Akshat Dave

IIT@MIT, Massachusetts Institute of Technology

Papers

Total Citations

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About

Akshat Dave is a rising researcher at the intersection of computational imaging, computer vision, and novel sensing systems, with a focus on pushing the boundaries of what cameras and depth sensors can perceive in challenging real-world conditions. His work addresses fundamental limitations in imaging hardware by developing intelligent, hybrid sensing pipelines that combine complementary sensor modalities. In his notable 2025 paper "Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging" (4 citations), Dave tackled the long-standing trade-off between low-light sensitivity and high-speed capture, demonstrating how pairing event cameras with single-photon avalanche diodes can circumvent traditional exposure constraints. His concurrent work, "Blurred LiDAR for Sharper 3D" (2 citations), showcases his versatility, leveraging diffuse LiDAR signals alongside RGB data to enable robust handheld 3D reconstruction in scenes that routinely defeat conventional methods — low-texture, low-light, and low-albedo environments critical to robotics and augmented reality. Though early in citation accumulation, Dave's research reflects a sophisticated, systems-level thinking about sensor fusion and computational optics, positioning him as a promising voice in next-generation imaging science worth following closely.