Santiago Calderón-Peña

Education

MSc in Advanced Computing (Computer Science)

Graduated with Distinction (among the top students in the cohort).
Master’s Thesis: “Real-Time Incremental Explanations and Saliency Maps for Object Detection in Videos” (92/100), supervised by Prof. Hana Chockler.
Scholarship: Colfuturo - Foundation for the Future of Colombia (ranked 4th nationwide, top 0.5% of 779 candidates).
Relevant Coursework: Computer Vision, Neural Networks and Deep Learning, Data Mining, Multi-Agent Systems.
Research Interests: Explainable AI, Computer Vision.
Extracurriculars: Research Assistant in Explainable AI; Student Lead, Google Developer Student Club (GDSC).

Graduated Cum Laude with the highest GPA in cohort (4.54/5.0).
Bachelor’s Thesis: “Design and Implementation of Nonlinear Controllers for 3D Printing Systems” (5.0/5.0), awarded Tesis Laureada (highest honors).
Honors & Awards: University Medal for Academic Merit, 5× Matrícula de Honor (highest semester GPA).
Scholarship: Full scholarship awarded by the Colombian Ministry of ICT.
Extracurriculars: Member of Davinci research group; Karate team competitor (multiple medals).

Research Experience

Developed the IncX algorithm for real-time explanations of object detectors, achieving an order-of-magnitude reduction in latency compared to benchmarks.
Conducting research in Explainable AI (XAI) with peer-reviewed publications and submissions to top-tier AI conferences.
Contributed to XAI methods for computer vision (IncX, ReX), leveraging PyTorch and ONNX within reproducible ML workflows.

Delivered tutorials for the Mechatronic Systems Models module.
Contributed to the Davinci research group, focusing on nonlinear control systems and applied mechatronics.

Industry Experience

Designed and deployed AI agents using Google’s ADK and A2A, developing MCP tools for real-time data retrieval, computation and system interaction.
Applied large language models (LLMs) for clustering and topic modeling, deriving insights from high-volume text data.
Optimized large-scale data processing pipelines, improving efficiency and scalability in production workflows.

Led a text classification project comparing traditional NLP methods with fine-tuned BERT-based models, incorporating SHAP for interpretability.
Developed a Retrieval-Augmented Generation (RAG) system using Azure AI Search and OpenAI GPT-4, enabling natural-language access to enterprise data.

Built and deployed Java RESTful APIs on GCP, supporting scalable automation and decision-making pipelines.

Volunteering

Led a workshop on MLOps in Google Cloud, demonstrating how to use Vertex AI to automatically train and deploy a neural network for digit recognition using the MNIST dataset.
Conducted a session on applying Vertex AI APIs for industry applications, including text-to-speech, speech-to-text, and face recognition.
Presented on developing APIs with Flask for NLP tasks such as lemmatization and named entity recognition using spaCy.

Taught basic robotics to children in low-income areas of Bogotá, empowering dozens of individuals with hands-on STEM skills.
Provided foundational JavaScript and HTML education to adolescents and adults, helping them build websites to support their entrepreneurial ventures.

Certifications