Alejandro is a biomedical AI researcher and full-stack ML developer focused on accelerating scientific discovery through intelligent systems. As a TechBio accelerationist, he builds machine learning methods and software infrastructure to transform R&D in the medicinal and life sciences. He believes that LLM agents grounded in hard science and unified data models can automate core research workflows across biology, chemistry, and materials science—bringing scientific progress to the pace of software. His mission is to help unlock the next era of human advancement by extending lifespans, scaling knowledge, and pushing the boundaries of what’s possible.
The core problem is that scientific research remains fragmented, manual, and slow—especially in fields like drug discovery, materials science, and chemistry where data silos and labor-intensive workflows dominate. We are building the world’s first platform for scientific digital intelligence, designed to unify and automate these processes at scale. We are developing an architecture to bring structured access, retrieval, and generation capabilities over a shared scientific data model. This enables LLM agents grounded in real science to reason across modalities, simulate experiments, and accelerate discovery in ways legacy tools and institutions simply can't.
He joined Calculus because building a platform for scientific intelligence requires speed, autonomy, and infrastructure that academia can't provide. Traditional institutions, in academia and industry, are too slow, too siloed, or too focused on publishable increments—while the path to scientific superintelligence demands bold, integrated engineering and relentless, open-source, iteration.
By september, Alex will have an Alpha release of a therapeutics scientific digital intelligence system with public, publication-ready, use cases and benchmarks.
Alejandro is a biomedical AI researcher and full-stack ML developer focused on accelerating scientific discovery through intelligent systems. As a TechBio accelerationist, he builds machine learning methods and software infrastructure to transform R&D in the medicinal and life sciences. He believes that LLM agents grounded in hard science and unified data models can automate core research workflows across biology, chemistry, and materials science—bringing scientific progress to the pace of software. His mission is to help unlock the next era of human advancement by extending lifespans, scaling knowledge, and pushing the boundaries of what’s possible.
The core problem is that scientific research remains fragmented, manual, and slow—especially in fields like drug discovery, materials science, and chemistry where data silos and labor-intensive workflows dominate. We are building the world’s first platform for scientific digital intelligence, designed to unify and automate these processes at scale. We are developing an architecture to bring structured access, retrieval, and generation capabilities over a shared scientific data model. This enables LLM agents grounded in real science to reason across modalities, simulate experiments, and accelerate discovery in ways legacy tools and institutions simply can't.
He joined Calculus because building a platform for scientific intelligence requires speed, autonomy, and infrastructure that academia can't provide. Traditional institutions, in academia and industry, are too slow, too siloed, or too focused on publishable increments—while the path to scientific superintelligence demands bold, integrated engineering and relentless, open-source, iteration.
By september, Alex will have an Alpha release of a therapeutics scientific digital intelligence system with public, publication-ready, use cases and benchmarks.
Alejandro is a biomedical AI researcher and full-stack ML developer focused on accelerating scientific discovery through intelligent systems. As a TechBio accelerationist, he builds machine learning methods and software infrastructure to transform R&D in the medicinal and life sciences. He believes that LLM agents grounded in hard science and unified data models can automate core research workflows across biology, chemistry, and materials science—bringing scientific progress to the pace of software. His mission is to help unlock the next era of human advancement by extending lifespans, scaling knowledge, and pushing the boundaries of what’s possible.
The core problem is that scientific research remains fragmented, manual, and slow—especially in fields like drug discovery, materials science, and chemistry where data silos and labor-intensive workflows dominate. We are building the world’s first platform for scientific digital intelligence, designed to unify and automate these processes at scale. We are developing an architecture to bring structured access, retrieval, and generation capabilities over a shared scientific data model. This enables LLM agents grounded in real science to reason across modalities, simulate experiments, and accelerate discovery in ways legacy tools and institutions simply can't.
He joined Calculus because building a platform for scientific intelligence requires speed, autonomy, and infrastructure that academia can't provide. Traditional institutions, in academia and industry, are too slow, too siloed, or too focused on publishable increments—while the path to scientific superintelligence demands bold, integrated engineering and relentless, open-source, iteration.
By september, Alex will have an Alpha release of a therapeutics scientific digital intelligence system with public, publication-ready, use cases and benchmarks.