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Celebrating Professor Rajeev K. Varshney's transformative research odyssey from genomics to the field on his induction as Fellow of the Royal Society.

Vanika GargRutwik BarmukhAnnapurna ChitikineniManish RoorkiwalChris OjiewoAbhishek BohraMahendar ThudiVikas Kumar SinghHimabindu KudapaRachit K SaxenaJake FountainReyazul Rouf MirChellapilla BharadwajXiaoping ChenXin LiuManish K Pandey
Published in: Plant biotechnology journal (2024)
Professor Rajeev K. Varshney's transformative impact on crop genomics, genetics, and agriculture is the result of his passion, dedication, and unyielding commitment to harnessing the potential of genomics to address the most pressing challenges faced by the global agricultural community. Starting from a small town in India and reaching the global stage, Professor Varshney's academic and professional trajectory has inspired many scientists active in research today. His ground-breaking work, especially his effort to list orphan tropical crops to genomic resource-rich entities, has been transformative. Beyond his scientific achievements, Professor Varshney is recognized by his colleagues as an exemplary mentor, fostering the growth of future researchers, building institutional capacity, and strengthening scientific capability. His focus on translational genomics and strengthening seed system in developing countries for the improvement of agriculture has made a tangible impact on farmers' lives. His skills have been best utilized in roles at leading research centres where he has applied his expertise to deliver a new vision for crop improvement. These efforts have now been recognized by the Royal Society with the award of the Fellowship (FRS). As we mark this significant milestone in his career, we not only celebrate Professor Varshney's accomplishments but also his wider contributions that continue to transform the agricultural landscape.
Keyphrases
  • climate change
  • single cell
  • human health
  • medical students
  • healthcare
  • mental health
  • heavy metals
  • south africa
  • machine learning
  • copy number
  • quality improvement
  • big data