About

Nabil Hossain is a highly skilled Research Scientist with a focus on Natural Language Processing (NLP), Machine Learning (ML), Deep Learning (DL), and Artificial Intelligence (AI). Currently working with Intel, he is engaged in cutting-edge research at the intersection of NLP and computer vision, with a special emphasis on sign language translation. With over 2.62 years of relevant experience, Nabil has a proven track record of delivering high-quality research in his field. Nabil completed his PhD in Computer Science from the University of Rochester, where his dissertation focused on creative natural language generation, with a particular emphasis on computational humor. His research areas include text generation and machine translation, and he has published several papers in top-tier conferences such as ACL 2020. Nabil's expertise in NLP and DL has also led him to work as a Research Intern at Facebook AI, where he worked on deep learning for text generation, and as an Applied Scientist Intern at Amazon, where he focused on adversarial paraphrase generation for natural language understanding, working in Alexa AI. Nabil's educational background is equally impressive, with a Bachelor of Arts in Mathematics and Computer Science from Bard College, a Master of Science in Computer Science from the University of Rochester, and additional coursework in Speech and Machine Learning from the Toyota Technological Institute at Chicago and Natural Language Processing, Machine Learning, and Data Analysis from the University of Houston. Nabil's technical skills include expertise in NLP, DL, AI, ML, and computer vision. He has a strong background in research and has demonstrated his ability to work in a collaborative environment. Nabil is an excellent communicator and has a passion for sharing his knowledge with others. He maintains an active presence on his personal website, Google Scholar, and LinkedIn, where he regularly shares his research and insights with the broader community.