My experience spans technical AI leadership with expertise in founding, growing and managing ML engineering, science and product teams. My work involves research and industry-wide practical applications related to the fields of machine learning, natural language processing (NLP), computer vision, data mining and computational decipherment (cracking codes with computers). This has led to scientific advances and industry-wide innovations in conversational AI, on-device machine learning for IoT devices, large-scale unsupervised and semi-supervised methods and their applications to structured prediction problems in NLP, image recognition, information extraction, multi-modal learning for language/vision, user modeling in social media, graph optimization algorithms for summarizing noisy data, computational decipherment and computational advertising.
Dr. Sujith Ravi is the Founder & CEO at Stealth AI/ML startup. Previously, he was the Director of Amazon Alexa AI where he led efforts to build the future of multimodal conversational AI experiences at scale. Prior to that, he was leading and managing multiple ML and NLP teams and efforts in Google AI. He founded and headed Google’s large-scale graph-based semi-supervised learning platform, deep learning platform for structured and unstructured data as well as on-device machine learning efforts for products used by billions of people in Search, Ads, Assistant, Gmail, Photos, Android, Cloud and YouTube. These technologies power conversational AI (e.g., Smart Reply), Web and Image Search; On-Device predictions in Android and Assistant; and ML platforms like Neural Structured Learning in TensorFlow, Learn2Compress as Google Cloud service, TensorFlow Lite for edge devices.
Dr. Ravi has authored over 100 scientific publications and patents in top-tier machine learning and natural language processing conferences. His work has been featured in press: Wired, Forbes, Forrester, New York Times, TechCrunch, VentureBeat, Engadget, New Scientist, among others, and also won the EACL Best Paper Award Honorable Mention in 2021, SIGDIAL Best Paper Award in 2019 and ACM SIGKDD Best Research Paper Award in 2014. For multiple years, he was a mentor for Google Launchpad startups. Dr. Ravi was the Co-Chair (AI and deep learning) for the 2019 National Academy of Engineering (NAE) Frontiers of Engineering symposium. He was also the Co-Chair for ACL 2021, EMNLP 2020, ICML 2019, NAACL 2019, and NeurIPS 2018 ML workshops and regularly serves as Senior/Area Chair and PC of top-tier machine learning and natural language processing conferences like NeurIPS, ICML, ACL, NAACL, AAAI, EMNLP, COLING, KDD, and WSDM.
My main research interests lie in Artificial Intelligence areas, specifically machine learning, natural language processing (NLP), computer vision, multimodal learning, large-scale data mining, and other areas such as computational decipherment. Here are a few (selected) research topics that I have worked on.
I have been a TA and taught lectures for the following graduate courses in the Computer Science Department at University of Southern California: