Jaydeep Rade
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View article: Conversational LLM-Based Decision Support for Defect Classification in AFM Images
Conversational LLM-Based Decision Support for Defect Classification in AFM Images Open
Atomic force microscopy (AFM) has emerged as a powerful tool for nanoscale imaging and quantitative characterization of organic (e.g., live cells, proteins, DNA, and lipid bilayers) and inorganic (e.g., silicon wafers and polymers) specime…
Machine learning approaches for improving atomic force microscopy instrumentation and data analytics Open
Atomic force microscopy (AFM) is a part of the scanning probe microscopy family. It provides a platform for high-resolution topographical imaging, surface analysis as well as nanomechanical property mapping for stiff and soft samples (live…
View article: 3D Reconstruction of Protein Structures from Multi-view AFM Images using Neural Radiance Fields (NeRFs)
3D Reconstruction of Protein Structures from Multi-view AFM Images using Neural Radiance Fields (NeRFs) Open
Recent advancements in deep learning for predicting 3D protein structures have shown promise, particularly when leveraging inputs like protein sequences and Cryo-Electron microscopy (Cryo-EM) images. However, these techniques often fall sh…
Latent Diffusion Models for Structural Component Design Open
Recent advances in generative modeling, namely Diffusion models, have revolutionized generative modeling, enabling high-quality image generation tailored to user needs. This paper proposes a framework for the generative design of structura…
3D Reconstruction of Protein Complex Structures Using Synthesized Multi-View AFM Images Open
Recent developments in deep learning-based methods demonstrated its potential to predict the 3D protein structures using inputs such as protein sequences, Cryo-Electron microscopy (Cryo-EM) images of proteins, etc. However, these methods s…
View article: Deep Learning for Live Cell Shape Detection and Automated AFM Navigation
Deep Learning for Live Cell Shape Detection and Automated AFM Navigation Open
Atomic force microscopy (AFM) provides a platform for high-resolution topographical imaging and the mechanical characterization of a wide range of samples, including live cells, proteins, and other biomolecules. AFM is also instrumental fo…
Deep learning frameworks for structural topology optimization Open
Topology optimization has emerged as a popular approach to refine a component's design and increasing its performance. However, current state-of-the-art topology optimization frameworks are compute-intensive, mainly due to multiple finite …
View article: AI Guided Measurement of Live Cells Using AFM
AI Guided Measurement of Live Cells Using AFM Open
Atomic force microscopy (AFM), a member of the 'scanning probe microscopy' family, is an excellent platform for high-resolution imaging and mechanical characterization of a wide range of samples, including live cells, proteins, and other b…
Physics-consistent deep learning for structural topology optimization. Open
Topology optimization has emerged as a popular approach to refine a component's design and increasing its performance. However, current state-of-the-art topology optimization frameworks are compute-intensive, mainly due to multiple finite …