Hey, I’m Alekhya.

I’m a Biomedical Engineer passionate about making healthcare more accessible and impactful. In my free time, I enjoy writing articles. Feel free to check out my blog linked below!

Check out my blog:)

Education

MS in Biomedical Engineering

I’m currently pursuing my Master’s in Biomedical Engineering at Columbia University in New York. My goal is to bridge technical innovation with real-world healthcare impact and contribute to making healthcare delivery more accessible:)

B.Tech in Computer Science and Engineering

I completed my Bachelor’s in Technology in Computer Science and Engineering at Mahindra University in India, where I strengthened my problem-solving and analytical skills. It was also where I first discovered my fascination with computational biology and explored how data can enhance our understanding of healthcare!

  • I write on Medium!

    Finding meaning in everyday stories and small moments

  • Graduate Admissions Ambassador

    Ensuring students feel informed and supported

AI Intern
GenePoweRx

I developed machine learning pipelines to predict patient susceptibility to mood disorders and automated genomic data workflows. I collaborated with clinicians, optimized data handling systems, and deployed scalable AWS-based tools that streamlined genomic analysis and reporting.

Skills: Machine Learning | Python | AWS | Data Automation

Experience

Bioinformatics Intern
3BIGS

I contributed to research at the intersection of bioinformatics and infectious disease modeling. I developed a multi-phase proposal for an AI-powered disease warning system, curated microbiome datasets, and supported R&D efforts in single-cell analysis using tools like Nextflow and Snakemake.

Skills: Bioinformatics | Workflow automation | Research communication

Projects

  • Engineered an automated AWS Batch solution for VCF file annotation, reducing processing time from 3 days to under 1 hour. Implemented multi-layer security with IAM controls, TOTP verification, and email-based MFA while ensuring scalability through Docker containers and ECR integration.

  • I explored the intersection of neuroscience and generative AI by decoding brain EEG signals into visual and textual representations. This involved implementing Stable Diffusion and CLIP image encoders in Python to translate neural signals and text inputs into high-quality images, and using BLIP for automated caption generation.

  • This project focused on improving clinical documentation using Named Entity Recognition (NER) techniques. I integrated rule-based and BiLSTM models to identify and extract medical entities from clinical text, built and annotated a MultiCardioNER dataset for model training, and designed the user interface for the accompanying web application using Figma.