Sayan K Chaki
Final-year doctoral candidate specialising in computer vision and digital humanities, with expertise in unsupervised analysis of historical ornaments. Collaborated with University of Oxford's VGG, IMAGINE École des Ponts ParisTech, and TU Vienna on computational analysis of cultural artefacts.
Professional Experience
PhD Scholar in Image, Vision, and Signal Processing
Inria, Laboratoire Hubert Curien | Sep 2022– Present
- Developing an equivariant model for unsupervised detection and segmentation of ornaments from historical manuscripts
- Affine transformation invariance with lowdata solutions
- Equivariance principles for model robustness in ANR project "Rey's Ornament Image Investigation"
Research (Master) Intern
Laboratoire Hubert Curien | Mar 2022– Jul 2022
- Developed Spatial Transformer AutoEncoder for anomaly segmentation
- Compiled benchmark vignettes dataset from ornaments in books
Software Developer Intern
IBM India & KLA Tencor | May 2021– Jul 2021
- Developed anomaly segmentation algorithms for 3D fault detection
- Created an integrated crossplatform ecosystem using React
Research & Publications
Making Spatial Transformer Networks Rotation-Equivariant: Variational Autoencoding to Object Detection
Submitted to ICML 2025
Led a team of researchers in addressing limitations in 3D reconstructions and modelling of byzantine seals
Anomaly localization and Pattern Comparison
One-to-many pattern comparison combining fully-connected autoencoder with spatial transformer for ornament investigation
View Paper
Computing the Early Page in Modern Europe
University of Oxford - March 2024
Invited talk on unsupervised decomposition of historical document elements, focused on early page structures of ancient European books
Intermediality and Computational Humanities Hackathon
University of Vienna - November 2024
Led a team of researchers in addressing limitations in 3D reconstructions and modelling of byzantine seals
Teaching Experience
Introduction to Machine Learning
Institut d'Optique Graduate School (24 hrs)
- Supervised/unsupervised learning, neural networks (CNNs, GANs, VAEs)
- Model evaluation with practical Python implementations
Introduction to Python
Institut d'Optique Graduate School (24 hrs)
- Python basics, data structures, libraries (NumPy, pandas)
- Applications in data analysis and machine learning
Summer Schools
Google DeepMind ProbAI Summer School
NTNU, Trondheim, Norway | June 2023
- Advanced probabilistic AI techniques in generative modeling
- Presented poster on probabilistic methods in document analysis
Generative Modelling Summer School (GeMSS)
TU Eindhoven, DTU, Inria | June 2024
- Advanced methods in generative modeling and variational inference
- Presented poster on applications in digital humanities