Abhijith C Dixith

• Provided data visualizations of cashflows using Airtable software to effectively communicate business insights, improving financial transparency and ensure key cost-saving opportunities across departments.
• Improved decision-making processes with accurate data analysis and visualization techniques, reducing manual effort by 28% and accelerated decision-making cycles by 23%.
• Supported marketing strategies by providing detailed customer segmentation analysis, boosting campaign ROI by 18% and informing target marketing strategies that increased engagement by 22%.

• Engineered an automated system leveraging generative AI to analyze diverse datasets and produce synthetic images, streamlining exploratory data analysis and reducing manual processing time by 40%.
• Designed and deployed over 5 custom generative models using prompt engineering and transformer-based architectures to support strategic analysis across healthcare and marketing domains, resulting in 27% faster insight generation and improved stakeholder engagement.
• Enabled scalable experimentation with multimodal data (text, image, and tabular) by integrating Python-based automation and cloud compute resources, enhancing reproducibility and accelerating model iteration cycles by 3x.

• Implemented a pipeline using DeSeq2 for RNA sequencing which involved studying the effect of a specific gene on gene dysregulation in a mouse model of a repeat expansion disease.
• Identified key differentially expressed genes responsible for Huntington's disease, contributing to the understanding of molecular mechanisms and potential therapeutic targets.
• Applied machine learning techniques to calculate surrogate variable analysis (SVA), improving signal detection and reducing batch effects across high-dimensional transcriptomic datasets.
• Collaborated with cross-disciplinary teams to validate findings and integrate results into broader neurogenetics research, resulting in faster hypothesis generation and downstream experimentation.