• 🔬 Deep Learning & AI Research: Advancing LLM/SLM architectures, fine-tuning methodologies, and RAG systems.
• 🛡️ AI-Powered Security: Engineering intelligent systems at the intersection of machine learning and vulnerability detection.
• ⚡ High-Performance Computing for AI: Optimizing mathematical operations and computational efficiency in ML pipelines through low-level systems programming, SIMD vectorization, and memory-aware architectures.
• ☁️ Distributed AI Infrastructure: Architecting scalable cloud-native ML systems with containerization, orchestration, and CI/CD automation for seamless model deployment and inference.

Languages: Python, C/C++, Java, JavaScript, SQL, Bash, Assembly ML/AI: PyTorch, TensorFlow, Hugging Face, LangChain, Ollama, scikit-learn, Keras
Web & Backend: React, Django, Flask, REST APIs, HTML/CSS
Tools & Platforms: Docker, Git, Azure, Linux/UNIX, GitHub CI/CD, QEMU
Data Science: NumPy, Pandas, Matplotlib, Seaborn

• 🧩 Bachelor Thesis – CTF-Solver LLM
  Building a transformer-based model specialized in CTF solving and vulnerability exploitation.
  Custom tokenizer optimized for code generation; trains on Python exploit tasks.

• 🧠 Email Filtering System Multimodal AI (2nd Place, SSCS 2025)
  SaaS email filtering platform detecting offensive content in text, audio, image, and video using Phi-4, Whisper, and CNNs.
  Stack: Flask + React/Tailwind + MongoDB + Docker (K8s-ready).

• 🧮 QuantSI – GSoC 2024 @ INCF
  Python package for managing SI units with seamless NumPy/Matplotlib integration.
  Achieved 95% test coverage, CI/CD deployment to PyPI.