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DPIIT‑Recognized Startup (Government of India) — AI & Machine Learning Sector


A Physics-informed Coupled Oscillator Framework for Synthetic ECG Generation
Coupled Oscillator Representation of Cardiac Electrical Activity The Synthetic ECG generation process begins with cardiac dynamics as network of biological oscillators. This network includes the Sinoatrial node (SA), the Atrioventricular (AV) node, and the His–Purkinje (HP) complex, each exhibiting an intrinsic rhythm and distinct electrical properties. Their ordered interaction gives rise to the heart's electrical signaling, guiding how these impulses propagate and enabling
Kasturi Murthy
May 64 min read
Synthetic Data, DPDPA and Tools
A Brief Overview of Synthetic Data Synthetic data is information that is artificially generated by computer algorithms rather than collected from real-world events or individuals. While it contains no real personal records, it accurately mimics the mathematical patterns, distributions, and correlations of the original dataset. In the context of machine learning, this is typically achieved using generative AI techniques. For example, instead of relying on a database of highly
Kasturi Murthy
Mar 64 min read


ECG Synthesis: From GPU Training to Edge Deployment on Raspberry Pi
Introduction In my previous blog post, I discussed the input data for the LSTMVAE model, which comes from the publicly available PTB-XL...
Kasturi Murthy
Aug 31, 20255 min read


LSTM-VAE: Deep Architecture for GPU-Accelerated ECG Generation
Introduction In this post, I explore a custom LSTM-based Variational Autoencoder (LSTMVAE) designed for sequential representation...
Kasturi Murthy
Aug 12, 20258 min read
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