About

Wen Shu Tang is a highly skilled and experienced software engineer with a focus on data engineering and machine learning. With over 15 years of relevant experience, she has played a key role in evolving early-stage startups into revenue-generating companies. Wen's broad and deep technical expertise spans full-stack development, cloud infrastructure, and complex software and data platforms. Wen's recent area of focus has been in ML/NLP in the clinical context. She has developed NLP models using state-of-the-art deep neural networks architecture (BERT), taking them from conception, data gathering, model experimentation, to production deployment. The end deliverables increased data processing efficiency and accuracy by orders of magnitude. As a proven leader in delivering production-ready systems, Wen has led numerous projects that delivered business-critical features, complex data strategies, and data processing pipelines. In those projects, she has led teams of engineers, data scientists, and QA engineers to collaborate on all aspects of the software development life-cycle. Wen is interested in tackling complex data problems, where once unraveled, can provide tangible benefits to end-users. She is especially enthusiastic about active learning systems where user interactions can incrementally enhance data labeling, creating a self-serving cycle that continuously improves the user experience. Wen's tech stack includes ML, Data Engineering, NLP, BERT, Software Engineering, QA, Neural Networks, Infra, AWS, Integration, CI/CD, Kubernetes, TensorFlow, Elastic Search, Microservices, DevOps, ETL, and Backend. She holds a BS and MS in Electrical and Computer Engineering from Carnegie Mellon University and attended the American Cooperative School. Wen is currently a Senior Staff Engineer - Machine Learning at Lacuna Technologies and has previously worked as a Senior Machine Learning Consultant at West Coast Informatics, LLC and a Senior Software Engineer at Ciitizen. At West Coast Informatics, she was part of the founding team that helped to scale the company from zero to a revenue-generating platform. She was one of the early engineers that helped to define the microservices-based architecture and core data pipeline. At Ciitizen, she experiment, developed, and deployed NLP-based ML solutions in a clinical context, including clinical entity recognition and classification.