activity
20172025
most citedAnalog Signal Compression and Multiplexing Techniques for Healthcare Internet of Things

16 citations · 141 across the 22 of their papers we have counts for

collaborators

22 papers

cs.RO2025

Real-Time Navigation for Autonomous Aerial Vehicles Using Video

Khizar Anjum, Parul Pandey, Vidyasagar Sadhu +2

Most applications in autonomous navigation using mounted cameras rely on the construction and processing of geometric 3D point clouds, which is an expensive process. However, there…

cs.MA2025★ 1 cited

ToMCAT: Theory-of-Mind for Cooperative Agents in Teams via Multiagent Diffusion Policies

Pedro Sequeira, Vidyasagar Sadhu, Melinda Gervasio

In this paper we present ToMCAT (Theory-of-Mind for Cooperative Agents in Teams), a new framework for generating ToM-conditioned trajectories. It combines a meta-learning mechanism…

cs.CV2023

Automatic Measures for Evaluating Generative Design Methods for Architects

Eric Yeh, Briland Hitaj, Vidyasagar Sadhu +3

The recent explosion of high-quality image-to-image methods has prompted interest in applying image-to-image methods towards artistic and design tasks. Of interest for architects i…

cs.AI2022

Sensor Control for Information Gain in Dynamic, Sparse and Partially Observed Environments

J. Brian Burns, Aravind Sundaresan, Pedro Sequeira +1

We present an approach for autonomous sensor control for information gathering under partially observable, dynamic and sparsely sampled environments that maximizes information abou…

eess.SP2020★ 1 cited

On-board Deep-learning-based Unmanned Aerial Vehicle Fault Cause Detection and Identification

Vidyasagar Sadhu, Saman Zonouz, Dario Pompili

With the increase in use of Unmanned Aerial Vehicles (UAVs)/drones, it is important to detect and identify causes of failure in real time for proper recovery from a potential crash…

eess.SP2020

Energy-efficient Analog Sensing for Large-scale and High-density Persistent Wireless Monitoring

Vidyasagar Sadhu, Xueyuan Zhao, Dario Pompili

The research challenge of current Wireless Sensor Networks (WSNs) is to design energy-efficient, low-cost, high-accuracy, self-healing, and scalable systems for applications such a…

eess.SP2020

Signal Recovery Performance Analysis in Wireless Sensing with Rectangular-Type Analog Joint Source-Channel Coding

Xueyuan Zhao, Vidyasagar Sadhu, Dario Pompili

The signal recovery performance of the rectangular-type Analog Joint Source-Channel Coding (AJSCC) is analyzed in this work for high and medium/low Signal-to-Noise Ratio (SNR) scen…

eess.SY2019★ 13 cited

UW-MARL: Multi-Agent Reinforcement Learning for Underwater Adaptive Sampling using Autonomous Vehicles

Mehdi Rahmati, Mohammad Nadeem, Vidyasagar Sadhu +1

Near-real-time water-quality monitoring in uncertain environments such as rivers, lakes, and water reservoirs of different variables is critical to protect the aquatic life and to…

eess.IV2019★ 9 cited

Real-time Image Enhancement for Vision-based Autonomous Underwater Vehicle Navigation in Murky Waters

Wenjie Chen, Mehdi Rahmati, Vidyasagar Sadhu +1

Classic vision-based navigation solutions, which are utilized in algorithms such as Simultaneous Localization and Mapping (SLAM), usually fail to work underwater when the water is…

eess.SP2019★ 12 cited

Low-power All-analog Circuit for Rectangular-type Analog Joint Source Channel Coding

Xueyuan Zhao, Vidyasagar Sadhu, Dario Pompili

A low-complexity all-analog circuit is proposed to perform efficiently Analog Joint Source Channel Coding (AJSCC), which can compress two or more sensor signals into one with contr…

cs.ET2019★ 5 cited

Towards Ultra-low-power Realization of Analog Joint Source-Channel Coding using MOSFETs

Vidyasagar Sadhu, Sanjana Devaraj, Dario Pompili

Certain sensing applications such as Internet of Things (IoTs), where the sensing phenomenon may change rapidly in both time and space, requires sensors that consume ultra-low powe…

eess.SP2019★ 11 cited

Towards Low-power Wearable Wireless Sensors for Molecular Biomarker and Physiological Signal Monitoring

Xueyuan Zhao, Vidyasagar Sadhu, Tuan Le +2

A low-power wearable wireless sensor measuring both molecular biomarkers and physiological signals is proposed, where the former are measured by a microfluidic biosensing system wh…

eess.SP2019★ 14 cited

Improved Circuit Design of Analog Joint Source Channel Coding for Low-power and Low-complexity Wireless Sensors

Xueyuan Zhao, Vidyasagar Sadhu, Anthony Yang +1

To enable low-power and low-complexity wireless monitoring, an improved circuit design of Analog Joint Source Channel Coding (AJSCC) is proposed for wireless sensor nodes. This inn…

eess.SP2019★ 9 cited

Energy-efficient Wireless Analog Sensing for Persistent Underwater Environmental Monitoring

Vidyasagar Sadhu, Sanjana Devaraj, Dario Pompili

The design of sensors or "things" as part of the new Internet of Underwater Things (IoUTs) paradigm comes with multiple challenges including limited battery capacity, not polluting…

cs.CR2019★ 2 cited

Secure Mobile Technologies for Proactive Critical Infrastructure Situational Awareness

Gabriel Salles-Loustau, Vidyasagar Sadhu, Dario Pompili +2

Trustworthy operation of our national critical infrastructures, such as the electricity grid, against adversarial parties and accidental failures requires constant and secure monit…

eess.SP2019★ 10 cited

Towards Wireless Health Monitoring via Analog Signal Compression based Biosensing Platform

Xueyuan Zhao, Vidyasagar Sadhu, Tuan Le +2

Wireless all-analog biosensor design for concurrent microfluidic and physiological signal monitoring is presented in this work. The key component is an all-analog circuit capable o…

eess.SP2019★ 16 cited

Analog Signal Compression and Multiplexing Techniques for Healthcare Internet of Things

Xueyuan Zhao, Vidyasagar Sadhu, Dario Pompili

Scalability is a major issue for Internet of Things (IoT) as the total amount of traffic data collected and/or the number of sensors deployed grow. In some IoT applications such as…

cs.LG2019★ 1 cited

Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data

Vidyasagar Sadhu, Teruhisa Misu, Dario Pompili

Corner cases are the main bottlenecks when applying Artificial Intelligence (AI) systems to safety-critical applications. An AI system should be intelligent enough to detect such s…

cs.CY2019★ 13 cited

Argus: Smartphone-enabled Human Cooperation via Multi-Agent Reinforcement Learning for Disaster Situational Awareness

Vidyasagar Sadhu, Gabriel Salles-Loustau, Dario Pompili +2

Argus exploits a Multi-Agent Reinforcement Learning (MARL) framework to create a 3D mapping of the disaster scene using agents present around the incident zone to facilitate the re…

cs.LG2019

HCFContext: Smartphone Context Inference via Sequential History-based Collaborative Filtering

Vidyasagar Sadhu, Saman Zonouz, Vincent Sritapan +1

Mobile context determination is an important step for many context aware services such as location-based services, enterprise policy enforcement, building or room occupancy detecti…

cs.NI2017★ 11 cited

CollabLoc: Privacy-Preserving Multi-Modal Localization via Collaborative Information Fusion

Vidyasagar Sadhu, Dario Pompili, Saman Zonouz +1

Mobile phones provide an excellent opportunity for building context-aware applications. In particular, location-based services are important context-aware services that are more an…

cs.NI2017★ 13 cited

Energy-efficient Analog Sensing for Large-scale, High-density Persistent Wireless Monitoring

Vidyasagar Sadhu, Xueyuan Zhao, Dario Pompili

The research challenge of current Wireless Sensor Networks~(WSNs) is to design energy-efficient, low-cost, high-accuracy, self-healing, and scalable systems for applications such a…