Hello, I'm
Serafeim Loukas, PhD
Senior Data Scientist @ IATA (Geneva, CH)
Short Bio
Since August 15th, 2024 I have been working as a Senior Data Scientist at the International Air Transport Association (IATA, Geneva Office).
At IATA, I am designing and implementing cross-divisional data science and machine learning solutions that drive business value across IATA's global aviation network. I am collaborating with data architects and engineering teams to develop advanced models and algorithms that tackle complex business challenges. I am leading initiatives in data collection, transformation, and analysis, while recommending improvements to our data environments and submission standards.
Prior to this, I worked as a Data Scientist in the Medical Algos and Data (MAD) team at Natural Cycles (Geneva, Switzerland) from March 2023 to May 2024.
Before joining NC, I worked as a Data Scientist at the University of Geneva & University Hospital of Bern since the 1st of June & July 2021, respectively. I hold a Ph.D. in Electrical Engineering from the Swiss Federal Institute of Technology Lausanne (EPFL), a M.Sc. in Neuroscience from the University of Geneva, and a Diploma in Electrical & Computer Engineering, equivalent to an M.Eng., from the National Technical University of Athens.
Senior Data Scientist
IATA, Geneva
Aug 2024 - Present
Data Scientist
Natural Cycles, Geneva
Mar 2023 - May 2024
Data Scientist
Uni. of Geneva & Uni. Hospital of Bern
Jun 2017 - Feb 2023
Ph.D., M.Sc., Diploma in Eng.
EPFL (CH) | UNIGE (CH) | NTUA (GR)
Education
My Expertise
I am particularly motivated and passionate about data science, machine learning, AI, biomedical/electrical engineering, computational modeling and more generally about data analysis. I rank 12 all-time respondent for Machine Learning on Stack Overflow.
Machine Learning & AI
Deep understanding of ML and statistical learning. Expertise in classification, regression, clustering, and timeseries forecasting.
Data Analysis
Gathering, cleaning, and organizing data. Analysis & visualization for technical and non-technical personnel using Python and R.
Engineering & Modeling
Signal processing, network science, graph theory, and computational modeling with significant background in electrical engineering.