Areas of focus

  • AI to automate patient diagnosis (Kohane Lab, aka "Zaklab")
  • Artificial Intelligence for Cancer Drug Discovery (Zitnik Lab)
  • Cancer treatment response (Kohane Lab, aka "Zaklab")
  • Computational genomics in cancer and neuroscience (Park Lab)
  • Data visualization, analysis, and management tools to study genomic structural variants, dynamics of the 3D genome, and cancer subtypes in patient cohorts (Gehlenborg Lab)
  • Drug-drug interaction detection in real-world claims data and healthcare records (Avillach Lab/Harvard-MIT Center for Regulatory Science)
  • Hospital opioid use and ulcerative colitis surgical trajectories (Surgical Informatics Lab)
  • Large Language Models (LLM) (Kohane Lab, aka "Zaklab")
  • Machine learning-enabled pathology (Yu Lab)
  • Pathogen genomics, epidemiology and evolution (Farhat Lab)
  • Phenotype extraction and biomedical ontologies (Avillach Lab)
  • Precision medicine, from genomics to clinical data science and machine learning (Berkowitz Family Living Laboratory)
  • Representation learning and embeddings for biomedical networks and knowledge graphs (Zitnik Lab)
  • Statistical genetics methods development (O'Connor Lab)