Expertise and Research Interests:

Dr. Sivaramakrishnan Rajaraman is an accomplished Research Scientist contributing to medical image processing ML/AI at the National Library of Medicine (NLM), National Institutes of Health (NIH), USA. His work revolves around harnessing computational sciences and engineering techniques to revolutionize automated medical decision-making. Dr. Rajaraman’s diverse research portfolio spans machine learning, data science, biomedical image analysis, and computer vision. Before joining NLM, he had 15 years of academic experience where he taught core and allied subjects in electronics, communication, and biomedical engineering while publishing extensively in national and international journals and conferences with a cumulative h-index of 24 (to date). Dr. Rajaraman serves on the Editorial Boards of premier journals like PeerJ Computer Science, PLOS ONE, PLOS Digital Health, and MDPI. He is actively involved in organizing special issues and conference workshops. He is reviewing manuscripts for over 100 prestigious journals and conferences and is holding memberships in SPIE, IEEE, and BMES, demonstrating his commitment to excellence in his field.

Honors and Awards:

Dr. Rajaraman received the NLM Special Acts/Services Group Award in 2018. He is placed in the top 1% of reviewers consecutively on Publons’ global reviewer database for the award years 2017-18 and 2018-19. This award is determined by the number of peer review reports performed during the given award year.

Publications:

Liang Z, Xue Z, Rajaraman S, Antani SK. Automated quantification of SARS-CoV-2 pneumonia with large vision model knowledge adaptation. New Microbes and New Infections, Volume 62, 2024, 101457, ISSN 2052-2975, https://doi.org/10.1016/j.nmni.2024.101457.

Liang Z, Xue Z, Rajaraman S, Antani S. Automated quantification of SARS-CoV-2 pneumonia with large vision model knowledge adaptation. New Microbes and New Infections. New Microbes and New Infections, Volume 62, 2024, 101457, ISSN 2052-2975, https://doi.org/10.1016/j.nmni.2024.101457.

Rajaraman S, Xue Z, Antani S. Editorial on Special Issue “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care”. Diagnostics. 2024; 14(17):1984. https://doi.org/10.3390/diagnostics14171984.

Rajaraman S, Liang Z, Xue Z, Antani S. Noise-Induced Modality-Specific Pretext Learning for Pediatric Chest X-ray Image Classification. Frontiers in Artificial Intelligence, vol. 7, 2024, doi: 10.3389/frai.2024.1419638, ISSN: 2624-8212.

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