Benjamin NemozM.D., Ph.D.
Physician-scientist · antibody engineering, structural immunology & machine learning
I build the models that design antibodies — grounded in a decade at the bench and in the clinic. My work runs from broadly neutralizing antibody discovery and high-throughput repertoire sequencing to antibody foundation models, somatic-hypermutation modeling, and the agentic tooling around them.
Bench
bnAb discovery, SOSIP trimers, BLI, and high-throughput natively-paired repertoire sequencing at the Scripps Research Institute.
Clinic
Medical virologist; led emerging-pathogen response and a BSL-3 lab through the pandemic. First-author case work in the NEJM.
Code
Antibody foundation & SHM models, affinity prediction, and agentic systems. Co-founder / CTO of an AI antibody-design company.
Selected publications
Full list on Google Scholar — 519 citations, h-index 11.
Projects
A nucleotide-level antibody foundation model (AbLM) and an SHM model that capture B-cell repertoire evolution. Antigen-agnostic AI-simulated SHM improved the neutralization potency of HIV-1 broadly neutralizing antibodies by up to 76-fold (poster).
A high-throughput platform for natively-paired antibody-repertoire sequencing — combinatorial barcoding at the scale of millions of heavy/light pairs.
From the HIV-1 elite-neutralizer donor PC94, isolation and end-to-end characterization of the broadly neutralizing lineage PC94-A (neutralization, BLI, cryo-EM), with model-guided maturation and an IgA study.
Binding-affinity prediction models, comparing quantum and classical computing approaches.
Company
Semi-autonomous design of next-generation, fully human therapeutic monoclonal antibodies. Bootstrapped; programs with DKFZ and a NASDAQ-listed biotech; awarded the French national “Deep Tech” label (Bpifrance).