Ioannis Kalfas is a multidisciplinary AI engineer and remote sensing scientist with 12 years of experience applying deep learning to Earth observation, agrifood, and bio‑sensing problems. He holds a PhD from KU Leuven and has moved research ideas into production—productizing VQ‑VAE‑2/CORSA for satellite image compression, building lightweight cloud‑masking CNNs that ranked top in CMIX‑2, and training global land‑cover models at scale. Comfortable across research and engineering, he designs PyTorch/MLOps pipelines for SLURM/HPC and maintains APIs and web tools for real‑world deployments, including FastAPI/Streamlit systems for insect monitoring. His background in neurophysiology and spiking neural networks informs a strong foundation in biologically inspired modelling and time‑series signal processing. Based in Leuven, he combines academic rigor with hands‑on production experience to bridge cutting‑edge research and scalable ML solutions.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD Bioscience Engineering. Deep learning , Doctor of Philosophy - PhD Bioscience Engineering. Deep learning at KU Leuven
Master of Science (MS) Machine Learning, Master of Science (MS) Machine Learning at KTH Royal Institute of Technology
Bachelor of Science (BS) Informatics, Bachelor of Science (BS) Informatics at Aristotle University of Thessaloniki (AUTH)
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Ioannis Kalfas - Remote Sensing Scientist AI Engineer at VITO