activity
20232026
most citedAdapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population Dynamics

14 citations · 15 across the 7 of their papers we have counts for

collaborators

7 papers

cs.DL2026

CA20108 COST Action: A Methodology for Developing FAIR Micrometeorological Networks

Branislava Lalic, Josef Eitzinger, Stevan Savić Ana Firanj Sremac +2

This article reports the outcomes of the FAIRNESS COST Action (CA20108), a coordinated European initiative aimed at advancing micrometeorological data toward compliance with the FA…

cs.AI2025★ 1 cited

The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)

Andrew Ferguson, Marisa LaFleur, Lars Ruthotto +97

This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 w…

q-bio.QM2025

Redefining Influenza Transmission Seasonality Using the Novel Seasonality Index

Branislava Lalic, Vladimir Koci, Ana Firanj Sremac +1

The impact of climate conditions on influenza epidemiology has mostly been studied by addressing a singular aspect of transmission and a climate variable correlating to it. As clim…

physics.ao-ph2025

Seasonal Changes -- Time for Paradigm Shift

Branislava Lalic, Ana Firanj Sremac

Season and their transitions play a critical role in sharpening ecosystems and human activities, yet traditional classifications, meteorological and astronomical, fail to capture t…

physics.bio-ph2024

Modelling Mosquito Population Dynamics using PINN-derived Empirical Parameters

Branislava Lalic, Dinh Viet Cuong, Mina Petric +3

Vector-borne diseases continue to pose a significant health threat globally with more than 3 billion people at risk each year. Despite some limitations, mechanistic dynamic models…

q-bio.PE2024★ 14 cited

Adapting Physics-Informed Neural Networks to Improve ODE Optimization in Mosquito Population Dynamics

Dinh Viet Cuong, Branislava Lalić, Mina Petrić +2

Physics informed neural networks have been gaining popularity due to their unique ability to incorporate physics laws into data-driven models, ensuring that the predictions are not…

cs.DL2023

Constructing a Searchable Knowledge Repository for FAIR Climate Data

Mark Roantree, Branislava Lalic, Stevan Savic +2

The development of a knowledge repository for climate science data is a multidisciplinary effort between the domain experts (climate scientists), data engineers whos skills include…