Introducing the educators

Hi, and welcome back. In this lecture we would like to introduce the educators that you will see throughout the MOOC. The MOOC is a collaboration of the Process Mining for Health Care Consortium. And in this Consortium, we try to enforce a relationship between healthcare professionals and process mining researchers. We aim to educate researchers on a professional needs. We also train professionals on the use of process mining tools. We also want to disseminate best practices and case studies. And this MOOC covers all four aspects. Should you want to know more, please visit our website. And as I said, in this MOOC we will therefore see several educators. And in this lecture, we will briefly introduce ourselves. So let’s start with myself.

I’m Joos Buijs. I did my PhD in Eindhoven University of Technology. And I’m currently an assistant professor at the Mathematics and Computer Science department in Eindhoven. My main research area is process mining in healthcare, and I’m also research program manager at the Data Science Center in Einhoven. Hi. My name is Carlos Fernandez-Llatas. And I work on ITACA Institute at Universitat Politecnica Valencia in Spain. I worked as a researcher on more than 20 projects through the 4, 5, 6, 7, and 8 Horizon 2020 European Framework projects. And on Spanish-funded ICT and health research projects. I have more than 10 years of experience as a researcher applying process mining techniques to health care. Hi. I’m Roberto Gatta.

I am a researcher at the Gemelli ART– Advanced Radiation Therapy and KBO lab, with is a Knowledge-Based Oncologoy lab in Rome. My main research areas are Process Mining in healthcare, Medical Image Analysis, and medical knowledge extraction and representation. Hi, I’m Jorge Munoz-Gama, assistant professor of the Computer Science department of the Pontificia Universidad Católica de Chile, and author of the book Conformance Checking and Diagnosis in Process Mining. My research areas include process-oriented data science and process mining applied to education and health care. I am Marcos Sepulveda. I am an Associate professor of the Computer Science department at the Pontificia Universidad Católica de Chile. I am also the director of the Information Technology Research Center for my university.

My research areas include business process management and process mining in healthcare and education. Hi. I’m Rene de la Fuente Sanhueza, anesthesiologist, assistant professor of the Anesthesiology department of the Faculty of Medicine of the Pontificia Universidad Católica de Chile. My research areas are medical education and medical informatics. I am Daniel Capurro. I am a medical doctor trained in internal medicine and I also hold a PhD in biomedical and health informatics from the University of Washington in Seattle Currently, I’m an associate professor at the Faculty of Medicine at Pontificia Universidad Católica de Chile.

I’m also the chief medical information officer at Red de Salud UC CHRISTUS And my main research goal is to develop methods to improve the use of clinical data for research. Hi. I’m Lucia Sacchi, and I’m assistant professor at the Department of Electrical, Computer and Biomedical Engineering of the University of Pavia. My main research interests are clinical data mining with a specific focus on process mining and temporal data mining. My name is Davide Aloini. I’m an assistant professor of business process management at the University of Pisa. My recent research includes business process management and collaborative ICT solutions, with a special focus on large scale projects, healthcare systems, and innovation.

Investigations includes process identification, modelling, analysis, and improvements in complex healthcare systems and networks. Hello everybody. My name is Alessandro Stefanini, and I’m PhD student at Rome Tor Vergata, but I’m carrying out my research at the University of Pisa. My main research topic is business process management, in particular in healthcare domain, where I’m investigating structured and unstructured processes by data driven approaches.