/ About this event
Join us for Causal AI for Drug Discovery: Learning from Patient Data - Learning causal structure across environments and task-aware data enhancement Much of the patient-derived biological data available for drug discovery is observational, capturing biology across individuals, disease states, tissues, and cellular contexts. These observations offer opportunities to learn more about causal relationships, while noise and sparsity create challenges for extracting reliable information.
What more can observational patient data reveal about causal relationships in biology? What theoretical foundations enable us to learn from differences across biological environments? How can task-aware data enhancement and synthetic data generation help us learn from noisy, sparse biological measurements? Join Synlico during SF Tech Week for a scientific discussion exploring two connected areas at the intersection of AI and biomedical research: causal discovery across environments and task-aware data enhancement. Moderator: Dr. Jingwei Lu, Founder & CEO at Synlico Speakers: Dr. Yingzhen Yang, Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University Topic: Task-aware data enhancement
Dr. Amin Jaber, Machine Learning Scientist at Synlico Topic: Learning causal structure across environments from observational data For researchers in causal inference, machine learning, generative AI, single-cell genomics, computational biology, and drug discovery who want to move from pattern recognition to causal models of biological intervention.
Synlico is developing SynCausal™, a patient-native causal AI platform using single-cell data to learn directed gene-gene causal graphs and inference interventional outcomes of target/pathways in patients, with application in target discovery, patient molecular response stratification and, potentially in the future, mechanistic toxicology. Learn more at www.synlico.com.
This event is a part of #SFTechWeek—a week of events hosted by VCs and startups to bring together the tech ecosystem. Learn more at www.tech-week.com.
