- Working on the application for a European Union project call on ‘AI in Materials Science’, focusing on developing a multimodal foundation model to analyse material structures across diverse datasets. The project aims to build a pipeline for property prediction, classification, and the discovery of new materials.
- AI for Multivariate Time Series Data Driven Delignification Process in Paper and Pulp Industry, collaboration with Chalmers University under WASP-WISE grant, Govt. of Sweden. Developing large interpretable time series models suitable for complex multivariate time series data analysis (forecasting, classification, anomaly detection).
- AI in Materials Informatics – analyse complex molecular structures of 3D and 2D materials, decision making classification process, and support chemical exfoliation process using large pretrained AI models, collaboration with IFM department, funded by WASP-WASP call and Wallenberg AI, Govt. of Sweden.
- Developing AI guided chemical scissor with layered/non-layered material’s structure analysis, collaboration with IFM department, funded by WASP-WISE call and Wallenberg AI, Govt. of Sweden.
- A project was on deep learning and game-based cognitive assessment for early dementia detection (published in EAAI journal, Elsevier). This work relates to one of my PhD scholars.
- One work is completed on developing end-to-end application to detect various objects (deep learning based object detection models) from an image and live video and provides description about them along with any valid relationship exists among the objects.
- My PhD research interests lie in enhancing machine learning algorithms using quantum computing principles, such as quantum clustering with 1D DTQW, quantum feature selection, VQE, and QAOA, alongside applied AI in industrial contexts. I also have experience in ternary quantum image representation, edge extraction, image denoising, and segmentation.
You can go through my homepage,
- Sanjay Chakraborty (Google site)
- Sanjay Chakraborty (Google Scholar)
