Engineering applied AI from model weights to production systems.
BS Artificial Intelligence graduate from FAST-NUCES. Specializing in computer vision pipelines (YOLOv11), sensor fusion (Kalman filters), autonomous agents, and low-latency FastAPI architectures.
Building systems where the machine learning model is only one piece of the puzzle.
I am a BS Artificial Intelligence graduate from FAST-NUCES with a deep commitment to practical, deployable AI engineering. While training models in Jupyter notebooks is foundational, true engineering begins when that model must interact with raw, noisy physical signals, high-throughput microservices, and human operators.
My work spans from edge computer vision (YOLOv11 custom architectures) and mathematical sensor fusion (Kalman filters) to autonomous agent orchestration and retrieval-augmented assistance. I believe in engineering complete feedback loops: from data curation and fine-tuning (LoRA/PEFT) to containerized inference pipelines with sub-100ms latency guarantees.
Featured AI & Systems Engineering
End-to-end production systems covering computer vision, autonomous agents, sensor fusion, and high-performance backends.
OmniDrive AI
Intelligent Automotive Diagnostic & Edge Perception Ecosystem
An automotive diagnostic and safety platform combining real-time computer vision, multi-modal OBD-II sensor data, 1D Kalman filter sensor fusion, and retrieval-augmented mechanical assistance.
Pipeline Architecture
Ecosystem Modules
CAN-Bus & Telemetry Ingestion
- -Real-time OBD-II PID polling pipeline streaming diagnostic telemetry at 20Hz.
- -1D Kalman filter sensor fusion denoising speed, acceleration, and RPM fluctuations.
- -Engine anomaly detection flagging overheating and misfires prior to CEL triggers.
Edge Computer Vision Core
- -Custom YOLOv11 model fine-tuned on 26,820 automotive engine and chassis images.
- -Multi-label classification of 50 mechanical failure modes and wear indicators.
- -FastAPI inference server optimized with batched tensor ingestion and asynchronous dispatch.
Retrieval-Augmented Diagnostic Assistant
- -RAG pipeline indexed with pgvector cosine similarity over vehicle technical service bulletins.
- -Context-grounded troubleshooting engine outputting verified step-by-step DIY repair workflows.
- -Integration with vehicle diagnostic codes (DTC) for automated root-cause analysis.
Production Infrastructure & Client HUD
- -Supabase PostgreSQL managing row-level security, auth, and relational telemetry history.
- -Role-based ecosystem supporting vehicle owners, certified mechanics, and fleet managers.
- -Cross-platform Flutter application rendering real-time telemetry HUD and AR diagnostics.
OmniDrive Signal-Flow & Edge Processing Pipeline
Recursively denoises sensor noise and removes accelerometer drift using predictive covariance updates.
class KalmanFilter1D:
def __init__(self, q=1e-4, r=1e-2):
self.q, self.r = q, r # Process & Measurement variance
self.x, self.p = 0.0, 1.0
def update(self, z: float) -> float:
# Predict & Correct cycle
self.p += self.q
k = self.p / (self.p + self.r) # Kalman Gain
self.x += k * (z - self.x)
self.p *= (1.0 - k)
return self.xAI Job Application Agent
Autonomous Multi-Agent Pipeline with Human-in-the-Loop Review
Autonomous AI agent that orchestrates web scraping via Playwright, evaluates candidate-role alignment using Groq LLaMA-3 reasoning, completes multi-step application workflows, and logs submissions to Google Sheets.
Pipeline Architecture
Key Engineering Highlights
- •Dynamic browser orchestration utilizing Playwright with human-behavior emulation.
- •Structured LLM reasoning ensuring exact schema conformance via Pydantic validators.
- •Human-in-the-loop validation checkpoint prior to irreversible application dispatch.
- •Real-time status synchronization and rate-limit handling across job boards.
Serene: AI Mental Health Companion
LoRA Fine-Tuned LLM with Local Emotion Classification
Mental wellness assistant fine-tuned with Low-Rank Adaptation (LoRA) on custom empathetic dialogue corpora, combined with a local DistilRoBERTa emotion classifier for real-time sentiment tracking.
Pipeline Architecture
Key Engineering Highlights
- •Fine-tuned causal language models using PEFT/LoRA to retain domain knowledge without catastrophic forgetting.
- •Integrated lightweight emotion classifier providing conversational guardrails and crisis detection.
- •Deterministic safety evaluation pipeline preventing ungrounded psychiatric recommendations.
- •Deployed with FastAPI inference backend and responsive Streamlit clinician dashboard.
NewsLens & TicketIQ: NLP Intelligence
Fine-Tuned BERT & Zero-Shot Classification Engine
Production-oriented NLP pipeline combining fine-tuned BERT for high-throughput news categorization with BART-large-MNLI for zero-shot customer support ticket classification and intent routing.
Pipeline Architecture
Key Engineering Highlights
- •Fine-tuned transformer encoder heads for multi-class hierarchical topic classification.
- •Zero-shot natural language inference pipeline for dynamic triage without re-training.
- •ONNX runtime model quantization delivering 3.2x CPU throughput acceleration.
- •Containerized microservice ready for Kubernetes horizontal pod auto-scaling.
Protomotive Car Care Studio
High-Performance Interactive Digital Showcase
High-end detailing studio showcase engineered with Next.js App Router, GSAP timeline choreography, Lenis inertial smooth scrolling, and Tailwind CSS v4.
Pipeline Architecture
Key Engineering Highlights
- •Inertial smooth scrolling architecture integrated with GSAP ScrollTrigger.
- •Server-rendered Next.js architecture with zero layout shift (CLS < 0.05).
- •Micro-interactions and fluid viewport-aware visual typography.
Research Prototypes & Client Systems
Construction Helmet Detection
Edge computer vision model trained on YOLOv5 for construction safety PPE compliance.
Mesh Shift Visualizer
Interactive WebGL visualization for complex 3D mesh topological coordinate transforms.
Clinical Heart Disease Prediction
Supervised classification pipeline benchmarked across Random Forest and XGBoost ensembles.
Verto Digital Agency Platform
High-conversion digital growth agency platform with dynamic Framer Motion interactions.
Engineering Experience
Professional engineering internships and academic teaching appointments at FAST-NUCES.
AI/ML Engineering Intern
- •Designed and deployed applied AI systems focusing on LLMs, RAG pipelines, and NLP classification.
- •Engineered modular applications integrating Hugging Face models, FAISS vector stores, and Streamlit interfaces.
- •Implemented fine-tuning pipelines using LoRA for custom instruction-following tasks.
AI Developer Intern
- •Built full-stack applications using React, Next.js, and Supabase.
- •Integrated the Gemini API and automated LLM workflows using n8n orchestration.
- •Developed data pipelines for web scraping, translation, and structured data generation.
Teaching Assistant — Programming Fundamentals
- •Mentored students in C++ and core programming fundamentals.
- •Evaluated code quality, logic-building, and project implementation.
Technical Toolkit
Core frameworks and technologies used across machine learning research, inference backends, and frontend delivery.
AI / ML
- Python
- PyTorch
- Scikit-learn
- Computer Vision
- NLP
- LLMs
- RAG
- LoRA
Models & Retrieval
- YOLOv11
- BERT
- GPT-Neo
- DistilRoBERTa
- BART-large-MNLI
- FAISS
- BM25
- SentenceTransformers
Backend & Data
- FastAPI
- REST APIs
- PostgreSQL
- Supabase
- Firebase
- Node.js
Frontend
- Flutter
- React
- Next.js
- Streamlit
Infrastructure & Tools
- Docker
- Git
- GitHub Actions
- Vercel
- n8n
- Postman
Verified Credentials
Formal industry internship certifications in AI/ML engineering and production systems.
AI/ML Engineering Internship Certificate
6-week AI/ML Engineering internship.
AI Developer Internship Certificate
Full-stack AI application development using React, Next.js, and Gemini API.