David Koes, Ph.D.
|Ph.D. in Computer Science, Carnegie Mellon University|
Phone: (412) 383-5745
The goal of my research is to develop novel computational methods and applications that unlock the potential of computational drug discovery to revolutionize the treatment of disease. I develop new applications of machine learning for computational drug discovery as well as discrete algorithms for accelerating the drug discovery workflow. In addition to developing new computational techniques, I deploy these techniques via easy to use online applications and apply them in prospective drug discovery exercises.
MSCBIO2025 Introduction to Bioinformatics Programming in Python (Fall Semester) This course is a graduate level introduction to programming in Python in the context of computational biology applications.
MSCBIO2065 Scalable Machine Learning for Big Data Biology (Spring Semester) This course is a rigorous introduction to the effective application of machine learning to large and complex biomedical data.
Publications (Google Scholar)