I am a Machine Learning Engineer with industry experience in both Natural Language Processing (NLP) and Computer Vision (CV). I am an avid learner, responsible, proactive, and goal-oriented. My aim is to create systems that add value to organizations through engineering principles, data science, machine learning, computer vision, and natural language processing.I currently lead key NLP and MLOps projects at Titan Intake Inc., focusing on enhancing the patient intake process within specialty clinics across the United States. Previously, I was an Assistant Professor at ICESI University, where I served as Director of the Master's Program in Data Science. I helped create the Center for Data Science (now Center for Data Science and AI) to provide on-demand training, applied research, and consultancy services to public and private organizations in Colombia.Before that, I worked at EAFIT University as a postdoctoral researcher on the PEAK Urban project, applying machine learning models to satellite images and GIS data to assess urban environments in developing cities. This research helped planners and public utility companies like EPM predict urban growth, aqueduct, and sewage demands in Medellín, Colombia.Over the years, I have applied data science, machine learning (including deep learning), natural language processing, computer vision, and digital signal and image processing as a lecturer, supervisor, researcher, developer, and consultant. I have worked on several projects utilizing machine learning and computer vision capabilities on edge devices such as GPU-enabled embedded platforms and smartphones. These projects successfully scaled, benefiting from fast data ingestion, storage, and visualization services in the cloud, enhancing performance and accessibility.Some of the projects I have led include extracting data from unstructured text in health applications; estimating city-wide per-capita income from real estate data; detecting nutrient deficiencies in oil palms from live images using convolutional neural networks; evaluating and geolocating urban noise in multiple frequency bands in real-time; identifying suspicious motion in images for surveillance; and automating walking-people counting in shopping centers to help retailers evaluate the impact of sales strategies.Overall, I am interested in applying machine learning, natural language processing, computer vision, and data science to industries, smart cities, agriculture, and autonomous systems. My ongoing journey in these fields aims to foster innovation and create impactful solutions.