Multimodal Generative Systems • Video Understanding • World Models
Building next-generation generative AI systems that understand and create multimodal content from text to motion to photorealistic video.
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🔹 Transformer-based architectures for text→video synthesis |
🔸 Distributed training pipelines (PyTorch DDP) |
┌─ Generative Video Systems │ ├─ 🧠 Transformer-based architectures │ ├─ 🎨 Diffusion model research │ ├─ ⏰ Temporal consistency modeling │ └─ 🎥 Text-to-motion-to-video synthesis │ ├─ World Models │ ├─ 🌍 Environment dynamics learning │ ├─ 🎮 Predictive modeling │ └─ 🔮 Temporal coherence │ └─ Multimodal AI ├─ 🔄 Cross-modal fusion ├─ 👁️ Vision-language models └─ 🎵 Audio-visual learning
┌─ Distributed Training │ ├─ ⚡ PyTorch DDP (8-GPU clusters) │ ├─ 📊 Large-scale dataset pipelines │ ├─ 🔬 Systematic experimentation │ └─ 📈 Mixed precision training │ ├─ Production ML │ ├─ 🚀 ONNX deployment │ ├─ ⚡ TensorRT optimization │ ├─ 📦 Model quantization │ └─ 🎯 Inference acceleration │ └─ Research Infrastructure ├─ 🔧 Experiment tracking ├─ 📉 Metric dashboards └─ 🛠️ Reproducible pipelines
| Domain | Technologies | Experience Level |
|---|---|---|
| 🧠 Generative Modeling | Diffusion • GANs • VAEs • Transformers • Temporal Consistency | ████████████ 95% |
| 🎬 Video & Motion | Pose Estimation • Temporal Modeling • Sequence Alignment • Motion Synthesis | ███████████░ 90% |
| 🔄 Multimodal Systems | Cross-modal Fusion • Vision-Language • Audio-Visual Learning | ██████████░░ 85% |
| ⚡ Distributed Training | PyTorch DDP • 8-GPU Clusters • Large-scale Pipelines • Experiment Tracking | ███████████░ 88% |
| 🚀 Model Deployment | ONNX • TensorRT • Quantization • Inference Optimization | ██████████░░ 82% |
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MSc Computer Vision, 📄 Dissertation: Cross-modal latent fusion for multimodal face generation |
2 Research Papers ✨ Generative AI Architectures 🔬 Computer Vision Systems |
AI Encode London Winner ⚡ Built a real-time AI prototype in 48 hours 🚀 Production-ready system demo |
MSc Dissertation: Latent fusion for multimodal synthesis
Tech: VAEs • Cross-modal Fusion • PyTorch
Status: Published Research
I'm actively seeking opportunities to collaborate on cutting-edge research problems:
| Research Area | Specific Interests |
|---|---|
| 🌍 World Models | Environment dynamics • Predictive modeling • Spatial reasoning |
| 🎬 Video Generation | Temporal coherence • Motion synthesis • Controllable generation |
| 🔄 Multimodal AI | Cross-modal fusion • Unified representations • Audio-visual learning |
| ⏰ Temporal Reasoning | Long-range dependencies • Sequence modeling • Event prediction |
| 🎮 Interactive Systems | Real-time generation • Human-AI collaboration • Embodied AI |
📍 London, United Kingdom
🎓 MSc Computer Vision, Robotics & ML @ University of Surrey
🔬 Researching at the intersection of generative AI, video understanding, and world models