Matthew Tamasi
Papers
6
Total Citations
291
H-Index
5
About
Matthew Tamasi is a materials scientist and polymer chemist whose research sits at the dynamic intersection of automated synthesis, machine learning, and biomaterials engineering. His most celebrated contribution involves pioneering the integration of robotic platforms with active machine learning to design polymer–protein hybrids — engineered materials capable of stabilizing proteins in non-native environments for medicinal, commercial, and industrial applications. This landmark work has garnered over 170 citations, establishing Tamasi as a leading voice in the emerging field of autonomous materials discovery. Beyond polymer–protein systems, Tamasi has made significant strides in advancing high-throughput controlled/living radical polymerization (CLRP), demonstrating how automation can dramatically accelerate synthetic polymer research — work that has accumulated over 60 citations. His subsequent development of a fully automated photoinitiated RAFT polymerization platform further underscores his commitment to scalable, reproducible polymer synthesis. Complementing these efforts, Tamasi has employed sophisticated biophysical characterization techniques — including small-angle X-ray scattering and quartz crystal microbalance with dissipation — to deepen mechanistic understanding of polymer–protein interactions. Collectively, his research represents a compelling vision for the future of materials science: one where robotics, data-driven methods, and polymer chemistry converge to accelerate discovery.
Research Focus
Key Achievements
Top Papers
- 1Machine Learning on a Robotic Platform for the Design of Polymer–Protein Hybrids173 citations · 2022
- 2Automation of Controlled/Living Radical Polymerization61 citations · 2019
- 3A fully automated platform for photoinitiated RAFT polymerization30 citations · 2023
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