A brief description about me
👨💻 AI Research Engineer with Production Skills 💻
Continual Learning for Agents | Trustworthy AI | MLOps
Hi there! I’m Gusseppe Bravo, a passionate AI Research Engineer with expertise in designing and deploying production-grade AI systems. I specialize in AI-based agents, continual learning solutions, and bridging the research-to-production gap. Currently working at the Barcelona Supercomputing Center with one of the world’s top supercomputers.
🤝 Current Collaborations
Lenovo (USA): Multi-year collaboration on continual learning and trustworthy AI, resulting in $250K+ in research funding and multiple production deployments.
Emory University: PhD internship developing cognitive architectures for diabetic retinopathy models, with publications at top-tier conferences including a Best Student Paper Award finalist.
💻 Core Skills
Production AI systems, Python/Linux/MLOps, Continual Learning, Problem solving, LLMs, Multi-agent systems, and enterprise-scale AI deployment.
🔬 Research Impact
- $250K+ in research funding secured from industry partnerships
- $10M+ revenue impact generated through AI fraud detection systems
- 40+ GitHub repositories for open-source ML/MLOps projects
- 10+ publications in top-tier conferences (AAMAS, ICPR, CVPR, VISAPP)
🏆 Recent Achievements
- Intel-Lenovo AI Innovators Award (2023) for cognitive architectures research
- VISAPP 2025 Best Student Paper Award Finalist for continual learning in healthcare
- AAMAS 2025 acceptance for adaptive cognitive architecture work
- Multiple CVPR grants from IEEE Computer Society and Accel AI Institute
🚀 Key Technologies & Expertise
- AI/ML Frameworks: PyTorch, TensorFlow, HuggingFace, LangGraph, AutoGen, Langchain
- MLOps & Infrastructure: MLflow, Ray, Docker, Kubernetes, Airflow, Spark
- Specialized Areas: Continual Learning, Multi-agent Systems, LLMs, RAG, Model Monitoring
- Production Systems: Enterprise-scale AI deployment, Model reliability, Drift detection
🔬 Research Focus
- Continual Learning: Task-agnostic domain adaptation enabling 6% performance improvements
- Cognitive Architectures: LLM-based agents for autonomous ML model monitoring
- Healthcare AI: Domain adaptation for medical imaging with 3.1% accuracy improvements
- Production MLOps: End-to-end systems processing 1TB+ data monthly
🌟 Personal Goal
I dream of creating AI systems that continuously adapt and improve in real-world environments, bridging the gap between research innovation and production deployment to solve meaningful problems at scale.
📫 Let’s Connect!
If you’re interested in connecting with me, feel free to send me a message or connect with me on LinkedIn!
