Lili Peng currently serves as the Computational Biology AI/ML Leader at Amgen, where she spearheads innovative projects that leverage artificial intelligence and machine learning to enhance drug discovery and development processes. With a robust background in computational chemistry and synthetic biology, Lili is at the...
Lili Peng currently serves as the Computational Biology AI/ML Leader at Amgen, where she spearheads innovative projects that leverage artificial intelligence and machine learning to enhance drug discovery and development processes. With a robust background in computational chemistry and synthetic biology, Lili is at the forefront of integrating advanced analytics into the research and development pipeline. Her role within the Computational Data Sciences team in the CRADI (Computational Research and Advanced Data Integration) division focuses on harnessing data-driven insights to address complex scientific challenges, ultimately accelerating the therapeutic discovery process.
One of Lili's key projects involves the application of machine learning algorithms to analyze large-scale biological datasets, enabling the identification of novel drug targets and biomarkers. By employing mathematical modeling and molecular dynamics simulations, she collaborates with cross-functional teams to optimize lead compounds and predict their interactions at the molecular level. Lili's expertise in sequence analysis and scientific computing further enhances her ability to derive actionable insights from genomic and proteomic data, driving innovation in biotechnology.
A firm believer in the collaborative nature of data science, Lili actively fosters a culture of teamwork and knowledge sharing within her organization. She is passionate about mentoring emerging talent in the field, ensuring that the next generation of scientists is equipped with the skills necessary to tackle the evolving landscape of drug discovery. With her enterprise mindset and innate curiosity, Lili Peng is committed to pushing the boundaries of computational biology, ultimately contributing to the development of groundbreaking therapies that improve patient outcomes.