Alexandre L. M. Levada
@alexandre-levada.bsky.social
B.Sc. in Computer Science
M.Sc. in Computer Science
Ph.D in Computational Physics
Professor at Federal University of São Carlos, São Carlos, SP, Brazil.
M.Sc. in Computer Science
Ph.D in Computational Physics
Professor at Federal University of São Carlos, São Carlos, SP, Brazil.
A reflection on human development
"Flowers only bloom when they are ready. People are the same way. You cannot rush or force them open just because you think it's time. Be patient."
~ Timber Hawkeye
Every person grows at their own pace. Trust the timing of your own blooming.
"Flowers only bloom when they are ready. People are the same way. You cannot rush or force them open just because you think it's time. Be patient."
~ Timber Hawkeye
Every person grows at their own pace. Trust the timing of your own blooming.
November 8, 2025 at 7:13 PM
A reflection on human development
"Flowers only bloom when they are ready. People are the same way. You cannot rush or force them open just because you think it's time. Be patient."
~ Timber Hawkeye
Every person grows at their own pace. Trust the timing of your own blooming.
"Flowers only bloom when they are ready. People are the same way. You cannot rush or force them open just because you think it's time. Be patient."
~ Timber Hawkeye
Every person grows at their own pace. Trust the timing of your own blooming.
🌌 Unraveling the Geometry of Time: Our New Study on Random Field Dynamics
How does time’s arrow emerge from systems governed by symmetric physical laws?
In our latest paper, we explore this question through a new lens — geometry.
iopscience.iop.org/article/10.1...
How does time’s arrow emerge from systems governed by symmetric physical laws?
In our latest paper, we explore this question through a new lens — geometry.
iopscience.iop.org/article/10.1...
October 25, 2025 at 6:34 PM
🌌 Unraveling the Geometry of Time: Our New Study on Random Field Dynamics
How does time’s arrow emerge from systems governed by symmetric physical laws?
In our latest paper, we explore this question through a new lens — geometry.
iopscience.iop.org/article/10.1...
How does time’s arrow emerge from systems governed by symmetric physical laws?
In our latest paper, we explore this question through a new lens — geometry.
iopscience.iop.org/article/10.1...
New paper!
NoLAW: A Recursive Non-Linear Adaptive Wiener Filter for Time Series Smoothing
link.springer.com/epdf/10.1007...
NoLAW: A Recursive Non-Linear Adaptive Wiener Filter for Time Series Smoothing
link.springer.com/epdf/10.1007...
NoLAW: A Recursive Non-Linear Adaptive Wiener Filter for Time Series Smoothing
link.springer.com
September 21, 2025 at 11:55 AM
New paper!
NoLAW: A Recursive Non-Linear Adaptive Wiener Filter for Time Series Smoothing
link.springer.com/epdf/10.1007...
NoLAW: A Recursive Non-Linear Adaptive Wiener Filter for Time Series Smoothing
link.springer.com/epdf/10.1007...
The Geodesic Dispersion Phenomenon in Random Field Dynamics: Probing the Shape of Time
doi.org/10.1088/2632...
via @ioppublishing.bsky.social
doi.org/10.1088/2632...
via @ioppublishing.bsky.social
The Geodesic Dispersion Phenomenon in Random Field Dynamics: Probing the Shape of Time - IOPscience
The Geodesic Dispersion Phenomenon in Random Field Dynamics: Probing the Shape of Time, Levada, Alexandre L. M.
doi.org
September 18, 2025 at 5:12 PM
The Geodesic Dispersion Phenomenon in Random Field Dynamics: Probing the Shape of Time
doi.org/10.1088/2632...
via @ioppublishing.bsky.social
doi.org/10.1088/2632...
via @ioppublishing.bsky.social
New research paper:
To be presented at SIBGRAPI 2025
A Curvature-Based Adaptive UMAP for Manifold Learning in Clustering and Classification
sibgrapi.sid.inpe.br/col/sid.inpe...
Congrats to Gustavo Henrique Chavari
To be presented at SIBGRAPI 2025
A Curvature-Based Adaptive UMAP for Manifold Learning in Clustering and Classification
sibgrapi.sid.inpe.br/col/sid.inpe...
Congrats to Gustavo Henrique Chavari
URLib - A Curvature-Based Adaptive UMAP for Manifold Learning in Clustering and Classification | 8JMKD2USNRW34M/4E8BJ2P
sibgrapi.sid.inpe.br
September 12, 2025 at 7:09 PM
New research paper:
To be presented at SIBGRAPI 2025
A Curvature-Based Adaptive UMAP for Manifold Learning in Clustering and Classification
sibgrapi.sid.inpe.br/col/sid.inpe...
Congrats to Gustavo Henrique Chavari
To be presented at SIBGRAPI 2025
A Curvature-Based Adaptive UMAP for Manifold Learning in Clustering and Classification
sibgrapi.sid.inpe.br/col/sid.inpe...
Congrats to Gustavo Henrique Chavari
New research paper:
Deep Learning for Protoplanetary Disk Classification from Hubble Images: A Comparative Study on Imbalanced Data
sibgrapi.sid.inpe.br/col/sid.inpe...
Congrats to Marília Fernandez and Pedro Bugatti
Deep Learning for Protoplanetary Disk Classification from Hubble Images: A Comparative Study on Imbalanced Data
sibgrapi.sid.inpe.br/col/sid.inpe...
Congrats to Marília Fernandez and Pedro Bugatti
URLib - Deep Learning for Protoplanetary Disk Classification from Hubble Images: A Comparative Study on Imbalanced Data | 8JMKD2USNRW34M/4E86NQ8
sibgrapi.sid.inpe.br
September 11, 2025 at 8:05 PM
New research paper:
Deep Learning for Protoplanetary Disk Classification from Hubble Images: A Comparative Study on Imbalanced Data
sibgrapi.sid.inpe.br/col/sid.inpe...
Congrats to Marília Fernandez and Pedro Bugatti
Deep Learning for Protoplanetary Disk Classification from Hubble Images: A Comparative Study on Imbalanced Data
sibgrapi.sid.inpe.br/col/sid.inpe...
Congrats to Marília Fernandez and Pedro Bugatti
New research (IEEE Access).
Minimum information trees for High Dimensional Data Visualization in Clustering
ieeexplore.ieee.org/document/111...
The developed method proposes the use of Minimum Information Trees, which provide a clear and interpretable representation of cluster structure.
Minimum information trees for High Dimensional Data Visualization in Clustering
ieeexplore.ieee.org/document/111...
The developed method proposes the use of Minimum Information Trees, which provide a clear and interpretable representation of cluster structure.
Minimum Information Trees for High Dimensional Data Visualization in Clustering
Visualizing the qualitative outcomes of clustering algorithms in high-dimensional spaces remains a persistent challenge in data analysis and machine learning. Traditional dimensionality reduction tech...
ieeexplore.ieee.org
September 10, 2025 at 11:19 PM
New research (IEEE Access).
Minimum information trees for High Dimensional Data Visualization in Clustering
ieeexplore.ieee.org/document/111...
The developed method proposes the use of Minimum Information Trees, which provide a clear and interpretable representation of cluster structure.
Minimum information trees for High Dimensional Data Visualization in Clustering
ieeexplore.ieee.org/document/111...
The developed method proposes the use of Minimum Information Trees, which provide a clear and interpretable representation of cluster structure.