🤖 AI Engineer & Full-Stack Developer

Muhammad Awais

Building the future with Deep Learning, Computer Vision, and Scalable Web Systems.
I turn cutting-edge research into real-world applications.

About Me

AI researcher, engineer, and problem solver.

I'm a Full-Stack AI Engineer with a passion for pushing the boundaries of machine learning. My work spans from real-time computer vision systems to large language model applications. I've built deepfake detectors, medical image segmentation tools, autonomous drone navigation systems, and intelligent document parsers.

I believe in using AI to solve meaningful problems – from healthcare to disinformation. Every project is an opportunity to learn and contribute to the open-source community.

🧠

Deep Learning Expert

CNNs, Transformers, GANs

🖥️

MLOps

Model deployment, Docker, AWS

📊

Data Science

PyTorch, TensorFlow, Scikit-learn

Real-time Systems

OpenCV, YOLOv8, MediaPipe

12+
AI/ML Projects
4+
Research Papers (Arxiv)
20+
Models Deployed
100K+
API Calls Served

Tech Stack & Expertise

Modern tools for next‑gen AI.

🔥

Deep Learning

PyTorchTensorFlowHuggingFaceONNX
👁️

Computer Vision

OpenCVYOLOv8Segment AnythingMediaPipe
🤖

LLMs & NLP

GPT-4Llama 3LangChainRAG
☁️

MLOps & Cloud

AWS SageMakerDockerFastAPIKubernetes
🛠️

Backend

DjangoPostgreSQLRedisWebSockets
📱

Frontend

ReactThree.jsTailwindWebRTC

Groundbreaking AI Projects

Real-world applications that push the boundaries of machine learning.

🎭

Real‑time Deepfake Detection

An ensemble of EfficientNet and Vision Transformers that detects AI-generated faces and voice deepfakes with 98.7% accuracy. Runs at 30 FPS on edge devices. Used by a fact-checking organization.

PyTorchViTOpenCVFastAPIWebRTC
🏥

AI‑Powered Liver Tumor Segmentation

A 3D U‑Net architecture trained on 1000+ CT scans to automatically segment liver tumors. Achieved Dice coefficient of 0.92. Deployed as a HIPAA‑compliant web tool for radiologists.

MONAIPyTorch 3DDockerReactFHIR
🚁

Autonomous Drone Navigation

Vision‑based navigation system for obstacle avoidance and target following using YOLOv8 and depth estimation. Integrated with ROS2 and PX4. Demonstrated in simulated and real forest environments.

YOLOv8ROS2PythonGazeboMavlink
⚖️

Legal Document AI (RAG System)

A retrieval‑augmented generation pipeline that answers complex queries from 5000+ legal PDFs. Uses Llama 3 8B + FAISS vector store. Reduces legal research time by 70% for a startup.

LangChainLlama 3FAISSStreamlitAWS
🤟

Sign Language to Text/Gloss

MediaPipe + LSTM model that translates 100+ American Sign Language gestures into text in real time. Achieves 94% accuracy on live webcam feed. Open‑sourced and used by accessibility groups.

MediaPipeLSTMTensorFlow.jsWebRTC
🏭

Predictive Maintenance with Sensor Data

A temporal fusion transformer model that predicts equipment failure 48 hours in advance using IoT sensor data. Deployed on edge gateways, saving a manufacturing client 30% in downtime costs.

TransformersInfluxDBMQTTGrafanaKafka

Let's Build Intelligence Together

Have an ambitious AI project? Reach out – I'm available for consulting, research collaborations, and full‑stack AI development.