- Hariharan Ganapathy
Hariharan Ganapathy’s path to a new job all started with one course. He was working in audio signal processing at Dolby Technologies when he started taking courses recreationally at Extension. He already had undergraduate and graduate degrees in electrical engineering as well as a few years of startup experience, but he kept taking courses in an effort to expand his industry knowledge and job opportunities.
“It’s always helpful to learn what’s out there,” Ganapathy says. “I used to work in audio, and my job was very specific—I was writing signal processing for particular audio modules. But audio doesn’t end there. Learning new things means that if there is a new challenge at your job, these new skills will help you.”
Ganapathy explored a number of different courses in Extension’s Embedded Systems program, including The Internet of Things: Connecting via Bluetooth, WiFi and ZigBee, Developing Applications for Android Mobile Devices, and Digital Video Interfaces and Protocols. It was the Digital Video Compression and Codec course that first helped him realize what he was looking for—a more comprehensive understanding of programming for video. As his interests shifted, Ganapathy realized he had completed so many of the courses at Extension that he might as well complete the Embedded Systems certificate.
“Most of my experience and knowledge was in audio engineering, and whatever video engineering I knew was from articles and papers,” Ganapathy says. “I was always interested in getting into video engineering. This course was a really good introduction for me…it actually helped me get a video job inside Dolby itself.”
In his position as senior design engineer, not only does he do Codec development for video, but he is at work on a project that would propose new Codec’s for full HD, high-quality broadcast for 3D channels. While the concepts he learned in Krishna Vallabhaneni’s Video Codec course are particularly helpful at work, he also relies on multicore programming skills he developed at Extension when working on algorithm parallelization.
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