Alexander Valverde Guillen

Deep learning researcher developing state-of-the-art models for the medical industry under the supervision of Dr.Yuyin Zhou.

Responsibilities

• Developed deep learning models to meet the requirements of the research employing diffusion techniques with semi-supervised learning.
• Supported a bachelor degree student during the research with tips and PyTorch training.
• Managed multiple research projects simultaneously, ensuring timely completion within budget constraints.
• Applied ethical considerations throughout all stages of the research.

Responsibilities:

• Lead the marketing data science team (3 data scientists) in developing cutting-edge models and solutions
• Drived strategic initiatives to enhance data utilization and business intelligence.
• Developed state-of-the-art solutions for business and society problems.

Key Projects:

• Salesforce Customer Data Platform: Developed the largest customer data platform in the region, integrating and analyzing large datasets to drive business insights.
• Binary Seashell Classification Model: Built the first seashell identification model in Costa Rica for a brand campaign, classifying Pacific and Caribbean seashells. Research paper in progress.
• Classification Models: Created classification algorithms to tailor customer email content, improving engagement and conversion rates.
• Campaign Prediction Models: Developed regression models to forecast campaign outcomes in Facebook Ads, optimizing marketing spend and targeting.
• Seashell Anomaly Detection System: Implemented an anomaly detection system leveraging vector databases for enhanced classification performance.
• Feature Extractor for Image Posts and Billboards: Designed a convolutional neural network-based feature extractor to identify key visual elements in social media posts and billboard ads.
• Image Generator for Brand Campaigns: Created an image generator using diffusion methods, incorporating brand-specific materials for Pilsen's marketing campaigns.

Responsibilities:

• Driving strategic initiatives to enhance data utilization and business intelligence.
• Developing state-of-the-art solutions for business and society problems.
• Training different marketing teams in data governance and strategic methods for data collection.