Rajan's Profile Photo

Rajan, PhD Scholar

School of Interdisciplinary Research (SIRe),
Indian Institute of Technology Delhi,
New Delhi, India

About

I’m a second-year 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 Dr. Ishaan Gupta. My research focuses on applying ML techniques to better understand complex biological data. I completed both my master’s and bachelor’s degrees from the University of Delhi, in 2021 and 2019 respectively.
Beyond research, I enjoy traveling, reading, and exploring new ideas—both within science and beyond.

Research

Machine Learning Enhanced SERS for SARS-CoV-2 Variant Classification

Applied machine learning (SVM) and deep learning (BiLSTM) models to enable rapid, on-site SERS-based detection and classification of SARS-CoV-2 variants and Omicron subvariants. (View Publication ; GitHub Repository)

acsomega.5c02860

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. 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

  2. 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

  3. 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

  4. 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]