Nandhini Ramalingam

I am an ambitious person who is always striving to reach my full potential. I was born and raised in a small town in the countryside where I developed a love for nature and the outdoors. Growing up, I was always fascinated by science and technology, which has led me to pursue a degree in computer engineering.

Throughout my academic career, I have consistently worked hard and maintained a high GPA, which has allowed me to be accepted into a prestigious university. I am confident that my education and experience will help me achieve my career goals and make a positive impact in the world.

Aside from my academic pursuits, I am also a very active person who loves to participate in various sports and activities. Whether it be hiking, playing basketball, or practicing martial arts, I find joy in staying physically fit and challenging myself.

Moreover, I am a very social person who enjoys spending time with friends and family. I believe that having strong relationships with loved ones is crucial in life and helps to bring happiness and fulfillment.

In conclusion, I am a determined, active, and social person who is committed to reaching my full potential and making a positive impact in the world. I am confident that my passion and dedication will help me achieve my goals and live a fulfilling life.

I started my career as a video codec with machine learning intern at Multicoreware and most recently i worked as senior software engineer leading a team on customer project. As a codec engineer I had the opportunity to work with x265 - an open source encoder owned by Multicoreware and it’s been used by most video streaming services. Svt_hevc proprietary encoder owned by Intel and then I teamed up with Habana labs based in Israel later then it was acquired by Intel. Basically they have 4 different standard of encoders & decoders such as h264, hevc, vp9, jpeg. And also they had two high performance AI processors namely Goya and Gaudi2 similar to NVIDIA GPUs. Our job was to integrate these encoders and decoder with these processors and perform model training and inference for the same. Machine learning is bringing new solutions for every industry and video codecs are no exemption from it. Video codec uses complex algorithms but Machine learning helps shorten the process as the model learns and adapts the algorithm. Thus it helps achieve effective video compression by minimizing the bitrate while keeping the image quality. I had the opportunity to work in this cutting edge technology.

After having for about 3+ years of experience in machine learning field to upskill my knowledge I'm currently pursuing masters in Data Science