Christopher Langmead

About Christopher Langmead

Expert in the development and application of Generative Modeling, AI, and Machine Learning techniques for the discovery and optimization of biologics. At Amgen, I lead a cross-functional team that performs a combination of pipeline project support and technology development. Previously, I was a tenured faculty member in the School of Computer Science at Carnegie Mellon. I left academia so that I could have real-world impact by \'putting theory into practice\'. As a faculty member at CMU, I was a founding member of the Department of Computational Biology, the co-founder of the MS program in Automated Science, former co-director of the MS program in Computational Biology, and founding faculty and former co-associate director of the Ph.D. program in Computational Biology.Specialties: Generative Modeling; Bayesian Optimization; Artificial Intelligence; Statistical Machine Learning; Reinforcement Learning; Computational Biology and Chemistry; Model Checking, Systems Biology Modeling in Pancreatitis, Sepsis, and Cancer.

Experience

1. Vice President, Ai-driven Molecular Design

   Danaher

   Jan 2026 — Present · US

   I set the technical and scientific vision for how AI can advance molecular design across Danaher’s portfolio of life sciences and diagnostics operating companies. My role spans strategy, platform development, and execution - translating rapid advances in generative AI, predictive modeling, agentic AI, and automation into scalable, high-impact capabilities for molecule discovery and optimization.My responsibilities include:* Defining the enterprise AI vision and technical roadmap for molecular design, aligned to operating company priorities and long-term business strategy.* Developing, evaluating, and deploying AI solutions across multiple molecular modalities - including proteins, antibodies, and mRNA - to enable both de novo design and molecular engineering, using a disciplined build-vs-buy-vs-partner decision framework.* Establishing shared AI and automation platforms, benchmarks, and proprietary data assets to drive differentiation and enable consistent, measurable impact across operating companies.* Collaborating closely with scientific domain experts and business leaders to identify high-value use cases, develop proof-of-concepts, and scale successful solutions into production.* Overseeing data acquisition, curation, and governance to ensure high-quality, fit-for-purpose datasets, to drive design-make-test-learn loops, while maintaining security and compliance.

Education

• Dartmouth College

  M.A., Computer Music

  1993 — 1995

• Dartmouth College

  Ph.D., Computer Science

  1998 — 2003

• Oberlin College

  B.M., Computer Music, Music Composition

  1989 — 1993

Skills

• Java
• Matlab
• Computational Chemistry
• Drug Design
• High Performance Computing
• Model Checking
• Modeling
• Mathematics
• Cancer
• Machine Learning
• Scientific Computing
• Parallel Computing
• Data Analysis
• Computer Science
• Homology Modeling
• Simulation
• Structural Biology
• Mathematical Modeling
• Python
• Latex
• Formal Methods
• Bioinformatics
• Statistical Modeling
• Statistics
• Molecular Dynamics
• R&D
• Molecular Biology
• Informatics
• C++
• Molecular Modeling
• Distributed Systems
• Structural Bioinformatics
• Research
• Artificial Intelligence
• Drug Discovery
• C
• Programming
• Optimization
• Algorithms
• Life Sciences