Manuel.

Publications

2023

"Alert Classification for the ALeRCE Broker System: The Anomaly Detector"

M. Pérez-Carrasco, G. Cabrera-Vives, L. Hernandez-García, F. Förster, P. Sanchez-Saez, A. M. Muñoz Arancibia, J. Arredondo, N. Astorga, F. E. Bauer, A. Bayo, M. Catelan, R. Dastidar, P. A. Estévez, P. Lira, and G. Pignata

The Astronomical Journal, 2023

2022

"Precision silviculture: use of UAVs and comparison of deep learning models for the identification and segmentation of tree crowns in pine crops"

M. Pérez-Carrasco, B. Karelovic, R. Molina, R. Saavedra-Passache, Pierluigi Cerulo, and G. Cabrera-Vives

International Journal of Digital Earth (IJDE), 2022

2021

"Searching for Changing-state AGNs in Massive Data Sets. I. Applying Deep Learning and Anomaly-detection Techniques to Find AGNs with Anomalous Variability Behaviors"

P. Sanchez-Saez, et al.

Astronomical Journal, 2021

2021

"The Automatic Learning for the Rapid Classification of Events (ALeRCE) Alert Broker"

F. Förster, et al.

The Astronomical Journal (AJ), 2021

2019

"Multiband galaxy morphologies for CLASH: a convolutional neural network transferred from CANDELS"

M. Pérez-Carrasco, G. Cabrera-Vives, M. Martinez-Marín, P. Cerulo, R. Demarco, P. Protopapas, J. Godoy, and M. Huertas-Company

Publications of the Astronomical Society of the Pacific, 2019

Conference Contributions

NeurIPS 2024: LatinX in AI Workshop - Finance and Sponsorship Co-Chair
ICML 2023: Workshop on Machine Learning for Astrophysics

"Positional encodings for light curve transformers: Playing with positions and attention". Oral Presentation.

Daniel Moreno-Cartagena, Guillermo Cabrera-Vives, Pavlos Protopapas, Cristobal Donoso-Oliva, Manuel Pérez-Carrasco, Martina Cádiz-Leyton

Paper Oral Presentation BibTex

"Multi-Class Deep SVDD: Anomaly Detection Approach in Astronomy with Distinct Inlier Categories". Poster Presentation.

M. Pérez-Carrasco, G. Cabrera-Vives, L. Hernández-Garcıa, F. Förster, P. Sánchez-Sáez, A. Munoz Arancibia, N. Astorga, F.E. Bauer, A. Bayo, M. Cádiz-Leyton, M. Catelan, P.A. Estévez

Paper Poster BibTex

"Domain adaptation via minimax entropy for real/bogus classification of astronomical alerts". Poster Presentation.

Guillermo Cabrera-Vives, César Bolivar, Francisco Förster, Alejandra M. Munoz Arancibia, Manuel Pérez-Carrasco, Esteban Reyes

Paper Poster BibTex
NeurIPS 2023: Workshop on Tackling Climate Change with Machine Learning

"Hyperspectral shadow removal with Iterative Logistic Regression and latent Parametric Linear Combination of Gaussians". Poster Presentation.

Core Francisco Park, Maya Nasr, Manuel Pérez-Carrasco, Eleanor Walker, Douglas Finkbeiner, Cecilia Garraffo

Paper Poster BibTex
NeurIPS 2021: Workshop on Distribution Shift - Poster Presenter

"Con2DA: Simplifying Semi-supervised Domain Adaptation by Learning Consistent and Contrastive Feature Representations"

Manuel Pérez-Carrasco, Pavlos Protopapas, Guillermo Cabrera-Vives

Paper Presentation BibTex
Astroinformatics 2019: Best Student Paper Award - Caltech, Pasadena, CA, USA

"Matching Embeddings for Domain Adaptation"

Manuel Pérez-Carrasco, Guillermo Cabrera-Vives, Pavlos Protopapas
Watch Presentation
ComputeFest 2019: Trainer - Harvard University, Boston, MA, USA
Repository

Teaching Experience

University of Concepción, Chile

Data Analysis

School of Engineering Department

Lecturer 2024-2

Designed curriculum, lectures, assessments, laboratories, and homework for audiences of ~40 students.

Deep Learning

School of Engineering Department

Lecturer 2022-1, 2023-1, 2024-1

Co-taught with Professor Guillermo Cabrera. Co-designed curriculum, lectures, assessments, laboratories, and homework for audiences of ~30 students.

Introduction to Data Science

School of Engineering Department

Lecturer 2021-2, 2022-2

Co-taught with Professor Guillermo Cabrera. Responsible for designing lectures, assessments, laboratories, and homework for audiences of ~30 students.

Advanced Topics in Machine Learning

Department of Industrial Engineering

Lecturer 2020-1

Co-taught with Professor Rodrigo de la Fuente. This elective course aimed at graduate and undergraduate students of engineering focused on deep learning fundamentals. The course covered neural network architectures such as MLP, CNN, and RNN, as well as advanced topics like reinforcement learning, representation learning, and deep generative models.

Introduction to Machine Learning

Department of Industrial Engineering

Lecturer 2019-2

Co-taught with Professor Rodrigo de la Fuente. This elective course aimed at undergraduate students covered the basics of machine learning, including supervised learning (Regression, Logistic regression, decision trees, Random Forest, SVM) and unsupervised learning (k-means, PCA).

Machine Learning for Business Intelligence

Department of Industrial Engineering

Teaching Assistant 2018-1

Responsible for recitations and laboratory sessions. This course mixed classical machine learning with deep learning algorithms, showing how to apply these techniques to large-scale industry problems.

System Modelling

Department of Industrial Engineering

Teaching Assistant 2017-2

Responsible for recitations. This mandatory course for 2nd year Industrial Engineering students taught mathematical modeling and solving basic operation research problems using linear programming.

Harvard University, Cambridge, MA, USA

Data Science 2: Advanced Topics in Data Science

Institute for Applied Computational Sciences

Teaching Fellow 2019-1

Served as teaching fellow for this mandatory course of the Master in Data Science program. Responsible for office hours, grading, and guiding student projects. The course covered advanced methods for data wrangling, data visualization, deep neural networks, and statistical modeling.

Education

MSc. Computer Science

University of Concepción | Mar. 2017 – Oct. 2019 | GPA: 6.1/7.0

  • Thesis: "Semi-supervised Adversarial Variational Domain Adaptation for Image Classification" (Perfect 7.0/7.0 Grade)
  • Research work received best student paper award at Astroinformatics 2019 conference, Caltech

B.S. Industrial Engineering

University of Concepción | Mar. 2013 – Sep. 2018 | GPA: 5.9/7.0

  • Undergraduate honor research thesis published in Publications of the Astronomical Society of the Pacific