want to thank them from the bottom of my heart. Well, we give your mom and sister a shout out here on theCUBE. Last question for you. Do you have any advice for allies? I know there are a lot of great men and other folks in the world who do want to support women like us and don't always know how. What would you tell them? Do you have any examples or things that come to mind when you think of the ways you've been supported by any agenda in your career path? Yeah, so there are so many organizations like Women in Data Science, Women in Data Science, Pew, Women Tech Network. So all of those organizations work so much together to provide support to women. So look for any communities nearby, in your region or something like that and they'll always be happy to include you or include your work or yeah, just go there. There's always someone who needs your help and there's always someone who'd be happy to listen to you. So yeah. Well said. Okay, bringing us back to today to wrap us up here. You are excited and I believe in charge of the poster blitz. What does that mean for the attendees at the show? So they'll be, it's going to be beautiful because today is the first time we're going to have poster session at the Central Conference at the Witt-Stanford University. So there'll be 23 young women presenting their research to the audience. So there'll be a poster blitz session where they'll get just one minute to talk about their research and then during the reception they'll have the opportunity to present their work using the posters. Oh my goodness, that's so exciting. I'm going to have to sneak in there. We're going to have to get the crew. We're going to have to get some b-roll of that. I think that sounds very, very exciting. Harshita, thank you so much for being here. You are such an inspiring woman in data science, also proud Husky. I'm going to be following your LinkedIn. I'm actually going to set up an alert so I can keep an eye on your very important mental health work. And thank you for being a truly fantastic and inspiring start to our day here on the show. Thank you so much. Thank you so much for having me here and it was really nice to meet you. Happy Women's Day. Yeah, happy International Women's Day. And happy International Women's Day to all of you out there watching theCUBE on our all day long live broadcast from Stanford University in a beautiful Palo Alto, California. My name's Savannah Peterson. You're watching theCUBE, the leading source for awesome women in tech coverage.