Dr. Denise Gosnell is the Chief Data Officer at DataStax, and an absolutely brilliant data scientist. Her impressive resume includes prestigious roles in the healthcare industry, where she developed software solutions for permissioned blockchains and applied machine learning to graph analytics and data science.

Her career is founded on a deep passion and unmatched capability for examining, applying, and advocating for the applications of graph data. She has patented, built, published, and given speeches on the most nuanced aspects of graphic theory.

Her knowledge base is both in-depth and wide ranging, spanning dozens of topics related to graph theory, graph algorithms, graph databases, and applications of graph data across all industry verticals. She is a leading expert in graph technology, to put it lightly. 

Meeting Dr. Gosnell at the Perfect Moment to Create Synergy

I had the pleasure of meeting Dr. Gosnell when it made the biggest difference possible: right when I was in the middle of launching my first startup, Wish Dish. After I was introduced to Machine Learning, a subsect of AI, I was absolutely fascinated and wanted to learn everything I could get my hands on. 

This new interest prompted me to attend a conference in Nashville. Once of the brilliant people I had the pleasure of meeting there was Denise. A few years later, we serendipitously reconnected through a mutual friend, who reintroduced us via email. I thought I recognized the name and put it together. Over the past four months, our team at BW Missions has been able to work with her on the launch of her book.

Dr. Gosnell’s one Away Moment: A Mentor who Made all the Difference

Denise’s One Away moment is the catalyst that sparked the beginning of her illustrious career in Graph Technology. Like many of our podcast guests, this experience centered around human connection and one person who changed everything. During the first year of her graduate program at East Tennessee State University, she met Dr. Haynes, one of the most decorated mathematicians of modern history, especially in graph theory.

“Dr. Haynes is one of the most inspiring women in mathematics that I’ve had the chance to get to work with. She’s probably one of the most decorated mathematicians of modern history, especially in graph theory.” 

Dr. Haynes completely transformed Denise’s conception of the world of data, and the limitless potential this technology holds to reshape the world. During her Masters’ Degree, Denise worked closely with Dr. Haynes on subjects that would shape her professional path and most passionate interests. 

Through this pivotal mentor, Dr. Gosnell got to meet several other renowned experts in the field. This new and exciting passion launched Denise onto an exciting trajectory that’s led to her current field of research and high-stakes professional responsibilities where she has the power to make a huge impact for the next generation of data scientists who follow in her footsteps. 

Top 5 Takeaways From Dr. Denise Gosnell

  1. Keep an Open Mind to the Idea of Changing Direction
  2. Don’t Be Intimidated by the Top Experts in Your Field
  3. Look for Practical Applications to Give Abstract Concepts Real-World Applications
  4. Find A Mentor Who Truly Believes in You
  5. Innovation is the Key to Catalyzing Concrete Change

As the Chief Data Officer of DataStax, Denise has the unique ability to channel her wide range of expertise and experiences for real-world applications that transform the landscape of her field. She translates her rigorous, high-level body of knowledge into making more informed, data-driven business decisions that yield maximum results for her company. Since she joined DataStax in 2017 to create and lead the Global Graph Practice, she’s been an integral part of building a team of experts who generate some of the most robust and sophisticated distributed graph applications in the world. It all started with one moment, one mentor, and one spark of inspiration. 

At a more personal level, Denise is incredibly unique. I’ve never met anyone like her, and I’m incredibly excited for you to hear her story today. Listen to her story in full in the YouTube video at the top, on Spotify, or on Apple Podcasts. A full transcript is available below for your reading convenience. I hope you enjoy this illuminating conversation as much as I did! This is seriously fascinating stuff.

Transcript

BRYAN WISH: How would you describe your One Away moment?

DR. DENISE GOSNELL: I love this question because it was such a fortuitous moment that I had. My One Away Moment occurred when I had was been locked out of my graduate courses in mathematics as a first-year freshman during my Masters program. You ha to take certain courses like Real Analysis and Number Theory, but I was locked out of all the required things. I had to sign up for an elective. There’s a very interesting connected path that forms solely because of this.

I had to take a class called Graph Theory because that’s all that was open. To be honest, I’m not the kid who reads the textbook before class. I thought graph theory was going to be business analytics; bar charts and diagrams. It turns out that graph theory, in the world of Dr. Teresa Haynes, who introduced me to it, is all about connected data and modeling the edges or the relationships or the links between data. It opened up my mind to this whole new world of understanding data that has become my cornerstone of my career and passion. 

From working with Teresa, there’s a directed connected line that got me to being on your podcast today.

BRYAN WISH: Talk about Teresa and her significance as a teacher and professional and someone you clearly followed into your professional career.

DR. DENISE GOSNELL: Dr. Haynes is one of the most inspiring women in mathematics that I’ve had the chance to get to work with. She’s probably one of the most decorated mathematicians of modern history, especially in graph theory. She is leading the way from East Tennessee State University up in Johnson City, Tennessee in the middle of nowhere, but she has some of the most connected and highly visible research on the graph theory and mathematics world that anyone who follows that space has found. 

There’s been some really cool work about new proofs and counter examples coming out with a long time theory from Hedetniemi, who’s in Clemson, and she has a ton of other connections with graph theorists around the world. That led me to learning, very directly, two specific things about her. First of which I learned how quickly how challenging she can be to get to work with. At the same time, how much she believes in her students and wants to lift them up to get them to achieve something that they never thought was possible. 

Getting to work with both of those dynamics through my many year collaboration with Dr. Haynes has been a really strong foundation to build my career on. 

BRYAN WISH: Was it something about her, beyond the frameworks and technical pieces, that really drew you?

DR. DENISE GOSNELL: Dr. Haynes’ style with her students is something I’ve never experienced before. It was specifically that we were a family. Her graduate students who were a part of the cutting edge work and research and papers of the year, we always met in her office, which is tiny, especially considering the massive bookshelf that she has to the right that has her hundreds of publications organized by year. It’s insane, but this office is maybe not even 10 feet wide. My memory makes it feel like a broom closet, but I know it was a lot bigger than that. She had, on one wall, all of her hundreds of publications. 

On the opposite wall, she has a white board. It’s a longer office. It’s narrower and then very long. We would sit in there and we’d have chairs along one side and we’d be focused on the white board just digging into every nook and cranny or corner of this new mathematical piece that we’d be trying to understand; a brand new theory of math that we were inventing from her office. It was really fun to be doing that together. We’d sit in there for hours and get lost within the math that we were working on. Her style of teaching felt like bringing us together as a family. and making it in such that close knit quarters was a different experience that I’ve never seen anywhere else. 

BRYAN WISH: For context, were you always into math or you had to go and have a math requirement and it led you to her class?

DR. DENISE GOSNELL: I totally was. This experience was for my Master’s in math. At this point, I had definitely self-selected to say that this is what I wanted to do. I was always the kid who was wanting to understand patterns and numbers. Once I found out about Rubik’s cubes, I then had to not only solve them, but solve them really fast. I was wanting to compete with people in solving them. Math and the beauty and patterns of numbers have always fascinated me ever since I can first remember. 

BRYAN WISH: You took her class. What happened next?

DR. DENISE GOSNELL: I took the class with Dr. Haynes and within the first five minutes, I had this realization that my understanding of the world and data was completely changing. It was like a moment of epiphany for me. I immediately fell in love with this new area of math and went on to work with her during my Master’s Degree. We published four papers there.

Towards the end of it, she helped get me connected to go to the University of Tennessee to continue my work in graph theory. However, that that work was in the computer science department. She helped get me sponsored by another NSF fellowship to go to the University of Tennessee in computer science, but I didn’t know how to code. Those first years, I found an amazing network with the well-renowned now Dr. Catherine Schuman of people who were willing to help support me from both ends.

I was advanced in the theoretical space from computer science, but obviously had a lot to learn when it came to picking up programing. I was able to build a network there and worked with Dr. Michael Berry for my research in social fingerprinting. Towards the end of that research, Dr. Berry connected me with a gentleman named Ted Tanner. Ted was coming after working for Steve Jobs at Apple. He was starting a startup and then that’s when you and I met, Bryan Wish. 

I was working for Ted Tanner building out a graph of the entire economy of the healthcare system; patients and the doctor’s they visited and the claims they filed with insurance, etc. There’s a short path from this to the podcast. That path is the software, I was using at the time, was a very popular open source or framework called the Titan Graph Database that was invented by a gentleman named Dr. Matthias Broecheler. When DataStax acquired his company, also co-founded by Dr. Marco Rodriguez, after a year of them owning that company, I followed over here to DataStax to work with that team. Dr. Matthias Broecheler and I are now publishing a book on the uses of distributed graph databases and distributed graph data. That is where you and I found each other again. That’s why I love the premise of this podcast because at the end of the day, if I hadn’t been locked out of real analysis and I hadn’t have taken that graph theory course, I would not be writing a book with Matthias who is known as one of the most infamous researchers of this time. 

BRYAN WISH: It’s like that Steve Jobs quote that he gave at Stanford. He said, “I had to drop out so I could drop in on the things that mattered to me.” That was my take away. He dropped in on things that really interested him. It was maybe a coincidence or not, but similar to your story, you were shown a different way for a reason. What has the work on DataStax afforded you to apply graph theory in ways you never thought possible? How has your relationship with Dr. Haynes established maybe even deeper or stronger because of your direct work in the field?

DR. DENISE GOSNELL: Coming over to DataStax and working with our graph product has opened up the door to me working with hundreds of teams around the world. Honestly, they’re the apps you probably have on your phone. We’re all designing their backend systems for high availability of data. Being able to work with teams around the world in the hundreds helped me see patterns. It helped me see how similar the thought processes are for people who are new to graph technology and the types of problems they want to solve. That recognition of patterns is the backbone of the book that Dr. Broecheler and I are writing because we abstracted the main patterns of usage for graph technology and wanted to make that available to everyone else so that they could get started faster and have a better user experience and learn new, cool technology. That’s what working here at DataStax has afforded me. It’s also a passion of mine. 

BRYAN WISH: Have you been doing things you never thought you’d be doing? 

DR. DENISE GOSNELL: Every part of my day, when I’m working with graph technology, is applying it in a way that I never envisioned. We’re tapping into the creative minds of people who want to use it to solve their problem, and it’s fascinating to see what people came up with. For an example, there was an airline that we were working with and that airline wanted to understand which major airports they should make as their home for their flight crews and their entire operations. When you go through and map in all the routes of how their planes fly, we were looking at well over 100 trillion different combinations of paths for how these planes are being routed around the world. They needed to translate this path problem into how you would select home airports for coverage. Only because of my background from working with Dr. Haynes and understanding different problems in graph theory, were we able to come up with a really unique solution that transformed it into a different specific graph theoretic solution and solve that for them in a system that can do it in real-time or near real-time. Any engineer knows that real-time is not actually a thing. 

It was really fascinating to be able to pull into listening to a user requirement on a very simple problem that sounds like paths like routing airplanes around airports, but in recognizing the real business solution they  need, translate it into a different graph problem to be able to solve it for them in a time that was going to be computationally feasible. That was one of my favorite examples of using graph tech in a way that wasn’t expected. 

BRYAN WISH: The technology has such a human component from a macro level. It can tough people in visceral ways across the board with how you simplify things and connect things to relational patterns. 

DR. DENISE GOSNELL: That’s exactly why the graph industry is taking off. The human connection to understanding the relationships between data is so much more meaningful than looking at data in rows and columns like in a spreadsheet. Working with data in a conceptual way that models it all the way down to how it’s stored on disks and then used in application is such an easier pathway for understanding and reasoning about connected data than using more traditional solutions. Connected data makes more sense to humans and that’s why people are turning to graph technology for using it. 

BRYAN WISH: It sounds like you’re at the cutting edge of putting graph technology at the front of the market. What’s that process like?

DR. DENISE GOSNELL: The process for getting graph technology widely adopted in the market is trying to move as fast as we can of making it much more usable. At the end of the day, people want to turn to graph technology because graphs make sense in their data and now we need to find a really easy way to use that same structure in a computer on disk. We’ve got a ton of brilliant innovations that are out there and what we’re learning now from some of those early adopters, who were using those technologies, that there is a need for easier or more standard ways of using graph data and applications. I really like to see that the community is pulling us towards that instead of us pushing it onto them. They’re pulling us in getting easier tools. As an example, you can imagine drawing the entities or the vertices of your data and then the edges between them. Having that drawing, if you do it within a Chrome web app, actually be the persistence of your schema all the way back on disk in your actual application. Making that as seamless as possible is what the industry is asking for and where I know there’s a lot of really exciting innovation coming from DataStax in that space.

BRYAN WISH: Let’s circle back to Dr. Teresa Haynes. How has that relationship grown?

DR. DENISE GOSNELL: She is a champion. I still talk with her very frequently today. Even so much so that there was a recent announcement of one of her colleagues and one of his early proofs and finally being disproved. We were talking about that in the past few months. When I do get the chance to return to the east Tennessee area, I like to make sure I go in and talk to her class, which I’ve done that once. We’re trying to find a window when I can come back. I definitely continue to reach out to her in addition to that entire team of researchers that we had. We consider ourselves the OG graph crew from back in 2010; those of us who are around that white board in her office working on different graph theorems and proofs. Most of us are out in the industry today and we still stay connected just like a graph would. It stays connected. We still have a network and not only do we still have a relationship with Dr. Haynes but we still have a relationship with each other because it really was a great, tightknit family.

BRYAN WISH: The direction that she gave you for your own life, has that inspired you to give back in a similar way one day? Or do you find yourself constantly mentoring young men and women on graph technology?

DR. DENISE GOSNELL: Yes, she has inspired me to think about how to give back. I do find that why I’m doing what I’m doing is always an attempt to give back. To mentor young women and to help future computer scientists, that’s another reason why we wrote this book. I wanted to show the rest of the community what you can do when you collaborate together with seemingly like-minded but at the same time, people who would take very different approaches to problem solving; namely myself and Matthias. The type of work we can create when you try and solve problems together and what that process can be like and what the end result can be. Through this work and the book that we’re writing, I’d love to encourage and inspire anyone else in your audience to think about what they’re most passionate about and see what they can do to get their work out there publicly.

BRYAN WISH: If you could go back to where you were as the woman locked outside your math class having to find a new direction, what advice would you give to someone in those similar shoes? 

DR. DENISE GOSNELL: It is just as useful to know what you don’t want to do than to have a full plan for the next five years. At any time, I had to make a decision in my career. The decision looked like a choice between one or two options. One option being something that I knew I definitely didn’t want to do and the other option looking interesting but it was scary and I didn’t really know what it entailed. I didn’t have a clear direction on what was going to happen. Solely by eliminating and knowing that that one path wasn’t for me, I took a risk and I leaped. It’s turned out to make the world of a difference. Learning what that is for yourself and drawing those lines to eliminate choices is just as helpful as thinking you have the next 5-10 years ironed out. 

BRYAN WISH: We have to connect the data points, right? 

DR. DENISE GOSNELL: Exactly. Keep connected.

BRYAN WISH: Where do people find you?

DR. DENISE GOSNELL: I’m very active in two places. You can always follow me on Twitter which is @Dr. Denise Gosnellkgosnell. Happy to get into some fun conversations and I love the community that’s been engaging with me on there. I also do a lot of posting on LinkedIn. My book is being published by O’Reilley Media. It’s on their platform now but you can also find it on Amazon. It’s called The Practitioner’s Guide to Graph Data by myself and Matthias Broecheler.