Muhammad Nouman Hanif
MN Hanif
Instructor - Computer Science (DS, CYS, AI) at FAST-NUCES

Muhammad Nouman Hanif

|

Building intelligent systems with AI, Machine Learning, and scalable cloud infrastructure. Passionate about turning data into actionable insights.

Profile photo of Muhammad Nouman Hanif
Python
C++
FastAPI
Next.js
React
Docker
Kubernetes
AWS
TensorFlow
PyTorch
OpenCV
PostgreSQL
MongoDB
TypeScript
Tailwind CSS
Git
Linux
RAG
LLMs
LangChain
Python
C++
FastAPI
Next.js
React
Docker
Kubernetes
AWS
TensorFlow
PyTorch
OpenCV
PostgreSQL
MongoDB
TypeScript
Tailwind CSS
Git
Linux
RAG
LLMs
LangChain
Python
C++
FastAPI
Next.js
React
Docker
Kubernetes
AWS
TensorFlow
PyTorch
OpenCV
PostgreSQL
MongoDB
TypeScript
Tailwind CSS
Git
Linux
RAG
LLMs
LangChain
Featured Work

AI & ML Projects

A curated selection of my research in Generative AI, Computer Vision, and Engineering.

Parameter-Efficient Fine-Tuning (PEFT) & Agentic Systems

Conducted a 42-run ablation study on DeBERTa-v3 using QLoRA, retaining 97% accuracy while reducing VRAM by 90%. Built a Multi-Agent Research Assistant using LangGraph to orchestrate agents for search, ranking, and summarization.

QLoRA
LangGraph
LLaMA-3
+2

Multimodal Pipeline: Story Generation & E-Commerce Mockups

Engineered an end-to-end pipeline combining BLIP (Image Captioning) and FLAN-T5 (Story Generation). Built an automated product mockup system using Stable Diffusion (img2img), optimizing denoising strength for photorealistic textures.

Stable Diffusion
BLIP
T5
+2

Brain Tumor Classification with Explainable AI (XAI)

Engineered a multi-class classification model (Glioma, Meningioma, Pituitary) achieving 99.65% accuracy. Implemented Grad-CAM and Attention Rollout to visualize decision heatmaps.

ViT
Grad-CAM
Medical AI
+2

Flood Severity Prediction with Ensemble Gradient Boosting

Engineered a robust flood forecasting pipeline using CatBoost and XGBoost, trained on a massive dataset of 1.1 million+ records. Achieved a high predictive accuracy of 0.85 R².

CatBoost
XGBoost
Scikit-Learn
+1

IoT-Enabled Smart Solar Inverter

Engineered an IoT-powered solar inverter with real-time Maximum Power Point Tracking (MPPT). Integrated a solar tracking system to enhance energy efficiency and power generation.

IoT
MPPT
Solar Energy
+2

Parameter-Efficient Fine-Tuning (PEFT) & Agentic Systems

Conducted a 42-run ablation study on DeBERTa-v3 using QLoRA, retaining 97% accuracy while reducing VRAM by 90%. Built a Multi-Agent Research Assistant using LangGraph to orchestrate agents for search, ranking, and summarization.

QLoRA
LangGraph
LLaMA-3
+2

Multimodal Pipeline: Story Generation & E-Commerce Mockups

Engineered an end-to-end pipeline combining BLIP (Image Captioning) and FLAN-T5 (Story Generation). Built an automated product mockup system using Stable Diffusion (img2img), optimizing denoising strength for photorealistic textures.

Stable Diffusion
BLIP
T5
+2

Brain Tumor Classification with Explainable AI (XAI)

Engineered a multi-class classification model (Glioma, Meningioma, Pituitary) achieving 99.65% accuracy. Implemented Grad-CAM and Attention Rollout to visualize decision heatmaps.

ViT
Grad-CAM
Medical AI
+2

Flood Severity Prediction with Ensemble Gradient Boosting

Engineered a robust flood forecasting pipeline using CatBoost and XGBoost, trained on a massive dataset of 1.1 million+ records. Achieved a high predictive accuracy of 0.85 R².

CatBoost
XGBoost
Scikit-Learn
+1

IoT-Enabled Smart Solar Inverter

Engineered an IoT-powered solar inverter with real-time Maximum Power Point Tracking (MPPT). Integrated a solar tracking system to enhance energy efficiency and power generation.

IoT
MPPT
Solar Energy
+2

Parameter-Efficient Fine-Tuning (PEFT) & Agentic Systems

Conducted a 42-run ablation study on DeBERTa-v3 using QLoRA, retaining 97% accuracy while reducing VRAM by 90%. Built a Multi-Agent Research Assistant using LangGraph to orchestrate agents for search, ranking, and summarization.

QLoRA
LangGraph
LLaMA-3
+2

Multimodal Pipeline: Story Generation & E-Commerce Mockups

Engineered an end-to-end pipeline combining BLIP (Image Captioning) and FLAN-T5 (Story Generation). Built an automated product mockup system using Stable Diffusion (img2img), optimizing denoising strength for photorealistic textures.

Stable Diffusion
BLIP
T5
+2

Brain Tumor Classification with Explainable AI (XAI)

Engineered a multi-class classification model (Glioma, Meningioma, Pituitary) achieving 99.65% accuracy. Implemented Grad-CAM and Attention Rollout to visualize decision heatmaps.

ViT
Grad-CAM
Medical AI
+2

Flood Severity Prediction with Ensemble Gradient Boosting

Engineered a robust flood forecasting pipeline using CatBoost and XGBoost, trained on a massive dataset of 1.1 million+ records. Achieved a high predictive accuracy of 0.85 R².

CatBoost
XGBoost
Scikit-Learn
+1

IoT-Enabled Smart Solar Inverter

Engineered an IoT-powered solar inverter with real-time Maximum Power Point Tracking (MPPT). Integrated a solar tracking system to enhance energy efficiency and power generation.

IoT
MPPT
Solar Energy
+2