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We interpret the world across pixels, motion signals, acoustic spectra, and multimodal inputs — building neural models that understand visual context, sensor abnormalities, waveform signatures, and real-time environments with production precision.
Built a geospatial vision workflow supporting pixel-level change detection, segmentation overlays and long-range landform monitoring, leveraging multi-band satellite imagery and structured mapping layers for observation continuity.
Created an adaptive representation framework for spectral signatures, vibration traces, thermal gradients and acoustic embeddings, enabling anomaly pattern discovery and contextual event grouping using graph-based modelling and structured feature fusion.
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