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Rosotics, Inc. Appoints Chandan Yadav as Director of Machine Learning

Graduate AI Researcher joins development team of autonomous systems.


PHOENIX, AZ, USA - SEPTEMBER 1, 2019 - Rosotics, Inc. (www.rosotics.com), creator of the world’s most mobile manufacturing systems, announces that Chandan Yadav has joined the company as Director of Machine Learning with immediate effect. Yadav will leverage his extensive background with artificial intelligence (AI), robotics, and machine learning to accelerate the development of Qualia, Rosotics' AI Platform that powers the intelligence and engagement capabilities of the company's robotic hardware, as well as help lead the integration of novel software applications into our process flow.



Chandan joins Rosotics as a graduate student and having working previously with Pegasystems, where he built a facial recognition system utilizing a haar cascade classifier based emotion detector. He also carries significant research in robotics and deep learning, having developed a voice-controlled robotic wheelchair for the physically disabled while working at the Indian Institute of Science. His research in highly intelligent navigation systems was received well at the ICAMMAET and published in IEEE. Yadav will be instrumental in advancing our research efforts in the areas where people, robotics and AI intersect, to explore how these technologies can make a profound societal impact. He is passionate about creating new products and technologies that can positively impact the world. 


For more information on Rosotics, please visit www.rosotics.com.


About Rosotics, Inc.

Born in the valley of the sun, Rosotics is a supercharged robotic manufacturing company that harnesses advanced additive manufacturing techniques to create large metal parts faster and more cost-effectively. Unlike most 3D metal printing organizations who produce using DMLS or other methods, Rosotics has developed a breakthrough process which eliminates size boundaries and allows the production of strong parts of enormous scale. Our technology utilizes swarm robotics, and is far more efficient than any that has come before it.


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