Passion Fuels Purpose!

Conducting advanced AI-driven research to enhance computational models for bioinformatics and genomic data analysis. Developing deep learning frameworks for pattern recognition in biological sequences, optimizing machine learning algorithms for high-throughput sequencing data, and integrating multi-omics data to derive novel biological insights. Collaborating with interdisciplinary teams to publish findings in high-impact journals and contribute to grant proposals.

Led multiple research projects focusing on deep learning and AI applications for large-scale biological data processing. Designed and implemented neural network architectures to analyze genomic and transcriptomic data, enhancing the accuracy of predictive models. Developed bioinformatics pipelines using Python and R for next-generation sequencing (NGS) analysis. Published peer-reviewed research and presented findings at international conferences.

Designed and optimized computational workflows for genome analysis, focusing on agricultural research applications. Developed custom Python and Bash scripts for data preprocessing, variant calling, and transcriptomic analysis. Conducted differential gene expression analysis to identify key regulatory genes in crop improvement studies. Provided bioinformatics training to researchers and assisted in publishing results in scientific journals.

Taught undergraduate courses in bioinformatics, computational biology, and biostatistics, covering topics such as sequence alignment, molecular modeling, and systems biology. Developed interactive course materials and guided students in research projects on bioinformatics applications in drug discovery. Organized workshops and seminars on emerging trends in computational biology and genomics.