I write about machine learning and biology, with a focus on practical applications in drug discovery, AI strategy for biotech, and career guidance for computational scientists. Below are featured articles that give an idea for what I like to write about - read the full posts on Substack.
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Companies that scaled before ChatGPT (Nov 2022) are “AI-encumbered”—structurally disadvantaged against AI-native startups. The real dividing line isn’t age, it’s whether your organization was built with AI from day one versus bolting it onto existing systems.
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Protein structure prediction advanced dramatically, but therapeutic antibody design faces a bottleneck: accurately predicting CDR loops, especially CDR H3, for novel sequences.
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Breaking into AI for Bio requires 1-5 years of sustained effort: solid fundamentals, meaningful research experience, demonstrated execution ability, and strong engineering practices. What actually matters when hiring managers review candidates.
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AI/ML value in drug discovery comes from automating routine decision-making and data synthesis. Protein binding prediction grabs headlines but misses the actual bottlenecks where ROI lives.