Richard Michael

Richard Michael is a PhD Fellow and Guest Researcher at the Machine Learning section of the Department of Computer Science, University of Copenhagen. His work focuses on bridging machine learning with computational biology, particularly in protein engineering and optimization of discrete sequences.

Research Interests

• High-dimensional Bayesian optimization for discrete sequences
• Regression models in biomolecular design
• Continuous relaxation techniques for discrete problems
• Fitness landscape analysis in protein engineering
• Gaussian processes for predictive modeling

Publication Trends
Recent work highlights interdisciplinary approaches combining machine learning with computational biology. Key areas include optimization of discrete sequences (e.g., proteins or DNA), systematic benchmarking of regression models for biomolecular tasks, and development of novel computational frameworks for high-dimensional problems. His publications span both conference proceedings (e.g., NeurIPS) and peer-reviewed journals (e.g., PLOS Computational Biology).

Contact
Email: richard.michael@di.ku.dk