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EphraimAsad/README.md

Zain Asad

Applied AI & Automation Engineer building intelligent systems that combine machine learning, domain knowledge, and automation to solve real-world problems.

I design and deploy AI systems across scientific workflows, predictive modelling, retrieval systems, and autonomous agents. My work focuses on turning complex processes into reliable AI-powered tools that reduce manual effort and improve decision-making.

Currently working as a Senior Microbiology Analyst while building production-grade AI systems in my own projects.

Core Focus Areas

  • Applied Machine Learning Systems
  • Autonomous AI Agents & Workflow Automation
  • Retrieval Augmented Generation (RAG)
  • Predictive Modelling & Simulation
  • Domain-Specific AI Systems
  • Scientific AI & Laboratory Automation

Featured Projects

BactAID

Hybrid AI system for phenotype-based bacterial identification.

  • Combines deterministic microbiology logic, machine learning, and LLM reasoning
  • 8,700 curated laboratory records across 140 bacterial genera
  • Achieved 95.1% genus classification accuracy
  • Full-stack architecture with Flask API and React frontend

Tech: Python, XGBoost, FLAN-T5, BART, Flask, React, Hugging Face

Demo: https://huggingface.co/spaces/EphAsad/BactAID-Demo

Iapetus

Predictive food microbiology simulation platform for modelling Listeria monocytogenes growth and shelf-life risk.

  • Machine learning prediction of microbial growth curves
  • Monte Carlo simulation for uncertainty estimation
  • Sensitivity analysis to identify dominant environmental risk drivers
  • FastAPI backend with React frontend interface

Tech: Python, CatBoost, FastAPI, React, Monte Carlo Simulation, Predictive Modelling, Ollama

Ephraim

Privacy-first local autonomous coding and workflow agent.

  • Planner/executor architecture separating reasoning from execution
  • Tool orchestration system with 60+ integrated tools
  • Schema validation and error recovery for reliable task execution
  • Designed for fully local AI development using Ollama

Tech: Python, Ollama, Multi-Agent Systems, Tool Routing, JSON Schema

DomainEmbedder

Domain-adaptive embedding model for multi-domain retrieval systems.

  • LoRA-based architecture enabling modular domain adapters
  • Reinforcement learning policy for automatic domain routing
  • Trained on NLI, semantic similarity, and paraphrase datasets
  • Achieved 2.7× improvement over baseline domain classification

Tech: PyTorch, Transformers, LoRA, Contrastive Learning, Reinforcement Learning

Model: https://huggingface.co/EphAsad/DomainEmbedder

FireSOP

AI-powered laboratory SOP retrieval assistant.

  • Hybrid RAG system combining FAISS vector search and BM25 keyword retrieval
  • Fine-tuned domain embeddings for laboratory terminology
  • Provides source-grounded procedural guidance for regulated environments

Tech: Python, FAISS, BM25, Streamlit, Ollama

FireAccess

Laboratory workflow automation platform built using Access VBA.

  • Parent-child database synchronization across 20+ laboratory test workflows
  • Automated colony count parsing and result aggregation
  • Media batch traceability and regulatory compliance tracking
  • Backup and recovery automation for laboratory data integrity

Tech: VBA, Microsoft Access, SQL, Laboratory Automation

Technical Skills

Programming

Python, JavaScript, SQL, VBA

Machine Learning

XGBoost, Random Forest, Transformers, Transfer Learning, LoRA, Model Evaluation

AI Systems

RAG, LLM Orchestration, Domain-Specific Embeddings, Prompt Engineering

Data & ML Tools

PyTorch, Scikit-learn, Pandas, NumPy, FAISS, BM25

Deployment

FastAPI, Flask, React, Streamlit, Hugging Face Spaces

Infrastructure

Git, GitHub Actions, Local LLMs (Ollama)

Domain Expertise

Clinical Microbiology, Bacterial Identification, Phenotypic Analysis, ISO 17025 Laboratory Workflows

Publications

BactAI-D: A Hybrid, Confidence-Aware AI System for Phenotype-Based Bacterial Identification
Zenodo Preprint
https://doi.org/10.5281/zenodo.18089381

DomainEmbedder v2.6: Domain-Adaptive Embedding Model for Cross-Domain Retrieval
Hugging Face Model Repository

Decomposing Sex Differences in Mortality Across Age and Cause in England and Wales, 1915–2015
SocArXiv Preprint

Links

LinkedIn
https://linkedin.com/in/zain-asad-1998eph

GitHub
https://github.com/EphraimAsad

Hugging Face
https://huggingface.co/EphAsad

Email
zainasad98@gmail.com

Current Interests

  • Autonomous AI agents
  • AI-powered scientific tooling
  • Predictive modelling systems
  • Local-first AI infrastructure
  • AI-driven workflow automation

Always open to interesting technical discussions and collaborations.

Pinned Loading

  1. BactAI-D BactAI-D Public

    Hybrid AI System For Microbiology Phenotype Identification

    Python 1

  2. Asclepius Asclepius Public

    A rules-first AI medical triage and lab-result interpretation web application

    Python 1

  3. Iapetus Iapetus Public

    Predictive microbiology for challenge-test style shelf-life simulation.

    Python 1

  4. EphraimAsad EphraimAsad Public

  5. VAE-Of-Mortality VAE-Of-Mortality Public

    Publication Research supporting Decomposing Sex Differences in Mortality Across Age and Cause in England and Wales, 1915–2015

    Python 1