Speaker Profile
Ph.D., Director, Amgen
Biography
Dr. Paul (Weibing) Shi has over 15 years of experience in computational biology, bioinformatics, and biomarker analysis. As Scientific Associate Director at Amgen, he leads a team generating critical biomarker data and overseeing infrastructure projects and Omics platform development. His team leverages AI/ML technologies for biomarker data processing and predictive signature development, enhancing drug discovery and development. At Roche and other renowned institutions, Dr. Shi developed bioinformatics workflows and managed large-scale NGS projects. Passionate about inclusivity, he champions the EPR (Encourage, Praise, and Recognize) approach to empower teams. Dr. Shi has authored over 20 scientific publications and is a certified SAFe® 5 Agilist.
Session Abstract – PMWC 2026 Silicon Valley
Track Chair:
Victor Velculescu, Johns Hopkins University
PMWC Award Ceremony
• Daniel De Carvalho, University of Toronto
From Mutation to Methylation: The Next Wave of Liquid Biopsy Biomarkers
• Chair: Victor Velculescu, Johns Hopkins University
• Daniel De Carvalho, University of Toronto
• Stephen Master, CHOP/U Penn
• Gordon Sanghera, Oxford Nanopore Technologies
Advancing Minimal Residual Disease Detection Through cfDNA & cfRNA Profiling
• Chair: Luis Diaz, Memorial Sloan Kettering Cancer Center
• Anne-Renee Hartman, Adela
• Minetta Liu, Natera
• Rita Shaknovich, Agilent
• Ajay Gannerkote, Integrated DNA Tech
AI-Informed Biomarker Trials: Turning Early Signals into Actionable Designs
• Chair: Manish Kohli, University of Utah
• Eric Klein, GRAIL
• Sarah Moseley, DELFI Diagnostics
• Samuel Levy, ClearNote Health
Role of AI in Liquid Biopsies & Cancer Detection
• Chair: Amoolya Singh, DELFI Diagnostics
• Ron Andrews, Dxcover
• Pankaj Vats, NVIDIA
• Paul Shi, Amgen
• Christopher Troll, Claret Bioscience
Integrating Genetic Risk with Early Detection: A Precision Prevention Framework for Cardiovascular Disease
• Paolo Di Domenico, Allelica
AI-Driven Metagenomic and Host RNA Profiling for Precision Diagnosis of Infections
• Charles Chiu, UCSF
AI-Driven Host–Pathogen Signatures from Plasma cfDNA: Bridging Infection Biology and Early Diagnostics
• Sivan Bercovici, Karius
Ultra-Sensitive Multimodal Liquid Biopsy for Early Cancer Detection: AI-Driven Signal Profiling
• John Sninsky, CellMax Life
Overcoming Limits of Traditional cfDNA Assays Using Active Chromatin
• Diana Abdueva, Aqtual
Whole-genome methylome-based early cancer signal detection
• Sally Mackenzie, EpiMethyl Analytics
BrainSee Sees the Brain: FDA-Approved AI for Predicting Modifiable Risk of Developing Alzheimer’s Within Five Year
• Padideh Kamali-Zare, Darmiyan
