I'm a Computer Science (IT) student who enjoys working between software engineering × cloud × machine learning.
I like taking an idea from:
💡 Concept → 🏗️ Architecture → 💻 Implementation → ☁️ Deployment
and making it actually work.
┌──────────────────────────────────────────────────────────────┐
│ │
│ 🌐 Full-Stack Systems 🤖 ML / AI Systems │
│ ☁️ Cloud Infrastructure ⚙️ Backend & APIs │
│ 🗄️ Data-Driven Applications 🚀 Production Deployments │
│ │
└──────────────────────────────────────────────────────────────┘
My current technical playground spans:
Java • Python • C++ • TypeScript • JavaScript • SQL
Next.js • React • Express.js • Flask
PostgreSQL • MySQL • MongoDB • Supabase
AWS • GCP • Docker • GitHub Actions • Vercel
PyTorch • Pandas • NumPy • Isolation Forest • Random Forest
DQN • MADDPG • QMIX • REST APIs • Microservices
PyTorch
├── Reinforcement Learning
│ ├── DQN
│ ├── MADDPG
│ └── QMIX
│
├── Anomaly Detection
│ └── Isolation Forest
│
└── Classical ML
└── Random Forest
Data
├── Pandas
└── NumPy
I don't see an application as just a frontend + backend.
I think about the whole system:
┌─────────────┐
│ CLIENT │
└──────┬──────┘
│
▼
┌─────────────┐
│ API / │
│ SERVICES │
└──────┬──────┘
│
┌─────────┴─────────┐
▼ ▼
┌─────────────┐ ┌─────────────┐
│ DATABASE │ │ ML / DATA │
└─────────────┘ └──────┬──────┘
│
▼
┌─────────────┐
│ CLOUD / │
│ DEPLOYMENT │
└─────────────┘
Architecture matters. Security matters. Deployment matters.
A feature isn't really finished if it only works on localhost.
Currently working with:
AWS EC2 · AWS S3 · Google Cloud · Docker · GitHub Actions · Vercel
I'm particularly interested in how applications move from:
local development → containerization → CI/CD → cloud infrastructure → production
I'm especially interested in problems where machine learning interacts with real systems.
if problem == "complex_decision_making":
explore("Reinforcement Learning")
elif problem == "anomalous_behavior":
explore("Anomaly Detection")
elif problem == "structured_data":
explore("Classical ML")
else:
build()Areas I've worked with include:
- Reinforcement Learning
- Multi-Agent Reinforcement Learning
- Anomaly Detection
- Classification
- Data Processing
- Model Optimization
- PyTorch-based experimentation
I care about the parts of software engineering that make systems survive beyond the demo:
- 🔐 Secure coding
- 🧪 Testing & debugging
- 🔍 Code reviews
- 🧱 Maintainable architecture
- 🔌 API design
- 🗄️ Database security
- 🐳 Containerization
- 🔄 CI/CD
- 🐧 Linux
- 📋 Agile / Scrum
Distributed Systems
↓
Cloud Architecture
↓
Machine Learning
↓
Intelligent Systems
↓
Production-grade Engineering
Always looking for interesting problems where software + data + intelligence intersect.
