Papers
2
Total Citations
14
H-Index
2
About
Anubhav Tripathi is a researcher whose work bridges the critical intersection of analytical chemistry and artificial intelligence, with a particular focus on mental health diagnostics and intelligent systems. His primary research areas include bioanalytical method development for psychiatric medications and the application of machine learning to virtual assistant technologies. Tripathi’s most impactful contribution is a highly detailed 2023 study on the quantification of four classes of antidepressants from human serum using LC–MS/MS, which has garnered 9 citations. This work addresses the growing global mental health crisis—where antidepressant prescriptions have tripled in two decades—by providing a robust analytical method to personalize treatment and resolve the critical mismatch between drug availability and patient response. Additionally, his 2019 correlative analysis of intelligent virtual assistants and machine learning (5 citations) explores how AI-driven voice interfaces are transforming daily human-computer interaction. Through these dual contributions, Tripathi demonstrates a unique ability to apply rigorous analytical science to pressing medical challenges while also advancing the frontiers of human-AI interaction.
Research Focus
Key Achievements
Top Papers
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