EXECUTIVE PROFILE

Scientist, AI innovator, and entrepreneur with 20+ years of experience across biomedical research, systems biology, oncology, translational medicine, advanced analytics, and scientific consulting. Combines rare depth in three areas: foundational AI development, deep biomedical and systems pharmacology expertise, and strong business-facing scientific judgment. Proven across leading research institutions and industry environments including DKFZ, Ghent University, Bayer, SAS, Genedata, IDBS, and (AI- and systems biology-driven consultancy, Name on request). Particularly effective in roles that require turning complex science and AI into actionable value for R&D, clinical development, innovation strategy, partnerships, or due diligence.  

CORE ADVANTAGES

• Foundational AI: Developed the Time-Delayed Recurrent Neural Network (TDRNN), an early architecture for reverse engineering dynamic systems and uncovering network topology from time-resolved data.
• Biomedical depth: Expertise in systems pharmacology, systems biology, translational medicine, oncology, multi-omics integration, biomarkers, patient stratification, and drug-development analytics.
• Commercial relevance: Strong track record translating advanced science into strategic decisions, AI adoption opportunities, high-value analytics, and innovation pathways for pharma and biotech.  

WHERE I CREATE VALUE

• AI adoption and scientific AI strategy for pharma, biotech, healthtech, CROs, and innovation teams
• Drug discovery and translational medicine analytics, including multimodal and multi-omics integration
• Clinical development support, patient stratification, digital biomarker strategy, and trial-risk reasoning
• Scientific consulting, solution design, innovation scouting, technical due diligence, and executive advisory
• Secure AI workflow design for biomedical knowledge extraction, literature intelligence, and decision support 

SELECTED IMPACT HIGHLIGHTS

• Built AI-supported platforms for mechanistic systems biology, simulation, and translational interpretation.
• Worked on prediction of patient-to-drug response using digital biomarkers in pharma R&D.
• Designed an AI-driven strategy to rescue failed clinical-trial assets through patient stratification and novel indications.
• Advised scientific and business stakeholders on high-value applications of AI in biomedical R&D. 

CORE EXPERTISE

Biomedical AI, translational medicine, systems pharmacology, systems biology, drug discovery analytics, clinical development analytics, patient stratification, digital biomarkers, multi-omics integration, genomics, transcriptomics, methylomics, single-cell contexts, dynamic systems modeling, machine learning, deep learning, mechanistic modeling, genetic algorithms, multi-objective optimization, agent-based modeling, scientific computing, Python, R, Matlab, C, Objective-C, Perl, executive scientific communication, innovation strategy, due diligence.