AI Researcher · Full-Stack Engineer · Product Builder

Building Intelligent Systems for Healthcare, Research & Global Careers.

I’m Bhavana Gutta, a Computer Science student and builder focused on machine learning, scalable web applications, healthcare AI, bioinformatics, and practical products that solve real problems.

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96.7%Custom CNN Accuracy
6+Major Portfolio Projects
AI + BioHealthcare Research Focus
About Me

I don’t just build apps — I build intelligent systems.

My work sits at the intersection of AI research, full-stack software engineering, healthcare technology, and bioinformatics. I enjoy taking complex ideas — like medical image classification, visa-sponsored job discovery, or genomic data analysis — and turning them into clear, usable, and scalable systems.

I’m currently strengthening my portfolio with production-style projects in AI platforms, dashboards, backend architecture, and research tools while continuing to build my technical depth in machine learning, data engineering, and scalable web systems.

Featured Projects

Engineering Portfolio

These projects show where I’m strongest: AI systems, healthcare ML, research tools, full-stack platforms, and scalable backend thinking.

01In Progress

VisaHire.ai — AI Job & Visa Platform

A full-stack AI platform designed to help international students discover visa-sponsored roles, filter companies by work authorization support, and track applications in one clean dashboard.

  • Built around Next.js, NestJS, TypeScript, PostgreSQL, and REST APIs.
  • Designed smart filters for H-1B, OPT, STEM OPT, relocation, and sponsorship-friendly roles.
  • Planned AI features include resume-job matching, company insights, and application tracking.
AI ProductNext.jsNestJSPostgreSQLTypeScript
02Research Project

Alzheimer’s Detection using Deep Learning

A healthcare AI research project focused on early Alzheimer’s disease detection from MRI scans using CNN-based deep learning and explainable AI.

  • Developed custom CNN and compared performance with ML/DL architectures.
  • Used preprocessing, augmentation, normalization, confusion matrix, ROC/AUC, and model evaluation.
  • Integrated Grad-CAM style explainability to support clinical interpretability.
Medical AICNNGrad-CAMMRITensorFlow
03Portfolio Build

AI Research Analytics Dashboard

A professional dashboard concept for visualizing model performance, experiment history, dataset balance, ROC curves, t-SNE/UMAP clusters, and classification reports.

  • Designed for research reporting and model comparison workflows.
  • Includes metrics such as accuracy, precision, recall, F1-score, ROC AUC, and confusion matrix.
  • Useful for turning ML notebooks into client-ready and professor-ready visual reports.
Data VisualizationML MetricsReactDashboardAnalytics
04Research Direction

3D Genome Structure Analysis using Hi-C Data

A computational biology workflow using Hi-C genomic interaction data to study 3D genome organization and visualize chromosome contact matrices.

  • Worked with .hic to .cool conversion workflows and HiCExplorer tools.
  • Generated interaction matrix visualizations for genomic structure analysis.
  • Exploring connections between AI, epigenomics, neurogenomics, and disease research.
BioinformaticsHi-CPythonData AnalysisGenomics
05Building

Netflix-Scale Backend Architecture

A system design project focused on scalable backend architecture inspired by streaming platforms, recommendation services, caching, and distributed systems.

  • Planned microservices for users, videos, recommendations, watch history, and payments.
  • Architecture includes API gateway, caching, database design, queues, and monitoring.
  • Built to demonstrate top-tier backend engineering and system design readiness.
System DesignBackendMicroservicesScalabilityCloud
06Concept / MVP

LabMind.ai — AI Research Assistant

An AI assistant concept for researchers that helps summarize papers, extract methods, compare experiments, and generate structured research notes.

  • Designed for students, labs, and early-stage research teams.
  • Planned features include paper summarization, literature comparison, and experiment tracking.
  • Positioned as a practical AI productivity tool for academic and applied research.
GenAIResearch ToolsRAGLLMsProduct Design
Research & Technical Identity

Healthcare AI, Explainability, and Scientific Computing.

My strongest research direction is early Alzheimer’s disease detection using AI/ML on MRI images, supported by explainability techniques like Grad-CAM and evaluation metrics such as ROC/AUC, confusion matrices, and class-wise performance. I’m also exploring 3D genome structure and computational biology workflows using Hi-C data.

Medical ImagingMRI preprocessing, CNNs, model comparison
Explainable AIGrad-CAM and visual model interpretation
BioinformaticsHi-C workflows and genome visualization
Research ReportingIEEE-style writing, posters, dashboards
Core Expertise

Skills & Technologies

AI / Machine Learning

TensorFlowPyTorchCNNsComputer VisionGrad-CAMScikit-learnModel Evaluation

Full-Stack Engineering

Next.jsReactNestJSNode.jsTypeScriptREST APIsAuthentication

Data & Cloud

PostgreSQLMongoDBAzure Data FactoryDockerETL PipelinesData Integration

Research & Bioinformatics

MRI AnalysisHi-C DataComputational BiologyData VisualizationResearch WritingIEEE Formatting
Journey

Where I’m Building From

2026

B.S. Computer Science Engineering

University of North Texas — focused on AI, software engineering, full-stack systems, and applied research.

2025 – Present

AI / ML Research

Developing healthcare AI research focused on Alzheimer’s detection, explainability, and model evaluation.

2025 – Present

Full-Stack Product Builder

Building VisaHire.ai and modern portfolio-ready products using Next.js, NestJS, TypeScript, APIs, and databases.

2025 – Present

Bioinformatics Research Direction

Exploring 3D genome structure, Hi-C workflows, computational biology, and AI-assisted scientific analysis.

Let’s build something intelligent, useful, and production-ready.

Open to internships, freelance projects, research collaborations, and AI/full-stack opportunities.

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