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Arun Rajasekaran

Arun is a seasoned, cross-functional engineering leader, an innovator, and a thought leader in all aspects of embedded systems: from silicon to software. Arun currently leads Market development and Business development efforts for Edge Impulse – a ground-breaking embedded machine learning development and deployment platform. Previously, as CTO of Voice BU at Poly, Arun led Technology Strategy and Technology Platforming efforts with a focus on wearable technologies. Before becoming the CTO, while his primary focus was around leading Plantronics' product development teams responsible for IoT-to-Cloud system architecture, embedded software, audio DSP, AI/ML technologies, and data insights & analytics, he was also leading Plantronics's strategic collaboration and partnership efforts with silicon, SaaS, and other ecosystem partners. Prior to Poly, Arun has held various engineering leadership positions at BlackBerry/RIMM, Ikanos/Conexant/GlobeSpan, and 3Com/USRobotics.

Embedded ML: The New Secret Weapon to IoT Success

Status: Available Now

Attempting to add-on AI and ML modeling to existing IoT networks delivers marginal results compared to when it's designed into the architecture. Organizations that have accomplished this in their IIoT/IoT architectures can support model processing in multiple stages of their solution while reducing networking throughput and latency, making everything more purposeful and even more secure.

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Enterprise Collaboration in Post-COVID world (2020)

Status: Available Now

Digital transformation is accelerating the evolution of IoT-to-Cloud architecture. Technology innovation from Silicon to Software, that initially was intended for cloud computing is now fast making its way to the end-point devices at the edge of the network. As a result, the edge devices are in the cusp of becoming way more smarter than they have ever been to take collaboration to the next level. Video and Audio are collaboration’s key corner stone technologies. A combination of modern Machine Learning techniques and traditional signal-processing techniques are bound to change for good how we collaborate in the future.

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