Filippos Tourlomousis | founder & CEO
Biological Lattice Industries Corp.
Filippos Tourlomousis is the founder of Biological Lattice Industries (BLI), a company building the new way to advance the bioeconomy through collaborative cyber-physical AI agents for innovators who design and make advanced formulations and devices serving human health and the environment.
His work bridges entrepreneurship, autonomous laboratories, biofabrication, materials engineering, and open-source scientific instrumentation. He also leads the Autonomous Science Lab at NCSR Demokritos in Athens and previously conducted postdoctoral research at MIT’s Center for Bits and Atoms.
His mission is to make AI-powered experimental platforms and self-driving labs more accessible, scalable, and impactful for materials discovery and bioengineering.
Appearances:
Day 2: 29th October @ 12:40
The Missing Infrastructure for Biomaterial Automation: A Cyber-Physical AI Workbench
Lab automation has transformed routine liquid handling. Biomaterials never got the same treatment, because they are hard in two ways. Some are complex liquids: viscous, non-Newtonian, multiphase formulations, such as hydrogels, emulsions, and skin-contact actives, that standard liquid handlers were never built for. Others are architected fibrous devices, such as absorbent cores, nonwovens, scaffolds, and implants, where performance comes from structure as much as chemistry. In both forms, R&D still runs on tacit recipes and manual handoffs, and results reach design teams long after the experiment.
AI models alone won't close this gap. A model reasons, but acting on matter requires a harness: memory, data, tools, safety rules, and direct access to machines with modular automation architectures. This talk presents a cyber-physical harness for autonomous science in biomaterial product development. On the liquid side, a self-driving formulation robot plans, mixes, measures, and chooses its next experiment without waiting for a human. On the fibrous side, robotic fabrication turns designs that carry their own process instructions into architected structures. One agent layer orchestrates both, and every run trains the next Design-Make-Test-Analyze cycle.
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