EDUCATION

UNIVERSIDAD TÉCNICA FEDERICO SANTA MARÍA

Civil Computer Engineering Mar 2015 – Aug 2021

Academic Degree: BSc in Computer Engineering & BESc. Recognition Roberto Ovalle Aguirre 2022 , from the Instituto de Ingenieros de Chile, for the best civil engineering thesis/project for the promotion of the national economy.

EXPERIENCE

ZIPPEDI INC.Las Condes, Chile

AI Engineer L2 Aug 2023 – Present

Led the research and application of cutting-edge models in Deep Learning, including unsupervised pre-training and image recognition using FAISS, significantly improving effectiveness in multimodal embedding and similarity search tasks. Evaluated new tools and platforms for cloud-based training, such as AWS SageMaker, MLFlow, and WebDatasets, adopting good practices for experiment tracking and efficient training of Deep Learning models for the team.

AI Engineer L1 Sept 2021 – July 2023

Develop Deep Learning models for object detection and text recognition in retail images, using PyTorch and third-party frameworks like Detectron2 and Ultralytics, which considerably improves model accuracy and latency. Optimized software architecture and automated the continuous integration and deployment process, enabling more efficient workload management and ensuring consistent tracking and deployment of models.

MEDX SPA Las Condes, Chile

Freelancer – AI Engineer Nov 2023 – Feb 2024

Designed and implemented a preprocessing and Deep Learning model training methodology for medical applications, using PyTorch and WebDatasets, which significantly improved the efficiency and scalability of the model development process. Integrated MLFlow for tracking and managing experiments, allowing for faster and more organized iteration, and facilitated collaboration and result reproduction in the startup environment.

DESAFÍO LATAMSantiago, Chile

Data Science Tutor July 2023 – Nov 2023

Created hands-on Data Science sessions for 38 students with no prior technical experience, using SQL, Tableau, and Python, ensuring all acquired fundamental competencies in data analysis. Adapted teaching methods to meet diverse learning needs, resulting in a significant increase in students’ confidence and skills in manipulating and analyzing large data sets. Monitored and assessed students’ progress in Data Science, providing guidance and specific feedback that contributed to their development and success in the course.

ZEKEViña del Mar, Chile

Intern – Artificial Vision Engineer Jan 2020 – Mar 2020

Implemented a computer vision solution using OpenCV (C++) and TensorFlow for object detection and tracking, acquiring near real-time analysis capability with YOLO. Developed an inventory control application through video analysis, which automated and optimized inventory management in commercial settings using artificial vision techniques.

UNIVERSIDAD TÉCNICA FEDERICO SANTA MARÍAValparaíso, Chile

Research AssistantMar 2019 – Jan 2022

Optimized the preprocessing of large volumes of astronomical data for gamma-ray regression, implementing convolutional neural networks with TensorFlow and data from the IACT technique, significantly improving performance and scalability when storing data in TFRecords.

Teaching Assistant (Laboratory)Mar 2019 – Dec 2020

Orchestrated interactive laboratory sessions using Jupyter Notebooks to teach computational statistics, facilitating the practical understanding of complex concepts using Python for 80 students. Collaborated in continuously improving course materials, integrating the latest trends and tools in computational statistics and machine learning, ensuring that students were up-to-date with the skills demanded in the industry.

Teaching Assistant (Theory)Aug 2016 – July 2020

Created and supervised programming assignments in "Data Structures and Algorithms", "Introduction to Engineering", and "Programming Languages", providing detailed and constructive feedback to over 75 students, resulting in a notable improvement in their programming skills. Collaborated closely with faculty to identify and address individual learning needs, contributing to the academic development and success of students in fundamental areas of engineering.

CENTRO CIENTÍFICO TECNOLÓGICO DE VALPARAÍSOValparaíso, Chile

Research AssistantMar 2019 – Dec 2019

Implemented and refined advanced algorithms for segmentation and classification in histopathology images, using TensorFlow and scientific Python packages. Contributed to research that culminated in the publication of my thesis on the application of Bayesian Deep Learning in medical diagnosis, exploring new methods in model uncertainty handling in medical image analysis.

SOLUNEGOCIOSSantiago, Chile

Intern – Computer Vision EngineerJan 2019 – Mar 2019

Developed and deployed computer vision web services using Python, OpenCV, TensorFlow, Flask, and Docker, focusing on precisely extracting information from scanned documents and forms. Designed a robust solution with document orientation correction, sign detection, and text extraction, ensuring that information and signatures were accurately detected, increasing accuracy to 94%.

PUBLICATIONS

Bórquez, S., , R., Salinas, L., & Torres, C. E. Uncertainty estimation in the classification of histopathological images with HER2 overexpression using Monte Carlo Dropout.

Implemented a breast cancer tissue classification method using Bayesian Deep Learning, achieving an accuracy of 0.89 and providing crucial uncertainty estimates for clinical decision-making. Published in the Biomedical Signal Processing and Control journal. DOI: doi.org/10.1016/j.bspc.2023.104864

Riquelme, D., Araya, M., Borquez, S., Panes, B., & Carquin, E. Deep Learning Semi-Supervised Strategy for Gamma/Hadron Classification of Imaging Atmospheric Cherenkov Telescope Events.

Designed a deep learning training framework for gamma/hadron classification and regression, in the context of the Cherenkov Telescope Array (CTA) project. The framework was used to train a convolutional neural network (CNN) for gamma/hadron classification. Loading data from TFRecords, the framework was able to train the CNN in a distributed fashion, using multiple GPUs in a large-scale cluster.

SKILLS

Programming Languages	Python, C++, Bash, SQL
AI Frameworks & Libraries	PyTorch, Tensorflow, NumPy, pandas, RAPIDS, OpenCV, MLFlow, OpenAI, FAISS, LangChain.
Development & Deployment	Flask, Docker, GCP, GitLab CI/CD, AWS
Certificaciones	Fundamentals of Accelerated Data Science with RAPIDS (NVIDIA DLI) Deep Learning Specialization Program (DeepLearning.AI)
Languages	Spanish (Native), English (C1)