collaborators

6 papers

cs.CV2026

GRADE: Single-Frame Generative Radar Depth Estimation Under Visual Degradation

Bin Zhao, Patrick Chiou, Nakul Garg

Dense 3D depth perception fails under smoke, fog, and darkness because optical sensors cannot penetrate airborne particulates. mmWave radar remains usable and measures range accura…

cs.RO2025

RadarSFD: Single-Frame Diffusion with Pretrained Priors for Radar Point Clouds

Bin Zhao, Nakul Garg

Millimeter-wave radar provides robust perception in fog, smoke, dust, and low light, making it attractive for size-, weight-, and power-constrained robotic platforms. Existing rada…

eess.SY2025

DeepSync: A Learning Framework for Pervasive Localization using Code Synchronization on Compressed Cellular Spectrum

Aritrik Ghosh, Nakul Garg, Nirupam Roy

Pervasive localization is essential for continuous tracking applications, yet existing solutions face challenges in balancing power consumption and accuracy. GPS, while precise, is…

cs.SD2025

Spatial Audio Processing with Large Language Model on Wearable Devices

Ayushi Mishra, Yang Bai, Priyadarshan Narayanasamy +2

Integrating spatial context into large language models (LLMs) has the potential to revolutionize human-computer interaction, particularly in wearable devices. In this work, we pres…

cs.LG20241 cited

IMUOptimize: A Data-Driven Approach to Optimal IMU Placement for Human Pose Estimation with Transformer Architecture

Varun Ramani, Hossein Khayami, Yang Bai +2

This paper presents a novel approach for predicting human poses using IMU data, diverging from previous studies such as DIP-IMU, IMUPoser, and TransPose, which use up to 6 IMUs in…

cs.NI2023

Fast Localization and Tracking in City-Scale UWB Networks

Nakul Garg, Irtaza Shahid, Ramanujan K Sheshadri +2

Localization of networked nodes is an essential problem in emerging applications, including first-responder navigation, automated manufacturing lines, vehicular and drone navigatio…