AI-Powered Protein Structure Prediction
Deep learning model leveraging transformer architectures to predict 3D protein structures from amino acid sequences with state-of-the-art accuracy.
Learn moreThe VB_WEB project aims to create a definitive personal website for Vishal B., establishing a permanent digital identity that is timeless, premium, elegant, intelligent, memorable, and globally competitive. The website will serve as a professional platform to communicate Vishal's expertise, projects, and research interests to a broad audience, including recruiters, collaborators, and fellow professionals.
The VB_WEB project is designed to appeal to a professionally focused audience in biotechnology, bioinformatics, healthcare, AI, and research-driven industries. It will communicate professionalism, intellectual curiosity, technical competence, research potential, and credibility. The website will be built using industry best practices to ensure long-term maintainability, scalability, performance, accessibility, and security.
The VB_WEB homepage will feature an interactive "Timeline of Achievements" that visually represents Vishal B.'s career milestones and achievements. This timeline will be a horizontal scrollable section where each milestone is represented by a card that expands on hover to reveal more details. The cards will be connected by a dynamic line that animates as the user scrolls, creating a sense of progression and continuity. The timeline will be built using framer-motion for smooth animations and react-spring for physics-based interactions. This concept will provide an engaging and memorable way for visitors to explore Vishal B.'s professional journey.
The landing page will use a "parallax" interaction model to create a layered depth effect as users scroll. Decorative elements will move at different speeds to add visual interest, while the main content will scroll naturally. This approach will enhance storytelling and create a visually rich first impression. Internal pages will use a "static" interaction model to prioritize layout clarity and readability.
This document outlines the comprehensive requirements for the VB_WEB project, ensuring a professional and scalable digital identity for Vishal B.

Bridging Biotechnology, Bioinformatics & Artificial Intelligence
Dedicated to advancing healthcare through the intersection of biological sciences and cutting-edge technology. I combine deep expertise in biotechnology with modern AI techniques to solve complex biological problems that matter.
A selection of projects showcasing expertise at the intersection of biotechnology, data science, and artificial intelligence.
Deep learning model leveraging transformer architectures to predict 3D protein structures from amino acid sequences with state-of-the-art accuracy.
Learn moreAutomated bioinformatics pipeline for processing raw sequencing data, variant calling, and annotating clinically relevant mutations at scale.
Learn moreReal-time analytics platform for clinical decision support, integrating patient data streams with predictive machine learning models.
Learn moreA visual chronicle of milestones, discoveries, and growth across my professional path — from foundational studies to active research.
Leading computational drug discovery research, developing novel deep learning architectures for molecular property prediction and compound screening.
Earned advanced certification in genomic data analysis, covering next-generation sequencing interpretation and population genetics.
Published peer-reviewed paper on protein-ligand interaction prediction using graph neural networks in a top-tier computational biology journal.
Developed machine learning models for early disease detection and clinical outcome prediction at a leading healthcare research institution.
Contributed sequence alignment algorithms to a major bioinformatics toolkit used by researchers and scientists worldwide.
Began undergraduate studies in biotechnology with a focus on molecular biology, genetics, and computational methods for biological systems.
Exploring frontiers where biological sciences meet artificial intelligence — driving meaningful advances in healthcare and life sciences.
Applying deep learning to accelerate identification and optimization of therapeutic compounds for complex diseases.
Developing AI models to predict protein folding patterns and understand molecular interactions at atomic resolution.
Building scalable pipelines to analyze large-scale genomic datasets for variant identification and functional annotation.
Creating machine learning systems to assist clinical decision-making and improve early diagnostic accuracy.
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