Dimitris Katsios
Lead AI Engineer at PwC
Greece
Summary
👤
Senior🎓
Top SchoolDimitris Katsios is a Lead AI Engineer with nine years of experience building production-grade AI systems, combining deep expertise in computer vision, NLP, and large language models with strong backend and MLOps skills. He has designed modular, agentic assistant architectures and REST APIs deployed on Azure, and led projects automating clinical EHR ingestion and large-scale web automation for job sourcing. A prolific educator and open-source contributor, he has authored CNN and deep learning workshop material used by Machine Learning Tokyo and built reusable DL frameworks that accelerated R&D-to-product integration. Known for pragmatic, scalable designs and clean code, he also brings uncommon domain breadth—from medical imaging algorithms with regulatory approvals to anti-bot countermeasures and browser automation—making him effective across startups, enterprises, and research teams.
9 years of coding experience
7 years of employment as a software developer
Master of Science (MSc), Oil & Gas Technology, 8.39 (with distinction), Master of Science (MSc), Oil & Gas Technology, 8.39 (with distinction) at TEI of KavalaMaster of Science (MSc), Systems Engineering & Management (Information & Communication Systems), 9.25 (first in class), Master of Science (MSc), Systems Engineering & Management (Information & Communication Systems), 9.25 (first in class) at Demokritos University of Thrace (DUTH)Master of Science - MS, Artificial Intelligence, 9.82 (first in class), Master of Science - MS, Artificial Intelligence, 9.82 (first in class) at University of the Aegean
English, Spanish
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (20)
convolutional-neural-networks10
python10
imagenet10
xception10
mask-rcnn10
keras10
deep-learning10
mobilenet10
tensorflow10
resnet10
faster-rcnn10
machine-learning9
image-processing8
dcgan7
cgan7
Programming languages (4)
Github contributions (5)
Machine-Learning-Tokyo/DL-workshop-series
Nov 2018 - Apr 2020
Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)
Role in this project:
ML Engineer
ML EngineerContributions:110 commits, 101 pushes, 1 branch in 1 year 5 months
Contributions summary:Dimitris contributed extensively to the development of deep learning models within the repository, which centers around deep learning workshops. The commits demonstrate the user's ability to implement various convolutional neural networks (CNNs) architectures, including AlexNet, VGG, Inception, Xception, and others. The user also created and updated notebooks related to image processing kernels and GANs, further indicating expertise in deep learning concepts.
pythonworkshopdeep-learningmltmachine-learning
Machine-Learning-Tokyo/CNN-Architectures
Mar 2020 - Apr 2020
Role in this project:ML Engineer
ML EngineerContributions:72 commits, 2 PRs, 76 pushes in 1 month
Contributions summary:Dimitris added implementations for several CNN architectures, including AlexNet, VGGNet, GoogLeNet, MobileNet, ResNet, Xception, and ShuffleNet. These implementations are provided in the form of `.ipynb` or `.html` files, and demonstrate the user's understanding of different convolutional neural network designs. The contributions involve building and documenting various deep learning models using TensorFlow/Keras.
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