Khyati Raghunath Chandratre is a Doctoral candidate and GRACE Fellowship awardee in the Zhang Lab. She investigates the changes in 3D genome organisation in different prostate cancer cell lines to study transcription dysregulation by integrating chromatin data,  multi-omics data (ChIP-Seq & RNA-Seq) and machine learning.

Xingyu’s research focuses on using applied machine learning / deep learning models to investigate and simulate the intricate process of tissue and organ boundary formation during the early developmental stages of C.elegans worms, uncovering critical insights into gene regulated cellular morphology.

Maithri’s research is centered on computationally studying the developmental systems of C. elegans. Its inherent invariance leads to exceptional experimental reproducibility, making it an ideal organism for exploring fundamental biological processes. Currently, her work involves predicting and modelling critical developmental events in the worm gut.

Chengcheng Liu’s research aims to combine single-cell sequencing (scRNA-seq, scATAC-seq), bulk transcriptomics, and whole genome sequence approaches to study cancer development.

Dr. Ben Niu studies Systems Biology with mathematical and machine learning approaches. He is currently focusing on understanding how gene expression regulation controls early embryogenesis using C. elegans as the model organism. His is specialised in data mining, image pattern recognition, bioinformatics, mathematical modelling and software engineering.

Dr. Ahmed Abbas Elmahdi interested in applying machine learning techniques to analyze and predict three-dimensional genome organisation.