About

Arghya Das is a multimedia software development lead at Intel Corporation with over 17 years of relevant experience. He is an expert in C/C++ programming, including C++ 11/14 and beyond, and Windows programming. He has delivered solutions in complex subsystems and is enthusiastic about C++ new standard adoption and secure, robust, and optimized code writing based on C++ core guidelines. Arghya is an expert on Windows Graphics and Media Technologies such as DirectX9/11 and Media Foundation as well as Intel Media SDKs framework for video encode/decode/processing. He is presently working as a lead multimedia developer working on both WebRTC stack (part of chromium source) and a UWP variant of WebRTC to optimize it for Intel platforms. He has optimized the camera capture/encode pipeline for WebRTC to significant power/performance gains and the desktop capture and encode pipeline for Windows and Mac capture client to significant performance gains allowing real-time sharing. Arghya has worked across application and driver stacks for graphics and media subsystem on Windows. He has worked on video decode, video processing, content protection, GPU shaders, 2D routines, power management interfaces, overlay plane handling across both user and kernel mode drivers. He has worked on 3 different graphics IPs during the past 13 years, NVIDIA, Imagination Technologies, and Intel Gen GPU. Arghya has expert knowledge of Windows OS and various debug methods and tools such as WinDbg and Visual Studio. He has debugged many system problems across platform components during multiple platform bring-ups in Intel. He has used h/w debugging tools such as ITP to co-debug issues with Silicon Validation and hardware design teams. Currently, Arghya is working on multimedia video conferencing/collaboration software solutions for Intel. Primarily, he works on Google's WebRTC stack optimization for Intel h/w and client-specific needs. In his current role, he has delivered an interactive collaboration solution for remote meeting rooms using WebRTC DataChannel. He has also worked on the Mac client and delivered a real-time desktop sharing experience based on the WebRTC stack. He is currently optimizing UWP implementation for WebRTC for Intel hardware and achieved significant optimizations in the capture/encode pipeline.