Hi there 👋, I am
Protein Engineer & ML Scientist
Innovative scientist applying generative AI, structural modeling, and biophysical assays to design biosimilar proteins and develop high-throughput methods for stability screening and binding analysis.
I'm a passionate scientist with a unique blend of biochemistry expertise and machine learning innovation. Currently working as a Scientist II at AbbVie, I specialize in applying cutting-edge AI tools like AlphaFold2, RFdiffusion, and ESM2 to solve complex protein design challenges.
My journey spans from academic research at Purdue University to industry innovation at Evozyne and now AbbVie. I've developed expertise in generative protein design, high-throughput screening, and thermodynamic analysis, always pushing the boundaries of what's possible in protein engineering.
I'm passionate about advancing the field through innovative research and have developed complementary pipelines for de novo protein design, comparing how different embedding backbones influence generative outcomes in protein sequence space.
Education: Thesis MS Biochemistry (Purdue), BS Biochemistry (Wartburg), Data Science Certificate
Current Role: Scientist II at AbbVie - Protein Design & ML Innovation
Research Focus: Generative AI for protein design, structural modeling, biophysical assays
Publications: First-author papers in JOVE and Frontiers in Plant Science
PyTorch, NumPy, scikit-learn, Matplotlib, seaborn, ESM2, AlphaFold2, ProteinMPNN, RFdiffusion
Biosimilar design, structural modeling, thermodynamic analysis, high-throughput screening, protein purification
Python, R, Git, GitHub, bash, Unix, VS Code, Jupyter, automated liquid handling systems
A modular machine learning pipeline combining ESM2 embeddings, latent diffusion, and transformer-based decoding for de novo protein design. Explores protein sequence space without structural supervision.
AbbVie | North Chicago, IL
Feb 2024 – Present
Leading innovative protein design projects using generative AI and structural modeling. Developed Python-based evaluation frameworks integrating AlphaFold2, ESM embeddings, and advanced sequence metrics for high-throughput screening. Designed biosimilar proteins using ProteinMPNN and RFdiffusion, achieving improved expression and stability profiles.
Evozyne | Chicago, IL
May 2021 – Feb 2024
Built high-throughput enzyme screening and kinetic modeling pipelines using Python. Developed comprehensive SOPs for protein expression, purification, and characterization. Led innovative thermal stability screening platforms using split NanoLuciferase technology, significantly expediting design-build-test cycles.
Xing Liu Lab, Purdue University
Aug 2017 – May 2021
Conducted comprehensive research on SCF E3 ligase protein dynamics. Developed R-based scripts for tissue-specific expression analysis and pioneered co-expression of Arabidopsis Cullin proteins. Mentored graduate and undergraduate researchers while contributing to multiple publications.
I'm always interested in discussing protein engineering, machine learning applications in biotechnology, and innovative approaches to drug discovery. Let's connect and explore opportunities for collaboration!