Nicola BALDO

Associate Professor

University of Udine

Italy

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Nicola Baldo is an Associate Professor at the University of Udine, Italy. His research focuses on the mechanical performance of asphalt mixtures, including the use of recycled materials and machine learning modeling techniques. Recent articles by Professor Baldo explore areas such as the circularity of recycled concrete aggregates, the use of plastic waste in asphalt, and the modeling of dynamic modulus in construction materials.

Articles (18)

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2025

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2025

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2025

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2025

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

Collaborators (7)

NITIN TIWARI

Assistant Professor

Southern Illinois University Carbondale

UNITED STATES

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Bernhard Hofko

TU Wien

AUSTRIA

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Piotr Pokorski

University of Warsaw

POLAND

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Marco Pasetto

Professor

University of Padova

ITALY

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Marcin Daniel Gajewski

Associate Professor

POLAND

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MATTEO MIANI

University of Udine

ITALY

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Jan Krol

Associate Professor

University of Warsaw

POLAND

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Nicola BALDO

Research Interests

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About

Articles (18)

Study of the Circularity of Recycled Concrete Aggregates Subjected to Different Mechanical and Chemical Treatments

A Review on the Use of Plastic Waste as a Modifier of Asphalt Mixtures for Road Constructions

Mechanical performance prediction of asphalt mixtures: a baseline study of linear and non-linear regression compared with neural network modeling

Discussion on the bitumen fatigue parameters interpretation for Linear Amplitude Sweep and time-sweep tests: Insights from ageing

A Deep Neural Network Approach towards Performance Prediction of Bituminous Mixtures Produced Using Secondary Raw Materials

Accuracy of Dynamic Modulus Models of Asphalt Mixtures Containing Reclaimed Asphalt (RA)

Improved predictions of asphalt concretes’ dynamic modulus and phase angle using decision-tree based categorical boosting model

Experimental and Machine Learning Approach to Investigate the Mechanical Performance of Asphalt Mixtures with Silica Fume Filler

Volumetric Properties and Stiffness Modulus of Asphalt Concrete Mixtures Made with Selected Quarry Fillers: Experimental Investigation and Machine Learning Prediction

Alternative Fillers in Asphalt Concrete Mixtures: Laboratory Investigation and Machine Learning Modeling towards Mechanical Performance Prediction

Stiffness Moduli Modelling and Prediction in Four-Point Bending of Asphalt Mixtures: A Machine Learning-Based Framework

Laboratory Investigation and Machine Learning Modeling of Road Pavement Asphalt Mixtures Prepared with Construction and Demolition Waste and RAP

Road Pavement Asphalt Concretes for Thin Wearing Layers: A Machine Learning Approach towards Stiffness Modulus and Volumetric Properties Prediction

Foamed Bitumen Mixtures for Road Construction Made with 100% Waste Materials: A Laboratory Study

Mechanical Characterization of Industrial Waste Materials as Mineral Fillers in Asphalt Mixes: Integrated Experimental and Machine Learning Analysis

Stiffness Data of High-Modulus Asphalt Concretes for Road Pavements: Predictive Modeling by Machine-Learning

Bituminous Mixtures Experimental Data Modeling Using a Hyperparameters-Optimized Machine Learning Approach

Surrogate Safety Measures Prediction at Multiple Timescales in V2P Conflicts Based on Gated Recurrent Unit

Collaborators (7)

NITIN TIWARI

Bernhard Hofko

Piotr Pokorski

Marco Pasetto

Marcin Daniel Gajewski

MATTEO MIANI

Jan Krol

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