General Electric Healthcare

GE Healthcare is the $16.7 billion healthcare business of GE. As a leading global medical technology and digital solutions innovator, GE Healthcare enables clinicians to make faster, more informed decisions through intelligent devices, data analytics, applications and services, supported by its Edison intelligence platform. With over 100 years of experience in the healthcare industry and more than 50,000 employees globally, the company helps improve outcomes more efficiently for patients, healthcare providers, researchers and life sciences companies around the world. GE Healthcare in Hungary employs around 700 people, mainly highly qualified, innovative engineers who work together to shape the future of medical imaging, workflow management and usage of Artificial Intelligence in healthcare. GE Healthcare opened its Software Development center in 2000 in Budapest then an office in Szeged, followed by GE’s first and only European Industrial Internet Software Centre of Excellence in Budapest. The center is in the forefront of GE Healthcare’s Edison initiative and delivers services to support data management and analytics. GE Healthcare’s largest European Data Science team in Hungary is using cutting edge Artificial Intelligence and Deep Learning techniques to research and deliver better, faster and more effective diagnosis, treatment and care delivery. GE Healthcare announced recently the first FDA approved artificial intelligence (AI) algorithms embedded on a mobile X-ray device developed by the Hungarian GE Healthcare professionals using the GE Healthcare’s Edison platform. The AI algorithms help to reduce the turn-around time it can take for radiologists to review a suspected pneumothorax, a type of collapsed lung.

David Varkonyi

David graduated summa cum laude from ELTE, one of the biggest Hungarian universities, studying computer science and specializing in numerical modelling. After acquiring his master’s degree in 2015 he stayed at the university for a year, to teach various courses in mathemathics and computer science, and writing publications in a wide area of fields, such as cryptography, celestial mechanics, and digital cartography. After leaving the university, he joined a Hungarian startup, as an AI researcher, to help develop algorithms for the automotive industry, which may power self-driving cars in the future. He joined GE Healthcare in 2019, as a Staff Data Scientist. Being skilled in Python and C++, many data science related frameworks, such as TensorFlow, PyTorch, Keras, having many years of experience in image processing algorithms and GPGPU computing, he currently serves as Manager of Data & Analytics on ultrasound and MRI related projects, leading a newly formed, research focused data science team.

Petra Takács

I have graduated from Budapest University of Technology and Economics as a Computer Science Engineer Bachelor in 2017, and from Pazmany Peter Catholic University as a Computer Science Engineer Master in 2019. Both of my thesis’ were connected to image processing and neural networks – my master thesis was a research about brain tumor segmentation on MRI data with saliency and deep learning. During my last semester in university I started to work in GE Healthcare Data Science team – after a 2-year internship period in MTA SZTAKI research institute – and I have continued organ- and anomaly segmentation in different projects, using Python, Keras and Tensorflow mainly. Woman health and ultrasound data are fresh directions for me after seeing head-and-neck data for years, and I am cheerful to dive into my own biology a bit more!

Richárd Zsámboki

Richard studied mechatronics and electrical engineering at the Budapest University of Technology and Economics. By the end of his studies I became familiar with AI and neural networks through working with MTA-SZTAKI on a research project. After university he worked as an AI Researcher at AImotive, a Hungarian startup working on self-driving cars. He contributed to several intelligent perception system, including segmentation, object detection, lane detection and parking space detection solutions. Since 2019 he is a Senior Data Scientist at GE Healthcare, where his main focus first was processing MR (Magnetic Resonance) images with neural networks to detect different kind of tumors on them, for example his team developed brain tumor segmentation model for the BRATS challenge. He joined the ultrasound team as a Staff Data Scientist bringing a widespread knowledge about image processing, neural networks and python programming to the team.

Martin Mienkina

Martin Mienkina leads the Advanced Technology Development for the Women’s Health Ultrasound business unit within GE Healthcare. He has been working and providing leadership at the intersection of research and development in the field of ultrasound imaging and workflow automation for more than a decade. He received a doctorate in Electrical Engineering, focusing on ultrasound imaging, from the Ruhr-University Bochum Germany in 2010.

Lehel Ferenczi

I am leading a Data Science team in GE Healthcare Hungary formed from data scientists, data analysts, software engineers and clinicians. I am passionate about healthcare, software development and machine learning. I have been working in the healthcare IT sector since 2001, mainly in oncology, neurology and radiology. Over the years, I have gained a wealth of experience in the health sector (product, compliance, regulation, risk management, standards). I have experience in the development of health products from wing to wing, from idea to delivery.
I graduated in Computer Programming and Automation from Timişoara Technical University (Temesvár) and studied post-graduate studies in computer controlled geometric design at the Technical University of Budapest.
From 2001, I led the development of a number of oncology/radiology applications and products for 14 years applications such as AdvantageSim MD, Integrated Registration (Fusion), Advantage 4D (CT, PET / CT).
From 2014 to 2017, I worked on innovative healthcare solutions as part of a consortium of scientists, university professors, clinical partners and GE Healthcare as an industrial partner, funded by a Hungarian national grant.  Within this consortium, my team and I have been able to develop innovative solutions that have made us to be part of GE Healthcare’s data research center since more than 2 years.
Since 2016 I am leading a data science team of over 30 experts dedicated to deliver machine and deep learning solutions for a variety of medical imaging techniques (CT, MR, PET, ultrasound and X-ray).

Daniella Nikov

I studied molecular bionics as my BSc since my interests were neurbiology and molecular biology and I gained a solid knowledge in these fields, however I wrote my thesis about 3D segmentation in CT and MR images, analzying the inner ear shape in children with statistic methods to ensure a better view for surgery. I was always interested in healthcare technologies, so during my final year I decided to start working in the Faculty of Medicine and Faculty of Science and Informatics, where I worked in web application development. I started Computer Science MSc and soon I started to work at GE Healthcare as a software developer intern, supporting and delivering new features to a healthcare related web application. During my MSc studies C++ was introduced to me, and I was fascinated at first sight. After the internship I joined the SUOG project where I can now utilize and improve my C++ skills.