Eva-Maria Strauch, PhD
Principal Investigator · Associate Professor
Protein design, viral immunogens, molecular recognition, and experimentally grounded AI for biomolecular engineering.
People
A team fluent in computation, proteins, viruses, and experiments.
Our work is intentionally interdisciplinary. Lab members learn to move between algorithmic reasoning and experimental validation while developing independent scientific questions.
Principal Investigator
Research Staff
Matthew Anderson
Research Associate
Supports the lab’s experimental protein-engineering and research operations.
Amruta Bapat, PhD
Research Scientist
Genomics workflows, flow cytometry, protein purification, and project management for high-throughput biomolecular engineering.
Raulia Syrlybaeva, PhD
Research Scientist
Computational chemistry, machine learning for protein design, and prediction of alternative protein conformations.
Ashish Sharma, PhD
Research Scientist
Protein production and characterization for biomolecular engineering projects in the Strauch Lab.
Graduate Students
Qingfa Hou
Graduate Student
Stabilization of influenza hemagglutinin using yeast display and deep mutational scanning to define sequence–stability relationships.
Je-Hoon Michael Oh
Graduate Student
Protein engineering and molecular design at the interface of computational modeling and experimental validation.
Ho Suk Lee
Graduate Student
Reverse genetics, mammalian cell culture, lentiviral systems, and viral pseudotyping for new experimental platforms.
Akshaj Jois
Master's Student
Master's student working on protein engineering and biomolecular design in the Strauch Lab.
Visiting Researchers
Martina Madrzak
RosettaCommons REU Intern
Visiting undergraduate researcher working with the Strauch Lab through the RosettaCommons REU program.
Lab culture
Collaborative by design.
We value rigorous thinking, generous collaboration, open scientific exchange, and the willingness to learn unfamiliar methods. Projects are structured to build both depth and cross-disciplinary independence.
Individual paths
Training plans align scientific ownership, technical development, publication goals, and each researcher’s long-term career direction.
Shared expertise
Computational and experimental researchers work together from project conception through validation, analysis, and communication.