Assistant Professor
Ludmil B. Alexandrov
Assistant Professor
Short Biography
Ludmil Alexandrov is an Oppenheimer Fellow in the Theoretical Biology and Biophysics Group and the Center for Nonlinear Studies at Los Alamos National Laboratory. He earned his Bachelor of Science degree in Computer Science from Neumont University and received his Master’s of Philosophy in Computational Biology as well as his Ph.D. in Cancer Genetics from the University of Cambridge.
Ludmil’s research has been focused on understanding mutational processes in human cancer through the use of mutational signatures. In 2013, he developed the first comprehensive map of the signatures of the mutational processes that cause somatic mutations in human cancer. This work was published in several well-regarded scientific journals and highlighted by the American Society of Clinical Oncology as a milestone in the fight against cancer. More recently, Ludmil mapped the signatures of clock-like mutational processes operative in normal somatic cells, demonstrated that mutational signatures have the potential to be used for targeted cancer therapy, and identified the mutational signatures associated with tobacco smoking.
Ludmil has 55 publications in peer-reviewed journals from which 14 publications in Nature, Science, or Cell and another 17 publications in Nature Genetics, Nature Medicine, or Nature Communications. In 2014, Ludmil Alexandrov was recognized by Forbes magazine as one of the “30 brightest stars under the age of 30” in the field of Science & Healthcare. In 2015, he was awarded the Prize for Young Scientists in Genomics and Proteomics by Science magazine and SciLifeLab, and he also received a Harold M. Weintraub Award by the Fred Hutchinson Cancer Center. In 2016, Ludmil was awarded the Carcinogenesis Young Investigator Award by Oxford University Press and the European Association for Cancer Research. Ludmil is currently one of six co-investigators leading the Mutographs of Cancer project, a $25 million initiative that seeks to fill in the missing gaps to identify the unknown cancer-causing factors and reveal how they lead to cancer.