![Kushal Dey](https://gradschool.weill.cornell.edu/sites/default/files/faculty_profile_images/dey-kushal-221207-01_rt-12x8.jpg)
Research
The Kushal Dey Lab builds statistical and machine learning models that integrate genetic and genomic data to prioritize variants, genes, and cell types, and to decode the causal functional architecture underlying heritable complex diseases — including immune-related diseases, like Alzheimer’s and inflammatory bowel disease, and heritable cancers, like breast cancer.
Nominating candidate risk genes and gene sets underlying disease-critical processes is of utmost importance for developing drug targets and informing CRISPR screening. The Kushal Dey Lab focuses on developing machine learning models and computational pipelines that integrate genomic and epigenomic data from RNA-seq, ChiP-seq, Perturb-seq and spatial transcriptomic experiments with genetic association studies (GWAS, WES) to enhance our understanding of the functional architecture of all heritable complex diseases, including immune-related diseases like Alzheimers’, IBD, Lupus and several heritable cancers like Breast and Prostate cancers.
Some of the research directions of interest include developing:
- Models to prioritize variants, genes and cell states for disease using a combination of genetic, genomic and perturbation data.
- Models to identify the causal directed graphs underlying gene and gene interaction models for disease.
- Benchmarking pipelines informed by disease genetics to validate and compare different genomic prediction models.
Current Projects:
Keywords: GWAS, Colocalization, Spatial Transcriptomics, Perturb-seq, RNA+ATAC multiome
Bio
Kushal Dey completed his undergraduate and masters training in statistics from Indian Statistical Institute, Kolkata, India. Then, he did his PhD in statistics in University of Chicago under the supervision of Dr. Matthew Stephens. After his PhD in 2018, he did his postdoctoral training with Dr. Alkes Price in Harvard T.H.Chan School of Public Health. He joined as an Assistant Professor in the Computational and Systems Biology Program at Memorial Sloan Kettering Cancer Center in February 2023. Kushal Dey’s research centers around building statistical and machine learning models integrating functional genomics and perturbation data with human disease genetics.
Distinctions
- Josie Robertson Investigator (2023–2028)
- NCI P30 CCSG Developmental Award (2023-2024)
- NCI P30 CCSG supplement – “LLMs in cancer research” (2023-2024)
- Catalog Working Group Co-chair + Disease Focus Group Lead: IGVF consortium (2023-)
- K99/R00 Pathway to Independence Award (NIH/NHGRI) (2022–2026)