Researcher
Developed deep-learning approaches for modelling and transferring perturbation responses across biological contexts, with a focus on biologically meaningful prediction and evaluation.
My Journey Through Computational Biology: From Data Analysis to Modern AI
Developed deep-learning approaches for modelling and transferring perturbation responses across biological contexts, with a focus on biologically meaningful prediction and evaluation.
GoldLab, University College Dublin, Ireland
Marie Skłodowska-Curie Actions Fellowship — competitive EU-wide award
Developed computational approaches to identify and characterise regulatory non-coding RNA targets using functional genomics, CRISPR perturbation, and multi-omics data.
Onkoslab, National Centre for Biological Sciences (NCBS), India
Applied computational genomics and machine learning to study cancer regulatory mechanisms, tumour heterogeneity, and biomarkers of immunotherapy response across bulk and single-cell datasets.
Institute of Bioinformatics and Applied Biotechnology (IBAB), India
Foundations in bioinformatics, genomics, and applied biotechnology.
PyTorch meta-learning framework that transfers gene and drug perturbation responses across biological contexts.
Cis-regulatory lncRNA discovery framework characterising 268 human and 134 mouse regulatory targets at controlled false-discovery rates.
Differential chromatin accessibility landscape of gain-of-function mutant p53 tumours.
Exploring prognostic association of immunoproteasome expression in solid tumours.
Investigating regulatory elements involved in RNA–DNA interactions. Exploring links between DNA–DNA and RNA–DNA interaction landscapes.
Pilot analysis of single-cell SCLC data to investigate how the local liver microenvironment influences tumour cell evolution.