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class AIEngineer:
 def __init__(self):
 self.name = "Nazmul Islam"
 self.role = "Junior AI Developer"
 self.company = "SM Technology"
 self.location = "Dhaka, Bangladesh 🇧🇩"
 self.languages = ["Python", "C++", "Java", "JavaScript", "SQL"]
 
 def get_education(self):
 return {
 "🎓 Masters": "MSc in IT | JU (CGPA: 4.00/4.00)",
 "🎓 Bachelors": "BSc in IT | UITS (CGPA: 3.94/4.00)",
 "📜 IELTS": "6.5 Overall Band"
 }
 
 def get_specializations(self):
 return [
 "🤖 Generative AI & LLMs",
 "🧠 Deep Learning & NLP",
 "🔐 Federated Learning",
 "👁️ Computer Vision",
 "🤝 Multi-Agent Systems",
 "📊 Data Science & ML"
 ]
 
 def get_research(self):
 return "📄 Published in MDPI Mathematics 2024 (Q1 Journal) ⭐"
 
 def current_work(self):
 return [
 "💼 Building production-ready AI applications",
 "🔬 Researching LLM-based multi-agent systems",
 "🛠️ Creating RAG-powered intelligent assistants",
 "🌟 Contributing to open-source AI projects"
 ]
me = AIEngineer()
print(me.get_research()) # 📄 Published in MDPI Mathematics 2024 (Q1 Journal) ⭐

🔹 Junior AI Developer @ SM Technology - Developing production-ready AI applications
🔹 Research Assistant @ UITS - Published in Q1 journal (MDPI)
🔹 300+ Problems solved on competitive programming platforms
🔹 IELTS Score: 6.5 Overall
🔹 Kaggle Contributor - Active in AI/ML competitions

Python C++ Java JavaScript SQL

TensorFlow PyTorch Keras scikit-learn Hugging Face LangChain OpenAI

Pandas NumPy Matplotlib Seaborn Power BI

React Next.js FastAPI Flask Streamlit

MongoDB MySQL Google Cloud Docker

Git GitHub VS Code Postman Linux

mindmap
 root((AI/ML
 Engineering))
 Machine Learning
 Supervised Learning
 Unsupervised Learning
 Ensemble Methods
 Deep Learning
 CNNs
 RNNs/LSTMs
 Transformers
 NLP & LLMs
 BERT
 GPT Models
 RAG Systems
 Generative AI
 Text Generation
 Image Synthesis
 Style Transfer
 Specialized
 Federated Learning
 Computer Vision
 Agentic AI
 Audio Processing

Multi-agent system using LangGraph for automated research report generation

• Tech: LangGraph, LangChain, OpenAI API, Python
• Features: Validation, citations, professional formatting

AI-powered email management with automated analysis & responses

• Tech: OpenAI, FastAPI, React, MongoDB
• Features: Smart categorization, context-aware responses

Enterprise-ready chatbot with semantic & hybrid search

• Tech: MongoDB, LangChain, RAG, Vector Search
• Features: Context-aware responses, document retrieval

Mental health monitoring using ML/DL models

• Tech: BERT, TensorFlow, Scikit-learn, PyTorch
• Features: 7 ML models, 4 DL models, custom dataset

Personal fitness & nutrition assistant

• Tech: OpenAI, Computer Vision, NLP
• Features: AI gym coach, meal planner, food analyzer

Artistic style transfer for images, videos & webcam

• Tech: TensorFlow, Keras, OpenCV
• Features: Real-time processing, multiple style options

Privacy-Preserving Federated Learning-Based Intrusion Detection for Cyber-Physical Systems
📖 Mathematics 2024 (MDPI) - Q1 Journal
👥 Mahmud, S.A.; Islam, N.; Islam, Z.; Rahman, Z.; Mehedi, S.T.
🔗 DOI: 10.3390/math12203194
⭐ Federated Learning | Deep Learning | IoT Security | Cybersecurity

• 🥇 300+ Problems solved on beecrowd platform
• 🎯 Kaggle Contributor - AI/ML competitions (NLI, Image Classification, NLP)
• 👨‍💼 Executive - Competitive Programming Wing, UITS IT Club (2021-2023)
• 📝 Published Researcher - MDPI Mathematics 2024
• 🌐 IELTS: 6.5 Overall Band Score
• 🏆 Multiple Codeforces contest participations

🔸 Building advanced multi-agent AI systems with LangGraph
🔸 Exploring large language models for enterprise applications
🔸 Developing RAG-based intelligent assistants
🔸 Contributing to open-source AI/ML projects
🔸 Researching federated learning applications in real-world scenarios

• 🤖 Machine Learning & Deep Learning
• 🧠 Natural Language Processing & LLMs
• ⚡ Generative AI & Prompt Engineering
• 🔐 Federated Learning & Privacy-Preserving AI
• 👁️ Computer Vision & Image Processing
• 🤝 Agentic AI & Multi-Agent Systems
• 📊 Data Analysis & Visualization