Company Filing History:
Years Active: 2022
Title: Mohit Dandekar: Innovator in Neural Network Technology
Introduction
Mohit Dandekar is a prominent inventor based in Heverlee, Belgium. He has made significant contributions to the field of neural networks, particularly through his innovative patent that enhances the efficiency of convolutional neural networks. His work is instrumental in advancing technology that supports complex data processing.
Latest Patents
Dandekar holds a patent for a "Convolution engine for neural networks." This invention discloses a method and hardware system for mapping an input map of a convolutional neural network layer to an output map. The system features an array of processing elements that are interconnected to support unidirectional data flows through the array along at least three different spatial directions. Each processing element is designed to combine values of data flows along different spatial directions into a new value for at least one of the supported data flows. For each data entry in the output map, a plurality of products from pairs of weights of a selected convolution kernel and selected data entries in the input map is provided and arranged into a plurality of associated partial sums. Products associated with the same partial sum are accumulated on the array into at least one data entry in the output map.
Career Highlights
Dandekar is currently associated with Imec Vzw, a leading research and innovation hub in nanoelectronics and digital technologies. His role at Imec allows him to work on cutting-edge projects that push the boundaries of technology and innovation.
Collaborations
Throughout his career, Dandekar has collaborated with notable professionals in the field, including Francky Catthoor and Praveen Raghavan. These collaborations have further enriched his work and contributed to advancements in neural network technologies.
Conclusion
Mohit Dandekar's contributions to the field of neural networks through his innovative patent demonstrate his commitment to advancing technology. His work continues to influence the development of efficient data processing systems.