Started Research Collaboration with Georgia Tech
🔬 Research opportunity! Thrilled to begin a research collaboration with the Robot Intelligence and Perception Lab (RIPL) at Georgia Institute of Technology!
Lab Overview
RIPL is at the forefront of:
- Computer Vision: Advanced perception systems for robotics
- Machine Learning: Novel algorithms for continual and lifelong learning
- Robotics: Intelligent systems that can adapt and learn in real-world environments
- AI Safety: Ensuring robust and reliable AI systems
Collaboration Overview
This industry-academic partnership allows me to:
- Maintain Full-time Role: Continue my work at Interactive Brokers
- Research Contribution: Apply industry experience to academic research
- Real-world Applications: Bridge theory and practice in financial ML
- Knowledge Exchange: Share production insights while learning cutting-edge research
Research Focus Areas
Working on projects that combine:
- Continual Learning: Algorithms that adapt to changing market conditions
- Federated Learning: Privacy-preserving learning across financial institutions
- Multi-modal Learning: Combining market data, news, and alternative data sources
- Production Applications: Converting research into deployable trading systems
Industry-Academic Bridge
This collaboration enables:
- Real Data Access: Using anonymized financial datasets for research
- Production Constraints: Research that considers latency and reliability requirements
- Practical Validation: Testing algorithms in real trading environments
- Publication Opportunities: Contributing to both academic and industry literature
Goals for the Collaboration
- Research Papers: Co-author publications on ML applications in finance
- Open Source Tools: Develop frameworks for financial ML research
- Student Mentoring: Share industry experience with graduate students
- Technology Transfer: Bring academic innovations to production systems
Why This Matters
This collaboration represents the perfect intersection of industry experience and academic research. It allows me to contribute real-world insights to cutting-edge research while bringing the latest academic developments into production systems.
The combination of practical trading experience and research innovation could lead to breakthrough applications in financial ML!
From production systems to research breakthroughs - the best of both worlds! 🔬💼