About Me
Tracing the strategic evolution from high-concurrency enterprise engineering to specialized Generative AI research.
Academic Architecture
FAST-NUCES Study
Full-Stack Deployment
Enterprise Systems
AI & Deep Learning
Neural Specialization
I am an AI Engineer at OneScreen, dedicated to architecting high-performance neural ecosystems where cutting-edge deep learning research meets advanced system architecture.
Currently at OneScreen, I direct AI engineering initiatives focused on scalable Multi-Agent Systems and high-performance neural architectures. My trajectory is defined by a strategic evolution from building high-concurrency enterprise architecture to pioneering research in Generative Intelligence and Multi-Agent Orchestration. I specialize in leveraging PyTorch and Transformers to push the boundaries of model performance, achieving extreme precision in biometric applications and optimizing neural synthesis for industrial impact.
My Experience
A record of specialized deployments in high-performance engineering and AI automation.
OneScreen
AI Engineer
AI Engineer
Directing AI engineering initiatives focused on scalable intelligent systems and high-performance neural architectures.
/ Researching and implementing advanced Multi-Agent Systems for specialized enterprise automation.
/ Developing high-performance intelligent systems leveraging PyTorch and Transformer architectures.
/ Optimizing deep learning models for scalable production deployments and real-time inference.
/ Architecting robust neural ecosystems to solve complex business logic challenges.
Nexium
AI Web Development Intern
AI Web Development Intern
Specialized in architecting AI-powered web ecosystems and implementing high-efficiency automation protocols.
/ Architected AI-powered web applications using Next.js 15 and TypeScript for specialized business logic.
/ Engineered intelligent workflow automation with n8n to synchronize distributed services.
/ Developed robust CI/CD pipelines via GitHub Actions, ensuring 100% deployment integrity.
/ Integrated multi-modal AI features leveraging Google Gemini for complex data synthesis.
/ Managed high-performance data layers with MongoDB and Supabase vector scaling.
/ Implemented modern design systems with Tailwind CSS following strictly optimized UX principles.
My Projects
A collection of projects showcasing my skills in various technologies and domains.
FaceForge: Transformer-Based Face Synthesis & Detection
End-to-end deep learning framework combining a Vision Transformer generator (252M parameters) with an XceptionNet detector for facial manipulation synthesis and detection. Validated on FaceForensics++ with adversarial optimization and high-fidelity identity transfer capabilities.
AI Virtual Try-On System
Deep learning-based virtual try-on system using multi-modal feature fusion (41 channels) and GANs to generate photorealistic garment transfer. Published research on Zenodo with comprehensive implementation.
AI Music DeepFake Detector
Hybrid deep learning system combining Convolutional Autoencoders and Transformer Encoders to detect AI-generated music with 95% accuracy, 100% recall for authentic music, and perfect protection for human-created content.
Agentic OSINT Intelligence Platform
Production-ready multi-agent OSINT system that autonomously monitors global intelligence sources 24/7, processing 1000+ articles/hour through Kafka streams. Features temporal knowledge graph (Neo4j), NLI-based contradiction detection, credibility scoring, and real-time analytics dashboard.
Code-Morph: Autonomous Multi-Agent Repository Migration Engine
Cutting-edge autonomous system that transforms entire codebases across frameworks (TensorFlow→PyTorch) with zero logical drift. Features AST-driven semantic understanding, 5-agent orchestration, LLM-powered transformations, and automated verification proving behavioral equivalence.
Human vs. AI Text Classification
Comprehensive ensemble-based text classification system achieving 99.59% F1-score in distinguishing human-written from AI-generated text using 6 diverse classifiers and 4 advanced ensemble techniques.
Real-Time Sign Language Translator
Production-ready ASL recognition system achieving 99.60% accuracy with real-time performance (25-30 FPS) using ResNet18 and MediaPipe hand detection on consumer hardware.
Fine-tuning PubMedBERT for Medical Literature Embeddings
Domain-specific fine-tuned PubMedBERT model optimized for generating high-quality medical text embeddings using contrastive learning on 1,918 PubMed Central articles, achieving 0.78+ similarity scores.
Comparative Analysis of TimeGAN and Diffusion Models for Synthetic Financial Time-Series Generation
Dual-objective research study evaluating TimeGAN vs Diffusion Models for synthetic data generation AND forecasting performance across 11 financial assets. TimeGAN achieves 54% better generation quality; ARIMA dominates forecasting with 97.51% accuracy.
Multimodal RAG System: Interactive PDF Chat with Vision & Text
End-to-end Retrieval-Augmented Generation pipeline processing 505 chunks from PDFs with hybrid Sentence-BERT + CLIP embeddings. Achieved MAP 0.253, Precision@1 62.5%, integrated LLaMA 3.2 via Ollama for local inference with 2.1s average response time.
Multi-Document Financial Analysis System Using RAG
Production-grade AI/NLP system for financial document analysis using Retrieval-Augmented Generation (RAG). Features LangChain integration, FastAPI REST API, multi-LLM support (Groq, OpenAI, Anthropic, Google, Cohere), and comprehensive testing with 45+ automated tests.
Skills
Professional technical arsenal spanning from low-level engineering to advanced neural network architectures.
Programming Languages
AI & Machine Learning
Web Architecture
Cloud & DevOps
Databases & Systems
Specialized Networks
Certifications
Professional certifications from leading institutions in AI, Machine Learning, and Data Science.
Get In Touch
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