2 citations · 2 across the 10 of their papers we have counts for
13 papers
CoRF: Cross-Scene RF Synthesis by Learning Propagation and Preserving Array Physics
Kang Yang, Duaa Nakshbandi, Wan Du +1
Existing radio-frequency (RF) neural fields fit each scene separately, making new-scene deployment measurement- and optimization-intensive. This work studies amortized cross-scene…
HoliBench: A Cross-Platform Benchmarking and Deployment Toolkit for Foundation Models in CPS-IoT Applications
Inesh Chakrabarti, Zejun Xiong, Pragya Sharma +1
Foundation models, including large language models, vision-language models, and time-series foundation models, are increasingly deployed on embedded and edge platforms for CPS and…
The Internet of Collaborating Things: Agentic Edge AI for Autonomous Cross-Domain Collaboration
Walid A. Hanafy, Nader Sehatbakhsh, David Irwin +2
The Internet of Things is on a trajectory toward a trillion connected devices deployed across multiple domains. These devices are no longer simple sensing and actuation endpoints;…
CREST: Deployment-Realistic Hardware-in-the-Loop NAS for Embedded Sensing Systems
Joseph Q. Zales, Pragya Sharma, Mani Srivastava
Deploying neural networks on low-power microcontrollers (MCUs) requires selecting model architectures under tight memory, latency, and energy constraints. Existing workflows often…
FMplex: Model Virtualization for Serving Extensible Foundation Models
Hetvi Shastri, Pragya Sharma, Walid A. Hanafy +3
Foundation models (FMs) are increasingly used as backbones for downstream tasks across language, vision, time-series, and multimodal applications. Yet existing model-serving system…
TS-Skill: A Benchmark for Evaluating Analytical Skills in Time-Series Question Answering
Liying Han, Kang Yang, Oliver Wang +9
Large language models (LLMs) and time-series language models (TSLMs) are increasingly applied to time-series question answering (TSQA). Unlike text-only QA, TSQA requires models to…
RxGS: Receiver-Generalizable 3D Gaussian Splatting for Radio-Frequency Data Synthesis
Kang Yang, Mani Srivastava
Radio-frequency (RF) data synthesis predicts the received signal given transmitter and receiver positions, and is essential for wireless applications. Recent 3D Gaussian Splatting…
FM-CAC: Carbon-Aware Control for Battery-Buffered Edge AI via Time-Series Foundation Models
Kang Yang, Walid A. Hanafy, Prashant Shenoy +1
As edge AI deployments scale to billions of devices running always-on, real-time compound AI pipelines, they represent a massive and largely unmanaged source of energy consumption…
FuseFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing
Gaofeng Dong, Kang Yang, Mani Srivastava
Existing Wi-Fi sensing systems rely on injecting high-rate probing packets to extract channel state information (CSI), leading to communication degradation and limited deployment f…
FMTK: A Modular Toolkit for Composable Time Series Foundation Model Pipelines
Hetvi Shastri, Pragya Sharma, Walid A. Hanafy +2
Foundation models (FMs) have opened new avenues for machine learning applications due to their ability to adapt to new and unseen tasks with minimal or no further training. Time-se…
Spectral Predictability as a Fast Reliability Indicator for Time Series Forecasting Model Selection
Oliver Wang, Pengrui Quan, Kang Yang +1
Practitioners deploying time series forecasting models face a dilemma: exhaustively validating dozens of models is computationally prohibitive, yet choosing the wrong model risks p…
CarbonX: An Open-Source Tool for Computational Decarbonization Using Time Series Foundation Models
Diptyaroop Maji, Kang Yang, Prashant Shenoy +2
Computational decarbonization aims to reduce carbon emissions in computing and societal systems such as data centers, transportation, and built environments. This requires accurate…
LLM-Driven Auto Configuration for Transient IoT Device Collaboration
Hetvi Shastri, Walid A. Hanafy, Li Wu +3
Today's Internet of Things (IoT) has evolved from simple sensing and actuation devices to those with embedded processing and intelligent services, enabling rich collaborations betw…