- Member of the leadership team in Microsoft's AI development acceleration division under Office of the CTO, driving the state-of-the-art in AI by developing advanced AI capabilities, products, and solutions applicable across the enterprise (Office M365 and Azure Copilots), as well as growing the next generation of AI leaders for transformational impact to the world. More details are available at: https://www.sadidhasan.com- Two decades of AI research and product development experience in the areas of Computational Linguistics, Natural Language Processing (NLP), Artificial Intelligence, and Machine Learning with a competitive mindset; built new competencies within teams towards contributing significant values to businesses via participating in 40+ external and internal NLP/AI challenges and competitions with top-ranked results. - Notable achievements include pioneering research contributions on generative AI including complex question answering, question decomposition, neural paraphrase generation, topic to question generation, and query-focused multi-document summarization; dependent reading for natural language inference, clinical diagnosis inference using memory networks & deep reinforcement learning, reinforcement learning for question answering with human in the loop; ~100 publications in top NLP/machine learning conferences, 31 granted patents, 30+ patents pending. - Well-recognized thought leader in AI, NLP, and machine learning research and business communities; regular program committee member of all major top-tier NLP/machine learning academic conferences, frequent invited/keynote speaker at the top deep learning/data science industry-academia conferences, founding organizer of the ImageCLEF medical domain VQA and VQG challenge.Previously:- Executive Director of Artificial Intelligence at CVS Health; led the teams responsible for developing and delivering advanced AI-enabled clinical care planning and automation initiatives.- Technical Lead of the AI Group for clinical AI/NLP R&D projects related to information extraction & retrieval, knowledge representation & reasoning, question answering, natural language inference, paraphrase generation, text classification, medical image caption generation etc. using advanced deep learning with extensive experience in globally distributed and cross-functional teams (research, engineering, business, design, IP, customer service etc.), academic collaborators (MIT, Stanford, BU, PUCPR), and research interns; accomplished 20+ business transfers.