Li Wang Email & Phone Number

New York, NY, US

Somerville, Massachusetts, US

• Lead company precision oncology team (5 PhD and 1 Master) using causal AI modeling for target and biomarker discovery.
• Oversee external research collaborations with pharmaceutical and academic partners to advance cancer biology, target and biomarker discovery programs.
• Work with business development team to craft collaboration project scopes and contracts.

Stamford, CT, US

• Leading development of advanced AI tools for integrating omics data and in-silico disease gene perturbation and prioritization
• Built and managed integrative causal gene network pipelines using AWS BATCH integrating gene expression, eQTL, TF-regulation and protein complex data.
• Constructed cell type and age-specific causal gene networks from single-cell and bulk tissue omics data for key-regulator identification.
• Used large language models (gene transformers) for in-silico gene perturbation and causal network construction.
• Modeled disease gene and phenotype knowledge graphs using graph attention networks (GAT) to facilitate causal variation prioritization.

Stamford, CT, US

• Recruited and managed a team of three Bioinformaticians, providing leadership and supervision for various industrial and academic collaborations, including but not limited to:
• Metabolic and Proteomics data analysis in NASH
• Comparative analysis of mouse and human single-cell RNA sequencing in bladder cancer
• Collaborative projects related to WTC (World Trade Center) prostate cancer projects
• Network-based biomarker discovery in Multiple Myeloma
• Identification of genetic modifiers using eQTL (Expression Quantitative Trait Loci)

New York, NY, US

• Pioneered the development of predictive disease and drug response models using single-cell omic data, with a primary focus on cancer immunotherapy. This foundational research has been instrumental in securing multiple.
• Led investigations into the understanding of the tumor microenvironment by employing cutting-edge techniques such as Visium Spatial-seq and Imaging Mass Spectrometry.
• Played a pivotal role in uncovering Myeloid Cell-associated Resistance to PD-1/PD-L1 Blockade in Urothelial Cancer through in-depth analysis, combining bulk and single-cell RNA sequencing data.
• Conducted comprehensive research into the gene expression associated with Epithelial-Mesenchymal Transition (EMT), T cell infiltration, and patient outcomes with PD-1 blockade in metastatic urothelial cancer, yielding.
• Developed a robust blood gene expression-based prognostic model for castration-resistant prostate cancer, enhancing patient management and treatment strategies

New York, NY, US

• Developed and implemented multiple innovative in-silico deconvolution techniques to dissect the various compartments within the mixed tissues, enabling refined cancer subtyping and disease phenotype prediction.
• Introduced a novel single-cell transcriptomic-informed deconvolution method for bulk transcriptomic data, allowing the identification of cellular subpopulations associated with immune checkpoint blockade resistance, a.
• Pioneered a new algorithm for identifying cancer-intrinsic subtypes within gene expression deconvolution, providing estimates of subtype-specific expression profiles. This breakthrough has substantial implications for.
• Designed a new strategy to construct blood-based disease-specific classifiers by leveraging both cell component changes and cell molecular state changes, improving diagnostic accuracy and disease monitoring.
• Developed a method to dissect tumor cell-specific gene regulatory networks based on Gaussian mixture models and Gaussian graphical models, contributing to a deeper understanding of the molecular mechanisms underlying.

Basel, Baselstadt, CH

• Played a significant role in predictive modeling efforts in the Cancer Cell Line Encyclopedia (CCLE) project, a collaborative venture with the Broad Institute. Many of the predictive have been rigorously validated in.
• Spearheaded biomarker discovery for patient stratification and for gaining insights into drug resistance mechanisms, contributing to the development of more effective treatment strategies.
• Undertook target mining initiatives, prioritizing potential new drugs and drug targets by analyzing sensitivity profiles of thousands of compounds with unknown or partially known mechanisms of action.
• Designed and implemented a web tool, featuring both a front-end web user interface for customized predictive modeling and a back-end parallel computing system in a high-performance cluster, facilitating user-friendly.

Seattle, WA, US

Ph.D., Computational Biology

M.S., Statisics

B.S., Biology & Computer Science