eSupervisor Detail

About me

I am a neuroscience and computational biology researcher focussing on unraveling the molecular mechanisms by integrating in-vivo in-silico techniques to decode the signaling cascades driving cognitive decline. Alongside mechanistic research, I develop AI/ML-based drug prediction alongwith molecular docking and simulations pipelines to identify therapeutic candidates. My long-term goal is to design clinically relevant interventions for neurodegenerative diseases with data-driven drug discovery.

Interests: My research interests lie at the intersection of neuroscience, computational biology, and data-driven life sciences research, with a strong emphasis on translational and interdisciplinary approaches. I am particularly focused on understanding the molecular mechanisms underlying neurodegenerative conditions such as post-stroke cognitive impairment (PSCI), especially through region-specific neuroinflammatory pathways in the cortex and hippocampus. My work integrates both experimental and computational domains. I have hands-on experience with in vivo rodent models, neurobehavioral assays, and molecular biology techniques, complemented by advanced skills in transcriptomics, network biology, and multi-omics data analysis. This dual expertise enables me to guide research from hypothesis generation to data interpretation with clarity and scientific rigor. In addition, I actively work on AI/ML-driven drug discovery pipelines, where I apply machine learning algorithms to molecular datasets (e.g., SMILES-based representations) to predict potential therapeutic candidates. I further validate these findings using molecular docking and simulation approaches, providing a comprehensive framework for computational drug discovery. Beyond my individual research, I am deeply interested in mentoring and guiding students in life sciences research. I aim to help learners build strong foundations in experimental design, data analysis, and scientific writing, while also introducing them to emerging areas such as bioinformatics and AI in biology. My goal is to foster critical thinking, interdisciplinary learning, and research independence among students.