The most important research project I have worked on is the massively parallel propagation-delay algorithm and FPGA (field-programmable gate array) microchip I independently designed for the Intel science Talent search. The chip was demonstrated to solve certain computationally difficult problems - graph theoretic shortest path problems - an order of magnitude more quickly than traditional computers, and the novel theoretical approach was shown to be generalizable to other, even more difficult problems such as the zubset sum problem. These innovations have applications in fields from network routing to cryptography to missile interception to computational biology. My research abstract is below. 

"This paper describes: the development, optimization, simulation, and practical FPGA (Xilinx Spartan-3E X3S500E) implementation of a new parallel algorithm for the NSSP (single source shortest path problem with nonnegative edge weights). Its run time has an upper bound of O(min(n, ?)), and it uses hardware resources on the order of O(m), the theoretical optimum. It was applied to standard benchmark problem instances and its performance was compared to that of the fastest general case implementation of Dijkstra's algorithm -- O(m + n log n). For practical instances of the problem, the propagation delay algorithm required on the order of 200-300 times fewer clock cycles. The hardware implementation achieved is fully scalable, and the paper proposes a second-generation chip architecture which, when implemented, will make the device efficiently problem-reconfigurable in real-time. The relatively low cost of the chip combined with its power and flexibility make it broadly applicable in a wide variety of laboratory and field situations. Moreover, the underlying algorithm is the product of a new parallel computing paradigm, which will be termed "accelerated propagation delay" because it is based on controlling and recording the relative speed of signals propagating in parallel through a network. This paradigm is generalizable to solve other problems that are even more computationally intensive than pathfinding, including the NF-complete subset sum and Hamiltonian path problems. An accelerated design to solve the first of these problems was developed as part of this project and is proposed briefly in the discussion."