papers

Publications (13)

cond-mat.stat-mech2022

Stochastic thermodynamic engines under time-varying temperature profile

Rui Fu, Olga Movilla Miangolarra, Amirhossein Taghvaei +2

In the present paper, we study the power output and efficiency of overdamped stochastic thermodynamic engines that are in contact with a heat bath having a temperature that varies…

cs.DB2025

The Impact of Modern AI in Metadata Management

Wenli Yang, Rui Fu, Muhammad Bilal Amin +1

Metadata management plays a critical role in data governance, resource discovery, and decision-making in the data-driven era. While traditional metadata approaches have primarily f…

cs.LG2025

Machine learning for modelling unstructured grid data in computational physics: a review

Sibo Cheng, Marc Bocquet, Weiping Ding +20

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for co…

eess.SY2021

Harvesting energy from a periodic heat bath

Rui Fu, Olga Movilla Miangolarra, Amirhossein Taghvaei +2

The context of the present paper is stochastic thermodynamics - an approach to nonequilibrium thermodynamics rooted within the broader framework of stochastic control. In contrast…

math.OC2020

Maximal power output of a stochastic thermodynamic engine

Rui Fu, Amirhossein Taghvaei, Yongxin Chen +1

Classical thermodynamics aimed to quantify the efficiency of thermodynamic engines by bounding the maximal amount of mechanical energy produced compared to the amount of heat requi…

cs.DB2015

Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers

Peng Cheng, Xiang Lian, Zhao Chen +4

With the rapid development of mobile devices and the crowdsourcig platforms, the spatial crowdsourcing has attracted much attention from the database community, specifically, spati…

cs.LG2017

DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction

Xingyuan Dai, Rui Fu, Yilun Lin +2

In this paper, we consider the temporal pattern in traffic flow time series, and implement a deep learning model for traffic flow prediction. Detrending based methods decompose ori…

cs.IT2023

RIS-based IMT-2030 Testbed for MmWave Multi-stream Ultra-massive MIMO Communications

Shuhao Zeng, Boya Di, Hongliang Zhang +13

As one enabling technique of the future sixth generation (6G) network, ultra-massive multiple-input-multiple-output (MIMO) can support high-speed data transmissions and cell covera…

math.OC2022

Underdamped stochastic thermodynamic engines in contact with a heat bath with arbitrary temperature profile

Olga Movilla Miangolarra, Rui Fu, Amirhossein Taghvaei +2

We study thermodynamic processes in contact with a heat bath that may have an arbitrary time-varying periodic temperature profile. Within the framework of stochastic thermodynamics…

cond-mat.stat-mech2021

Energy harvesting from anisotropic fluctuations

Olga Movilla Miangolarra, Amirhossein Taghvaei, Rui Fu +2

We consider a rudimentary model for a heat engine, known as the Brownian gyrator, that consists of an overdamped system with two degrees of freedom in an anisotropic temperature fi…

cond-mat.stat-mech2021

On the relation between information and power in stochastic thermodynamic engines

Amirhossein Taghvaei, Olga Movilla Miangolarra, Rui Fu +2

The common saying, that information is power, takes a rigorous form in stochastic thermodynamics, where a quantitative equivalence between the two helps explain the paradox of Maxw…

math.NA2024

Solving High-dimensional Parametric Elliptic Equation Using Tensor Neural Network

Hongtao Chen, Rui Fu, Yifan Wang +1

In this paper, we introduce a tensor neural network based machine learning method for solving the elliptic partial differential equations with random coefficients in a bounded phys…

eess.SY2018

Stability Theory of Stochastic Models in Opinion Dynamics

Zahra Askarzadeh, Rui Fu, Abhishek Halder +2

We consider a certain class of nonlinear maps that preserve the probability simplex, i.e., stochastic maps, that are inspired by the DeGroot-Friedkin model of belief/opinion propag…