Rajan's Profile Photo

Rajan, PhD Scholar

School of Interdisciplinary Research
Indian Institute of Technology Delhi
New Delhi, India

About

I’m a PhD student at the Indian Institute of Technology Delhi, working at the intersection of biology and machine learning (ML). I'm part of the Functional Genomics Lab , advised by Prof. Ishaan Gupta. My research focuses on applying ML models to better understand complex biological data.

Research

Machine learning based stratification and risk scoring of healthy and MASLD (No-MASH and MASH) individuals using targeted global lipidomics profiling of plasma samples.

[Publication] [Code]

MASLD Lipidomics

Developed machine-learning models (SVM & BiLSTM) to classify SARS-CoV-2 variants and Omicron subvariants using Surface-Enhanced Raman Spectroscopy (SERS) data from clinical nasopharyngeal swab samples.

[Publication] [Code]

SERS SARS-CoV-2

Education

  • PhD Interdisciplinary Research, Indian Institute of Technology Delhi — Present
  • MSc Zoology, Department of Zoology, University of Delhi — 2021
  • BSc Life Science, Ramjas College, University of Delhi — 2019

Experience

  • Bioinformatics Engineer, Indian Institute of Technology Delhi — Apr 2024 - Present
  • Data Analyst, Indian Institute of Technology Delhi — May 2023 – Mar 2024
  • Project Associate-I, CSIR-Institute of Genomics and Integrative Biology — Dec 2021 – Mar 2023
  • Project Trainee, Department of Zoology, University of Delhi — Aug 2021 – Nov 2021

Publications

  1. Khan, A.*, Rajan*, Malakar, D., Maan, K., Biswas, S., Sheikh, S., Bajaj, A., Shalimar, Gupta, I., & Dasgupta, U. (2026). Identification of plasma lipids as non-invasive signatures for metabolic dysfunction-associated steatotic liver disease. Communications Health, 1(1). https://doi.org/10.1038/s44528-026-00039-w (*Co-first Authors)

  2. Senapati, S., Kaushik, A., Rajan, Singh, A., Gupta, I., Virkar, R., Kulkarni, S. S., Arankalle, V., & Singh, J. P. (2025). Rapid, on-site SARS-CoV-2 variant detection and differentiation using GLAD-pristine silver nanorod arrays and machine learning-enhanced SERS. ACS Omega, 10(39), 44978–44988. https://doi.org/10.1021/acsomega.5c02860

  3. Birla, M., Rajan, Roy, P. G., Gupta, I., & Malik, P. S. (2025). Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review. Oncology, 103(1), 69–81. https://doi.org/10.1159/000540494

  4. Rawat, A., Rajan, Malhi, H. K., & Chaudhary, K. (2023). Artificial intelligence using multiomics/genetic tools and application in liver disease. In Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine in Liver Diseases (pp. 109–131). Elsevier. https://doi.org/10.1016/b978-0-323-99136-0.00015-5

  5. Sharma, V., Singh, A., Gaur, M., Rawat, D., Yadav, A., Rajan, Kumar, C., Varma-Basil, M., Lohiya, S., Khanna, V., Khanna, A., Chaudhry, A., Singh, Y., & Misra, R. (2022). Evaluating the efficacy of stool sample on Xpert MTB/RIF Ultra and its comparison with other sample types by meta-analysis for TB diagnostics. European Journal of Clinical Microbiology & Infectious Diseases, 41(6), 893–906. https://doi.org/10.1007/s10096-022-04449-w

Contact

Email: srz248212@iitd.ac.in

Social Profiles: [LinkedIn] [GitHub]

Research Profiles: [Google Scholar] [ResearchGate] [ORCID]