Daniel McNeela is a senior technology specialist whose practice focuses on assisting in patent litigation in district court and before the International Trade Commission. He also assists in the preparation and prosecution of domestic patent applications. He joined WilmerHale in 2025.

Mr. McNeela is a machine learning engineer and researcher with extensive experience in applying AI and machine learning to biomedical domains. Prior to joining the firm, he held research and engineering positions at artificial intelligence companies and pharmaceutical labs, where he contributed to the building of natural language processing models, distributed software platforms for analyzing developability properties of therapeutic antibody candidates, and neural network models for use in molecular dynamics simulations. He is currently pursuing his JD from Arizona State University’s Sandra Day O’Connor College of Law.

Mr. McNeela earned an MS in Biomedical Data Science from the University of Wisconsin, Madison. He also spent time in the PhD program in Computer Science at the University of Wisconsin, Madison, where he researched geometric deep learning methods and their application to drug discovery, molecular dynamics, and computational network biology. His research has been published in venues such as the International Conference on Machine Learning Workshop on Computational Biology, the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, the International Conference on Machine Learning 2nd Workshop on Generative AI and Law, and the Great Lakes Bioinformatics Conference.