Patty Seifert: «ETH helped me get into Berkeley to get my Ph.D.»

You studied at ETH Geophysics. What are your memories of that time?

I have wonderful memories of the ETH. Stepping out from the lectures and being on the ETH terrace with the most gorgeous view of Zurich at the end of day. The professors were in general great and helped me with guidance, connections and recommendations to progress my education abroad. One professor even organized a trip to South Africa and Namibia to visit different mines which was a once in a lifetime experience. I am still in contact with some of my colleagues I studied with and they are now scattered all over the world.

Did your degree from ETH help you in your career?

The ETH has definitely a good worldwide reputation and helped me get into Berkeley to get my Ph.D. Also, there is the Alumni Chapter Bay Area and it helps to connect, stay in touch with the ETH and network abroad with likeminded people.

Geophysics is really where big data analytics started and hence it gave me a good entry point into artificial intelligence and machine learning, the field I am currently in.

You currently work in the energy sector. How does a normal working day look like?

I am the director of product management at Siemens for EnergyIP Analytics, so no day is alike. Maybe in general one could define it as problem solving, if that is helping the customer to put a business case into an analytical model, educating sales on products and competitive advantages, brain storming on how product strategy fits best with overall global strategy of the business unit etc. There is also some travel involved in my job. I either go to conferences to present new findings in the Energy analytics space or meet with customers to understand their product needs. As in general in product management one has to work with many different groups such as development, marketing, sales, quality assurance, legal, user interface, documentation, customer etc. It allows seeing many different aspects of a product, which makes my daily work interesting. I like my job particularly because every day is different and new challenges come my way for which I must find new solutions.

How do topics like smart cities, machine learning and energy forecasting have to do with big data in the energy sector?

With the implementation of Smart Meters just the meter data itself has increased thousand-fold. In addition, more and more Internet of Things devices have been installed along the grid that can provide Supervisory Control and Data Acquisition data in milli-second intervals. So big data began to enter the utility and energy field in a significant way.

Furthermore, the grid that was designed as a one-way system from generation to end-user and has now become a two-way system with distributed energy generation such as solar. This provides additional challenges to maintain a stable grid and provide electricity in a reliable fashion to the end-user. So transformers do not blow up, customers do not experience flickering or outages. Also, global warming and the once in a century storms which we now experience more commonly have a huge impact on the grid reliability. This is where big data and machine learning can have an impact to predict maintenance issues, power outages and vegetation management. This helps customers with their electricity consumption, and gives advice when the electric vehicles can be charged most economically.