Carlo De Michele

Professor of Hydrology and Water Engineering

Politecnico di Milano

Italy

Research Interests

Explore related searches

Professors in Italy

Contact this professor

ORCID

Google Scholar

Academic Page

About

Carlo De Michele is a Professor of Hydrology and Water Engineering at Politecnico di Milano in Italy. His research areas include multifractal analysis of channel networks, forecasting soil temperature dynamics using deep learning, and risk analysis related to dam inflow. He has contributed to several recent articles focusing on hydrological modeling, disaster classification, and innovations in rainfall estimation techniques.

Carlo De Michele

Research Interests

Explore related searches

Contact this professor

About

Articles (29)

A Review of Technical Aspects and Challenges in Opportunistic Rainfall Estimation Using Satellite and Terrestrial Microwave Links: How wireless infrastructure can be used for rainfall monitoring

Multifractal analysis of braided channel networks using structure functions and fixed-mass measures

Archaeo-Hydraulic Investigations of the Ancient Water Supply System in the Lorestan Province

Deep learning and vine copula-based sequencing: approaches under investigation for forecasting soil temperature dynamics

Disasters classification in a compound event perspective: insights from existing databases

Improvements in forecasting and normalizing limited displacement responses of long-span steel bridges subjected to seasonal temperature variability

Statistical behavior of temporally compounding multi-peak flood events

Risk analysis of inflow to the Zayandehrud Dam under historical and future scenarios using reliability, resiliency, and vulnerability indicators: a comparative study of the runoff risk index and runoff risk ranking methods

Displacement prediction for long-span bridges via limited remote sensing images: An adaptive ensemble regression method

A systematic correlation analysis for regression model selection: Application to bridge response prediction using contact and remote sensor systems

An innovative predictive method based on supervised teacher-student learning for forecasting limited structural responses of long-span bridges from satellite images

Application of regression and remote sensing technology for determining sufficiency of contact-based sensors in long-term SHM of civil structures

Rainfall Observation Leveraging Raindrop Sounds Acquired Using Waterproof Enclosure: Exploring Optimal Length of Sounds for Frequency Analysis

Temporal clustering of precipitation for detection of potential landslides

Temporal Clustering of Precipitation Driving Landslides Over the Italian Territory

Exploring the joint probability of precipitation and soil moisture over Europe using copulas

Understanding the cost of soil erosion: An assessment of the sediment removal costs from the reservoirs of the European Union

Historical changes in the Causal Effect Networks of compound hot and dry extremes in central Europe

Investigating an extreme precipitation network with a threshold on the interest factor

Investigation of Temperature Effects into Long-Span Bridges via Hybrid Sensing and Supervised Regression Models

Elimination of Thermal Effects from Limited Structural Displacements Based on Remote Sensing by Machine Learning Techniques

A REPLICABLE OPEN-SOURCE MULTI-CAMERA SYSTEM FOR LOW-COST 4D GLACIER MONITORING

Application of copula-based and ARCH-based models in storm prediction

Application of copula‐based approach as a new data‐driven model for downscaling the mean daily temperature

Asymmetric Dependence in Hydrological Extremes

Compound flood hazard at Lake Como, Italy, is driven by temporal clustering of rainfall events

Online Hybrid Learning Methods for Real-Time Structural Health Monitoring Using Remote Sensing and Small Displacement Data

Detection of Partially Structural Collapse Using Long-Term Small Displacement Data from Satellite Images

Hydrological response of a peri-urban catchment exploiting conventional and unconventional rainfall observations: the case study of Lambro Catchment

Collaborators (7)

Cristina Deidda

Changhyun Jun

Alireza Entezami

Joaquim G. Pinto

MICHELE D'AMICO

Hyeon-Joon Kim

Filippo Giannetti

How do I reach out?

Meet Kite AI