Sometimes we forget the humans behind the tech in our ever busy world. DSF is fortunate enough to know some incredible tech leaders across the world and has the privilege of hearing them present at our events. That being said, our Speaker Spotlight sets the stage to get to know our speakers on a more personal level and connect them with our growing community. Read the mini interview below!
A bit about Ekaterina:
Ekaterina is a senior data scientist at NVIDIA. She specializes in leveraging multimodal generative AI to tackle challenges in computer vision and natural language understanding. She is skilled in end-to-end AI productization, encompassing the entire process from development to optimized deployment, whether in the cloud or at the edge. Previously, Ekaterina was a research engineer applying deep learning to medical image analysis. She has also authored several peer-reviewed journals and conference publications on various applications of image- based 3D reconstruction, localization and tracking. Ekaterina received her Ph.D. in Computer Science, a M.Sc in Media Informatics, and she also holds a Diploma in Business Informatics.
How did you start out in your tech career?
After finishing my master’s in computer science at RWTH Aachen in Germany, I was invited to do a PhD at the Institute of Medical Informatics at the same university. It was a great opportunity, focusing on multidisciplinary applied research in healthcare and civil engineering. During my PhD studies, Computer Vision became my focus area. At some point, AI got very popular and rapidly infiltrated the field. Having finished my PhD studies, I got a job in R&D applying AI to medical image understanding at the Japanese company Konica Minolta. After some time, I was recruited by NVIDIA, the world leader in accelerated computing.
What are the signs of success in your field?
AI is a very broad field so there is no one-size-fits-all definition of success. In my current role as a customer-facing engineer, I feel really proud when I my customers succeed — whether they’re beating another AI benchmark or raising funds. In addition to my day-to-day engineering job, I also enjoy speaking at conferences and sharing my knowledge. I consider it a success when people come to me after my talk and say that I have helped them understand a complicated concept.
What is the best and worst thing about your job role?
It’s undoubtedly very exciting to have the opportunity to work with cutting-edge technology. It feels empowering to be on top of things and know how the technology works and what’s equally important – how it can be applied in different industries. It also means that I need to invest lots of time keeping up to date with the rapid pace of technology.
What can you advise someone just starting out to be successful?
To be successful in any field, one needs to truly like what they are doing. Treat your work as if it was your hobby, and you’ll achieve great results.
How do you switch off?
When I’m not working, you can find me traveling, doing physical exercises (running is my favourite), learning foreign languages (currently Arabic), shopping for clothes, meeting with friends, and watching movies.
What advice would you give your younger self?
Keep doing everything you‘re doing, you are on the right track!
What is next for you?
I have recently moved to the Middle East to help our local team grow the adoption of generative AI in the region. I’m very excited about this opportunity and I’m sure there will be a lot to learn and experience.
If you could do anything now, what would you do? Why?
I’m generally happy with what I’m doing now, but there is always so much more one can do. I’d love to start an educational YouTube channel someday. I also wish I could have more free time to contribute to fundamental research and to open-source projects.
What are your top 5 predictions in tech for the next 5 years?
● Generative computer vision AI will catch up in quality with language-based models.
● In fact, we will witness true multimodality: instead of having specialised architectures for every modality (images, sound, text, code, etc.), we will have versatile models working with all kinds of data.
● AI will become good at understanding complex structures like PDF documents and at solving math problems.
● Humanoid robots will become very useful and popular.
● Every business will rely on AI.
Watch Ekaterina’s session with the Data Science Festival here.
Thank you to all our wonderful speakers for taking part in our Speaker Spotlight!
Want to become a DSF Speaker? Apply here!