Rajesh Pandey’s tryst with Biological Science started with Graduate degree in Zoology from University of Calcutta, followed by Master’s degree in Zoology, from University of Delhi. During PhD in Biotechnology from CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), he functionally elucidated the regulatory role played by Noncoding RNAs in Stress Response. Subsequently, Rajesh’s postdoctoral stint at Johns Hopkins University, Maryland, USA, and MRC Harwell Institute, Oxfordshire, UK, helped enhance the understanding further with exposure to different diseases and strength of Genomics. As Principal Scientist and Group leader at CSIR-IGIB, his lab is focussed on INtegrativeGENomics of HOst-PathogEn (INGEN-HOPE) to elucidate the hierarchical regulation of factors modulating Disease severity sub-phenotypes and Clinical outcome. The pathogen and host response findings have been published in more than 120 research articles in journals inclusive of Genome Biology, iScience, NAR, Frontiers in Immunology, Clinical & Translational Medicine, Microbiology Spectrum, Life Science Alliance, mBio, Nature, Science, and Lancet Infectious diseases. Rajesh has academic interest towards writing books elucidating aspects of host-pathogen Interactome. His two books, (i) RNA-based Regulation in Human Health and Disease, and (ii) Genomic Surveillance and Pandemic Preparedness, published by Elsevier, is having global readership.
Ramanathan Sethuraman has 28 years of research and development expertise in multimedia and healthcare analytics. After his PhD from the Indian Institute of Science in Digital Signal Processor architectures, he has worked as a Research Scientist at Philips Research Labs (PRL) in The Netherlands, as a Director and Product Manager at Silicon Hive, and as a Media/Healthcare Architect and Principal Engineer at Intel. In healthcare analytics, his research focus has been on understanding multimodal Health and Life Sciences (HLS) data, leading to novel insights that point towards disease causation rather than just correlation. His research premise is centered around AI-ML-DL based learning from HLS Big Data (OMICS of hologenome) of metaorganisms (organisms that coexist with their microbiota), which reveals more comprehensive disease manifestation pathways, allowing for earlier disease detection and more efficacious interventions. He holds 20 US patents and over 60 peer-reviewed publications.