Siddarth Dey

Siddarth Dey serves as Associate Professor in Chemical Engineering at UC Santa Barbara's College of Engineering with dual affiliation in Bioengineering. His research program integrates chemical engineering principles with biological discovery to address fundamental questions in cellular heterogeneity.

Educational background:

• BS in Chemical Engineering, Institute of Chemical Technology (2006)
• PhD in Chemical and Biomolecular Engineering, University of California, Berkeley (2012)

His laboratory pioneers single-cell multi-omics technologies to simultaneously profile epigenomes and transcriptomes within individual cells. This innovative approach reveals how identical genomic blueprints produce diverse cellular functions in tissues like heart, brain, and intestine. Current research focuses on epigenetic regulation during early mammalian development, tissue regeneration mechanisms, tumor progression pathways, and cellular lineage tree reconstruction for regenerative medicine applications.

Analysis of his publication record shows consistent focus on technological innovation in single-cell epigenomics, particularly DNA methylation dynamics. His work bridges molecular biology, quantitative engineering, and computational analysis to decode cellular decision-making processes.

Major recognitions include:

• NSF CAREER Award (2024) for early-career research excellence
• Potter Lecture at Cincinnati Children's Hospital Medical Center (2021)
• Shu Chien Early Career Jury Prize (2022)

Professor Dey actively mentors graduate students and postdoctoral researchers, currently advertising two postdoc positions. His research program is supported by competitive grants including the NSF CAREER award. The lab maintains strong collaborations across bioengineering and developmental biology disciplines to advance single-cell analysis methodologies.

Research operations are conducted in laboratory space 2206 of the BioEngineering Building, where the team develops integrated sequencing platforms for simultaneous epigenome-transcriptome measurements. The group emphasizes quantitative approaches to unravel gene expression heterogeneity in complex biological systems.