Computational Biology Consultant | Biomarker Strategist | Pharma R&D, Data & AI

I am an independent computational biology consultant with over a decade of experience spanning academic research, AI-driven biopharma, and translational science.

My work sits at the intersection of biological data analysis, AI/ML, and pharmaceutical R&D. I help translate complex biological datasets, design proof-of-concept studies, and develop data-driven strategies that inform drug development decisions. A recurring focus of this work is biomarker development, using multi-omics data to identify patient populations, predict drug response, and support precision medicine approaches. I am equally comfortable working hands-on with data and developing strategies, communicating findings to executive and clinical stakeholders.

My background includes a PhD in computational biology, postdoctoral research at the NCBI, NIH (integrating genomic, structural, and small molecule data for precision medicine), and six years as scientific and strategic lead at Genialis, an AI-based RNA biopharma startup, where I led cross-functional projects delivering data science solutions for global pharma clients.

I currently work independently on a project basis. I offer the following services:

1. Data Analysis - from raw data to biological insights

2. Biomarker strategy - design and execution of AI-driven biomarker discovery pipelines. Patient stratification, drug response prediction, and companion diagnostic strategy

3. Strategic Scientific Advisory - translating high-level pharma challenges into data-driven AI/ML strategies. Advising startups and growth-stage companies on data assets, pipeline design, and R&D direction.

At this summit I am open to conversations about consulting engagements, collaborative research projects, and partnerships with companies working in precision medicine, translational research, or AI-driven drug development.