About

Adam Wang is a highly experienced Senior Software Engineer and Machine Learning expert with a career spanning almost 20 years. Currently, he is working at Netflix, where he is responsible for deep learning for ASR, speech synthesis, and automatic speech recognition and speaker diarization for dialog list creation given proxy video and audio tracks. He is also involved in active speaker detection/recognition and speaker on/off screen detection, as well as automatic audio mixing for the dubbing process. Prior to joining Netflix, Adam worked as a Speech Scientist at Verizon, where he led speech algorithm development for IPTV and smart home devices. He developed Keyword Spotting (KWS) based on DNN and CNN to wake up speech-enabled set-top-box. Before that, he worked as a Senior Member Technical Staff at Maxim Integrated, where he focused on algorithms for loudspeaker enhancement and protection with a focus on micro-speaker impedance modeling and excursion control. He also worked on an ultrasound gesture recognition system. Adam holds a PhD in Electrical and Computer Engineering from the University of Rhode Island, where he specialized in his field of study. He is skilled in ML, Software Engineering, Deep Learning, CNN, and Research Science, among other areas. His expertise and experience make him an invaluable asset to any team working on complex machine learning projects. Adam's LinkedIn profile summary is short and to the point, highlighting his key skills and expertise. It is clear that he is a highly experienced and skilled professional who has worked on a variety of challenging projects throughout his career. He is a team player who is dedicated to delivering high-quality results and is always looking for new challenges and opportunities to learn and grow.