Summary
Dorian is a Research Associate within the Next Generation Neural Interfaces (NGNI) lab and the Centre for Bio-Inspired Technology (CBIT) at Imperial College London and a Royal Academy of Engineering Enterprise Fellow.
He is also a Co-Founder of MintNeuro – an Imperial College spinout – where he is leading a team of engineers and neuroscientists developing innovative micro-implantable bioelectronics.
His research interests include:
implantable medical devices, brain-computer interfaces, bioelectronics, biomedical circuits and systems, and intrabody communication systems.
Dorian received his BSc in Electronic Engineering in 2012 at Politecnico di Torino, Italy. He continued his studies with an MSc in Electronic Engineering, specializing in communication and wireless systems. He was awarded a scholarship for developing the MSc thesis project at the CBIT, where he designed and implemented an innovative thermally controlled system for bio-applications using low-cost PCB technology.
After his MSc graduation, in 2015 Dorian joined the NGNI lab at Imperial College London as a Research Assistant, working on implantable medical devices and neurotechnologies within the CANDO project. In the meantime, he started a part-time Ph.D. programme on power management and data communications for implantable microsystems, concluding his doctorate studies in August 2021 at the VIVA, without thesis corrections. He serves as a committee member of the Imperial Postdoc and Fellow Enterprise Network (IPFEN) and is a member of various associations/institutes (IEEE, IET, FENS, SfN, BNA, etc).
In July 2020, Dorian joined the MedTech SuperConnector programme as a member of the 4th Cohort, focusing on the commercialisation potential of radar sensing/monitoring for back pain prevention and management. In July 2021 he was awarded the RAEng Enterprise Fellowship, with the goal of exploring business opportunities for medical devices based on micro implantable neural technologies.
Selected Publications
Conference
Haci D, Liu Y, Constandinou TG, 2017, 32-channel ultra-low-noise arbitrary signal generation platform for biopotential emulation, IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, Pages:698-701