18 citations · 29 across the 11 of their papers we have counts for
13 papers
A Diffusion-Model Subpopulation Digital Twin for Mobile Health Deployment: A Case Study on the HeartSteps Intervention
Ziping Xu, Yuyi Chang, Chenshun Ni +5
Mobile-health interventions increasingly use online learning and decision making algorithms to personalize when to nudge users toward healthier behavior, but a poorly designed algo…
Neural Implicit Representations for 3D Synthetic Aperture Radar Imaging
Nithin Sugavanam, Emre Ertin
Synthetic aperture radar (SAR) is a tomographic sensor that measures 2D slices of the 3D spatial Fourier transform of the scene. In many operational scenarios, the measured set of…
Designing a Secure and Resilient Distributed Smartphone Participant Data Collection System
Foad Namjoo, Neng Wan, Devan Mallory +6
Real-world health studies require continuous and secure data collection from mobile and wearable devices. We introduce MotionPI, a smartphone-based system designed to collect behav…
MPADA: Open source framework for multimodal time series antenna array measurements
Yuyi Chang, Yingzhe Zhang, Asimina Kiourti +1
This paper presents an open-source framework for collecting time series S-parameter measurements across multiple antenna elements, dubbed MPADA: Multi-Port Antenna Data Acquisition…
Microwave lymphedema assessment using deep learning with contour assisted backprojection
Yuyi Chang, Nithin Sugavanam, Emre Ertin
We present a method for early detection of lymphatic fluid accumulation in lymphedema patients based on microwave imaging of the limb volume across an air gap. The proposed algorit…
MrSARP: A Hierarchical Deep Generative Prior for SAR Image Super-resolution
Tushar Agarwal, Nithin Sugavanam, Emre Ertin
Generative models learned from training using deep learning methods can be used as priors in inverse under-determined inverse problems, including imaging from sparse set of measure…
CardiacGen: A Hierarchical Deep Generative Model for Cardiac Signals
Tushar Agarwal, Emre Ertin
We present CardiacGen, a Deep Learning framework for generating synthetic but physiologically plausible cardiac signals like ECG. Based on the physiology of cardiovascular system f…
Bayesian Sparse Blind Deconvolution Using MCMC Methods Based on Normal-Inverse-Gamma Prior
Burak Cevat Civek, Emre Ertin
Bayesian estimation methods for sparse blind deconvolution problems conventionally employ Bernoulli-Gaussian (BG) prior for modeling sparse sequences and utilize Markov Chain Monte…
High Resolution Radar Sensing with Compressive Illumination
Nithin Sugavanam, Siddharth Baskar, Emre Ertin
We present a compressive radar design that combines multitone linear frequency modulated (LFM) waveforms in the transmitter with a classical stretch processor and sub-Nyquist sampl…
Blind Reconstruction of Multilayered Tissue Profiles with UWB Radar Under Bayesian Setting
Burak Cevat Civek, Emre Ertin
In this paper, we investigate the problem of inverse electromagnetic scattering to recover multilayer human tissue profiles using ultrawideband radar systems in a Bayesian setting.…
Sparse Signal Models for Data Augmentation in Deep Learning ATR
Tushar Agarwal, Nithin Sugavanam, Emre Ertin
Automatic Target Recognition (ATR) algorithms classify a given Synthetic Aperture Radar (SAR) image into one of the known target classes using a set of training images available fo…
Recovery guarantees for multifrequency chirp waveforms in compressed radar sensing
Nithin Sugavanam, Emre Ertin
Radar imaging systems transmit modulated wideband waveform to achieve high range resolution resulting in high sampling rates at the receiver proportional to the bandwidth of the tr…
Wald-Kernel: Learning to Aggregate Information for Sequential Inference
Diyan Teng, Emre Ertin
Sequential hypothesis testing is a desirable decision making strategy in any time sensitive scenario. Compared with fixed sample-size testing, sequential testing is capable of achi…