Turning biological & visual data into deployed AI systems.
I'm a Bioinformatics graduate and Machine Learning Engineer who builds the full pipeline — from data and model training to Flask APIs and Flutter apps — for healthcare and agriculture AI products.
Where I've worked
From government data pipelines to production AI products — always covering the full stack from model to interface.
- Contributing to multiple AI-driven products, including a crop disease detection mobile app and a hybrid skin disease diagnosis web application
- Building and optimizing CNN / EfficientNet models for image classification, end to end from data pipeline to deployment
- Additional AI/ML initiatives in progress, with new projects launching soon
- Collected, cleaned, and validated large-scale government & urban socio-economic datasets for policy decisions
- Performed statistical trend and pattern analysis across district-level datasets using Python and Excel
- Built dashboards and visual reports for non-technical stakeholders, and applied GIS-based spatial analysis
Research & product projects
Each project covers a slice of the same pipeline: data → model → API → interface.
A hybrid web application combining image processing and CNN-based classification (EfficientNetV2) to detect skin cancer types from dermoscopy images, with a full ML pipeline through to Flask REST API deployment.
AI-powered mobile app for real-time crop disease detection from leaf images across 20+ species, paired with a treatment recommendation engine on a Flutter / Flask / MongoDB stack.
Real-time sign language recognition bridging communication for deaf and mute individuals, using CNN + MediaPipe hand-gesture classification for Urdu/English sign language, on a Flutter + Flask stack.
Full-stack symptom checker with a Flutter frontend, Flask backend, and real-time health recommendations. Presented at an inter-university mobile app development competition.
Python pipeline analyzing district-wise commodity prices across Punjab (2020–2025) with interactive visualizations to support flood / non-flood agricultural policy forecasting.
A web application for DNA sequence classification, covering preprocessing and feature extraction pipelines — bridging bioinformatics with applied machine learning.
Skills & technologies
Full-stack across the ML lifecycle — from sequence data to shipped mobile apps.
Education & certifications
Coursework in Bioinformatics & Computational Biology, Genomics & Transcriptomics, Proteomics & Sequence Analysis, Molecular Biology & Genetics, Biostatistics, and Database Management.
- AI Agentic Development Using n8n n8n / Online Platform · 2025
- Climate Change, Air Quality & Smog Analysis Environmental Data Science Program · 2025
- Virus Phylogenetics & Phylogenetic Tree Construction and Interpretation Bioinformatics Workshop · 2025
- Molecular Cross Between Virus, Vector & Host: A Case Study of Geminivirus Molecular Biology Seminar / Workshop · 2025
- NGS Data Analysis Workshop FastQC, Trimmomatic, BWA, SAMtools, GATK · 2025
Building something in ML, healthcare AI, or bioinformatics? Let's talk.
Currently working remotely as a Machine Learning Engineer, and open to new opportunities in data science, applied ML, and AI product development.