Anandasankar Ray

The paper uses machine learning to identify repellent odorants for honey bees, validated in both lab and field settings, showing potential for pesticide mitigation.

The paper uses machine learning to predict odor valence in humans and insects, screening millions of compounds to identify pleasant-smelling insect repellents.

The paper investigates how exposure to volatile chemicals, like diacetyl, affects gene expression and physiology by inhibiting HDACs in Drosophila and human cells.

This study shows that Gr2 and Gr3 subunits are sufficient for CO2 detection in Drosophila, while Gr1 modulates sensitivity and ligand diversity.

This study shows that light-evoked attraction/avoidance behaviors in mosquitoes are circadian and vary between day- and night-biting species.

The paper identifies 4-methylpiperidine as a repellent with a larger protective zone than DEET, showing it does not require Or function in Aedes aegypti.