Michail Iliadis
Senior Research Engineer at Apple
San Jose, California, United States
Summary
👤
Senior🎓
Top SchoolMichail Iliadis is a Senior Research Engineer at Apple with 11 years of experience applying deep learning to computer vision, face recognition, document analysis, and efficient semantic segmentation for resource-constrained devices. He holds a Ph.D. in EECS from Northwestern University and has a track record of taking projects end-to-end—from data collection and bias-aware dataset curation to distributed training and production deployment. At Clarifai he scaled face detection and ArcFace-style embeddings across millions of images, improving true positive rates and robustness to extreme poses, and earlier work produced patentable systems for one-shot classification and near-duplicate retrieval. Michail combines rigorous academic research with product-focused engineering, optimizing both model accuracy and interoperability of ML pipelines. Based in San Jose, he blends low-level algorithmic innovation with practical systems work, often improving runtime or deployment efficiency in real-world settings.
11 years of coding experience
10 years of employment as a software developer
Master of Science (MS), Department of Computer Science, Master of Science (MS), Department of Computer Science at University of BathDoctor of Philosophy (PhD), Electrical Engineering and Computer Science Department, Doctor of Philosophy (PhD), Electrical Engineering and Computer Science Department at Northwestern UniversityBachelor of Science (BS), Department of Digital Systems, Bachelor of Science (BS), Department of Digital Systems at Panepistimion Pireos
Greek, English
Stackoverflow
1reputation
0reached
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Github Skills (21)
scene-text10
optical-flow10
arabic10
image-processing9
ocr9
data-mining9
latin9
devanagari9
lstm9
optical-character-recognition9
cyrillic9
python8
easyocr8
information-retrieval8
machine-learning8
Programming languages (3)
Github contributions (5)
miliadis/miliadis.github.io
Mar 2019 - Nov 2023
Contributions:42 pushes in 4 years 9 months
miliadis/retinaface-tf2
May 2021 - Aug 2021
RetinaFace (Single-stage Dense Face Localisation in the Wild, 2019) implemented (ResNet50, MobileNetV2 trained on single GPU) in Tensorflow 2.0+. This is an unofficial implementation. With Colab.
Contributions:2 PRs, 33 pushes, 1 branch in 3 months
stageresnet50deep-learninggpuretinaface
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