 Live from Houston, Texas, it's The Cube, covering Grace Hopper Celebration of Women in Computing. Welcome back to The Cube's coverage of the Grace Hopper Conference here in Houston, Texas. I am your host, Rebecca Knight. Today we are joined by Judy Logan and Karen Mathis, both of the Institute for Computational and Mathematical Engineering at Stanford. Thank you so much for joining us. Oh, our pleasure. Thanks for having us. So I want to start by asking about a conference that you're both working on organizing at Stanford, Women in Data Science. It's happening for the second time this year. How did this conference come about? What was the need that you saw? Right. Well, the conference came about as we were exploring ways to improve the percentage of women in areas of computing and data science and engineering. I mean, the numbers are, as you know, very low. They've even gone down since the 1990s when I was back in school. And so what we wanted to do is support women who were getting into the field for the first time, but also support women who were in the field because attrition is quite a big challenge. And so we wanted to, we really have three goals. We wanted to inspire women and share rockstar women who are doing amazing things, who often don't get the same level of recognition that their male counterparts do. We wanted to educate everyone on new technologies around data science. And we cast a broad net around data science so it's everything from machine learning and AI, cybersecurity, data visualization, all sorts of different areas. And then the third thing is connect and allow women to network. And I think that's really powerful. Women gave us great feedback. They enjoyed that at the first conference. But we were talking about this with a few of our external partners, which I work with at Stanford. And we were talking with some people at Walmart in particular, and they loved this idea that we would pilot something together. And then within four months, we actually had our first conference last November up and running. In partnership with Walmart. Not a typical company that you'd think of when you think of computer science. Exactly, but we've had some alumni from Stanford, ICME going to Walmart in Walmart Labs. Some amazing people. And they, as a company, really need to build up their core competency around data science. So they want to- It's the biggest logistics company in the country. Exactly, yeah. Absolutely. I mean, it's a huge area for them. And so they want to attract more talent, get their name out there. And so they've been, in fact, they've continued to support us this year. They're one of our strongest partners in this conference. And the conference is not just- I heard the Walmart Labs folks say that they're actually looking at what the next generation of retail looks like. And so that's a lot of what the Walmart Labs people are looking at. So they're doing a lot of data science work. That's just, it might not be obvious, but it's really out there. Well, in talking about the next generation, I mean, so many, you both work at Stanford, one of the best computer science programs in the country. And so many students are majoring in computer science, but it's computer science and. So it's another discipline that they're adding on to their computer science. What's driving this trend? I think that there's so many industries that need these core skills. So in our institute it's applied mathematics, computational mathematics, combined with statistics and computing. It's really that intersection of all those areas. And we see that every field from retail, like Walmart, to oil and gas, financial services, certainly in the medical field, every industry really needs to have these kind of capabilities to drive their business to the next level. And what we hear from the students is that they love to be part of this interdisciplinary approach, to work on teams with people with different backgrounds coming together to solve these really important business and engineering problems. And the conference is not just at Stanford. That's right. So we actually, the first conference we discovered that there was more demand than we really knew about. We actually sold out very quickly. And then we surprised ourselves because we added a live stream and then 6,000 people joined us on the live stream. And so we thought, well, how do we sort of harness that? How do we take that and then allow, you know, try to bring this to more people? So we came up with a WIDS ambassador program and where we are offering the content, the live stream content and then some support materials to folks who actually want to bring WIDS to their local environment. So for instance, in New York, we're working with SAP and NYU and Columbia University. And they're putting on an event that's just as big as the Stanford University event. It's gonna be 400 people large and they're actually going to have some live speakers that are different from our speakers as well in addition to taking the live stream. So they're creating their own event that's more relevant for their target audience. And then similarly, we actually have conferences going on, for instance, in Beirut, in Lebanon at the American University of Beirut. They're actually having, they're featuring Arab women in data science for an entire day. And then they're joining us, their nighttime is the beginning of our day and they'll join the live stream just for the beginning of our day. So it's incorporating all the time zones. It's incorporating all the time zones. And even in places where the conference timeframe doesn't work at all, like in India and actually in Chile where February is a terrible month to host a conference, they're actually doing delayed broadcast events. So they might be doing events a month later. So they'll cherry pick or take some of the live stream content and then combine it with local content. We found last year we taped all the sessions and made it available. And this year we'll do the same thing as well as all these events. If they have some great content, we'll make that available as well. So it really become this core base of inspiration and education that people can enjoy, not just during the conference, but for a long time to come. Yeah, and a source for great content too. I mean, because all of these different areas that were who are getting their own speakers or other things to talk about besides the base conference. For instance, in London, they're going to have an event at the Isaac Newton Institute in December. And so their content, we're going to upload to our Women in Data Science YouTube channel because, and then we can actually share all of that great content from all of the sessions around the world. And I think that that's really exciting. People can actually look through it all. What made it really come home for me is that one of the new students in our program this year, a master's student from India, from IIT. She had found the videos online. She learned about ICME in Stanford and she applied because she was inspired because of the videos to go into data science. So it's having a big impact. It's powerful. So that to me was really exciting to see, oh, this really is getting out there with a really broad reach to hopefully continue to grow like a movement over the next few years. I know this young woman, she's from India. She was living in Singapore and she found us. And so having that global reach and that global impact is something that, it really, it's a very exciting time. I want to ask you both as veterans of the technology industry, in between you have worked at Apple and Netscape, Cellular One. You're both consultants at Indigo Partners. So you've been in this industry for a while. What's it like? Is it as bad as we hear? Are things getting better? What are your impressions and what are your hopes and dreams for this next generation of women who are coming up? As an engineer, I'd love to get your take. Well, I started out in systems engineering. I worked in telecom for a few years and I think it's changed dramatically since when I started out. So I'm very excited to see all these women, young women here today. And I think they have great prospects. I definitely felt much more like there was blatant discrimination. I mean, often well-meaning, not, you know, nasty intended, but for instance, one time when I was starting out, all the men, I was always the only woman in engineering groups. All the men said, hey, you can join us if you want, but we're going to a lingerie luncheon. Oh my God. I mean, the concept, I didn't even know what it was. I still don't know what it is. It sounds like a bachelorette party to me. It was in a big hall where these women in lingerie served you food. Oh my God. Yeah. And that was a team-bonding exercise. Okay. All right. That was kind of us. So did you go? I did. And I, you know. Because you would have missed out on the conversation otherwise. Right. If you're talking business, absolutely. And they were great guys. And I loved working with them. You know, they all had their calendars that at the time there were pin-up calendars because engineers at conferences were given free, girly calendars. And, you know, as long as I kept it light and talk business with them, I was one of the gang. Right, right. So I, there's a lot of instances like that. But it definitely sets a tone with those kinds of calendars hanging in the cubicles. And it's- Absolutely. I think now what we face, and it's been discussed, I'm really glad a lot of the sessions here is those implicit bias. It's those much more subtle these days. And in fact, some people wouldn't even consider themselves bias, but it's filtering in all sorts of ways. You know, there's studies that show that just by changing the name from male to female, there's a different and less positive reaction. And so those are the kinds of implicit bias challenges, I think everyone still really faces. Just not as over as lingerie luncheons anymore. Well, Karen Mathis, Judy Logan, thank you so much for joining us. This has been a real treat talking to you both. Thank you so much. Nice to talk to you. I'm Rebecca Knight, your host for the Cubes coverage of the Grace Hopper Conference here in Houston, Texas. We will be back after this break. Was there a moment? Did you ever think about-