activity
20202026
collaborators

6 papers

math.OC2026

Communication-Efficient Differentially Private Gradient Tracking for Distributed Optimization via Local Updates

Mihitha Maithripala, Chenyang Qiu, Zongli Lin

This paper studies privacy-preserving distributed optimization using gradient tracking with one communication-free local update between consecutive communication rounds. Since loca…

math.OC2026

A Momentum-based Stochastic Algorithm for Linearly Constrained Nonconvex Optimization

Chenyang Qiu, Mihitha Maithripala, Zongli Lin

This paper studies a stochastic algorithm for linearly constrained nonconvex optimization, where the objective function is smooth but only unbiased stochastic gradients with bounde…

eess.SY2026

Dynamic Average Consensus with Privacy Guarantees and Its Application to Battery Energy Storage Systems

Mihitha Maithripala, Chenyang Qiu, Zongli Lin

A privacy-preserving dynamic average consensus (DAC) algorithm is proposed that achieves consensus while preventing external eavesdroppers from inferring the reference signals and…

eess.SY2026

Privacy-Preserving Dynamic Average Consensus by Masking Reference Signals

Mihitha Maithripala, Zongli Lin

In multi-agent systems, dynamic average consensus (DAC) is a decentralized estimation strategy in which a set of agents tracks the average of time-varying reference signals. Becaus…

eess.SY2025

Privacy-Preserving Distributed Control for a Networked Battery Energy Storage System

Mihitha Maithripala, Zongli Lin

The increasing deployment of distributed Battery Energy Storage Systems (BESSs) in modern power grids necessitates effective coordination strategies to ensure state-of-charge (SoC)…

eess.SP2020

Modified Auto Regressive Technique for Univariate Time Series Prediction of Solar Irradiance

Umar Marikkar, A. S. Jameel Hassan, Mihitha S. Maithripala +3

The integration of renewable resources has increased in power generation as a means to reduce the fossil fuel usage and mitigate its adverse effects on the environment. However, re…