Meet the 2020 Commercialization Fellows
Seven students are examining the business prospects for a diverse array of Cornell technologies – including wireless charging for electric vehicles, a DIY social robot, wastewater ion separation, and stretchable light guides – as the 2020 class of commercialization fellows.
The fellows, all engineering doctoral students, are spending a fully funded semester and summer exploring the commercial viability of their respective technologies. From intellectual property management to supply chains, the fellowship offers a deep and personalized experience in learning what’s needed to bring products to market.
The 2020 fellows and their technologies are:
Hedan (Lillia) Bai ’16, M.S. ’19, stretchable lightguides for multimodal sensing: A highly stretchable fiber-optic sensor that can simultaneously measure mechanical deformations such as stretching; bending; pressing; detecting location; and magnitude. The lightguides can provide sensing functions for a number of potential applications, including sensing for human tissue, clothes and robotics, and have been implemented as a wireless VR glove.
Houston Claure, resource allocation with fairness constraints: An algorithm developed for deployment in team settings where resources – such as time, attention and tools – need to be distributed by an individual or robot. The algorithm assists in making such decisions by learning about each team member’s skill level while taking the notion of fairness into consideration. It has potential applications for teachers and coaches.
Yehou Gnopo, M.S. ’18, mucosally delivered vaccine system: A multiantigen vaccine delivery system that induces mucosal immunity by a simple swab of the cheek with a cotton swab. The system consists of bacterial outer membrane vesicles that are engineered to induce a strong immune response at mucosal surfaces such as the mouth, nose and lungs, which are primary sites of pathogen infection.
Meishen Liu, wastewater ion separation using carbon dioxide: A method of capturing carbon dioxide from the air using sodium glycinate, then using the resulting solution to separate valuable elements – such as soluble carbonates of lithium, calcium and magnesium – from industrial wastewater streams, rendering the method cash positive and carbon negative.
Brandon Regensburger, M.S. ’19, wireless charging for electric vehicles: A capacitive wireless power transfer system suitable for in-motion charging of electric vehicles. The approach uses electric field coupling between metal plates to transfer energy, allowing the capacitive system to be much smaller, lighter, less expensive and easier to embed in the ground than traditional inductive charging systems.
Jaejeong (Jane) Shin, real-time intelligent sensor path planning: A path-planning algorithm for autonomous air, ground and underwater vehicles that combines computer vision with information theory. The algorithm requires significantly low computational time so the optimal path can be determined in real time as the vehicle is moving and the sensors are obtaining new information about the environment.
Michael Suguitan, DIY social robot: A social robotics kit that is uniquely “nonrobotic” in that its exterior is made from soft materials and its interior is mechanically compliant. Users are directly involved in its construction and deep learning models are used to generate its behaviors. It is designed as an accessible platform for teaching the technical and creative aspects of robotics engineering to a broad audience.