 Python |
 TensorFlow |
 Docker |
 AWS |
 Azure |
 PyTorch |
 MongoDB |
 Git |
 PostgreSQL |
🚀 Professional Experiences (Click to Expand)
2024 - Present
- Engineered document pipeline handling
- Designed neural search architecture
- Architected hybrid SQL/vector database schema
2024 - Present
- Optimized models for 35% latency reduction
- Deployed distributed training across Multiple GPUs
- Automated client workflows with CI/CD pipelines
2023 - 2024
- Authored emotion classifier (F1-score: 0.92)
- Reduced ETL pipeline costs by 40% via Spark optimization
- Scraped/analyzed 100K+ reviews for sentiment insights
| Project | Description | Impact | Stack |
|---|---|---|---|
| Intelligent Document Summarization & Analysis Tool | Open-source NLP tool for automated document analysis (summarization, entity recognition, sentiment analysis). | ⏩ 20% faster processing with optimized algorithms. | BERT, FastAPI, Transformers, spaCy |
| HiveMind RL Framework | Multi-agent reinforcement learning (RL) system for collaborative AI models. | 🚀 3x efficiency in multi-agent decision-making. | PyTorch, Python |
| Gesture-Controlled Drone | Hand gesture-based drone control using deep learning vision models. | 🎯 95% recognition accuracy in real-time. | ResNet, OpenCV, TensorFlow |
| CV Parser | Automated resume parsing tool with NLP for structured extraction and summarization. | 📄 Improved hiring insights through semantic understanding. | BERT, React, Python |
| Emotion Classification & Review Analysis | NLP model for analyzing customer emotions from 100K+ reviews. | 📊 92% classification accuracy across 28 emotions. | Transformers, PyTorch, Pandas |
| Object Detection for Hand Gestures | Developed a custom ResNet model to enable intuitive hand gesture recognition for DJI Tello drones. | 🛸 Real-time control with high precision. | ResNet, TensorFlow, OpenCV |
| CNN for MNIST | Deep learning model for digit classification. | 🔢 99% accuracy on MNIST dataset. | CNN, TensorFlow, Keras |
📚 Academic Journey
📍 Cyprus International University | 2024 – Present
- Research Focus: Expanding on the HiveMind framework from MSc research to develop efficient, intelligent, and scalable language models.
- Investigating innovative methodologies to enhance LLM performance for real-world applications.
- GPA: 4.0
📍 University of Kent, Canterbury | 2022 – 2023
- Thesis: "From A3C to HiveMind: Exploring Collaborative Learning in Gridworld Dynamics"
- Research Highlights:
- Developed HiveMind RL Framework, a collaborative reinforcement learning system for multi-agent environments.
- Experimented with custom RL models in Gridworld, optimizing distributed and adaptive AI systems.
- Applied advanced reinforcement learning techniques to improve scalability and learning efficiency.
- Award: Merit (for outstanding academic performance).
📍 Canterbury Christ Church University | 2018 – 2022
- Specialization: Software Development, High-Performance Computing (HPC), and Algorithm Design.
- Key Projects:
- Designed computational algorithms for complex problem-solving.
- Applied object-oriented programming principles to software development.
- Worked on various programming frameworks to develop scalable applications.
