Ankith Mohan

Title: Innovations of Ankith Mohan

Introduction

Ankith Mohan is an accomplished inventor based in Blacksburg, VA (US). He has made significant contributions to the field of quantum computing and graph theory. With a total of 2 patents, his work showcases the intersection of classical and quantum methodologies.

Latest Patents

Ankith's latest patents include a method for hybrid classical-quantum unsupervised multiclass classification. This method involves obtaining a multi-dimensional training dataset that includes multiple datums, each corresponding to a number of quantum bits (qubits) representing a quantum state. The process also includes generating a Gram matrix using a quantum computing device and determining multiple operators with a classical computing device based on constraints defined by the Gram matrix. Each operator acts as a proxy for a corresponding datum, which is then assigned a label.

Another notable patent focuses on the identification of influential nodes in graph datasets using combinatorial optimization formulations. This method begins with obtaining a graph dataset that represents a social network, which includes a plurality of nodes. The dataset is partitioned into two clusters, and influential nodes are identified within these clusters. The process culminates in selecting influencer nodes and identifying corresponding objects within the social network.

Career Highlights

Ankith Mohan is currently employed at Fujitsu Corporation, where he continues to innovate and develop new technologies. His work is at the forefront of integrating quantum computing with practical applications, making significant strides in both theoretical and applied research.

Collaborations

Ankith collaborates with talented individuals such as Sarvagya Upadhyay and Xiaoyuan Liu, contributing to a dynamic research environment that fosters innovation and creativity.

Conclusion

Ankith Mohan's contributions to the fields of quantum computing and graph theory are noteworthy. His innovative patents reflect a deep understanding of complex systems and a commitment to advancing technology.