Women in Tech: "The key to overcoming challenges is to see them as temporar...

Women are becoming an increasingly important part of the tech landscape, but they still have a long way to go in terms of equal representation and treatment in this male-dominated industry. devmio seeks to empower women in tech by offering a platform for them to share their stories and inspire others.

Every Wednesday, we celebrate women in the tech world. This week, we’d like to introduce you to Zuzanna Stamirowska, CEO of Pathway.com.

Today’s Woman in Tech: Zuzanna Stamirowska

Zuzanna is the CEO of Pathway.com, a data processing framework for building​ real-time and reactive data products that scale, enabling real-time machine learning. Zuzanna is the author of the state-of-the-art model for forecasting maritime trade published by the National Academy of Sciences of the USA. While working on this project she saw that the digitization of the logistics industry was slowed down by the lack of a software infrastructure capable of doing automated reasoning on top of data streams, in real time. This was the spark to launch Pathway. She holds a Master’s degree in Economics and Public Policy from Sciences Po, Ecole Polytechnique, and ENSAE, as well as a PhD in Complexity Science.

What first got you interested in technology?

I was very curious to look at how small, “local” interactions and incentives lead to the appearance of systems. We talk a lot about the famous butterfly effect, well, how does it really work? I wanted to understand. So I became interested in Economics, and Game Theory. It may be helpful to mention that it was around 2008, when the Financial Crisis was about to start.

Now, when you try to understand the butterfly effect, you quickly get into graphs, you start seeing graph structures everywhere, then you see them overlaid, evolving, then you get into ML to find generative models of systems, and eventually real-time, because well… the world is a living creature.

What path did you take to get to your current position?

My pathway was fluid (not to say curvy), but I mostly followed my interests. I studied at Sciences Po, the school for French politicians, where I focused on economics. During my 3rd year I spent a semester at Stockholm School of Economics studying game-theory, and worked in a tech startup which developed the first online platform for hackathons - Spoj.com. This was the place where all the world’s top competitive programmers trained their skills, and where I met one of my current co-founders. After that, I knew that the way to make a difference in the world was through technology and that I needed to pursue a career in tech. I applied for a Master’s degree in Economics at the engineering school Ecole Polytechnique.

After graduating, I decided to do a PhD in Complexity Science. I am the author of the state-of-the-art model for forecasting maritime trade published in the Proceedings of the National Academy of Sciences of the United States. While working on this project I saw a blocker for digitization of the industry which was in the data processing layer - specifically the ability to perform reasoning on top of live streams of events. This was the spark to launch Pathway.

What are you most proud of in your career?

I’m most proud of creating Pathway. Absolutely. We’ve been able to build up a brilliant platform, with support from folkslike Lukasz Kaiser (OpenAI), and we’ve now got a number of high-calibre transport industry customers onboard.

One thing I learnt over my career is that once you get the data model right, the rest becomes so much easier, and that a finite state automaton is really not the way to go for logistics and supply chains.

What does your typical workday look like?

One of the interesting parts of being a CEO of a deeptech startup in the fast moving real-time data processing space is that each day of my work is different. One day I may work from home and be 100% focused on some strategic tech decisions, and the next day I may need to travel abroad to meet with clients, and end the day with a dinner with investors. On a calm day I usually start work around 9am, ideally I catch up on my emails and prioritize topics for the day, then I get started with the key value-bringing task that we have at hand. I tend to have more external communication in the afternoons, especially since a number of our partners are in the US or Canada. I like to spend a lot of time coaching my direct team, to empower them in leading their own teams. To the extent possible, I tend to spend the evenings with my family.

In your career, what role does AI have in the transport industry? What are some use cases that the average person may not know about?

Real-time machine learning comes in very handy already at the stage of understanding where things (trucks, containers, parcels) actually are. Getting there is already big for the industry.

Specifically, de-noising ‘jumping’ GPS signals is tricky, because you don’t want to confuse the noise in location data with actual anomalies - which may represent, for example, theft. Having one source of truth replaces numerous phone calls and emails.

The next step is learning and structuring the transportation process - so automatic building of the data model directly from the data, and making sure that it evolves as the real-world operations evolve. One thing I learnt over my career is that once you get the data model right, the rest becomes so much easier, and that a finite state automaton is really not the way to go for logistics and supply chains.

Once we know where the things are, and we have the data model, we can be content with “the current state of affairs” and start predicting the future. A very well known example are ETAs (Estimated Times of Arrival) which are key for the delivery of your parcels by Amazon (for you not to get upset!), but also for the orchestration of the entire world trade flows. Some lesser well known cases are ETAs linked with predicting destinations of ships - this information may be used for buying futures on some raw materials and in general, for fun economic intelligence.

Who are some of your role models?

Hard to say who exactly I see as role models, but there are some people that I admire. One of them is Jacques Attali, for the role he’s played in history and how he maximized his influence. I had a chance to meet him in person and he certainly does make an impression.

Another, this time historical figure, would be John von Neumann.

As an industry, we must make sure that our community of practitioners is inclusive and diverse, which includes gender issues but is not limited to them.

How can the industry help support and retain women in tech?

Personally, I think we need to have more women who are extremely successful in their careers and who are visible to inspire peers and future generations of women to join this exciting field.

As an industry, we must make sure that our community of practitioners is inclusive and diverse, which includes gender issues but is not limited to them. There are many ways to begin addressing the underrepresentation in tech, including developing a pipeline of talented individuals, ensuring that career paths offer an exciting trajectory, and fostering an environment where people feel valued and can flourish.

What was the biggest challenge you have faced in your career, and how did you overcome it?

I think I could write a book about the challenges I have faced, but I would consider it only after getting to Sergey Brin’s level of success [laughs]. No need to dwell on them when there is so much work to be done in front of me.

Regarding the second part of the question, I think that the key to overcoming challenges is to see them as temporary obstacles, zooming out to see the full spectrum of possibilities and outcomes, and then decomposing them into smaller actionable steps. This approach saved my neck multiple times.

I am excited about low energy computing and anything that can get us there. If you think about the brain, it performs advanced operations in real-time while being very energy efficient.

What tech topic would you like to learn more about?

I would like to understand how personalities form in people at the very early stage of their lives and how it impacts the ways in which they learn. I think that knowing the intrinsic drivers of oneself, and of others, makes collaboration way easier. I am not sure if neuroscience counts as a tech topic - for me it does :-)

Currently, what would you say is the most exciting thing about your career path? What innovations are you looking forward to exploring more?

I am excited about low energy computing and anything that can get us there. If you think about the brain, it performs advanced operations in real-time while being very energy efficient.

What advice would you like to give women looking to start their careers in tech?

Bet on intrinsic motivation (channel your motivation from within) and keep on going - every day is a new opportunity.