Zeyu Jiang

Data and Clinical Scientist for the collaborations with KOLs and medical institutions to enhance AI capabilities in critical healthcare applications, directly influencing market strategies and product positioning:

• Led a partnership with Taipei Veterans General Hospital, applying machine learning and deep learning to detect Hemodynamic Instability and Acute Respiratory Distress Syndrome (ARDS). This collaboration not only resulted in the development of 2 advanced inference engines, expanding product features, but also led to the delivery of 2 significant publications. One article was published in a leading journal within the critical care field, and another is currently under review with the aim of placement in a top-tier journal.
• Directed a collaboration with RuiJin Hospital to develop machine learning models for ICU hemodynamic interventions, enhancing early detection and response times. This effort culminated in a research article published in a leading journal in the critical care field.
• Managed a project with The First Hospital of China Medical University, creating a data-driven, personalized prognosis tool for ICU interventions, tailored to individual patient needs.
• Oversaw a strategic collaboration with Philips Research United States, focusing on the localization of AI products and supporting FDA application processes.

As a Product Manager overseeing AI and Healthcare Analytics, I led a pivotal industry-academic collaboration with the School of Computer Science at Zhejiang University, focusing on advancing technologies in precision medicine.

• Developed and delivered a data-driven visual analytics application, providing patient profiling tools that are essential for the exploration of precision medicine.
• Engineered and implemented advanced classification models to systematically identify and categorize patterns in cardiovascular disease patients, enhancing the precision of medical diagnostics and treatments.
• Created predictive models capable of forecasting patient outcomes prematurely, which are critical in optimizing clinical decision-making.
• Utilized cutting-edge D3 JavaScript and other interactive visual technologies to present analytical results dynamically, improving user interaction and data comprehension.
• Designed a novel tool for transforming unstructured data into structured formats, significantly improving data utilization for further classification and predictive analysis.
• Coordinated the handover of technical developments to the commercial department to ensure the project’s seamless transition to market commercialization.

As a Data Scientist, focused on designing algorithms to optimize departmental operations, aligning closely with both customer needs and our company’s product development goals. My key contributions included:

• Tailored integer and dynamic programming algorithms to improve procedure scheduling, directly addressing operational challenges highlighted by hospital staff. The application of these algorithms led to a 15% reduction in pre-operative waiting times for PCI surgeries
• Developing integrated data quality profiles to guide infrastructure upgrades and efficiency enhancements within hospital workflows.
• Implementing automated KPI monitoring systems to swiftly identify and address operational inefficiencies, ensuring solutions were both effective and aligned with strategic objectives.