Electrical Stimulation
for Neural Repair

Dr Alex Casson is a specialist in non-invasive bioelectronic interfaces: the design and application of wearable sensors, and skin-conformal flexible sensors, for human body monitoring and data analysis from highly artefact prone naturalistic situations. This work is highly multi-disciplinary, spanning ultra-low power sensing, signal processing and machine learning in power constrained rich environments, and real-time data analysis towards closed loop systems for remote monitoring and digital therapeutics. He has research experience in: •Manufacturing using 3D printing, screen printing, and inkjet printing. •Ultra low power microelectronic circuit and system design at the discrete and fully custom microchip levels. •Sensor signal processing and machine learning for power and time constrained motion artefact rich environments. •Using bespoke and off-the-shelf wearable devices in clinical and non-clinical environments. He has particular interests in closed loop systems: those which are tailored to the individual by personalised manufacturing via printing; and tailored to the individual by adjusting non-invasive stimulation (light, sound, electrical current) using data driven responses/outputs from real-time signal processing. Dr Casson’s ultra low power sensors work is mainly for health and wellness applications, with a strong background in brain interfacing (EEG and transcranial current stimulation) and heart monitoring.

Dr. Daniel Franklin employs adjacent branches of optics, engineering, and biology to produce the next generation of materials and devices for fundamental medical science and clinical translation. Examples include: •Wearable health devices for advanced hemodynamic monitoring, such as blood pressure, cardiac output, and systemic vascular resistance. Applications include our fundamental understanding of heart disease and commercial/clinical health telemetry. •Wireless implants for physiological monitoring and closed-loop stimuli/feedback. Applications include disease models, animal behavioral studies and neuromodulation. •Exploration of novel materials, such as liquid crystal, which can self-assemble into bioresorbable temperature sensors with applications in imaging and photodynamic therapy. Through the multidisciplinary study of these bioelectronic and biophotonic systems, we aim to shed light on unexplored aspects of human physiology.

Hani Naguib is a Professor at the University of Toronto, and director of the Toronto Institute for Advanced Manufacturing. His major expertise is in the area of advanced manufacturing of emerging materials including smart materials, adaptive structures, and biomaterials. His research group focus on new micro and nanofabrication and additive manufacturing techniques for these systems. Naguib is the recipient of many honours and awards such as the Canada Research Chair, the Premier’s Early Research Award of Ontario, the Canada Foundation of Innovation, and the faculty Early Teaching Award. He is a Professional Engineer in Canada, a Chartered Engineer in U.K., Fellow of the Institute of Materials Minerals and Mining IOM3, Fellow of the American Society of Mechanical Engineers ASME, Fellow of the Society of Plastics Engineers SPE, Fellow of the Canadian Society of Mechanical Engineers CSME, and Fellow of the International Society for Optics and Photonics SPIE. The main goal of his research program is to develop sustainable and transformational materials and manufacturing for the energy, environment and health care sectors.

Dr. HaoTian Harvey Shi is an Assistant Professor of advanced manufacturing in the Department of Mechanical and Materials Engineering at Western. Prior to joining Western, Dr. Shi was a post-doctoral research associate at the University of Cambridge, U.K., developing multi-lengths-scale hierarchical fiber-based printing technologies for fog harvesting and breath sensing applications. Dr. Shi’s research group (Data-Driven Advanced Manufacturing (D2M) Group) is working on designing the next generation of sustainable functional materials for additive hierarchical manufacturing across multiple length scales. By combining materials science fundamentals and mechanical design principles, improved materials properties along with optimal hierarchical manufacturing parameters can be revealed for enhanced device performance in the following application areas: •Energy Storage (Supercapacitors and Zn-ion Batteries) •Biomedical Sensors (Tactile, Strain, Temperature, Humidity, etc.)