About

Rahul Saxena is a software engineer at Microsoft with a strong background and interest in optimization algorithms and deep learning. He is a fast learner with a passion for data science and natural language processing. With 2.20 years of relevant experience, Rahul has worked in various domains including web development, android development, competitive programming, security management, and machine learning. Rahul is a double major in Electrical and Electronics Engineering and Economics from the Indian Institute of Technology, Kanpur. He has a strong academic background and is proficient in various programming languages such as Golang, Javascript, Tensorflow, and Pytorch. In his current role at Cohesity, Rahul serves as a Member of Technical Staff. Prior to this, he has worked as a Research Intern at Saarthi.ai and Adobe. At Saarthi.ai, he built an end-to-end speaker diarization pipeline from scratch, involving taking an audio file and creating a speaker-wise transcript of the audio. At Adobe, he worked on developing an end-to-end text-to-speech architecture using deep learning, capable of producing human-like voice and changing its voice attributes by recognizing the emotional context of text. Rahul has also created a proprietary dataset for training models using the existing pipeline and developed a framework for evaluating the model using the Diarization Error Rate (DER) metric. His work at Adobe has been filed for a patent by the company. Overall, Rahul is a highly skilled software engineer with a passion for data science and machine learning. He is constantly seeking new challenges and opportunities to learn and grow.