Heather Chen
Vice President North America at GPI IBERIA
United States
Summary
👤
Senior🎓
Top SchoolHeather Chen is a technology executive and former software engineer with 12 years of experience building and commercializing web-based healthcare applications across North America and international markets. As Vice President for North America at GPI Iberia, she has led FDA-cleared product deployments and scaled go-to-market operations for e-Delphyn donor and laboratory management systems. She blends hands-on engineering roots—contributing to core NLP tooling in projects like Stanford CoreNLP—with entrepreneurship and a user-centered approach to product design. Her background in systems-level UNIX and SCSI development at Motorola informs a pragmatic view of reliability and performance in healthcare software. Known for prioritizing the human factor, she connects customers and teams to turn complex clinical workflows into intuitive, compliant solutions. Based in the United States and trained in computer science at the University of Pennsylvania, she actively explores breakthrough technologies to drive impact in health tech.
12 years of coding experience
9 years of employment as a software developer
Computer Science, (Networks and Social Systems Engineering), Computer Science, (Networks and Social Systems Engineering) at University of Pennsylvania
Github Skills (4)
natural-language-processing10
java10
nlp10
javas10
Programming languages (1)
Github contributions (2)
stanfordnlp/CoreNLP
Jul 2014 - Jul 2014
CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:11 commits in 1 day
Contributions summary:Heather primarily contributed to the core NLP tools within the stanfordnlp/corenlp repository. Their work included modifying Java code in various files related to parsing and language parameters, with a focus on category combinations and options. The user also made changes to lexer and classification components, suggesting work in multiple areas of the NLP pipeline. These changes demonstrate the user's involvement in refining the core functionalities of the NLP tools.
word-embeddingssentiment-analysisnatural-language-processingstanford-nlpsuite
ajutscaria/CS224U
Nov 2013 - Jan 2014
Contributions:53 commits in 2 months
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