activity
20142026
most citedRandomized opinion dynamics over networks: influence estimation from partial observations

12 citations · 52 across the 36 of their papers we have counts for

collaborators

39 papers

cs.AI2026

Learning Linear Temporal Specifications from Demonstrations with Uncertainty

Parastou Fahim, Constantino Lagoa, Rômulo Meira-Góes

Learning temporal logic specifications from system demonstrations is essential for tasks such as formal verification and controller synthesis, especially in safety-critical domains…

eess.SY2026

A Dynamic Phasor Framework for Analysis of Subsynchronous Oscillations in Multi-Machine Systems with IBRs and Large Loads

Fiaz Hossain, Nilanjan Ray Chaudhuri, Constantino M. Lagoa +3

Although the electromagnetic transient (EMT) framework can capture subsynchronous oscillations (SSOs), it faces scalability issues for large-scale systems. Thus motivated, we propo…

eess.SY2026

A Dynamic Phasor Framework for Analysis of IBR-Induced SSOs in Multi-Machine Systems

Fiaz Hossain, Nilanjan Ray Chaudhuri, Constantino M. Lagoa

We propose a generalized dynamic phasor (DP) framework to analyze inverter-based resources (IBRs) connected to multi-machine systems under balanced and unbalanced conditions. It ca…

eess.SY2026

RAIN-FIT: Learning of Fitting Surfaces and Noise Distribution from Large Data Sets

Omar M. Sleem, Sahand Kiani, Constantino M. Lagoa

This paper proposes a method for estimating a surface that contains a given set of points from noisy measurements. More precisely, by assuming that the surface is described by the…

eess.SY2026

Willems' Fundamental Lemma with Large Noisy Fragmented Dataset

Sahand Kiani, Constantino M. Lagoa

Willems' Fundamental Lemma enables parameterizing all trajectories generated by a Linear Time-Invariant (LTI) system directly from data. However, this lemma relies on the assumptio…

math.OC2026

Decision-Scaled Scenario Approach for Rare Chance-Constrained Optimization

Jaeseok Choi, Anand Deo, Constantino Lagoa +1

Chance-constrained optimization is a suitable modeling framework for safety-critical applications where violating constraints is nearly unacceptable. The scenario approach is a pop…