Rohit Kumar Verma

About

I am a computational biologist with a background in bioinformatics and machine learning. My research mainly focuses on cancer genomics and computational biology. I am currently working as a Senior Research Officer at the University of Essex. Before this, I worked as a postdoctoral researcher at the Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre in Navi Mumbai, India.
I completed my PhD in Bioinformatics from Shiv Nadar Institution of Eminence (SNIoE), India, under the guidance of Dr. Ashutosh Singh and Dr. Prashant Kumar Srivastava. During my PhD, I developed computational methods to integrate multi-omics data for identifying meaningful biological changes in gastrointestinal tract cancers, and to discover key biomarkers using machine learning and bioinformatics approaches. I also hold an MTech in Computational Biology from Indraprastha Institute of Information Technology, Delhi.
My interest in molecular biology started during my college days, when I became curious about how DNA works in living systems. Over time, this interest grew into a focus on epigenetics and applying machine learning to solve complex biological problems.

Employment

• ACTREC Post Doctoral
  2025 - Present
• Shiv Nadar University PhD Scholar
  2019 - 2025

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (8)

• Identification of Biomarkers for Colorectal Cancer using Machine Learning and Bioinformatics Approaches
  2025 International Conference on Innovation in Computing and Engineering (ICE) 2025 DOI: 10.1109/ice63309.2025.10983928
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• Machine Learning-Based Identification of B4GALNT1 as a Key Player in Hepatocellular Carcinoma: A Comprehensive Bioinformatics and Structural Analysis
  2024 DOI: 10.1101/2024.01.29.577885
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• Leveraging ChatGPT and Bard: What does it convey for water treatment/desalination and harvesting sectors?
  Desalination 2024 DOI: 10.1016/j.desal.2023.117085
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• A holistic review on how artificial intelligence has redefined water treatment and seawater desalination processes
  Desalination 2023 DOI: 10.1016/j.desal.2022.116221
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• Machine learning classification of triple negative breast cancer using transcriptomic data
  Unpublished 2023 DOI: 10.13140/RG.2.2.24741.68329
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• Molecular dynamics study of tropical calcific pancreatitis (TCP) associated calcium-sensing receptor single nucleotide variation
  Frontiers in Molecular Biosciences 2022 DOI: 10.3389/fmolb.2022.982831
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• Exploration of time series model for predictive evaluation of long-term performance of membrane distillation desalination
  Process Safety and Environmental Protection 2022 DOI: 10.1016/j.psep.2022.01.058
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• Computational challenges in detection of cancer using cell-free DNA methylation
  Computational and Structural Biotechnology Journal 2022 DOI: 10.1016/j.csbj.2021.12.001
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